[go: up one dir, main page]
Skip to main content

Advertisement

Springer Nature Link
Log in

Understanding the Landscape of X-linked Variants Causing Intellectual Disability in Females Through Extreme X Chromosome Inactivation Skewing

  • Original Article
  • Published:
Molecular Neurobiology Aims and scope Submit manuscript

Abstract

Intellectual disability (ID) affects 30% more males than females. This sex bias can be attributed to the enrichment of genes on the X chromosome playing essential roles in the central nervous system and their hemizygous state on males. Moreover, as a result of X chromosome inactivation (XCI), most genes on one of the X chromosomes in female somatic cells are epigenetically silenced, so that females carrying X-linked variants are not expected to be so severely affected as males. Consequently, the knowledge about X-linked ID (XLID) in females is still scarce. Herein, we used extreme XCI skewing (≥ 90%) to predict X-linked variants in females with idiopathic ID. XCI profiles from 53 probands were estimated from blood and buccal mucosa through a methylation-sensitive AR/RP2 assay. DNA samples with extreme XCI skewing were then submitted to array-comparative genomic hybridization and whole-exome sequencing. Seven females (13.2%) exhibited extreme XCI skewing, a percentage significantly higher than expected for healthy females in our population. XLID-potentially related variants were identified in five patients with extreme XCI skewing, including one pathogenic rstructural rearrangement [der(X) chromosome from a t(X;2)] and four single nucleotide variants in NLGN4X, HDAC8, TAF1, and USP9X genes, two of which affecting XCI escape genes. XCI skewing showed to be an outstanding approach for the characterization of molecular mechanisms underlying XLID in females. Beyond expanding the spectrum of variants/phenotypes associated with ID, our results pointed to compensatory biological pathways underlying XCI and uncover new insights into the involvement of escape genes on XLID, impacting genetic counseling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Neri G, Schwartz CE, Lubs HA, Stevenson RE (2018) X-linked intellectual disability update 2017. Am J Med Genet Part A 176:1375–1388. https://doi.org/10.1002/ajmg.a.38710

    Article  PubMed  Google Scholar 

  2. Greenwood Genetic Center, X-linked intellectual disability, 2020, https://www.ggc.org/xlid-genetic-research/

  3. Fieremans N, Van Esch H, Holvoet M et al (2016) Identification of intellectual disability genes in female patients with a skewed X-inactivation pattern. Hum Mutat 37:804–811. https://doi.org/10.1002/humu.23012

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Carrel L, Brown CJ (2017) When the Lyon(ized chromosome) roars: ongoing expression from an inactive X chromosome. Phil Trans R Soc A B372:20160355. https://doi.org/10.1098/rstb.2016.0355

    Article  CAS  Google Scholar 

  5. Ørstavik KH (2009) X chromosome inactivation in clinical practice. Hum Genet 126:363–373. https://doi.org/10.1007/s00439-009-0670-5

    Article  PubMed  Google Scholar 

  6. Plenge RM, Stevenson RA, Lubs HA, Schwartz CE, Willard HF (2002) Skewed X-chromosome inactivation is a common feature of X-linked mental retardation disorders. Am J Hum Genet 71:168–173. https://doi.org/10.1086/341123

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fieremans N, Bauters M, Belet S, Verbeeck J, Jansen AC, Seneca S, Roelens F, de Baere E et al (2014) De novo MECP2 duplications in two females with intellectual disability and unfavorable complete skewed X-inactivation. Hum Genet 133:1359–1367. https://doi.org/10.1007/s00439-014-1469-6

    Article  PubMed  Google Scholar 

  8. McMahon A, Monk M (1983) X-chromosome activity in female mouse embryos heterozygous for Pgk-1 and Searle’s translocation, T(X; 16) 16H. Genet Res 41:69–83. https://doi.org/10.1017/s0016672300021078

    Article  CAS  PubMed  Google Scholar 

  9. Gupta N, Goel H, Phadke SR (2006) Unbalanced X; autosome translocation. Indian J Pediatr 73:840–842. https://doi.org/10.1007/BF02790399

    Article  PubMed  Google Scholar 

  10. Balaton BP, Cotton AM, Brown CJ (2015) Derivation of consensus inactivation status for X-linked genes from genome-wide studies. Biol Sex Differ 6:35. https://doi.org/10.1186/s13293-015-0053-7

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Carrel L, Willard HF (2005) X-inactivation profile reveals extensive variability in X-linked gene expression in females. Nature 434:400–404. https://doi.org/10.1038/nature03479

    Article  CAS  PubMed  Google Scholar 

  12. Tukiainen T, Villani A-C, Yen A, Rivas MA, Marshall JL, Satija R, Aguirre M, Gauthier L et al (2017) Landscape of X chromosome inactivation across human tissues. Nature 550:244–248. https://doi.org/10.1038/nature24265

    Article  PubMed  PubMed Central  Google Scholar 

  13. Machado FB, Faria MA, Lovatel VL et al (2014) 5meCpG epigenetic marks neighboring a primate-conserved core promoter short tandem repeat indicate X-chromosome inactivation. PLoS One 9:e103714. https://doi.org/10.1371/journal.pone.0103714

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Rosenberg C, Freitas ÉL, Uehara DT, Auricchio MTBM, Costa SS, Oiticica J, Silva AG, Krepischi AC et al (2016) Genomic copy number alterations in non-syndromic hearing loss. Clin Genet 89:473–477. https://doi.org/10.1111/cge.12683

    Article  CAS  PubMed  Google Scholar 

  15. Richards S, Aziz N, Bale S et al (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genetics in Medicine 17:405–423. https://doi.org/10.1038/gim.2015.30

    Article  PubMed  PubMed Central  Google Scholar 

  16. Li Q, Wang K (2017) InterVar: clinical interpretation of genetic variants by ACMG-AMP 2015 guideline. Am J Hum Genet 100:1–14. https://doi.org/10.1016/j.ajhg.2017.01.004

    Article  CAS  Google Scholar 

  17. Kopanos C, Tsiolkas V, Kouris A, Chapple CE, Albarca Aguilera M, Meyer R, Massouras A (2018) VarSome: the human genomic variant search engine. Oxford Bioinformatics 35:1978–1980. https://doi.org/10.1093/bioinformatics/bty897

    Article  CAS  Google Scholar 

  18. El-Gebali S, Mistry J, Bateman A et al (2019) The Pfam protein families database in 2019. Nucleic Acids Res 47:D427–D432. https://doi.org/10.1093/nar/gky995

    Article  CAS  PubMed  Google Scholar 

  19. Liu W, Xie Y, Ma J, Luo X, Nie P, Zuo Z, Lahrmann U, Zhao Q et al (2015) Sequence analysis IBS : an illustrator for the presentation and visualization of biological sequences. Bioinformatics 31:3359–3361. https://doi.org/10.1093/bioinformatics/btv362

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504. https://doi.org/10.1101/gr.1239303

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Vissers LELM, Gilissen C, Veltman JA (2016) Genetic studies in intellectual disability and related disorders. Nat Rev Genet 17:9–18. https://doi.org/10.1038/nrg3999

    Article  CAS  PubMed  Google Scholar 

  22. Gonçalves TF, dos Santos JM, Gonçalves AP, Tassone F, Mendoza-Morales G, Ribeiro MG, Kahn E, Boy R et al (2016) Finding FMR1 mosaicism in fragile X syndrome. Expert Rev Mol Diagn 16:501–507. https://doi.org/10.1586/14737159.2016.1135739

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Bittel DC, Theodoro MF, Kibiryeva N, Fischer W, Talebizadeh Z, Butler MG (2008) Comparison of X-chromosome inactivation patterns in multiple tissues from human females. J Med Genet 45:309–313. https://doi.org/10.1136/jmg.2007.055244

    Article  CAS  PubMed  Google Scholar 

  24. Cotton AM, Lam L, Affleck JG, Wilson IM, Peñaherrera MS, McFadden DE, Kobor MS, Lam WL et al (2011) Chromosome-wide DNA methylation analysis predicts human tissue-specific X inactivation. Hum Genet 130:187–201. https://doi.org/10.1007/s00439-011-1007-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Sharp A, Robinson D, Jacobs P (2000) Age- and tissue-specific variation of X chromosome inactivation ratios in normal women. Hum Genet 107:343–349. https://doi.org/10.1007/s004390000382

    Article  CAS  PubMed  Google Scholar 

  26. Borges BPCN (2018) Investigação de padrões de inativação do cromossomo X em mulheres saudáveis residentes no Estado do Rio de Janeiro. Universidade do Estado do Rio de Janeiro

  27. Ziats CA, Schwartz CE, Gecz J et al (2020) X-linked intellectual disability: phenotypic expression in carrier females. Clin Genet 97:418–425. https://doi.org/10.1111/cge.13667

    Article  CAS  PubMed  Google Scholar 

  28. Busque L, Paquette Y, Provost S, Roy DC, Levine RL, Mollica L, Gary Gilliland D (2009) Skewing of X-inactivation ratios in blood cells of aging women is confirmed by independent methodologies. Blood 113:3472–3474. https://doi.org/10.1182/blood-2008-12-195677

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lonsdale J, Thomas J, Salvatore M, Phillips R, Lo E, Shad S, Hasz R, Walters G et al (2013) The genotype-tissue expression (GTEx) project. Nat Genet 45:580–585. https://doi.org/10.1038/ng.2653

    Article  CAS  Google Scholar 

  30. Li JY, Daniels G, Wang J, Zhang X (2015) TBL1XR1 in physiological and pathological states. Am J Clin Exp Urol 3:13–23 http://www.ncbi.nlm.nih.gov/pubmed/26069883

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Kruusvee V, Lyst MJ, Taylor C, Tarnauskaitė Ž, Bird AP, Cook AG (2017) Structure of the MeCP2–TBLR1 complex reveals a molecular basis for Rett syndrome and related disorders. PNAS 114:E3243–E3250. https://doi.org/10.1073/pnas.1700731114

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zaghlula M, Glaze DG, Enns GM, Potocki L, Schwabe AL, Suter B (2018) Current clinical evidence does not support a link between TBL1XR1 and Rett syndrome: description of one patient with Rett features and a novel mutation in TBL1XR1, and a review of TBL1XR1 phenotypes. Am J Med Genet Part A 176:1683–1687. https://doi.org/10.1002/ajmg.a.38689

    Article  PubMed  Google Scholar 

  33. Vaqueiro AC, de Oliveira CP, Cordoba MS, Versiani BR, de Carvalho CX, Alves Rodrigues PG, de Oliveira SF, Mazzeu JF et al (2018) Expanding the spectrum of TBL1XR1 deletion: report of a patient with brain and cardiac malformations. Eur J Med Genet 61:29–33. https://doi.org/10.1016/j.ejmg.2017.10.008

    Article  PubMed  Google Scholar 

  34. Armour CM, Smith A, Hartley T, Chardon JW, Sawyer S, Schwartzentruber J, Hennekam R, Majewski J et al (2016) Syndrome disintegration: exome sequencing reveals that Fitzsimmons syndrome is a co-occurrence of multiple events. Am J Med Genet Part A 170:1820–1825. https://doi.org/10.1002/ajmg.a.37684

    Article  CAS  PubMed  Google Scholar 

  35. O’Roak BJ, Vives L, Fu W et al (2012) Multiplex targeted sequencing identifies recurrently mutated genes in autism spectrum disorders. Science 338:1619–1622. https://doi.org/10.1126/science.1227764

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. O’Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP, Levy R, Ko A et al (2012) Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature 485:246–250. https://doi.org/10.1038/nature10989

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Saitsu H, Tohyama J, Walsh T, Kato M, Kobayashi Y, Lee M, Tsurusaki Y, Miyake N et al (2014) A girl with West syndrome and autistic features harboring a de novo TBL1XR1 mutation. J Hum Genet 59:581–583. https://doi.org/10.1038/jhg.2014.71

    Article  CAS  PubMed  Google Scholar 

  38. Pons L, Cordier MP, Labalme A, Till M, Louvrier C, Schluth-Bolard C, Lesca G, Edery P et al (2015) A new syndrome of intellectual disability with dysmorphism due to TBL1XR1 deletion. Am J Med Genet Part A 167:164–168. https://doi.org/10.1002/ajmg.a.36759

    Article  CAS  Google Scholar 

  39. Tabet A-C, Leroy C, Dupont C, Serrano E, Hernandez K, Gallard J, Pouvreau N, Gadisseux JF et al (2014) De novo deletion of TBL1XR1 in a child with non-specific developmental delay supports its implication in intellectual disability. Am J Med Genet Part A 164:2335–2337. https://doi.org/10.1002/ajmg.a.36619

    Article  CAS  Google Scholar 

  40. Riehmer V, Erger F, Herkenrath P, Seland S, Jackels M, Wiater A, Heller R, Beck BB et al (2017) A heritable microduplication encompassing TBL1XR1 causes a genomic sister-disorder for the 3q26.32 microdeletion syndrome. Am J Med Genet Part A 173:2132–2138. https://doi.org/10.1002/ajmg.a.38285

    Article  CAS  PubMed  Google Scholar 

  41. Żylicz JJ, Bousard A, Žumer K et al (2019) The implication of early chromatin changes in X chromosome inactivation. Cell 176:182–197.e23. https://doi.org/10.1016/j.cell.2018.11.041

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Zhang J, Kalkum M, Chait BT, Roeder RG (2002) The N-CoR-HDAC3 nuclear receptor corepressor complex inhibits the JNK pathway through the integral subunit GPS2. Mol Cell 9:611–623. https://doi.org/10.1016/s1097-2765(02)00468-9

    Article  CAS  PubMed  Google Scholar 

  43. Banerjee S, Riordan M, Bhat MA (2014) Genetic aspects of autism spectrum disorders: insights from animal models. Front Cell Neurosci 8:58. https://doi.org/10.3389/fncel.2014.00058

    Article  PubMed  PubMed Central  Google Scholar 

  44. Landini M, Merelli I, Raggi M, Galluccio N, Ciceri F, Bonfanti A, Camposeo S, Massagli A et al (2016) Association analysis of noncoding variants in neuroligins 3 and 4x genes with autism spectrum disorder in an Italian cohort. Int J Mol Sci 17:1765. https://doi.org/10.3390/ijms17101765

    Article  CAS  PubMed Central  Google Scholar 

  45. Bouazzi H, Lesca G, Trujillo C, Alwasiyah MK, Munnich A (2015) Nonsyndromic X-linked intellectual deficiency in three brothers with a novel MED12 missense mutation [c.5922G>T (p.Glu1974His)]. Clin Case Rep 3:604–609. https://doi.org/10.1002/ccr3.301

    Article  PubMed  PubMed Central  Google Scholar 

  46. Cukier HN, Dueker ND, Slifer SH, Lee JM, Whitehead PL, Lalanne E, Leyva N, Konidari I et al (2014) Exome sequencing of extended families with autism reveals genes shared across neurodevelopmental and neuropsychiatric disorders. Mol Autism 5:1. https://doi.org/10.1186/2040-2392-5-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Kou Y, Betancur C, Xu H, Buxbaum JD, Ma’ayan A (2012) Network- and attribute-based classifiers can prioritize genes and pathways for autism spectrum disorders and intellectual disability. Am J Med Genet Part C 160:130–142. https://doi.org/10.1002/ajmg.c.31330

    Article  CAS  Google Scholar 

  48. Murtaza M, Jolly LA, Gecz J, Wood SA (2015) La FAM fatale: USP9X in development and disease. Cell Mol Life Sci 72:2075–2089. https://doi.org/10.1007/s00018-015-1851-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Johnson BV, Kumar R, Oishi S, Alexander S, Kasherman M, Vega MS, Ivancevic A, Gardner A et al (2019) Partial loss of USP9X function leads to a male neurodevelopmental and behavioral disorder converging on transforming growth factor β signaling. Biol Psychiatry 87:100–112. https://doi.org/10.1016/j.biopsych.2019.05.028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Petrovski S, Wang Q, Heinzen EL, Allen AS, Goldstein DB (2013) Genic intolerance to functional variation and the interpretation of personal genomes. PLoS Genet 9:e1003709. https://doi.org/10.1371/journal.pgen.1003709

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Reijnders MRF, Zachariadis V, Latour B, Jolly L, Mancini GM, Pfundt R, Wu KM, van Ravenswaaij-Arts C et al (2016) De novo loss-of-function mutations in USP9X cause a female-specific recognizable syndrome with developmental delay and congenital malformations. Am J Hum Genet 98:373–381. https://doi.org/10.1016/j.ajhg.2015.12.015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Peeters SB, Cotton AM, Brown CJ (2014) Variable escape from X-chromosome inactivation: identifying factors that tip the scales towards expression. BioEssays 36:746–756. https://doi.org/10.1002/bies.201400032

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Talebizadeh Z, Simon SD, Butler MG (2006) X chromosome gene expression in human tissues: male and female comparisons. Genomics 88:675–681. https://doi.org/10.1016/j.ygeno.2006.07.016

    Article  CAS  PubMed  Google Scholar 

  54. Yang C, Chapman AG, Kelsey AD, Minks J, Cotton AM, Brown CJ (2011) X-chromosome inactivation: molecular mechanisms from the human perspective. Hum Genet 130:175–185. https://doi.org/10.1007/s00439-011-0994-9

    Article  PubMed  Google Scholar 

  55. Zweier C, Kraus C, Brueton L, Cole T, Degenhardt F, Engels H, Gillessen-Kaesbach G, Graul-Neumann L et al (2013) A new face of Borjeson–Forssman–Lehmann syndrome? De novo mutations in PHF6 in seven females with a distinct phenotype. J Med Genet 50:838–847. https://doi.org/10.1136/jmedgenet-2013-101918

    Article  CAS  PubMed  Google Scholar 

  56. Snijders Blok L, Madsen E, Juusola J, Gilissen C, Baralle D, Reijnders MR, Venselaar H, Helsmoortel C et al (2015) Mutations in DDX3X are a common cause of unexplained intellectual disability with gender-specific effects on Wnt signaling. Am J Hum Genet 97:343–352. https://doi.org/10.1016/j.ajhg.2015.07.004

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Deardorff MA, Bando M, Nakato R, Watrin E, Itoh T, Minamino M, Saitoh K, Komata M et al (2012) HDAC8 mutations in Cornelia de Lange syndrome affect the cohesin acetylation cycle. Nature 489:313–317. https://doi.org/10.1038/nature11316

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Kaiser FJ, Ansari M, Braunholz D, Concepción Gil-Rodríguez M, Decroos C, Wilde JJ, Fincher CT, Kaur M et al (2014) Loss-of-function HDAC8 mutations cause a phenotypic spectrum of Cornelia de Lange syndrome-like features, ocular hypertelorism, large fontanelle and X-linked inheritance. Hum Mol Genet 23:2888–2900. https://doi.org/10.1093/hmg/ddu002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Feng L, Zhou D, Zhang Z, Liu Y, Yang Y (2014) Exome sequencing identifies a de novo mutation in HDAC8 associated with Cornelia de Lange syndrome. J Hum Genet 59:536–539. https://doi.org/10.1038/jhg.2014.60

    Article  CAS  PubMed  Google Scholar 

  60. Harakalova M, van den Boogaard M-J, Sinke R, van Lieshout S, van Tuil MC, Duran K, Renkens I, Terhal PA et al (2012) X-exome sequencing identifies a HDAC8 variant in a large pedigree with X-linked intellectual disability, truncal obesity, gynaecomastia, hypogonadism and unusual face. J Med Genet 49:539–543. https://doi.org/10.1136/jmedgenet-2012-100921

    Article  CAS  PubMed  Google Scholar 

  61. Krawczynska N, Wierzba J, Wasag B (2019) Genetic mosaicism in a group of patients with Cornelia de Lange syndrome. Front Pediatr 7:203. https://doi.org/10.3389/fped.2019.00203

    Article  PubMed  PubMed Central  Google Scholar 

  62. Helgeson M, Keller-Ramey J, Knight Johnson A, Lee JA, Magner DB, Deml B, Deml J, Hu YY et al (2018) Molecular characterization of HDAC8 deletions in individuals with atypical Cornelia de Lange syndrome. J Hum Genet 63:349–356. https://doi.org/10.1038/s10038-017-0387-6

    Article  CAS  PubMed  Google Scholar 

  63. Dowsett L, Porras AR, Kruszka P, Davis B, Hu T, Honey E, Badoe E, Thong MK et al (2019) Cornelia de Lange syndrome in diverse populations. Am J Med Genet A 179:150–158. https://doi.org/10.1002/ajmg.a.61033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. O’Rawe JA, Wu Y, Dörfel MJ, Rope AF, Au PYB, Parboosingh JS, Moon S, Kousi M et al (2015) TAF1 variants are associated with dysmorphic features, intellectual disability, and neurological manifestations. Am J Hum Genet 97:922–932. https://doi.org/10.1016/j.ajhg.2015.11.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Gudmundsson S, Wilbe M, Filipek-Górniok B, Molin AM, Ekvall S, Johansson J, Allalou A, Gylje H et al (2019) TAF1, associated with intellectual disability in humans, is essential for embryogenesis and regulates neurodevelopmental processes in zebrafish. Sci Rep 9:10730. https://doi.org/10.1038/s41598-019-46632-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Janakiraman U, Yu J, Moutal A, Chinnasamy D, Boinon L, Batchelor SN, Anandhan A, Khanna R et al (2019) TAF1-gene editing alters the morphology and function of the cerebellum and cerebral cortex. Neurobiol Dis 132:104539. https://doi.org/10.1016/j.nbd.2019.104539

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Domingo A, Amar D, Grütz K, Lee LV, Rosales R, Brüggemann N, Jamora RD, Cutiongco-dela Paz E et al (2016) Evidence of TAF1 dysfunction in peripheral models of X-linked dystonia-parkinsonism. Cell Mol Life Sci 73:3205–3215. https://doi.org/10.1007/s00018-016-2159-4

    Article  CAS  PubMed  Google Scholar 

  68. Hurst SE, Liktor-Busa E, Moutal A, Parker S, Rice S, Szelinger S, Senner G, Hammer MF et al (2018) A novel variant in TAF1 affects gene expression and is associated with X-linked TAF1 intellectual disability syndrome. Neuronal Signaling 2:NS20180141. https://doi.org/10.1042/NS20180141

    Article  PubMed  PubMed Central  Google Scholar 

  69. Sans N, Ezan J, Moreau MM, Montcouquiol M (2016) Planar cell polarity gene mutations in autism spectrum disorder, intellectual disabilities, and related deletion/duplication syndromes. In neuronal and synaptic dysfunction in autism spectrum disorder and intellectual disability. Elsevier:189–219. https://doi.org/10.1016/B978-0-12-800109-7.00013-3

  70. White J, Mazzeu JF, Hoischen A, Jhangiani SN, Gambin T, Alcino MC, Penney S, Saraiva JM et al (2015) DVL1 frameshift mutations clustering in the penultimate exon cause autosomal-dominant Robinow syndrome. Am J Hum Genet 96:612–622. https://doi.org/10.1016/j.ajhg.2015.02.015

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Long JM, LaPorte P, Paylor R, Wynshaw-Boris A (2004) Expanded characterization of the social interaction abnormalities in mice lacking Dvl1. Genes Brain Behav 3:51–62. https://doi.org/10.1046/j.1601-183x.2003.00045.x

    Article  CAS  PubMed  Google Scholar 

  72. Santos-Rebouças CB, Boy R, Vianna EQ, Gonçalves AP, Piergiorge RM, Abdala BB, dos Santos JM, Calassara V et al (2020) Skewed X-chromosome inactivation and compensatory upregulation of escape genes precludes major clinical symptoms in a female with a large Xq deletion. Front Genet 11:101. https://doi.org/10.3389/fgene.2020.00101

    Article  PubMed  PubMed Central  Google Scholar 

  73. Carrette LLG, Wang C-Y, Wei C, Press W, Ma W, Kelleher RJ III, Lee JT (2018) A mixed modality approach towards Xi reactivation for Rett syndrome and other X-linked disorders. PNAS 115:E668–E675. https://doi.org/10.1073/pnas.1715124115

    Article  CAS  PubMed  Google Scholar 

  74. Jiang J, Jing Y, Cost GJ, Chiang JC, Kolpa HJ, Cotton AM, Carone DM, Carone BR et al (2013) Translating dosage compensation to trisomy 21. Nature 500:296–300. https://doi.org/10.1038/nature12394

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The authors thank the studied families for their kind cooperation and Genome Facility Platform from the National Cancer Institute of Brazil.

Funding

This work was supported by funds from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ), Fundação de Amparo à Pesquisa do Estado de São Paulo (CEPID - FAPESP), Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001, and Centro de Produção da Universidade do Estado do Rio de Janeiro (CEPUERJ).

Author information

Authors and Affiliations

  1. Department of Genetics, Institute of Biology Roberto Alcantara Gomes, State University of Rio de Janeiro, Rua São Francisco Xavier, 524, PHLC – sala 501F, Maracanã, Rio de Janeiro, RJ, 20550-013, Brazil

    Evelyn Quintanilha Vianna, Rafael Mina Piergiorge, Andressa Pereira Gonçalves, Jussara Mendonça dos Santos, Veluma Calassara, Márcia Mattos Gonçalves Pimentel & Cíntia Barros Santos-Rebouças

  2. Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo, São Paulo, Brazil

    Carla Rosenberg & Ana Cristina Victorino Krepischi

  3. Pedro Ernesto University Hospital, State University of Rio de Janeiro, Rio de Janeiro, Brazil

    Raquel Tavares Boy da Silva

  4. Gaffrée and Guinle University Hospital, Federal University of Rio de Janeiro State, Rio de Janeiro, Brazil

    Suely Rodrigues dos Santos

  5. Clinical Genetics Service, IPPMG, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

    Márcia Gonçalves Ribeiro

  6. Department of Biological Sciences, Minas Gerais State University, Belo Horizonte, Minas Gerais, Brazil

    Filipe Brum Machado

  7. Laboratory of Biotechnology, State University of Northern Rio de Janeiro Darcy Ribeiro, Rio de Janeiro, Brazil

    Enrique Medina-Acosta

Authors
  1. Evelyn Quintanilha Vianna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rafael Mina Piergiorge
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andressa Pereira Gonçalves
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jussara Mendonça dos Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Veluma Calassara
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carla Rosenberg
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ana Cristina Victorino Krepischi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Raquel Tavares Boy da Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Suely Rodrigues dos Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Márcia Gonçalves Ribeiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Filipe Brum Machado
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Enrique Medina-Acosta
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Márcia Mattos Gonçalves Pimentel
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Cíntia Barros Santos-Rebouças
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conception and design: C.B.S.R.

Acquisition of data: C.B.S.R, E.Q.V., R.M.P., A.P.G., J.M.S., V.C., A.C.V.K., C.R., F.B.M., E.M.A.

Clinical evaluation: R.T.B.S., S.R.S., M.G.R.

Analysis and interpretation: C.B.S.R, E.Q.V., R.M.P., A.C.V.K., C.R., M.M.G.P.

Manuscript drafting: C.B.S.R, E.Q.V., R.M.P, R.T.B.S., S.R.S., M.G.R.

Obtained funding: C.B.S.R, M.M.G.P., A.C.V.K., C.R.

Corresponding author

Correspondence to Cíntia Barros Santos-Rebouças.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Web Resources

The URLs for data presented herein are as follows:

ClinVar, 2020, https://www.ncbi.nlm.nih.gov/clinvar/

Database of Genomic Variants - DGV, 2020, http://projects.tcag.ca/variation/

Decipher v9.28, 2020, https://decipher.sanger.ac.uk/

Ensembl Genome Browser, 2020, http://www.ensembl.org/index.html

ExAC Browser, 2020, http://exac.broadinstitute.org/

Geneimprint, 2020, http://www.geneimprint.com/site/genes-by-species

GnomAD, 2020, https://gnomad.broadinstitute.org/

Mutation Taster, 2020, http://www.mutationtaster.org

OMIM, 2020, http://www.omim.org/

Pfam 32.0 platform, 2020, http://pfam.sanger.ac.uk/

RefSeq, 2020, http://www.ncbi.nlm.nih.gov/RefSeq

RepeatMasker program, 2020, http://repeatmasker.genome.washington.edu

UCSC Genome Browser (Hg19), 2020, http://genome.ucsc.edu

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

ESM 1

(PPTX 24481 kb)

Supplemental Table 2

In silico pathogenicity predictions and conservation data for the sequence variants found in females with extreme XCI skewing subjected to WES (excel file). (XLSX 10 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vianna, E.Q., Piergiorge, R.M., Gonçalves, A.P. et al. Understanding the Landscape of X-linked Variants Causing Intellectual Disability in Females Through Extreme X Chromosome Inactivation Skewing. Mol Neurobiol 57, 3671–3684 (2020). https://doi.org/10.1007/s12035-020-01981-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12035-020-01981-8

Keywords