Genes

19 pages, 6244 KiB

Open AccessArticle

Expression of Piwi, MMP, TIMP, and Sox during Gut Regeneration in Holothurian Eupentacta fraudatrix (Holothuroidea, Dendrochirotida)

by Igor Yu. Dolmatov, Nadezhda V. Kalacheva, Ekaterina S. Tkacheva, Alena P. Shulga, Eugenia G. Zavalnaya, Ekaterina V. Shamshurina, Alexander S. Girich, Alexey V. Boyko and Marina G. Eliseikina

Genes 2021, 12(8), 1292; https://doi.org/10.3390/genes12081292 - 23 Aug 2021

Cited by 13 | Viewed by 2498

Abstract

Mesodermal cells of holothurian Eupentacta fraudatrix can transdifferentiate into enterocytes during the regeneration of the digestive system. In this study, we investigated the expression of several genes involved in gut regeneration in E. fraudatrix. Moreover, the localization of progenitor cells of coelomocytes, juvenile [...] Read more.

Mesodermal cells of holothurian Eupentacta fraudatrix can transdifferentiate into enterocytes during the regeneration of the digestive system. In this study, we investigated the expression of several genes involved in gut regeneration in E. fraudatrix. Moreover, the localization of progenitor cells of coelomocytes, juvenile cells, and their participation in the formation of the luminal epithelium of the digestive tube were studied. It was shown that Piwi-positive cells were not involved in the formation of the luminal epithelium of the digestive tube. Ef-72 kDa type IV collagenase and Ef-MMP16 had an individual expression profile and possibly different functions. The Ef-tensilin3 gene exhibited the highest expression and indicates its potential role in regeneration. Ef-Sox9/10 and Ef-Sox17 in E. fraudatrix may participate in the mechanism of transdifferentiation of coelomic epithelial cells. Their transcripts mark the cells that plunge into the connective tissue of the gut anlage and give rise to enterocytes. Ef-Sox9/10 probably controls the switching of mesodermal cells to the enterocyte phenotype, while Ef-Sox17 may be involved in the regulation of the initial stages of transdifferentiation. Full article

(This article belongs to the Special Issue The Molecular Genetics and Major Concepts Underlying Whole Body Regeneration in the Animal World)

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15 pages, 33305 KiB

Open AccessArticle

Regional Specific Differentiation of Integumentary Organs: Regulation of Gene Clusters within the Avian Epidermal Differentiation Complex and Impacts of SATB2 Overexpression

by Gee-Way Lin, Yung-Chih Lai, Ya-Chen Liang, Randall B. Widelitz, Ping Wu and Cheng-Ming Chuong

Genes 2021, 12(8), 1291; https://doi.org/10.3390/genes12081291 - 23 Aug 2021

Cited by 5 | Viewed by 2876

Abstract

The epidermal differentiation complex (EDC) encodes a group of unique proteins expressed in late epidermal differentiation. The EDC gave integuments new physicochemical properties and is critical in evolution. Recently, we showed β-keratins, members of the EDC, undergo gene cluster switching with overexpression of [...] Read more.

The epidermal differentiation complex (EDC) encodes a group of unique proteins expressed in late epidermal differentiation. The EDC gave integuments new physicochemical properties and is critical in evolution. Recently, we showed β-keratins, members of the EDC, undergo gene cluster switching with overexpression of SATB2 (Special AT-rich binding protein-2), considered a chromatin regulator. We wondered whether this unique regulatory mechanism is specific to β-keratins or may be derived from and common to EDC members. Here we explore (1) the systematic expression patterns of non-β-keratin EDC genes and their preferential expression in different skin appendages during development, (2) whether the expression of non-β-keratin EDC sub-clusters are also regulated in clusters by SATB2. We analyzed bulk RNA-seq and ChIP-seq data and also evaluated the disrupted expression patterns caused by overexpressing SATB2. The results show that the expression of whole EDDA and EDQM sub-clusters are possibly mediated by enhancers in E14-feathers. Overexpressing SATB2 down-regulates the enriched EDCRP sub-cluster in feathers and the EDCH sub-cluster in beaks. These results reveal the potential of complex epigenetic regulation activities within the avian EDC, implying transcriptional regulation of EDC members acting at the gene and/or gene cluster level in a temporal and skin regional-specific fashion, which may contribute to the evolution of diverse avian integuments. Full article

(This article belongs to the Special Issue Genomics and Evolution of Sauropsid Traits in the Genomics Era)

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Figure 1
Epidermal differentiation complex (EDC) on Chr25 with different transcriptional profiles of non-β-keratin EDC (NB-EDC) members during embryonic development in feathers, scales, and beaks. (a) Illustration of gene organization for the non-β-EDC on Chr25. Five sub-clustered genes are highlighted here and marked with different colors; the genomic regions for β-keratin and non-β-EDC are in a fixed ratio. (b–b’’) Transcriptional profiles of feathers from E7 to E16 viewed by IGV; (c–c’’) Transcriptional profiles of scales from E9 to E16 viewed by IGV; (d–f) Gene expression level (CPM, count-per-million) of non-β-EDC in E16-feathers, E16-scales, and E14-beaks, respectively. Five sub-clusters were underlined with black bars in each panel. The expression profiles across different skin appendages (f: feather, s: scale, b: beak) were marked; (g) Expression levels of selected S100 genes among all skin appendages viewed by IGV. The red color marks the high expression level of EDC peaks/genes over 2000 CPM, while the orange color marks the intermediate expression level of EDC peaks/genes ranging from 500 to 2000 CPM in feathers (panel b,b’,d). The indigo color marks the high expression level of EDC peaks/genes over 1000 CPM, while the orange color marks the intermediate expression level of EDC peaks/genes ranging from 100 to 500 CPM in scales (panel c,c’,e). This analysis is based on the galGal6 genome version, while related work in our previous study is based on galGal4 [<a href="#B27-genes-12-01291" class="html-bibr">27</a>]. Please see discussion. Full article ">Figure 2
Epidermal differentiation complex on Chr25 with divergent epigenetic landscapes in E14 feathers and scales. (a) The locations of two parts of the non-β-EDC (NB-EDC) on Chr25 in the galGal6 genome version; (b–b’’) Profiles of RNA-seq and three chromatin marks in the N-terminal part of the non-β-EDC within 75 kb of the gene start sites. (b’,b’’) Enlargement of the two predicted enhancer regions (enhancers 1 and 3, e1 and e3, black arrowheads) from (b); blue arrowhead indicates the putative poised enhancer; (c–c’’’’) Profiles of RNA-seq and three chromatin marks in the C-terminal part of the non-β-EDC within 150 kb of the transcription start site. (c’–c’’’’) Enlargement of the five predicted enhancer regions (e4 to e8, black arrowheads) and the five predicted promotor regions (green arrowheads) from (c). The values on the y axis for ChIP-Seq data are input normalized intensities. The yellow color marks putative enhancer regions, while the green color marks the putative promoter regions. The gene name in bold may be under enhancer-mediated expression. Full article ">Figure 3
The related expression level of non-β-EDC on Chr25 when SATB2 proteins are overexpressed in different skin appendages. (a–a’’) Feathers at E14; (b–b’’) Feathers at E16; (c–c’’) Scales at E16; (d–d’’) Beaks at E14. The fold changes and statistical significance of DEG indicated in (a–d) are collected from <a href="#app1-genes-12-01291" class="html-app">Supplementary Tables S2–S5</a>. DEG with an FDR < 0.05 are indicated by asterisks (*) and DEG with a Log2 fold change over 1.5 or less than −1.5, under the excess of SATB2, is marked by double asterisks (**). Five sub-clusters of EDC members (EDDA, EDCH, EDCRP, EDQM, and S100) are indicated by different colors, the same as those in <a href="#genes-12-01291-f001" class="html-fig">Figure 1</a>a. Full article ">Figure 4
Expression patterns of selected non-β-keratin EDCs in developing beaks, scales, and feathers were analyzed by section in situ hybridization. Beaks and scales, sagittal sections. Feathers, cross sections. (a–c, a’–c’) In situ hybridization of EDMTF4 probes at E14 and E16, respectively; (d–f, d’–f’) In situ hybridization of EDCH4 probes at E14 and E16, respectively; (g–i, g’–i’) In situ hybridization of EDPE probes at E14 and E16, respectively. Filled arrowheads indicate the location of in situ hybridization signals. The expression levels (CPM, counts per million mapped reads) of each gene from RNA-seq data are indicated in the bottom right. Abbreviations: BC, barb cortex; BM, barb medulla; DB, downy barbules; FS, feather sheath; PD, periderm; SB, stratum basal; SC, stratum corneum; SI, stratum intermedium; SP, subperiderm. Full article ">Figure 5
Altered expression patterns of selected non-β-keratin EDCs in beaks, scales, and feathers with SATB2-overexpression are studied by section in situ hybridization. Beaks and scales, sagittal sections. Feathers, cross sections. (a–c, a’–c’). In situ hybridization of EDMTF4; (d–f, d’–f’), EDCH4; (g–i, g’–i’), EDQREP; (j–l, j’–l’), EDPE; (m–o, m’–o’) and EDDM. Filled arrowheads indicate the location of in situ hybridization signals. The expression levels (CPM) of each gene from RNA-seq data, and disrupted trends when SATB2 is overexpressed, are indicated in the bottom right. Abbreviations: DB, downy barbules; FS, feather sheath; PD, periderm; SB, stratum basal; SC, stratum corneum; SI, stratum intermedium; SP, subperiderm. Full article ">Figure 6
SATB2-mediated or putative enhancer-mediated expression for non-β-keratin EDC genes in different developing integumentary organs. (a,b) Summary of non-β-keratin EDC genes or gene clusters in which expression was disrupted under RCAS -SATB2 infection at E14 of feathers and beaks (a) or at E16 of feathers and scales (b) from <a href="#genes-12-01291-f003" class="html-fig">Figure 3</a>. Red arrows indicate candidate genes were down- or up- regulated under the SATB2-RCAS infection. (c) Summary of SATB2-mediated sub-clusters in divergent regions from (a) and (b). The opposite regulation of EDC sub-clusters such as EDCRP and EDCH between feathers and scales or feathers and beaks, respectively. (d) Summary of non-β-keratin EDC genes with putative enhancers (e1 to e8) in feather or scale regions from <a href="#genes-12-01291-f002" class="html-fig">Figure 2</a>. Genes in bold indicate their expression level over 500 CPMs in <a href="#genes-12-01291-f001" class="html-fig">Figure 1</a>. (e) Potential genes mediated by both SATB2 and enhancers. Full article ">

15 pages, 2584 KiB

Open AccessArticle

siRNA Mediate RNA Interference Concordant with Early On-Target Transient Transcriptional Interference

by Zhiming Fang, Zhongming Zhao, Valsamma Eapen and Raymond A. Clarke

Genes 2021, 12(8), 1290; https://doi.org/10.3390/genes12081290 - 23 Aug 2021

Cited by 1 | Viewed by 2427

Abstract

Exogenous siRNAs are commonly used to regulate endogenous gene expression levels for gene function analysis, genotype–phenotype association studies and for gene therapy. Exogenous siRNAs can target mRNAs within the cytosol as well as nascent RNA transcripts within the nucleus, thus complicating siRNA targeting [...] Read more.

Exogenous siRNAs are commonly used to regulate endogenous gene expression levels for gene function analysis, genotype–phenotype association studies and for gene therapy. Exogenous siRNAs can target mRNAs within the cytosol as well as nascent RNA transcripts within the nucleus, thus complicating siRNA targeting specificity. To highlight challenges in achieving siRNA target specificity, we targeted an overlapping gene set that we found associated with a familial form of multiple synostosis syndrome type 4 (SYSN4). In the affected family, we found that a previously unknown non-coding gene TOSPEAK/C8orf37AS1 was disrupted and the adjacent gene GDF6 was downregulated. Moreover, a conserved long-range enhancer for GDF6 was found located within TOSPEAK which in turn overlapped another gene which we named SMALLTALK/C8orf37. In fibroblast cell lines, SMALLTALK is transcribed at much higher levels in the opposite (convergent) direction to TOSPEAK. siRNA targeting of SMALLTALK resulted in post transcriptional gene silencing (PTGS/RNAi) of SMALLTALK that peaked at 72 h together with a rapid early increase in the level of both TOSPEAK and GDF6 that peaked and waned after 24 h. These findings indicated the following sequence of events: Firstly, the siRNA designed to target SMALLTALK mRNA for RNAi in the cytosol had also caused an early and transient transcriptional interference of SMALLTALK in the nucleus; Secondly, the resulting interference of SMALLTALK transcription increased the transcription of TOSPEAK; Thirdly, the increased transcription of TOSPEAK increased the transcription of GDF6. These findings have implications for the design and application of RNA and DNA targeting technologies including siRNA and CRISPR. For example, we used siRNA targeting of SMALLTALK to successfully restore GDF6 levels in the gene therapy of SYNS4 family fibroblasts in culture. To confidently apply gene targeting technologies, it is important to first determine the transcriptional interference effects of the targeting reagent and the targeted gene. Full article

(This article belongs to the Collection Genotype-Phenotype Study in Disease)

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13 pages, 571 KiB

Open AccessEditor’s ChoiceReview

MiRNAs and Cancer: Key Link in Diagnosis and Therapy

by Yu Shi, Zihao Liu, Qun Lin, Qing Luo, Yinghuan Cen, Juanmei Li, Xiaolin Fang and Chang Gong

Genes 2021, 12(8), 1289; https://doi.org/10.3390/genes12081289 - 23 Aug 2021

Cited by 59 | Viewed by 5038

Abstract

Since the discovery of the first microRNA (miRNA), the exploration of miRNA biology has come to a new era in recent decades. Monumental studies have proven that miRNAs can be dysregulated in different types of cancers and the roles of miRNAs turn out [...] Read more.

Since the discovery of the first microRNA (miRNA), the exploration of miRNA biology has come to a new era in recent decades. Monumental studies have proven that miRNAs can be dysregulated in different types of cancers and the roles of miRNAs turn out to function to either tumor promoters or tumor suppressors. The interplay between miRNAs and the development of cancers has grabbed attention of miRNAs as novel tools and targets for therapeutic attempts. Moreover, the development of miRNA delivery system accelerates miRNA preclinical implications. In this review, we depict recent advances of miRNAs in cancer and discuss the potential diagnostic or therapeutic approaches of miRNAs. Full article

(This article belongs to the Special Issue The Role of MicroRNA in Cancer)

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Figure 1
miRNA biogenesis and mechanism of action. miRNA production remains conserved across species. RNA polymerase II transcribes pri-miRNA from genome sequence. Drosha and its cofactor protein bind to primary miRNAs (pri-miRNA) leading to the excision of the loop structure to generate precursor miRNA (pre-miRNA). Then Exportin-5 transports pre-miRNA from nucleus to cytosol. Dicer complex, composed of TAR RNA-binding protein (TRBP) and protein activator of the interferon-induced protein kinase (PACT), manipulates maturation of miRNA and formation of RNA-induced silencing complex (RISC) complex. Mature RISC complex binds to target mRNA with complementary sites, resulting in the translational suppression or target degradation. Full article ">Figure 2
miRNAs modulate different hallmarks of cancer. miRNAs manipulate a set of biological processes that ultimately influences the proliferation and migration of cancer cells. ADAMDEC1, a disintegrin and metalloproteinase domain-like protein decysin 1; FEF2, Fibroblast growth factor 2; FGFR1, FGF receptor 1; ZEB1, Zinc-finger E-box-binding homeobox 1; PRKD1, serine/threonine-protein kinase D1; EMT, Epithelial–mesenchymal transition; PDCD7, Programmed Cell Death 7; CCND1, cyclin D1; p21, cyclin dependent kinase inhibitor 1A; THBS2, Thrombospondin-2. Full article ">Figure 3
Chemical modifications and delivery system of miRNA in vivo application. The chemical modifications of miRNA mimics and antimiRs increase their stability to ensure the integrality of miRNA-based therapeutic particles, while development of delivery systems facilitates the efficiency of miRNA therapy in vivo. Some of the commonly used delivery vehicles includes adenoviral vector, Poly (lactide-co-glycolide) (PGLA), EnGeneIC Delivery Vehicle (EDV) nanocells and polyethylenimine (PEI) molecules. Safety issue as well as tumor-specific delivery systems are still tested in animal models and clinical trials. Full article ">

24 pages, 59957 KiB

Open AccessReview

Dermoscopic Criteria, Histopathological Correlates and Genetic Findings of Thin Melanoma on Non-Volar Skin

by Cesare Massone, Rainer Hofman-Wellenhof, Stefano Chiodi and Simona Sola

Genes 2021, 12(8), 1288; https://doi.org/10.3390/genes12081288 - 23 Aug 2021

Cited by 7 | Viewed by 3905

Abstract

Dermoscopy is a non-invasive, in vivo technique that allows the visualization of subsurface skin structures in the epidermis, at the dermoepidermal junction, and in the upper dermis. Dermoscopy brought a new dimension in evaluating melanocytic skin neoplasms (MSN) also representing a link between [...] Read more.

Dermoscopy is a non-invasive, in vivo technique that allows the visualization of subsurface skin structures in the epidermis, at the dermoepidermal junction, and in the upper dermis. Dermoscopy brought a new dimension in evaluating melanocytic skin neoplasms (MSN) also representing a link between clinical and pathologic examination of any MSN. However, histopathology remains the gold standard in diagnosing MSN. Dermoscopic–pathologic correlation enhances the level of quality of MSN diagnosis and increases the level of confidence of pathologists. Melanoma is one of the most genetically predisposed among all cancers in humans. The genetic landscape of melanoma has been described in the last years but is still a field in continuous evolution. Melanoma genetic markers play a role not only in melanoma susceptibility, initiation, and progression but also in prognosis and therapeutic decisions. Several studies described the dermoscopic specific criteria and predictors for melanoma and their histopathologic correlates, but only a few studies investigated the correlation among dermoscopy, pathology, and genetic of MSN. The aim of this work is to review the published data about dermoscopic features of melanoma, their histopathological correlates with regards also to genetic alterations. Particularly, this review will focus on low-CSD (cumulative sun damage) melanoma or superficial spreading melanoma, high-CSD melanoma, and nevus-associated melanoma. Full article

(This article belongs to the Special Issue Skin Cancer: Genetics, Diagnosis and Prevention)

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Superficial spreading melanoma (T1a, Breslow 0.5 mm) on the abdomen of an 82-y old man. This de novo slow-growing melanoma shows on polarized contact dermoscopy (Dermalite ProHR®, 3Gen, San Juan Capistrano, CA USA) an asymmetric polychromatic multicomponent pattern with atypical pigment network (Panel A: labeled ^), white regression (Panel A: labeled *), structureless blue pigmentation (Panel A: labeled °) and structureless brown-blue bichromatic areas (Panel A: labeled +). The atypical network correlates with the hyperpigmented rete ridges with atypical melanocytes in single units and irregular nests mostly arranged at the DEJ (Panel C: labeled ^); the presence of a heavy lymphohistiocytic infiltrate with melanophages and acanthosis of the epidermis and heavily pigmented atypical nest and melanocytes in the epidermis are responsible for the structureless blue pigmentation (Panel C: labeled °). Panel B shows in the dermis fibrosis with a lymphohistiocytic infiltrate that correlates with the area of regression (Panel B: labeled *) while the atypical melanocytes in single units and irregular nests mostly arranged at the DEJ and the melanophages in the dermis correlate with structureless bichromatic brown-blue areas (Panel B,D: labeled +). (original magnification: Panel B,C: HE, 40×; Panel D: HE, 100×). Full article ">Figure 2
Superficial spreading melanoma (T1a, Breslow 0.53 mm) on the left chest of a 44-y old man. Panel A: Polarized contact dermoscopy (Dermaview®, Tre T Medical, Camposano, NA, Italy) shows asymmetry, multiple colors, pseudopods (labeled *), atypical network, structureless black areas (labeled °), structureless blue areas (labeled ^), irregular globules (labeled +) and dots. Pseudopods correlate with peripheral, confluent, and heavily pigmented atypical junctional nests of melanocytes (Panel B; HE: 100×). Irregular globules correspond to irregularly large atypical nests of melanocytes at the DEJ (Panel C; HE: 100×) while irregular dots to small atypical nests of melanocytes or irregular clumps of melanin in the epidermis (Panel D; HE: 100×). The structureless black and blue areas are related to the heavy band-like lymphohistiocytic infiltrate with melanophages in the dermis. Full article ">Figure 3
Melanoma in situ on the left flank of a 62-y old man. This small diameter melanoma showed upon polarized contact dermoscopy (Dermaview®, Tre T Medical, Camposano, NA, Italy) an asymmetric growth at 1-year digital follow-up (Panel A,B), atypical network, structureless brown areas, and irregular pigmented areas. Histology (Panel C; HE, ×100) shows a proliferation of atypical melanocytes in single units and nest in all layers of the epidermis and a dense lymphohistiocytic infiltrate with melanophages in the dermis. Pagetoid spread is confirmed also by Melan-A staining (Panel E, 200×). The irregular pigmented areas correlate with the clumps of melanin and pigmented parakeratosis (Panel D; 200×); the structureless brown areas correlate with the dense lymphohistiocytic infiltrate with melanophages in the dermis. Full article ">Figure 4
Nevus-associated melanoma in a 76-y old woman on the right buttock. Polarized contact dermoscopy (Panel A; Dermalite ProHR®, 3Gen, San Juan Capistrano, CA, USA) shows an asymmetric lesion with central hypopigmented-brown structureless areas and an atypical network on the right side. Histology shows an asymmetric melanocytic lesion composed on the left side by a dermal proliferation of monomorphous melanocytes with maturation (corresponding to the central hypopigmented-brown-structureless areas) and on the right shoulder elongated rete-ridges with atypical melanocytes in single units and irregular nests in all the epidermal layers, correlating to the atypical network (Panel B; HE: 20×). The Melan-A staining highlights the pagetoid spread (Panel C: ×20; Panel D: 200×). Full article ">Figure 5
Lentigo maligna on the left temporal region of a 77-y old man. Panel A: asymmetric, irregularly pigmented macule. Panel B: polarized contact dermoscopy (Dermaview®, Tre T Medical, Camposano, NA, Italy) shows asymmetry and multiple colors; asymmetric pigmentation of the hair follicles, dots, and annular-granular pattern. Panel C,D: Histology shows atypical melanocytes and irregular nests at the DEJ and in the epidermis with involvement of the hair follicles (correlate with the asymmetric pigmentation of the hair follicles); in the dermis, there is prominent solar elastosis, melanophages (correlate with the dots and annular-granular pattern) and a discrete lymphohistiocytic infiltrate. (Panel C,D: HE, 400×). Full article ">

15 pages, 2393 KiB

Open AccessArticle

Evolution and Functional Characteristics of the Novel elovl8 That Play Pivotal Roles in Fatty Acid Biosynthesis

by Shouxiang Sun, Yumei Wang, Pei-Tian Goh, Mónica Lopes-Marques, L. Filipe C. Castro, Óscar Monroig, Meng-Kiat Kuah, Xiaojuan Cao, Alexander Chong Shu-Chien and Jian Gao

Genes 2021, 12(8), 1287; https://doi.org/10.3390/genes12081287 - 23 Aug 2021

Cited by 19 | Viewed by 3950

Abstract

Elongation of very long-chain fatty acid (Elovl) proteins are key enzymes that catalyze the rate-limiting step in the fatty acid elongation pathway. The most recently discovered member of the Elovl family, Elovl8, has been proposed to be a fish-specific elongase with two gene [...] Read more.

Elongation of very long-chain fatty acid (Elovl) proteins are key enzymes that catalyze the rate-limiting step in the fatty acid elongation pathway. The most recently discovered member of the Elovl family, Elovl8, has been proposed to be a fish-specific elongase with two gene paralogs described in teleosts. However, the biological functions of Elovl8 are still to be elucidated. In this study, we showed that in contrast to previous findings, elovl8 is not unique to teleosts, but displays a rather unique and ample phylogenetic distribution. For functional determination, we generated elovl8a (elovl8a⁻^/−) and elovl8b (elovl8b⁻^/−) zebrafish using CRISPR/Cas9 technology. Fatty acid composition in vivo and zebrafish liver cell experiments suggest that the substrate preference of Elovl8 overlapped with other existing Elovl enzymes. Zebrafish Elovl8a could elongate the polyunsaturated fatty acids (PUFAs) C18:2n-6 and C18:3n-3 to C20:2n-6 and C20:3n-3, respectively. Along with PUFA, zebrafish Elovl8b also showed the capacity to elongate C18:0 and C20:1. Gene expression quantification suggests that Elovl8a and Elovl8b may play a potentially important role in fatty acid biosynthesis. Overall, our results provide novel insights into the function of Elovl8a and Elovl8b, representing additional fatty acid elongases not previously described in chordates. Full article

(This article belongs to the Section Animal Genetics and Genomics)

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20 pages, 300 KiB

Open AccessReview

Genetic Determinants of Inherited Endocrine Tumors: Do They Have a Direct Role in Bone Metabolism Regulation and Osteoporosis?

by Francesca Marini, Francesca Giusti, Teresa Iantomasi and Maria Luisa Brandi

Genes 2021, 12(8), 1286; https://doi.org/10.3390/genes12081286 - 23 Aug 2021

Cited by 1 | Viewed by 2167

Abstract

Endocrine tumors are neoplasms originating from specialized hormone-secreting cells. They can develop as sporadic tumors, caused by somatic mutations, or in the context of familial Mendelian inherited diseases. Congenital forms, manifesting as syndromic or non-syndromic diseases, are caused by germinal heterozygote autosomal dominant [...] Read more.

Endocrine tumors are neoplasms originating from specialized hormone-secreting cells. They can develop as sporadic tumors, caused by somatic mutations, or in the context of familial Mendelian inherited diseases. Congenital forms, manifesting as syndromic or non-syndromic diseases, are caused by germinal heterozygote autosomal dominant mutations in oncogenes or tumor suppressor genes. The genetic defect leads to a loss of cell growth control in target endocrine tissues and to tumor development. In addition to the classical cancer manifestations, some affected patients can manifest alterations of bone and mineral metabolism, presenting both as pathognomonic and/or non-specific skeletal clinical features, which can be either secondary complications of endocrine functioning primary tumors and/or a direct consequence of the gene mutation. Here, we specifically review the current knowledge on possible direct roles of the genes that cause inherited endocrine tumors in the regulation of bone modeling and remodeling by exploring functional in vitro and in vivo studies highlighting how some of these genes participate in the regulation of molecular pathways involved in bone and mineral metabolism homeostasis, and by describing the potential direct effects of gene mutations on the development of skeletal and mineral metabolism clinical features in patients. Full article

(This article belongs to the Special Issue Key Genetic Determinants of Osteoporosis: From Bench to Bedside)

21 pages, 1438 KiB

Open AccessArticle

Genetic Background and Antibiotic Resistance Profiles of K. pneumoniae NDM-1 Strains Isolated from UTI, ABU, and the GI Tract, from One Hospital in Poland, in Relation to Strains Nationally and Worldwide

by Magdalena Wysocka, Roxana Zamudio, Marco R. Oggioni, Justyna Gołębiewska, Marek Bronk and Beata Krawczyk

Genes 2021, 12(8), 1285; https://doi.org/10.3390/genes12081285 - 22 Aug 2021

Cited by 5 | Viewed by 2863

Abstract

In recent years, there has been an observed increase in infections caused by carbapenem-resistant Klebsiella pneumonia (Kp) strains. The aim of this study was the phenotypic and genotypic analysis of eight K. pneumoniae NDM (Kp NDM) isolates, recovered in Poland during the years [...] Read more.

In recent years, there has been an observed increase in infections caused by carbapenem-resistant Klebsiella pneumonia (Kp) strains. The aim of this study was the phenotypic and genotypic analysis of eight K. pneumoniae NDM (Kp NDM) isolates, recovered in Poland during the years 2016 and 2018 from seven patients with urinary tract infections (UTIs), asymptomatic bacteriuria (ABU), or colonization of the gut. PCR melting profile genotyping indicated a close relationship between the strains derived from 2018, which were not related to the strain isolated in 2016. WGS results were analyzed in relation to international Kp isolates. Clonal and phylogenetic analyses were performed based on multilocus sequence typing (MLST) and single nucleotide polymorphisms (SNPs) of the core genome. The metallo-β-lactamase was assigned to the NDM-1 type and the sequence was identified as ST11. Eleven antimicrobial resistance genes were detected, mostly from plasmid contigs. Unprecedented profiles of plasmid replicons were described with the IncFII/pKPX-1 dominant replicon. In terms of the KL24 and O2v1 capsular antigen profiles, these isolates corresponded to Greek strains. Strains isolated from UTI, ABU, and colonization GI tract patients were not carrying environment-specific virulence genes. Based on the assessment of strain relationships at the genome level and their direction of evolution, the international character of the sublines was demonstrated, with a documented epidemic potential in Poland and Greece. In conclusion, some groups of patients, e.g., renal transplant recipients or those with complicated UTIs, who are frequently hospitalized and undergoing antibiotic therapy, should be monitored not only for the risk of UTI, but also for colonization by Kp NDM strains. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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Graphical abstract
Full article ">Figure 1
Genetic relatedness of 7 K. pneumoniae NDM-1 strains isolated from six patients and a reference K. pneumoniae NDM-1 strain (from another hospital used as a control) based on the PCR MP method. A dendrogram of similarity of the genetic profiles of the tested strains was developed using FPQuest Software version 4.5 (BIO-RAD) (Dice, UPGMA). Cp—the complete similarity equal to 73%; Pi—the level of identity equal to 96%; unique genotypes (Gp) are marked with the letters A–C; IS—isolate; P—patient. Full article ">Figure 2
K. pneumoniae core-gene phylogenetic tree. A maximum likelihood phylogenetic tree was constructed using 4014 core genes with the genome sequences of 180 K. pneumoniae isolates. The cluster numbers (#1–#10) are labelled on the phylogenetic tree and the colour of the circle in the external node is linked to the cluster (purple—cluster no. 1, cyan—cluster no. 2, green—cluster no. 3, black—cluster no. 4, pink—cluster no. 5, orange—cluster no. 6, red—cluster no. 7, yellow—cluster no. 8, blue—cluster no. 9, magenta—cluster no. 10). The origin of the isolates is distinguished by font colours in the tree: light blue—isolates sequenced in this work; blue—from Poland; deep blue—from Europe; black—from other countries. The sequence type (ST) is indicated for each isolate, following the isolate name. Numbers after the isolate name correspond to original numbers of the study isolates or GenBank assembly numbers. In the heatmap, the presence of the blaNDM-1 gene is indicated by red (present) or gray (absent) and the presence/absence profile of the genotype for 60 genes encoding antimicrobial resistance (green—present, gray—absent), 11 genes encoding virulence determinants (blue—present, gray—absent), and 40 plasmid replicons is indicated. Full article ">

19 pages, 2561 KiB

Open AccessEditor’s ChoiceArticle

Development and Evaluation of the Ancestry Informative Marker Panel of the VISAGE Basic Tool

by María de la Puente, Jorge Ruiz-Ramírez, Adrián Ambroa-Conde, Catarina Xavier, Jacobo Pardo-Seco, Jose Álvarez-Dios, Ana Freire-Aradas, Ana Mosquera-Miguel, Theresa E. Gross, Elaine Y. Y. Cheung, Wojciech Branicki, Michael Nothnagel, Walther Parson, Peter M. Schneider, Manfred Kayser, Ángel Carracedo, Maria Victoria Lareu, Christopher Phillips and on behalf of the VISAGE Consortium

Genes 2021, 12(8), 1284; https://doi.org/10.3390/genes12081284 - 22 Aug 2021

Cited by 21 | Viewed by 5237

Abstract

We detail the development of the ancestry informative single nucleotide polymorphisms (SNPs) panel forming part of the VISAGE Basic Tool (BT), which combines 41 appearance predictive SNPs and 112 ancestry predictive SNPs (three SNPs shared between sets) in one massively parallel sequencing (MPS) [...] Read more.

We detail the development of the ancestry informative single nucleotide polymorphisms (SNPs) panel forming part of the VISAGE Basic Tool (BT), which combines 41 appearance predictive SNPs and 112 ancestry predictive SNPs (three SNPs shared between sets) in one massively parallel sequencing (MPS) multiplex, whereas blood-based age analysis using methylation markers is run in a parallel MPS analysis pipeline. The selection of SNPs for the BT ancestry panel focused on established forensic markers that already have a proven track record of good sequencing performance in MPS, and the overall SNP multiplex scale closely matched that of existing forensic MPS assays. SNPs were chosen to differentiate individuals from the five main continental population groups of Africa, Europe, East Asia, America, and Oceania, extended to include differentiation of individuals from South Asia. From analysis of 1000 Genomes and HGDP-CEPH samples from these six population groups, the BT ancestry panel was shown to have no classification error using the Bayes likelihood calculators of the Snipper online analysis portal. The differentiation power of the component ancestry SNPs of BT was balanced as far as possible to avoid bias in the estimation of co-ancestry proportions in individuals with admixed backgrounds. The balancing process led to very similar cumulative population-specific divergence values for Africa, Europe, America, and Oceania, with East Asia being slightly below average, and South Asia an outlier from the other groups. Comparisons were made of the African, European, and Native American estimated co-ancestry proportions in the six admixed 1000 Genomes populations, using the BT ancestry panel SNPs and 572,000 Affymetrix Human Origins array SNPs. Very similar co-ancestry proportions were observed down to a minimum value of 10%, below which, low-level co-ancestry was not always reliably detected by BT SNPs. The Snipper analysis portal provides a comprehensive population dataset for the BT ancestry panel SNPs, comprising a 520-sample standardised reference dataset; 3445 additional samples from 1000 Genomes, HGDP-CEPH, Simons Foundation and Estonian Biocentre genome diversity projects; and 167 samples of six populations from in-house genotyping of individuals from Middle East, North and East African regions complementing those of the sampling regimes of the other diversity projects. Full article

(This article belongs to the Special Issue Advances in Forensic Genetics)

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Figure 1
Accumulating population specific divergence values for each of the main population groups and the six sets of SNPs informative for their differentiation. The cumulative values are shown obtained from 88 binary SNPs (i.e., excluding 12 Eurasian-informative SNPs) and from the addition of the 15 tri-allelic SNPs in BT (VISAGE Basic Tool). Full article ">Figure 2
The 38 BT ancestry SNPs with the highest numbers of discordant genotypes between 1000 Genomes low coverage vs. high coverage sequence data. An additional 29 had only one discordant genotype. The full set of genotype comparisons for all BT SNPs and all 1000 Genomes samples are given in <a href="#app1-genes-12-01284" class="html-app">File S3B</a>. Full article ">Figure 3
Ancestry analysis with 115 BT ancestry SNPs of the six populations of the standardised reference dataset (AFR: brown; EUR: blue; SAS: yellow; EAS: pink; OCE: green; AMR: purple), with consistent colours across three statistical analyses of A, C and D. (A) STRUCTURE cluster membership proportions at K = 6, indicated to be the optimum K number of genetic clusters by: (B) the mean L(K) (log probability of data) and ΔK plots from STRUCTURE runs, following the analyses of Evanno et al. [<a href="#B31-genes-12-01284" class="html-bibr">31</a>]. (C) Multi-dimensional scaling (MDS) analysis showing principal component (PC) 1 vs. PC2 coordinates, PC1 vs. PC3 and PC2 vs. PC3 two-dimensional plots. (D) Neighbour joining tree (NJT) analysis. (E) Summary classification success table of cross validation of the standardised reference set. Full article ">Figure 4
Pairwise comparison of individual co-ancestry proportions (cluster membership proportions) in 504 admixed samples from 1000 Genomes, analysed using the standardised reference set with Human Origins array, comprising >572,000 SNPs (using ADMIXTURE) and 115 VISAGE BT ancestry SNPs (using STRUCTURE). Co-ancestry proportions in four genetic clusters representing, African, European, Native American and East Asian, ancestries are given in <a href="#app1-genes-12-01284" class="html-app">File S4</a>. The r2 correlation analysis plots of each admixed population group are shown below the corresponding cluster patterns. Full article ">

14 pages, 1825 KiB

Open AccessArticle

When Two plus Two Is More than Four: Evidence for a Synergistic Effect of Fatty Acids on Peroxisome Proliferator—Activated Receptor Activity in a Bovine Hepatic Model

by Sebastiano Busato and Massimo Bionaz

Genes 2021, 12(8), 1283; https://doi.org/10.3390/genes12081283 - 21 Aug 2021

Cited by 8 | Viewed by 2703

Abstract

The inclusion of fat in livestock diets represents a valuable and cost-effective way to increase the animal’s caloric intake. Beyond their caloric value, fatty acids can be understood in terms of their bioactivity, via the modulation of the ligand-dependent nuclear peroxisome proliferator-activated receptors [...] Read more.

The inclusion of fat in livestock diets represents a valuable and cost-effective way to increase the animal’s caloric intake. Beyond their caloric value, fatty acids can be understood in terms of their bioactivity, via the modulation of the ligand-dependent nuclear peroxisome proliferator-activated receptors (PPAR). Isotypes of PPAR regulate important metabolic processes in both monogastric and ruminant animals, including the metabolism of fatty acids (FA), the production of milk fat, and the immune response; however, information on the modulation of bovine PPAR by fatty acids is limited. The objective of this study was to expand our understanding on modulation of bovine PPAR by FA, both when used individually and in combination, in an immortalized cell culture model of bovine liver. Of the 10 FA included in the study, the greatest activation of the PPAR reporter was detected with saturated FA C12:0, C16:0, and C18:0, as well as phytanic acid, and the unsaturated FA C16:1 and C18:1. When supplemented in mixtures of 2 FA, the most effective combination was C12:0 + C16:0, while in mixtures of 3 FA, the greatest activation was caused by combinations of C12:0 with C16:0 and either C18:0, C16:1, or C18:1. Some mixtures display a synergistic effect that leads to PPAR activation greater than the sum of their parts, which may be explained by structural dynamics within the PPAR ligand-binding pocket. Our results provide fundamental information for the development of tailored dietary plans that focus on the use of FA mixtures for nutrigenomic purposes. Full article

(This article belongs to the Special Issue Nutrigenomics in Dairy Animals)

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Activation of the PPAR reporter at specified doses of fatty acids octanoic acid (A), decanoic acid (B), dodecanoic acid (C), myristic acid (D), palmitic acid (E), palmitoleic acid (F), stearic acid (G), oleic acid (H), linoleic acid (I), and phytanic acid (J). Shown in each graph: significance level of the model (L = linear, Q = quadratic, C = cubic) and adjusted R2. Interpolations are presented as trend lines surrounded by a 95% confidence interval (dotted lines). Full article ">Figure 2
PPAR activation by combinations of two fatty acids. Compound doses are: C12:0, 500; C16:0, 158; C16:1, 158; C18:0, 190; C18:1, 158; C20:0 BCFA, 158 µM. Dissimilar letters above bars refer to statistically significant (p < 0.05) difference between each treatment when all pairwise comparisons are considered; green cells below the graph indicate significant differences (p < 0.05) in PPAR activation between the mixture and the individual fatty acid within the mixture reported on the left, when considering pairwise comparisons between the various mixture containing the fatty acid and the individual fatty acid, while gray cells indicate no significant differences (p > 0.05). Full article ">Figure 3
PPAR activation by combinations of three fatty acids. Compound doses are: C12:0, 167; C16:0, 53; C16:1, 53; C18:0, 63; C18:1, 53; C20:0 BCFA, 53 µM. Dissimilar letters above bars refer to statistically significant (p < 0.05) difference between each treatment when all pairwise comparisons are considered; green cells below the graph indicate significant differences (p < 0.05) in PPAR activation between the mixture and the individual fatty acid within the mixture reported on the left, when considering pairwise comparisons between the various mixture containing the fatty acid and the individual fatty acid, while gray cells indicate no significant differences (p > 0.05). Full article ">Figure 4
Dot plot comparing mean of experimentally measured PPAR activation by combinations of two (A) or three (B) fatty acids, when compared to the hypothetical weighted average model (red dots) and additive model (blue dots). Diagonal line represents threshold where ratio of actual/expected activation is equal to 1. Labeled in the figure: mixtures with an actual/expected activation ratio greater than one. (12 = dodecanoic acid; 16 = palmitic acid; 16:1 = palmitoleic acid; 18 = stearic acid; 18:1 = oleic acid; 20B = phytanic acid). Full article ">

15 pages, 1725 KiB

Open AccessArticle

A Novel Missense Mutation in TNNI3K Causes Recessively Inherited Cardiac Conduction Disease in a Consanguineous Pakistani Family

by Shafaq Ramzan, Stephanie Tennstedt, Muhammad Tariq, Sheraz Khan, Hafiza Noor Ul Ayan, Aamir Ali, Matthias Munz, Holger Thiele, Asad Aslam Korejo, Abdul Razzaq Mughal, Syed Zahid Jamal, Peter Nürnberg, Shahid Mahmood Baig, Jeanette Erdmann and Ilyas Ahmad

Genes 2021, 12(8), 1282; https://doi.org/10.3390/genes12081282 - 21 Aug 2021

Cited by 8 | Viewed by 4325

Abstract

Cardiac conduction disease (CCD), which causes altered electrical impulse propagation in the heart, is a life-threatening condition with high morbidity and mortality. It exhibits genetic and clinical heterogeneity with diverse pathomechanisms, but in most cases, it disrupts the synchronous activity of impulse-generating nodes [...] Read more.

Cardiac conduction disease (CCD), which causes altered electrical impulse propagation in the heart, is a life-threatening condition with high morbidity and mortality. It exhibits genetic and clinical heterogeneity with diverse pathomechanisms, but in most cases, it disrupts the synchronous activity of impulse-generating nodes and impulse-conduction underlying the normal heartbeat. In this study, we investigated a consanguineous Pakistani family comprised of four patients with CCD. We applied whole exome sequencing (WES) and co-segregation analysis, which identified a novel homozygous missense mutation (c.1531T>C;(p.Ser511Pro)) in the highly conserved kinase domain of the cardiac troponin I-interacting kinase (TNNI3K) encoding gene. The behaviors of mutant and native TNNI3K were compared by performing all-atom long-term molecular dynamics simulations, which revealed changes at the protein surface and in the hydrogen bond network. Furthermore, intra and intermolecular interaction analyses revealed that p.Ser511Pro causes structural variation in the ATP-binding pocket and the homodimer interface. These findings suggest p.Ser511Pro to be a pathogenic variant. Our study provides insights into how the variant perturbs the TNNI3K structure-function relationship, leading to a disease state. This is the first report of a recessive mutation in TNNI3K and the first mutation in this gene identified in the Pakistani population. Full article

(This article belongs to the Special Issue Recent Advance in Cardiovascular Genetics)

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Figure 1
Pedigree, sequencing chromatogram, and location of the TNNI3K variant in the family with cardiac conduction disease (CCD). (a) Family pedigree. The open symbols represent unaffected individuals and the filled symbols represent affected individuals; symbols with a diagonal line represent deceased individuals; and the arrowhead designates the proband. An asterisk indicates family members from whom DNA was available. The genotypes of the TNNI3K mutation are indicated below each examined member: CC (homozygote); TC (heterozygote); number inside the circle denote the number of individuals. (b) Sequencing chromatograms. Vertical arrows indicate the mutation site. (c) Schematic of the human TNNI3K gene. The positions of coding exons (black) and UTRs (white) are indicated. Black arrows indicate previously reported pathogenic variants and the red arrow shows the novel variant c.1531T>C in exon 16. (d) Initial 3D structure of TNNI3K-WT (PDB-ID: 4YFI [<a href="#B29-genes-12-01282" class="html-bibr">29</a>]) shown as a ribbon. Monomer I is shown in gray and monomer II in green. The Cα atoms of Ser511 (red), Gly526 (blue), and Thr539 (blue) of monomer I are shown in spheres relative to the ATP-binding pocket (orange surface) of monomer I. Gly526 and Thr539 are known TNNI3K missense variants. (e) TNNI3K protein domain structure. Coiled coil domain (gray); functional ankyrin repeat domains, ANK1–ANK10 (purple); kinase domain (orange), where the homozygous mutation p.Ser511Pro resides (arrowed); and a serine-rich domain (spring green). Full article ">Figure 2
Root mean square fluctuation, hydrogen bond analysis, and electrostatic surface potential map. (a) Comparison of root mean square fluctuation values of TNNI3K-WT (green) and TNNI3K-S511P (blue) during three independent 1 µs MD simulations with error bars. Alignments and measurements were performed for the Cα carbon atoms. (b) Hydrogen bond analysis. Length of the hydrogen bonds between Cys507 and Ser511 in TNNI3K-WT as a mean value of three independent MD simulations (1 µs). (c,d) A comparison of the electrostatic surface potential of TNNI3K-WT (c) and TNNI3K-S511P (d), demonstrating that p.Ser511Pro leads to a more hydrophobic protein surface (“red white blue” color ramp with a minimum of −0.3 and a maximum of 0.3). Full article ">Figure 3
Average intra/inter residue-residue contact maps and MM/GBSA analysis. (a) Contact map of the residues of helix 2 in monomer I and the residues of the corresponding monomer, and (b) residues of helix 2 in monomer II and the residues of the corresponding monomer. Each point represents the mean of the average residue-residue contact difference between TNNI3K-WT and TNNI3K-S511P over the last 200 ns from the three independent MD simulations (spectrum range from green to white to blue, from 100% to −100% contact; green means more contacts in TNNI3K-WT and blue means more contacts in TNNI3K-S511P). (c) Contact map between residue-residue pairs in the dimer interface for TNNI3K-WT vs. TNNI3K-S511P. The contact spectrum ranging from green to white to blue, representing 100% to −100% contact, where green indicates more contacts in TNNI3K-WT and blue indicates more contacts in TNNI3K-S511P. Each point represents the mean difference in the residue-residue contact over the last 200 ns from the three independent MD simulations. (d) MM/GBSA analysis applied for dimerization of TNNI3K. Every 10th snapshot of the last 200 ns of the MD simulation was used. Each violin plot represents the mean from the three independent simulations (95% confidence interval). Full article ">

18 pages, 1062 KiB

Open AccessReview

Current Epigenetic Insights in Kidney Development

by Katrina Chan and Xiaogang Li

Genes 2021, 12(8), 1281; https://doi.org/10.3390/genes12081281 - 21 Aug 2021

Cited by 7 | Viewed by 6550

Abstract

The kidney is among the best characterized developing tissues, with the genes and signaling pathways that regulate embryonic and adult kidney patterning and development having been extensively identified. It is now widely understood that DNA methylation and histone modification patterns are imprinted during [...] Read more.

The kidney is among the best characterized developing tissues, with the genes and signaling pathways that regulate embryonic and adult kidney patterning and development having been extensively identified. It is now widely understood that DNA methylation and histone modification patterns are imprinted during embryonic development and must be maintained in adult cells for appropriate gene transcription and phenotypic stability. A compelling question then is how these epigenetic mechanisms play a role in kidney development. In this review, we describe the major genes and pathways that have been linked to epigenetic mechanisms in kidney development. We also discuss recent applications of single-cell RNA sequencing (scRNA-seq) techniques in the study of kidney development. Additionally, we summarize the techniques of single-cell epigenomics, which can potentially be used to characterize epigenomes at single-cell resolution in embryonic and adult kidneys. The combination of scRNA-seq and single-cell epigenomics will help facilitate the further understanding of early cell lineage specification at the level of epigenetic modifications in embryonic and adult kidney development, which may also be used to investigate epigenetic mechanisms in kidney diseases. Full article

(This article belongs to the Special Issue Current Genetic Insights in Organ Development)

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Formation of nephrons in the metanephros. The ureteric bud signals for the metanephric mesenchyme to form a cap around it, which signals the formation of the renal vesicle. The vesicle elongates into the comma-shaped, then the S-shaped body, before attaching to the ureteric bud branch and further differentiating into a nephron. The nephron continues to elongate and mature throughout the prenatal period. Full article ">Figure 2
Major genes and signaling pathways in the formation of the ureteric bud branches, mesenchyme cap and subsequent nephrons. (A) Regulatory signaling pathways identified in the early metanephric mesenchyme. Foxd1 regulates specification of the metanephric mesenchyme to form the ureteric bud cap. Vegf, Six2 and Wnt11 are vital early progenitor factors that activate the Gdnf/Ret pathway for the proper branching of the ureteric bud and subsequent nephron formation. Fgf1 also contributes to proper ureteric bud branching in the ureteric bud. Fgf20 regulates Fgf1/2 in the formation of the ureteric cap. β-catenin mediated the induction of Wnt9 regulates Wnt4 and Fgf8, which are critical for renal vesicle formation. (B) Key genetic markers identified in the metanephric mesenchyme and nascent nephrons. Hoxa11 and Hoxd11 regulate ureteric bud growth. Six1 and Six2 are important for continued mesenchyme differentiation. Pax2 and Pax8 are important for continued nephric duct formation. E-cadherin and the other cadherins indicate the segmentation of the S-shaped body, and E-cadherin is expressed in the distal segments where the S-shaped body joins the ureteric bud. Pdfgr plays a role in the formation of the glomerulus. Full article ">

13 pages, 5521 KiB

Open AccessArticle

PlantMirP2: An Accurate, Fast and Easy-To-Use Program for Plant Pre-miRNA and miRNA Prediction

by Dashuai Fan, Yuangen Yao and Ming Yi

Genes 2021, 12(8), 1280; https://doi.org/10.3390/genes12081280 - 21 Aug 2021

Cited by 6 | Viewed by 2753

Abstract

MicroRNAs (miRNAs) are a kind of short non-coding ribonucleic acid molecules that can regulate gene expression. The computational identification of plant miRNAs is of great significance to understanding biological functions. In our previous studies, we have put firstly forward and further developed a [...] Read more.

MicroRNAs (miRNAs) are a kind of short non-coding ribonucleic acid molecules that can regulate gene expression. The computational identification of plant miRNAs is of great significance to understanding biological functions. In our previous studies, we have put firstly forward and further developed a set of knowledge-based energy features to construct two plant pre-miRNA prediction tools (plantMirP and riceMirP). However, these two tools cannot be used for miRNA prediction from NGS (Next-Generation Sequencing) data. In addition, for further improving the prediction performance and accessibility, plantMirP2 has been developed. Based on the latest dataset, plantMirP2 achieves a promising performance: 0.9968 (Area Under Curve, AUC), 0.9754 (accuracy), 0.9675 (sensitivity) and 0.9876 (specificity). Additionally, the comparisons with other plant pre-miRNA tools show that plantMirP2 performs better. Finally, the webserver and stand-alone version of plantMirP2 are available. Full article

(This article belongs to the Section Bioinformatics)

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21 pages, 1736 KiB

Open AccessArticle

Population Genomics Reveals Gene Flow and Adaptive Signature in Invasive Weed Mikania micrantha

by Xiaoxian Ruan, Zhen Wang, Yingjuan Su and Ting Wang

Genes 2021, 12(8), 1279; https://doi.org/10.3390/genes12081279 - 20 Aug 2021

Cited by 2 | Viewed by 3024

Abstract

A long-standing and unresolved issue in invasion biology concerns the rapid adaptation of invaders to nonindigenous environments. Mikania micrantha is a notorious invasive weed that causes substantial economic losses and negative ecological consequences in southern China. However, the contributions of gene flow, environmental [...] Read more.

A long-standing and unresolved issue in invasion biology concerns the rapid adaptation of invaders to nonindigenous environments. Mikania micrantha is a notorious invasive weed that causes substantial economic losses and negative ecological consequences in southern China. However, the contributions of gene flow, environmental variables, and functional genes, all generally recognized as important factors driving invasive success, to its successful invasion of southern China are not fully understood. Here, we utilized a genotyping-by-sequencing approach to sequence 306 M. micrantha individuals from 21 invasive populations. Based on the obtained genome-wide single nucleotide polymorphism (SNP) data, we observed that all the populations possessed similar high levels of genetic diversity that were not constrained by longitude and latitude. Mikania micrantha was introduced multiple times and subsequently experienced rapid-range expansion with recurrent high gene flow. Using F_ST outliers, a latent factor mixed model, and the Bayesian method, we identified 38 outlier SNPs associated with environmental variables. The analysis of these outlier SNPs revealed that soil composition, temperature, precipitation, and ecological variables were important determinants affecting the invasive adaptation of M. micrantha. Candidate genes with outlier signatures were related to abiotic stress response. Gene family clustering analysis revealed 683 gene families unique to M. micrantha which may have significant implications for the growth, metabolism, and defense responses of M. micrantha. Forty-one genes showing significant positive selection signatures were identified. These genes mainly function in binding, DNA replication and repair, signature transduction, transcription, and cellular components. Collectively, these findings highlight the contribution of gene flow to the invasion and spread of M. micrantha and indicate the roles of adaptive loci and functional genes in invasive adaptation. Full article

(This article belongs to the Section Plant Genetics and Genomics)

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Sampling distribution of M. micrantha populations. The red dots represent 21 invasive populations from six regions, including Hong Kong, Macao, Shenzhen, Neilingding Island, Dongguan, and Zhuhai. Full article ">Figure 2
Principal component analysis (PCA) of the 306 M. micrantha individuals from 21 invasive populations. The top two principal components (PC1 and PC2) explained 4.022% and 2.526% of the total genetic variation, respectively. Full article ">Figure 3
Population genetic structure analysis of the 306 M. micrantha individuals inferred from the software ADMIXTURE. The height of each colored column represents the proportion of individual assigned to different genetic clusters. Full article ">Figure 4
The scatter plot from Bayesian outlier analysis of SNPs. The vertical black line shows the threshold of log10 (PO) = 2, and SNP loci with log10 (PO) > 2 were considered outlier SNPs. The blue and red circles represent the outlier SNPs with negative and positive α values, respectively. Full article ">Figure 5
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of 683 gene families unique to M. micrantha. Full article ">

13 pages, 677 KiB

Open AccessArticle

Prediction of Parkinson’s Disease Risk Based on Genetic Profile and Established Risk Factors

by Paraskevi P. Chairta, Andreas Hadjisavvas, Andrea N. Georgiou, Maria A. Loizidou, Kristia Yiangou, Christiana A. Demetriou, Yiolanda P. Christou, Marios Pantziaris, Kyriaki Michailidou and Eleni Zamba-Papanicolaou

Genes 2021, 12(8), 1278; https://doi.org/10.3390/genes12081278 - 20 Aug 2021

Cited by 5 | Viewed by 3071

Abstract

Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk [...] Read more.

Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors. Methods: Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors. Results: The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population. Conclusions: These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

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19 pages, 1306 KiB

Open AccessArticle

Benefits of Exome Sequencing in Children with Suspected Isolated Hearing Loss

by Roxane Van Heurck, Maria Teresa Carminho-Rodrigues, Emmanuelle Ranza, Caterina Stafuzza, Lina Quteineh, Corinne Gehrig, Eva Hammar, Michel Guipponi, Marc Abramowicz, Pascal Senn, Nils Guinand, Helene Cao-Van and Ariane Paoloni-Giacobino

Genes 2021, 12(8), 1277; https://doi.org/10.3390/genes12081277 - 20 Aug 2021

Cited by 11 | Viewed by 3444

Abstract

Purpose: Hearing loss is characterized by an extensive genetic heterogeneity and remains a common disorder in children. Molecular diagnosis is of particular benefit in children, and permits the early identification of clinically-unrecognized hearing loss syndromes, which permits effective clinical management and follow-up, including [...] Read more.

Purpose: Hearing loss is characterized by an extensive genetic heterogeneity and remains a common disorder in children. Molecular diagnosis is of particular benefit in children, and permits the early identification of clinically-unrecognized hearing loss syndromes, which permits effective clinical management and follow-up, including genetic counselling. Methods: We performed whole-exome sequencing with the analysis of a panel of 189 genes associated with hearing loss in a prospective cohort of 61 children and 9 adults presenting mainly with isolated hearing loss. Results: The overall diagnostic rate using exome sequencing was 47.2% (52.5% in children; 22% in adults). In children with confirmed molecular results, 17/32 (53.2%) showed autosomal recessive inheritance patterns, 14/32 (43.75%) showed an autosomal dominant condition, and one case had X-linked hearing loss. In adults, the two patients showed an autosomal dominant inheritance pattern. Among the 32 children, 17 (53.1%) had nonsyndromic hearing loss and 15 (46.7%) had syndromic hearing loss. One adult was diagnosed with syndromic hearing loss and one with nonsyndromic hearing loss. The most common causative genes were STRC (5 cases), GJB2 (3 cases), COL11A1 (3 cases), and ACTG1 (3 cases). Conclusions: Exome sequencing has a high diagnostic yield in children with hearing loss and can reveal a syndromic hearing loss form before other organs/systems become involved, allowing the surveillance of unrecognized present and/or future complications associated with these syndromes. Full article

(This article belongs to the Special Issue Genetics and Epigenetics of Hearing Loss)

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12 pages, 1814 KiB

Open AccessArticle

Hypomethylation of AHRR (cg05575921) Is Related to Smoking Status in the Mexican Mestizo Population

by Omar Andrés Bravo-Gutiérrez, Ramcés Falfán-Valencia, Alejandra Ramírez-Venegas, Raúl H. Sansores, Rafael de Jesús Hernández-Zenteno, Andrea Hernández-Pérez, Leonor García-Gómez, Jennifer Osio-Echánove, Edgar Abarca-Rojano and Gloria Pérez-Rubio

Genes 2021, 12(8), 1276; https://doi.org/10.3390/genes12081276 - 20 Aug 2021

Cited by 2 | Viewed by 3489

Abstract

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to [...] Read more.

Tobacco smoking results in a multifactorial disease involving environmental and genetic factors; epigenome-wide association studies (EWAS) show changes in DNA methylation levels due to cigarette consumption, partially reversible upon tobacco smoking cessation. Therefore, methylation levels could predict smoking status. This study aimed to evaluate the DNA methylation level of cg05575921 (AHRR) and cg23771366 (PRSS23) and their correlation with lung function variables, cigarette consumption, and nicotine addiction in the Mexican smoking population. We included 114 non-smokers (NS) and 102 current tobacco smokers (TS); we then further subclassified them as heavy smokers (HS) (n = 53) and light smokers (LS) (n = 49). We used restriction enzymes (MspI/HpaII) and qPCR to determine the DNA methylation level. We observed significant hypomethylation of cg05575921 in smokers compared to NS (p = 0.003); further analysis found a difference between HS and NS (p = 0.02). We did not observe differences between other groups or a positive correlation between methylation levels and age, BMI, cigarette consumption, nicotine addiction, or lung function. In conclusion, the cg05575921 site of AHRR is significantly hypomethylated in Mexican smokers, especially in HS (≥20 cigarettes per day). Full article

(This article belongs to the Special Issue Deciphering Epigenetic Signature in Human Health and Disease)

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Full article ">Figure 1
Patient selection process according to the STREGA guidelines [<a href="#B34-genes-12-01276" class="html-bibr">34</a>]. Full article ">Figure 2
Methylation percentage between smokers and non-smokers. (a) cg05575921 (AHRR) site and (b) cg23771366 (PRSS23) site; the p-value was obtained by the Mann–Whitney U test with a Bonferroni post-hoc correction. Full article ">Figure 3
Methylation percentage comparison between HS, LS, and NS; p-value by Bonferroni correction. (a) cg05575921 (AHRR) site and (b) cg23771366 (PRSS23) site. The p-value was obtained by the Kruskal–Wallis test with a post-hoc Dunn test. Full article ">Figure 4
Spearman correlation matrix in tobacco smokers’ group. (a) cg05575921 (AHRR) site and (b) cg23771366 (PRSS23) site. BMI, body mass index; FVC, forced vital capacity; FEV1, forced expiratory volume in the first second; cpd, cigarette per day; TI, tobacco index; FTND, Fagerström test for nicotine dependence. Full article ">Figure 5
Mean methylation percentage (with standard deviation error bars) of cg05575921 (AHRR) site. The red square represents the non-smokers’ group; blue circles represent European American and African American smokers. The green square and circle represent the data obtained in this study. 1, non-smokers and white ethnicity [<a href="#B32-genes-12-01276" class="html-bibr">32</a>]; 2, non-smokers in our study; 3, smokers with white ethnicity [<a href="#B32-genes-12-01276" class="html-bibr">32</a>]; 4, African American smokers [<a href="#B52-genes-12-01276" class="html-bibr">52</a>]; 5, European American smokers [<a href="#B52-genes-12-01276" class="html-bibr">52</a>]; and 6, smokers included in this study. Full article ">

14 pages, 602 KiB

Open AccessArticle

A Case Series of Familial ARID1B Variants Illustrating Variable Expression and Suggestions to Update the ACMG Criteria

by Pleuntje J. van der Sluijs, Mariëlle Alders, Alexander J. M. Dingemans, Kareesma Parbhoo, Bregje W. van Bon, Jennifer C. Dempsey, Dan Doherty, Johan T. den Dunnen, Erica H. Gerkes, Ilana M. Milller, Stephanie Moortgat, Debra S. Regier, Claudia A. L. Ruivenkamp, Betsy Schmalz, Thomas Smol, Kyra E. Stuurman, Catherine Vincent-Delorme, Bert B. A. de Vries, Bekim Sadikovic, Scott E. Hickey, Jill A. Rosenfeld, Isabelle Maystadt and Gijs W. E. Santen Show full author list Hide full author list

Genes 2021, 12(8), 1275; https://doi.org/10.3390/genes12081275 - 20 Aug 2021

Cited by 7 | Viewed by 4848

Abstract

ARID1B is one of the most frequently mutated genes in intellectual disability (~1%). Most variants are readily classified, since they are de novo and are predicted to lead to loss of function, and therefore classified as pathogenic according to the American College of [...] Read more.

ARID1B is one of the most frequently mutated genes in intellectual disability (~1%). Most variants are readily classified, since they are de novo and are predicted to lead to loss of function, and therefore classified as pathogenic according to the American College of Medical Genetics and Genomics (ACMG) guidelines for the interpretation of sequence variants. However, familial loss-of-function variants can also occur and can be challenging to interpret. Such variants may be pathogenic with variable expression, causing only a mild phenotype in a parent. Alternatively, since some regions of the ARID1B gene seem to be lacking pathogenic variants, loss-of-function variants in those regions may not lead to ARID1B haploinsufficiency and may therefore be benign. We describe 12 families with potential loss-of-function variants, which were either familial or with unknown inheritance and were in regions where pathogenic variants have not been described or are otherwise challenging to interpret. We performed detailed clinical and DNA methylation studies, which allowed us to confidently classify most variants. In five families we observed transmission of pathogenic variants, confirming their highly variable expression. Our findings provide further evidence for an alternative translational start site and we suggest updates for the ACMG guidelines for the interpretation of sequence variants to incorporate DNA methylation studies and facial analyses. Full article

(This article belongs to the Collection Study on Genotypes and Phenotypes of Pediatric Clinical Rare Diseases)

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20 pages, 5499 KiB

Open AccessArticle

Disparity of Hepatocellular Carcinoma in Tumor Microenvironment-Related Genes and Infiltrating Immune Cells between Asian and Non-Asian Populations

by Lien-Hung Huang, Ting-Min Hsieh, Chun-Ying Huang, Yueh-Wei Liu, Shao-Chun Wu, Peng-Chen Chien and Ching-Hua Hsieh

Genes 2021, 12(8), 1274; https://doi.org/10.3390/genes12081274 - 20 Aug 2021

Cited by 4 | Viewed by 2134

Abstract

Hepatocellular carcinoma (HCC) is the most common cause of primary liver cancer deaths worldwide. The major risk factors for liver cancer development are cirrhosis, hepatitis B virus (HBV), hepatitis C virus (HCV) infection, and chronic alcohol abuse. HCC displays heterogeneity in terms of [...] Read more.

Hepatocellular carcinoma (HCC) is the most common cause of primary liver cancer deaths worldwide. The major risk factors for liver cancer development are cirrhosis, hepatitis B virus (HBV), hepatitis C virus (HCV) infection, and chronic alcohol abuse. HCC displays heterogeneity in terms of biology, etiology, and epidemiology. In Southeast Asia and Africa, chronic HBV infection is a major risk factor for HCC, whereas chronic HCV infection is a risk factor for HCC in western countries and Japan. Environmental and genetic conditions also play a role in the regional and temporal variations in the incidence of HCC. In this study, we used the ESTIMATE (ESTIMATE, Estimation of stromal and immune cells in malignant tumor tissues using expression data) algorithm and the CIBERSOFT tool to analyze gene expression profiles and infiltrating immune cells in HCC between Asian and non-Asian patients. The results showed that stromal and immune scores were dependent on overall survival (OS) in non-Asian patients but not in Asian patients. Kaplan–Meier survival analysis revealed four differentially expressed genes (DEGs) that were significantly associated with OS in non-Asian patients only. CIBERSORT (CIBERSORT, Cell type identification by estimating relative subsets of known RNA transcripts) analysis indicated that the composition of infiltrating immune cells was significantly different between Asian and non-Asian patients. By parsing the subclasses of HCC, the ability to predict prognosis and guide therapeutic targets for potentially actionable HCC may be improved. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

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15 pages, 2401 KiB

Open AccessArticle

Uniparental Lineages from the Oldest Indigenous Population of Ecuador: The Tsachilas

by Tullia Di Corcia, Giuseppina Scano, Cristina Martínez-Labarga, Stefania Sarno, Sara De Fanti, Donata Luiselli and Olga Rickards

Genes 2021, 12(8), 1273; https://doi.org/10.3390/genes12081273 - 20 Aug 2021

Cited by 2 | Viewed by 3144

Abstract

Together with Cayapas, the Tsachilas constitute the oldest population in the country of Ecuador and, according to some historians, they are the last descendants of the ancient Yumbos. Several anthropological issues underlie the interest towards this peculiar population: the uncertainty of their origin, [...] Read more.

Together with Cayapas, the Tsachilas constitute the oldest population in the country of Ecuador and, according to some historians, they are the last descendants of the ancient Yumbos. Several anthropological issues underlie the interest towards this peculiar population: the uncertainty of their origin, their belonging to the Barbacoan linguistic family, which is still at the center of an intense linguistic debate, and the relations of their Yumbo ancestors with the Inca invaders who occupied their ancient territory. Our contribution to the knowledge of their complex past was the reconstruction of their genetic maternal and paternal inheritance through the sequencing of 70 entire mitochondrial genomes and the characterization of the non-recombinant region of the Y chromosome in 26 males. For both markers, we built comprehensive datasets of various populations from the surrounding geographical area, northwestern South America, NW, with a known linguistic affiliation, and we could then compare our sample against the overall variability to infer relationships with other Barbacoan people and with other NW natives. We found contrasting patterns of genetic diversity for the two markers, but generally, our results indicated a possible common origin between the Tsachilas, the Chachi, and other Ecuadorian and Colombian Barbacoans and are suggestive of an interesting ancient linkage to the Inca invaders in Yumbo country. Full article

(This article belongs to the Special Issue The Peopling of the Americas: A Genetic Perspective)

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Figure 1
Map showing the reference location of samples investigated in the present study. The red dot indicates the city of Santo Domingo de los Tsachilas within the homonym canton. Full article ">Figure 2
Median joining network for A2, B2, C1, and D1 haplotypes of mtDNA entire genomes (n = 313) among Peruvian, Bolivian, Colombian, and Ecuadorian populations color-coded by ethnicity/linguistic affiliation. The haplotypes are represented by circles with sizes proportional to the number of individuals and branch lengths proportional to the number of mutational steps. The Quechua populations are divided by country (Peruvian, Bolivian, and Ecuadorian Quechua are indicated by Quechua_P, Quechua_B, and Quechua_E, respectively). Full article ">Figure 3
MDS plot based on φst genetic distances (stress value = 0.093) among 15 Ecuadorian, Peruvian, Bolivian, and Colombian populations. Full article ">Figure 4
Median joining network for 14 Y-STRs haplotypes (n = 316) among Peruvian, Ecuadorian, and Colombian populations, color-coded by ethnicity/linguistic affiliation. The haplotypes are represented by circles with sizes proportional to the number of individuals and branch lengths proportional to the number of mutational steps. The Quechua populations are divided by country (Peruvian and Ecuadorian Quechua are indicated by Quechua_P and Quechua_E, respectively). Full article ">Figure 5
MDS plot based on Fst genetic distances (stress value = 0.079) among 17 Ecuadorian, Peruvian, and Colombian populations. Full article ">

10 pages, 1276 KiB

Open AccessReview

Alternative Splicing and Hypoxia Puzzle in Alzheimer’s and Parkinson’s Diseases

by Eglė Jakubauskienė and Arvydas Kanopka

Genes 2021, 12(8), 1272; https://doi.org/10.3390/genes12081272 - 20 Aug 2021

Cited by 9 | Viewed by 3822

Abstract

Alternative pre-mRNA splicing plays a very important role in expanding protein diversity as it generates numerous transcripts from a single protein-coding gene. Therefore, alterations lead this process to neurological human disorders, including Alzheimer’s and Parkinson’s diseases. Moreover, accumulating evidence indicates that the splicing [...] Read more.

Alternative pre-mRNA splicing plays a very important role in expanding protein diversity as it generates numerous transcripts from a single protein-coding gene. Therefore, alterations lead this process to neurological human disorders, including Alzheimer’s and Parkinson’s diseases. Moreover, accumulating evidence indicates that the splicing machinery highly contributes to the cells’ ability to adapt to different altered cellular microenvironments, such as hypoxia. Hypoxia is known to have an effect on the expression of proteins involved in a multiple of biological processes, such as erythropoiesis, angiogenesis, and neurogenesis, and is one of the important risk factors in neuropathogenesis. In this review, we discuss the current knowledge of alternatively spliced genes, which, as it is reported, are associated with Alzheimer’s and Parkinson’s diseases. Additionally, we highlight the possible influence of cellular hypoxic microenvironment for the formation of mRNA isoforms contributing to the development of these neurodegenerative diseases. Full article

(This article belongs to the Special Issue Alternative Splicing in Human Physiology and Disease)

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The events of alternative splicing. Various combinations of exons can be spliced to form multiple mRNA and protein products from a single gene. Boxes represent exon sequences, black lines represent intronic sequences. White boxes indicate constitutively spliced exons, gray boxes indicate alternatively spliced regions. Full article ">Figure 2
Schematic representation of cis-acting elements and trans-acting factors that regulate splicing. Generally, exonic/intronic splicing enhancers (ESE/ISE) are bound by SR proteins that enhance the splicing, whereas exonic/intronic splicing silencers (ESS, ISS) are bound by hnRNPs that can antagonize the positive effect of SR proteins and inhibit splicing from nearby splice sites. The box indicates exon sequence and the line indicates intronic sequence. ss—splice site, BPS—branch point adenosine, PPT—polypyrimidine tract. Full article ">Figure 3
A schematic depiction of alternatively spliced genes contributing to neurodegeneration. (a) Alternative APP pre-mRNA splicing forms three major isoforms, APP770, APP751, and APP695, in neurons. (b) Alternative BACE1 pre-mRNA splicing and four RNA transcripts: BACE1 501, BACE1 457, BACE1 432, and BACE1 476. (c) Alternative splicing of tau exon 10 leads to formation of tau isoforms with three (3R) or four (4R) microtubule-binding repeats. (d) Alternative promoter usage for the APOE4 gene generates APOE4-001, -002, and -005 isoforms. (e) Three splice variants, SNCA 140, SNCA 126, and SNCA 112, of alternative SNCA pre-mRNA splicing. (f) Alternative SRRM2 pre-mRNA splicing produces the longer SRRM2 001 and the shorter SRRM 003 transcripts. Full article ">

11 pages, 325 KiB T Polymorphism in Primary Myelofibrosis: Susceptibility, Clinical Co-Variates, and Outcomes" data-journal="genes">

Open AccessArticle

Clinical Relevance of VEGFA (rs3025039) +936 C>T Polymorphism in Primary Myelofibrosis: Susceptibility, Clinical Co-Variates, and Outcomes

by Laura Villani, Adriana Carolei, Vittorio Rosti, Margherita Massa, Rita Campanelli, Paolo Catarsi, Carlotta Abbà, Robert Peter Gale and Giovanni Barosi

Genes 2021, 12(8), 1271; https://doi.org/10.3390/genes12081271 - 20 Aug 2021

Cited by 5 | Viewed by 2252

Abstract

We evaluated the association of VEGFA rs3025039 polymorphism with clinical co-variates and outcomes in 849 subjects with primary myelofibrosis (PMF) and 250 healthy controls. Minor T-allele frequency was higher in subjects with JAK2^V617F compared with those without JAK2^V617F (18% vs. 13%; [...] Read more.

We evaluated the association of VEGFA rs3025039 polymorphism with clinical co-variates and outcomes in 849 subjects with primary myelofibrosis (PMF) and 250 healthy controls. Minor T-allele frequency was higher in subjects with JAK2^V617F compared with those without JAK2^V617F (18% vs. 13%; p = 0.014). In subjects with JAK2^V617F, the TT genotype was associated at diagnosis with lower platelet concentrations (p = 0.033), higher plasma LDH concentration (p = 0.005), higher blood CD34-positive cells (p = 0.027), lower plasma cholesterol concentration (p = 0.046), and higher concentration of high-sensitivity C-reactive protein (p = 0.018). These associations were not found in subjects with PMF without JAK2^V617F. In subjects with the TT genotype, risk of death was higher compared with subjects with CC/CT genotypes (HR = 2.12 [1.03, 4.35], p = 0.041). Finally, the TT genotype was associated with higher frequency of deep vein thrombosis in typical sites (12.5% vs. 2.5%; OR = 5.46 [1.51, 19.7], p = 0.009). In conclusion, in subjects with PMF, the VEGFA rs3025039 CT or TT genotypes are more common in those with JAK2^V617F than in those without JAK2^V67F mutation and are associated with disease severity, poor prognosis, and risk of deep vein thrombosis. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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21 pages, 1397 KiB

Open AccessReview

Complex Interactions in Regulation of Haematopoiesis—An Unexplored Iron Mine

by Ranita De, Kulkarni Uday Prakash and Eunice S. Edison

Genes 2021, 12(8), 1270; https://doi.org/10.3390/genes12081270 - 20 Aug 2021

Cited by 5 | Viewed by 2497

Abstract

Iron is one of the most abundant metals on earth and is vital for the growth and survival of life forms. It is crucial for the functioning of plants and animals as it is an integral component of the photosynthetic apparatus and innumerable [...] Read more.

Iron is one of the most abundant metals on earth and is vital for the growth and survival of life forms. It is crucial for the functioning of plants and animals as it is an integral component of the photosynthetic apparatus and innumerable proteins and enzymes. It plays a pivotal role in haematopoiesis and affects the development and differentiation of different haematopoietic lineages, apart from its obvious necessity in erythropoiesis. A large amount of iron stores in humans is diverted towards the latter process, as iron is an indispensable component of haemoglobin. This review summarises the important players of iron metabolism and homeostasis that have been discovered in recent years and highlights the overall significance of iron in haematopoiesis. Its role in maintenance of haematopoietic stem cells, influence on differentiation of varied haematopoietic lineages and consequences of iron deficiency/overloading on development and maturation of different groups of haematopoietic cells have been discussed. Full article

(This article belongs to the Special Issue Genetic Regulation in Iron Homeostasis)

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16 pages, 1259 KiB

Open AccessArticle

High-Throughput Sequencing to Identify Mutations Associated with Retinal Dystrophies

by Fei Song, Marta Owczarek-Lipska, Tim Ahmels, Marius Book, Sabine Aisenbrey, Moreno Menghini, Daniel Barthelmes, Stefan Schrader, Georg Spital and John Neidhardt

Genes 2021, 12(8), 1269; https://doi.org/10.3390/genes12081269 - 20 Aug 2021

Cited by 3 | Viewed by 2687

Abstract

Retinal dystrophies (RD) are clinically and genetically heterogenous disorders showing mutations in over 270 disease-associated genes. Several millions of people worldwide are affected with different types of RD. Studying the relevance of disease-associated sequence alterations will assist in understanding disorders and may lead [...] Read more.

Retinal dystrophies (RD) are clinically and genetically heterogenous disorders showing mutations in over 270 disease-associated genes. Several millions of people worldwide are affected with different types of RD. Studying the relevance of disease-associated sequence alterations will assist in understanding disorders and may lead to the development of therapeutic approaches. Here, we established a whole exome sequencing (WES) pipeline to rapidly identify disease-associated mutations in patients. Sanger sequencing was applied to identify deep-intronic variants and to verify the co-segregation of WES results within families. We analyzed 26 unrelated patients with different syndromic and non-syndromic clinical manifestations of RD. All patients underwent ophthalmic examinations. We identified nine novel disease-associated sequence variants among 37 variants identified in total. The sequence variants located to 17 different genes. Interestingly, two cases presenting with Stargardt disease carried deep-intronic variants in ABCA4. We have classified 21 variants as pathogenic variants, 4 as benign/likely benign variants, and 12 as variants of uncertain significance. This study highlights the importance of WES-based mutation analyses in RD patients supporting clinical decisions, broadly based genetic diagnosis and support genetic counselling. It is essential for any genetic therapy to expand the mutation spectrum, understand the genes’ function, and correlate phenotypes with genotypes. Full article

(This article belongs to the Special Issue Genetics in Inherited Retinal Diseases)

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Bioinformatic pipeline to identify disease-causing mutations from WES datasets. We have performed the WES analyses in four steps with different filter settings using the Varvis platform that enabled step-by-step analyses of disease-associated variants in genomic DNAs derived from peripheral blood of individual patient. The filter “Variant Impact: high or moderate” excludes synonymous changes (not predicted to change the amino acid sequence) to enrich for more likely pathogenic variants. The filter “AllexesFound:” shows the number of persons in the allexes database that carry the variant. The filter “GnomTotal:” described the population allele frequency from merged exome and genome data sets of the gnomAD database. The filter “Coverage:” shows numbers of sequencing reads in the target region. The filter “Reads-Index:” describes the numbers of reads at the position of the variant. Full article ">Figure 2
Statistical analysis of RD-associated variants detected in this study. (A) Disease-associated genes detected in this study. In total, 17 different genes were detected in 26 RD-affected patients. Disease associated genes are color coded. (B) Distribution of different types of sequence variants in known RD-associated genes. Among 37 sequenced variants, 59% nonsynonymous substitution was found, followed by 14% small InDel variants, 11% Splice variants, 8% nonsense variants, and 8% deep-intronic variants. Full article ">Figure 3
Pedigrees of all RD-affected patients for whom co-segregation analyses were performed. Black arrowheads indicate the affected index patients in each family. Filled symbols represent affected family members. Co-segregation analyses were performed in the underlined family members. The numbers on the left side of the pedigrees refer to <a href="#genes-12-01269-t001" class="html-table">Table 1</a> and <a href="#app1-genes-12-01269" class="html-app">Table S1</a>. Question mark: phenotype information not available. M: mutation. Ref: reference sequence. Full article ">Figure 4
Optical coherence tomography (OCT) images of the macular region of patient 023 and 024 carrying ABCA4 deep-intronic variants. Genetic nomenclature of the variants identified in ABCA4 is shown above the OCT images. OD: oculus dexter, right eye. OS: oculus sinister, left eye. Full article ">

6 pages, 454 KiB

Open AccessArticle

Variants Affecting the C-Terminal Tail of UNC93B1 Are Not a Common Risk Factor for Systemic Lupus Erythematosus

by Sarah Kiener, Camillo Ribi, Irene Keller, Carlo Chizzolini, Marten Trendelenburg, Uyen Huynh-Do, Johannes von Kempis, on behalf of Swiss SLE Cohort Study (SSCS) and Tosso Leeb

Genes 2021, 12(8), 1268; https://doi.org/10.3390/genes12081268 - 19 Aug 2021

Viewed by 2265

Abstract

Systemic lupus erythematosus (SLE) is a heterogeneous multifactorial disease. Upregulated TLR7 signaling is a known risk factor for SLE. Recently, it was shown that specific genetic variants in UNC93B1 affect the physiological regulation of TLR7 signaling and cause characteristic autoimmune phenotypes with monogenic [...] Read more.

Systemic lupus erythematosus (SLE) is a heterogeneous multifactorial disease. Upregulated TLR7 signaling is a known risk factor for SLE. Recently, it was shown that specific genetic variants in UNC93B1 affect the physiological regulation of TLR7 signaling and cause characteristic autoimmune phenotypes with monogenic autosomal recessive inheritance in mutant mice and dogs. We therefore hypothesized that homologous variants in the human UNC93B1 gene might be responsible for a fraction of human SLE patients. We analyzed 536 patients of the Swiss SLE Cohort Study for the presence of genetic variants affecting the C-terminal tail of UNC93B1. None of the investigated patients carried bi-allelic UNC93B1 variants that were likely to explain their SLE phenotypes. We conclude that genetic variants affecting the C-terminal tail of UNC93B1 are not a common risk factor for SLE. It cannot be excluded that such variants might contribute to other heritable autoimmune diseases. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

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14 pages, 4191 KiB

Open AccessArticle

Whole-Genome Sequencing Improves the Diagnosis of DFNB1 Monoallelic Patients

by Anaïs Le Nabec, Mégane Collobert, Cédric Le Maréchal, Rémi Marianowski, Claude Férec and Stéphanie Moisan

Genes 2021, 12(8), 1267; https://doi.org/10.3390/genes12081267 - 19 Aug 2021

Cited by 5 | Viewed by 3097

Abstract

Hearing loss is the most common sensory defect, due in most cases to a genetic origin. Variants in the GJB2 gene are responsible for up to 30% of non-syndromic hearing loss. Today, several deafness genotypes remain incomplete, confronting us with a diagnostic deadlock. [...] Read more.

Hearing loss is the most common sensory defect, due in most cases to a genetic origin. Variants in the GJB2 gene are responsible for up to 30% of non-syndromic hearing loss. Today, several deafness genotypes remain incomplete, confronting us with a diagnostic deadlock. In this study, whole-genome sequencing (WGS) was performed on 10 DFNB1 patients with incomplete genotypes. New variations on GJB2 were identified for four patients. Functional assays were realized to explore the function of one of them in the GJB2 promoter and confirm its impact on GJB2 expression. Thus, in this study WGS resolved patient genotypes, thus unlocking diagnosis. WGS afforded progress and bridged some gaps in our research. Full article

(This article belongs to the Collection Genotype-Phenotype Study in Disease)

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21 pages, 28704 KiB

Open AccessReview

Zona Pellucida Genes and Proteins: Essential Players in Mammalian Oogenesis and Fertility

by Paul M. Wassarman and Eveline S. Litscher

Genes 2021, 12(8), 1266; https://doi.org/10.3390/genes12081266 - 19 Aug 2021

Cited by 29 | Viewed by 9725

Abstract

All mammalian oocytes and eggs are surrounded by a relatively thick extracellular matrix (ECM), the zona pellucida (ZP), that plays vital roles during oogenesis, fertilization, and preimplantation development. Unlike ECM surrounding somatic cells, the ZP is composed of only a few glycosylated proteins, [...] Read more.

All mammalian oocytes and eggs are surrounded by a relatively thick extracellular matrix (ECM), the zona pellucida (ZP), that plays vital roles during oogenesis, fertilization, and preimplantation development. Unlike ECM surrounding somatic cells, the ZP is composed of only a few glycosylated proteins, ZP1–4, that are unique to oocytes and eggs. ZP1–4 have a large region of polypeptide, the ZP domain (ZPD), consisting of two subdomains, ZP-N and ZP-C, separated by a short linker region, that plays an essential role in polymerization of nascent ZP proteins into crosslinked fibrils. Both subdomains adopt immunoglobulin (Ig)-like folds for their 3-dimensional structure. Mouse and human ZP genes are encoded by single-copy genes located on different chromosomes and are highly expressed in the ovary by growing oocytes during late stages of oogenesis. Genes encoding ZP proteins are conserved among mammals, and their expression is regulated by cis-acting sequences located close to the transcription start-site and by the same/similar trans-acting factors. Nascent ZP proteins are synthesized, packaged into vesicles, secreted into the extracellular space, and assembled into long, crosslinked fibrils that have a structural repeat, a ZP2-ZP3 dimer, and constitute the ZP matrix. Fibrils are oriented differently with respect to the oolemma in the inner and outer layers of the ZP. Sequence elements in the ZPD and the carboxy-terminal propeptide of ZP1–4 regulate secretion and assembly of nascent ZP proteins. The presence of both ZP2 and ZP3 is required to assemble ZP fibrils and ZP1 and ZP4 are used to crosslink the fibrils. Inactivation of mouse ZP genes by gene targeting has a detrimental effect on ZP formation around growing oocytes and female fertility. Gene sequence variations in human ZP genes due to point, missense, or frameshift mutations also have a detrimental effect on ZP formation and female fertility. The latter mutations provide additional support for the role of ZPD subdomains and other regions of ZP polypeptide in polymerization of human ZP proteins into fibrils and matrix. Full article

(This article belongs to the Special Issue Genetic and Genomic Regulation of Ovarian and Testicular Functions in Animals)

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Stages of follicular growth in mammals. Follicular growth begins with stage-1 primordial follicles in the ovary, which consists of a non-growing oocyte (blue) surrounded by a few epithelial-like somatic cells (yellow). As growth is initiated in stage-2 follicles, the somatic cells or granulosa cells (yellow) become cuboidal. During stages-3–5, the granulosa cells proliferate while the oocyte continues to increase in diameter and lays down a thin ZP (blue; outermost layer) that continues to thicken throughout oocyte growth. In stage-6, a fluid-filled cavity or antrum begins to form and by stage-8 the antrum is complete. Surrounded by a relatively thick ZP, the fully grown oocyte sits at the end of a stalk of granulosa cells and is surrounded by several layers of cumulus cells (yellow; stage-8). At stage-9, the fully grown oocyte (blue), which has arrested at metaphase II of meiosis, is ovulated into the oviduct surrounded by cumulus cells (yellow). The follicle that is left behind becomes an endocrine gland, the corpus luteum, that supports pregnancy. In female mice it takes ≈2–3 weeks for this developmental process to be completed. This figure is adapted from [<a href="#B14-genes-12-01266" class="html-bibr">14</a>], Figures 2–9, with permission from Cambridge University Press, CSIRO 2002. Full article ">Figure 2
(A) Schematic representation of steps involved in the conversion of female germ cells in the mouse fetus to fertilized eggs in the adult mouse. In the fetus primordial germ cells convert to mitotic oogonia and then to meiotic oocytes with crossing over and recombination. Soon after birth, all oocytes are arrested in meiosis at diplotene (dictyate) of the first meiotic prophase. At puberty, during each reproductive cycle, some mouse oocytes grow ≈ 300-fold in volume over ≈2–3 weeks, their surrounding follicle cells proliferate and differentiate, and fully grown oocytes surrounded by cumulus cells are ovulated. At about the time of ovulation, oocytes undergo meiotic maturation with emission of a first polar body following separation of homologous chromosomes (1st meiotic division). In this manner fully grown oocytes become haploid unfertilized eggs. Upon fusion with a single sperm, fertilized eggs emit a second polar body following separation of chromatids (2nd meiotic division) but are restored to a diploid state by the haploid sperm genome. (B) Schematic representation of ZP production during oocyte growth in mice. Non-growing oocytes lack a ZP, but as soon as oocyte growth begins, they lay down a ZP that continues to thicken throughout the growth phase (≈2–3 weeks; ≈300-fold increase in oocyte volume) and results in a 6.2 ± 1.9 μm thick ZP around fully-grown oocytes and ovulated eggs. The ZP remains around the early embryo until the expanded blastocyst stage when the embryo hatches from the ZP and implants in the uterus. Full article ">Figure 3
Organization of mZP and hZP proteins. The polypeptide has a signal sequence (magenta), a ZPD that consists of ZP-N (green) and ZP-C (cyan) subdomains, and a linker region (blue); a CFCS (arrow); a TMD) (yellow); and a short CT (black) in the CTP. mZP1, hZP1, and hZP4 also have a TD (brown). mZP2 (713 aa) has 3 additional ZP-N subdomains, N1–N3 (green), between the N-terminus of the polypeptide and the ZPD. mZP1 (623 aa), hZP1 (638), and hZP4 (540 aa) have one additional ZP-N subdomain, N1 (green), between the N-terminus of the polypeptide and the TD. mZP3, the smallest of the 3 mouse ZP proteins (424 aa), consists primarily of a ZPD. mZP1 and mZP2 have only 3 or 4 aa between the ZPD and the CFCS (red), whereas mZP3 has 47 aa, which is a region of positive Darwinian selection during evolution (red) [<a href="#B63-genes-12-01266" class="html-bibr">63</a>] and is the binding site for acrosome-intact, free-swimming sperm during fertilization [<a href="#B64-genes-12-01266" class="html-bibr">64</a>]. Full article ">Figure 4
Three-dimensional structures of ZPD subdomains ZP-N and ZP-C that are related to C- and V-type Ig-like domains. (A) ZP3 subdomain ZP-N and C-type Ig-like domains. β-strands are labeled using Ig terminology; helices are indicated by rectangles. Opposing β-sheets 1 and 2 are blue and green, respectively, with termini circled. The E′ strand is orange and disulfides magenta. (B) ZP2 ZP-C and V-type Ig-like domains. As in panel A, except for the additional A′ and C′/C″ strands that are yellow and red, respectively. This figure was adapted with permission from L. Jovine ([<a href="#B11-genes-12-01266" class="html-bibr">11</a>], Figure 4), Copyright 2018. Full article ">Figure 5
A general mechanism for assembly of nascent ZP proteins. In all ZPD precursor proteins, the ZPD consists of 2 subdomains, ZP-N (blue) and ZP-C (pink). The subdomains are followed by a CTP that contains a CFCS (magenta), an EHP (cyan), and a TMD (yellow). Precursors do not polymerize within the cell, either as a result of direct interaction between the EHP and IHP (gray) or because they adopt a conformation dependent on the presence of both hydrophobic patches. Proteolytic processing at the CFCS (marked by a cross) leads to dissociation of mature proteins from the EHP and activation of the ZPD for polymerization into fibrils and matrix. Full article ">Figure 6
Scanning electron micrographs of the surface of human and mouse oocytes. (A) Human oocyte showing the presence of many pores (9000× magnification) on the outer surface of the ZP. (B) Higher magnification of a human oocyte showing the fibrillar organization of the ZP (50,000× magnification); fibrils are 0.1–0.4 μm long and 10–14 nm wide. (C) Outer surface of a mouse oocyte showing the fibrillar organization of the ZP (50,000× magnification). Samples were treated with saponin–ruthenium red–osmium–thiocarbohydrazide to reveal ZP fibrils. This figure was adapted with permission from G. Familiari ([<a href="#B113-genes-12-01266" class="html-bibr">113</a>], Figure 3), Copyright 2012. Full article ">

15 pages, 2130 KiB

Open AccessArticle

Whole Genome Sequencing Reveals Multiple Linked Genetic Variants on Canine Chromosome 12 Associated with Risk for Symmetrical Lupoid Onychodystrophy (SLO) in the Bearded Collie

by Liza C. Gershony, Janelle M. Belanger, Marjo K. Hytönen, Hannes Lohi and Anita M. Oberbauer

Genes 2021, 12(8), 1265; https://doi.org/10.3390/genes12081265 - 19 Aug 2021

Cited by 4 | Viewed by 4708

Abstract

In dogs, symmetrical lupoid onychodystrophy (SLO) results in nail loss and an abnormal regrowth of the claws. In Bearded Collies, an autoimmune nature has been suggested because certain dog leukocyte antigen (DLA) class II haplotypes are associated with the condition. A genome-wide association [...] Read more.

In dogs, symmetrical lupoid onychodystrophy (SLO) results in nail loss and an abnormal regrowth of the claws. In Bearded Collies, an autoimmune nature has been suggested because certain dog leukocyte antigen (DLA) class II haplotypes are associated with the condition. A genome-wide association study of the Bearded Collie revealed two regions of association that conferred risk for disease: one on canine chromosome (CFA) 12 that encompasses the DLA genes, and one on CFA17. Case-control association was employed on whole genome sequencing data to uncover putative causative variants in SLO within the CFA12 and CFA17 associated regions. Genotype imputation was then employed to refine variants of interest. Although no SLO-associated protein-coding variants were identified on CFA17, multiple variants, many with predicted damaging effects, were identified within potential candidate genes on CFA12. Furthermore, many potentially damaging alleles were fully correlated with the presence of DLA class II risk haplotypes for SLO, suggesting that the variants may reflect DLA class II haplotype association with disease or vice versa. Strong linkage disequilibrium in the region precluded the ability to isolate and assess the individual or combined effect of variants on disease development. Nonetheless, all were predictive of risk for SLO and, with judicious assessment, their application in selective breeding may prove useful to reduce the incidence of SLO in the breed. Full article

(This article belongs to the Special Issue Canine Genetics 2)

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Figure 1
Flowchart illustrating dataset processing for imputation. Software and relevant parameters used are indicated at each step. The publicly available dataset required no additional filtering and phasing prior to merging. CFA, canine chromosome; N, number of individuals; Ne, effective population size; SNP, single nucleotide polymorphism; HWE, Hardy–Weinberg equilibrium; bp, base pairs; Mb, megabases. Full article ">Figure 2
Filtering process of whole genome sequence variants identified within the GWAS regions of association on canine chromosomes (CFA) 12 and 17 for further exploration of their association with symmetrical lupoid onychodystrophy (SLO) in Bearded Collies. Chromosome locations are based on the CanFam3.1 reference genome. Software used in each step indicated in parenthesis. Full article ">Figure 3
Genotypes for the 11 variants of interest on canine chromosome 12 in 82 unrelated Bearded Collies (30 SLO and 52 healthy controls). Dogs were sorted by SLO status; the homozygous reference genotypes (red) are notably absent in the SLO dogs, which predominantly carry homozygous non-reference (blue) genotypes. Heterozygous genotypes are colored in yellow. Variant locations are based on the CanFam3.1 reference genome. CFA—canine chromosome; SLO—symmetrical lupoid onychodystrophy. Full article ">Figure 4
Chromosome 12 linkage disequilibrium matrix showing pairwise r-squared values for the imputed genotypes of 82 unrelated Bearded Collies at 11 variants of interest. Variants are labeled by chromosome and location, as defined by the CanFam3.1 reference genome. Image generated using the R package gaston. The intensity of red corresponds to the r-squared value, with deeper red indicating greater r-squared values. Full article ">

16 pages, 5040 KiB

Open AccessArticle

In Utero Fetal Weight in Pigs Is Regulated by microRNAs and Their Target Genes

by Asghar Ali, Eduard Murani, Frieder Hadlich, Xuan Liu, Klaus Wimmers and Siriluck Ponsuksili

Genes 2021, 12(8), 1264; https://doi.org/10.3390/genes12081264 - 19 Aug 2021

Cited by 8 | Viewed by 2505

Abstract

Impaired skeletal muscle growth in utero can result in reduced birth weight and poor carcass quality in pigs. Recently, we showed the role of microRNAs (miRNAs) and their target genes in prenatal skeletal muscle development and pathogenesis of intrauterine growth restriction (IUGR). In [...] Read more.

Impaired skeletal muscle growth in utero can result in reduced birth weight and poor carcass quality in pigs. Recently, we showed the role of microRNAs (miRNAs) and their target genes in prenatal skeletal muscle development and pathogenesis of intrauterine growth restriction (IUGR). In this study, we performed an integrative miRNA-mRNA transcriptomic analysis in longissimus dorsi muscle (LDM) of pig fetuses at 63 days post conception (dpc) to identify miRNAs and genes correlated to fetal weight. We found 13 miRNAs in LDM significantly correlated to fetal weight, including miR-140, miR-186, miR-101, miR-15, miR-24, miR-29, miR-449, miR-27, miR-142, miR-99, miR-181, miR-199, and miR-210. The expression of these miRNAs decreased with an increase in fetal weight. We also identified 1315 genes significantly correlated to fetal weight at 63 dpc, of which 135 genes were negatively correlated as well as identified as potential targets of the above-listed 13 miRNAs. These miRNAs and their target genes enriched pathways and biological processes important for fetal growth, development, and metabolism. These results indicate that the transcriptomic profile of skeletal muscle can be used to predict fetal weight, and miRNAs correlated to fetal weight can serve as potential biomarkers of prenatal fetal health and growth. Full article

(This article belongs to the Section Molecular Genetics and Genomics)

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Heatmap of miRNAs significantly correlated to fetal weight (FDR < 0.05) in LDM of 118 pig fetuses at 63 dpc. Heatmap of the miRNAs expression profiles was generated using the hierarchical clustering method of heatmap.2 function of gPlots package (version 3.0.1) in the R programing environment (version 4.0.3) [<a href="#B29-genes-12-01264" class="html-bibr">29</a>]. A total of 13 miRNAs correlated to fetal weight were distributed in two clusters based on their co-expression with cut-off criteria of variance-stabilizing transformations ≥ 2, |logFC ≥ 1|. In the color key, the red color represents high expression, the green color represents low expression, and the black color represents no change in expression. Full article ">Figure 2
Correlation network of miRNAs and their target genes correlated to fetal weight at 63 dpc. The stroke color indicates the value of correlation coefficient according to the color key. The correlation coefficient ranged from −0.18 to −0.45. Full article ">Figure 3
KEGG pathway enrichment analysis of genes significantly correlated to fetal weight at 63 dpc. KEGG pathways with a p ≤ 0.05 were considered significantly enriched. Full article ">Figure 4
Gene ontology enrichment analysis, with a focus on biological processes, of genes significantly correlated to fetal weight at 63 dpc. Biological processes with a p ≤ 0.05 were considered significantly enriched. Full article ">Figure 5
KEGG pathway enrichment analysis of fetal weight-correlated target genes of fetal weight-correlated miRNAs. KEGG pathways with a p ≤ 0.05 were considered significantly enriched. Full article ">Figure 6
Gene ontology enrichment analysis, with a focus on biological processes, of fetal weight-correlated target genes of fetal weight-correlated miRNAs. Biological processes with a p ≤ 0.05 were considered significantly enriched. Full article ">Figure 7
(a) Comparison of miRNAs correlated to fetal weight and miRNAs upregulated during IUGR. (b) Common miRNAs and their negatively correlated target genes. (c) KEGG pathway enrichment analysis of target genes of miR-210. Full article ">

27 pages, 1095 KiB

Open AccessReview

Epigenetic Regulation of Circadian Clocks and Its Involvement in Drug Addiction

by Lamis Saad, Jean Zwiller, Andries Kalsbeek and Patrick Anglard

Genes 2021, 12(8), 1263; https://doi.org/10.3390/genes12081263 - 19 Aug 2021

Cited by 11 | Viewed by 5586

Abstract

Based on studies describing an increased prevalence of addictive behaviours in several rare sleep disorders and shift workers, a relationship between circadian rhythms and addiction has been hinted for more than a decade. Although circadian rhythm alterations and molecular mechanisms associated with neuropsychiatric [...] Read more.

Based on studies describing an increased prevalence of addictive behaviours in several rare sleep disorders and shift workers, a relationship between circadian rhythms and addiction has been hinted for more than a decade. Although circadian rhythm alterations and molecular mechanisms associated with neuropsychiatric conditions are an area of active investigation, success is limited so far, and further investigations are required. Thus, even though compelling evidence connects the circadian clock to addictive behaviour and vice-versa, yet the functional mechanism behind this interaction remains largely unknown. At the molecular level, multiple mechanisms have been proposed to link the circadian timing system to addiction. The molecular mechanism of the circadian clock consists of a transcriptional/translational feedback system, with several regulatory loops, that are also intricately regulated at the epigenetic level. Interestingly, the epigenetic landscape shows profound changes in the addictive brain, with significant alterations in histone modification, DNA methylation, and small regulatory RNAs. The combination of these two observations raises the possibility that epigenetic regulation is a common plot linking the circadian clocks with addiction, though very little evidence has been reported to date. This review provides an elaborate overview of the circadian system and its involvement in addiction, and we hypothesise a possible connection at the epigenetic level that could further link them. Therefore, we think this review may further improve our understanding of the etiology or/and pathology of psychiatric disorders related to drug addiction. Full article

(This article belongs to the Special Issue Gene Expression and Chromatin Modification in the Brain)

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