Genet Resour Crop Evol (2020) 67:1193–1208 https://doi.org/10.1007/s10722-020-00905-8 (0123456789().,-volV) ( 01234567 89().,-volV) RESEARCH ARTICLE Genetic diversity of provitamin-A cassava (Manihot esculenta Crantz) in Sierra Leone I. Kamanda . E. T. Blay . I. K. Asante . A. Danquah . B. E. Ifie . E. Parkes . P. Kulakow . I. Rabbi . A. Conteh . J. S. Kamara . H. K. Mensah . J. B. A. Whyte . Sayo Sesay Received: 18 February 2019 / Accepted: 17 February 2020 / Published online: 4 March 2020 Ó The Author(s) 2020 Abstract Understanding the genetic diversity among accessions and germplasm is an important requirement for crop development as it allows for the selection of diverse parental combinations for enhancing genetic gain in varietal selection, advancement and release. The study aimed to characterize 183 provitamin A cassava (Manihot esculenta Crantz) accessions and five Sierra Leonean varieties using morphological traits, total carotenoid content and SNP markers to develop a collection for conservation and further use in the cassava breeding program. Both morphological parameters and 5634 SNP markers were used to assess the diversity among the provitamin-A cassava I. Kamanda (&)
A. Conteh
S. Sesay Sierra Leone Agricultural Research Institute, P. O. Box, 1313, Freetown, Sierra Leone e-mail: ikamanda@wacci.ug.edu.gh I. Kamanda
E. T. Blay
I. K. Asante
A. Danquah
B. E. Ifie West Africa Centre for Crop Improvement (WACCI), University of Ghana, Legon, Ghana accessions and varieties. Significant differences were observed among the accessions for most of the traits measured. The first five PCs together accounted for 70.44% of the total phenotypic variation based on yield and yield components among the 183 provitamin-A cassava accessions and five Sierra Leonean varieties. The present study showed that provitamin-A cassava accessions in Sierra Leone have moderate to high diversity based on morphological and molecular assessment studies. The similarity index among the 187 and 185 cassava accessions grouped them into 6 and 9 distinct clusters based on morphological and molecular analyses, respectively. A significant positive, but low correlation (r = 0.104; p \ 0.034), was observed between the two dendrograms. The results obtained will serve as a guide and basis of germplasm management and improvement for total carotenoid content, yield and African cassava mosaic disease resistance in Sierra Leone. Keywords Manihot esculenta accession
Morphological traits
Total carotenoid content
Collection SNP markers E. Parkes
P. Kulakow
I. Rabbi
J. B. A. Whyte International Institute Tropical Agriculture, PMB 5320, Oyo Road, Ibadan, Nigeria J. S. Kamara Njala University, Njala, Sierra Leone H. K. Mensah Department of Plant and Environmental Biology, University of Ghana, Legon, Ghana Introduction Genetic diversity provides species with the ability to adapt to changing environments. Several studies have been reported on the use of morphological descriptors 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1194 Genet Resour Crop Evol (2020) 67:1193–1208 to determine the genetic diversity among cassava genotypes (Rimoldi et al. 2010; Asare et al. 2011; Thompson 2013). Recent advances in molecular biology techniques have led to the development of important tools for genetic diversity study in several plant species. The accuracy in accession characterization may therefore, be enhanced/achieved with the use of molecular markers associated with morphological traits. Previous studies in plant genetic diversity used DNA molecular markers for beta carotene improvement in cassava (Ferreira et al. 2008; Rimoldi et al. 2010), and included amplified fragment length polymorphism (Benesi et al. 2010), simple sequence repeats (Alves et al. 2011; Parkes 2009; Oliveria et al. 2012; Costa et al. 2013) and single nucleotide polymorphism (Kizito et al. 2005; Tangphatsornruang et al. 2008; Ferguson et al. 2011; Thompson 2013; Rabbi et al. 2015). With recent advances in high throughput genotyping technologies, single nucleotide polymorphism markers (SNPs) are increasingly becoming markers of preference for plant genetic studies and breeding. SNPs are the most common types of genetic variation among species, involving just a change in a single nucleotide. Expressed Sequence Tags (ESTs) have been exploited to explain and detect SNPs in maize (Zea mays L.) (Ching et al. 2002) and soybean (Glycine max L. Merr.) (Zhu et al. 2003). Lopez et al. (2005) and Rabbi et al. (2014, 2015) have also reported SNPs detection from ESTs in cassava. Cassava being an outbreeding and highly heterogeneous crop, possesses an extreme level of phenotypic plasticity, and thereby, lacks the potential for unified classification system for cultivars (Kawano 1978). Consequently, characterization of agronomic traits becomes a challenge. To conduct a successful genetic diversity study on cassava germplasm in Sierra Leone, there is a need to unravel the genetic potential existing among Sierra Leone’s cassava breeding program, which consists of fourteen released varieties and provitamin-A cassava accessions induction from Institute of International Tropical Agriculture, Nigeria. Thus, the need for assessing and understanding the genetic diversity among the provitamin-A cassava accessions and identifying gaps to be filled within the breeding program in Sierra Leone is required. The objectives of the study, therefore, were to characterize, quantify and exploit the diversity of 183 provitamin-A cassava accessions and five Sierra Leonean varieties using morphological traits, SNP markers and total carotene content and to develop a collection for conservation and future use in the breeding programmes. Materials and methods Germplasm sources and experimental design The plant materials used in the study consisted of 183 provitamin-A cassava accessions known for their varying levels of provitamin- A properties, obtained from the International Institute of Tropical Agriculture (IITA, Ibadan, Nigeria) and established at the Taiama experimental site in Sierra Leone, in 2014 (Table 1) and five Sierra Leonean cassava varieties. The trial was established and evaluated during the cropping season of 2015–2016 at the Njala Agricultural Research Institute (NARC), Foya crop site, Njala, representing the transitional rain forest agro-climatic zone (Van Vuure et al. 1972; Odell et al. 1974). The trial was laid out in an Alpha lattice design with two replications, and each replication had four blocks with 47 entries per block. The blocks were separated by 1 m and 2 m alleys between and within blocks to reduce intra and inter block plant competition, respectively. Each entry was grown on 10 m row ridge at a spacing of 1 m 9 1 m between and within ridges, respectively. Cassava cuttings of 20–25 cm length were obtained from healthy stem cuttings and horizontally planted. Morphological traits Agro-morphological data was collected at 1, 3, 6 and 9 months after planting (MAP) on the parameters listed below using the IITA cassava descriptor (Fukuda et al. 2010) (Table 2). Harvesting was done at 12 MAP (August–September). The following parameters were taken at harvest: number of marketable roots (expressed as count numbers), number of non-marketable roots (expressed as count numbers), total number of storage roots (expressed as count numbers), roots weight/tuber (kg), inner skin color, and outer skin color, ease of peel, root shape, marketable weight (kg), and non- marketable weight (kg). Dry matter content, expressed in 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 1195 Table 1 Provitamin–A studied accessions and sierra leonean varieties and their pedigrees No. Accession name Pedigree Origin No. Accession name Pedigree Origin 1 TR 1563 IBA 082708 Ubiaja 101 TR 1073 IBA 102429 Ubiaja 2 TR 1337 IBA 011368 Ubiaja 102 TR 0890 IBA 070749 Ubiaja 3 4 TR 0421 TR 1207 IBA 051652 SM 3374 Ubiaja Ubiaja 103 104 TR 0316 TR 1199 IBA051740 IBA051740 Ubiaja Ubiaja 5 TR 0267 IBA 961439 Ubiaja 105 TR 1144 IBA 100224 Ubiaja 6 TR 0626 MM 050626 Ubiaja 106 TR 0982 IBA 102480 Ubiaja 7 TR 0431 IBA 011735 Ubiaja 107 TR 1244 IBA 050099 Ubiaja 8 TR 0085 IBA 050311 Ubiaja 108 TR 1279 SM 3374 Ubiaja 9 TR 1295 IBA 011412 Ubiaja 109 TR 1008 IBA 100198 Ubiaja 10 TR 1627 TMEB 693 Ubiaja 110 TR 0861 GM 3594 Ubiaja 11 TR 0224 IBA 000351 Ubiaja 111 TR 0983 IBA 070738 Ubiaja 12 TR 1578 BA 011371 Ubiaja 112 TR 1031 IBA 070593 Ubiaja 13 TR 0222 IBA 020134 Ubiaja 113 TR 0683 SM 3666 Ubiaja 14 TR 1755 IBA 070749 Ubiaja 114 TR 0772 KIBAHA Ubiaja 15 TR 0854 KIBAHA Ubiaja 115 TR 1229 GM 3594 Ubiaja 16 TR 1051 IBA961089A Ubiaja 116 TR 0118 IBA 100403 Ubiaja 17 TR 0261 IBA 961439 Ubiaja 117 TR 0840 IBA 102286 Ubiaja 18 TR 1201 SM 3374 Ubiaja 118 TR 0396 IBA I011086 Ubiaja 19 20 TR 0894 TR 0232 IBA 102710 BA 010169 Ubiaja Ubiaja 119 120 TR 1788 TR 0485 SM 3374 IBA 970219 Ubiaja Ubiaja 21 TR 1302 IBA 070520 Ubiaja 121 TR 1152 SM 3444 Ubiaja 22 TR 1128 IBA 100198 Ubiaja 122 TR 0990 KIBAHA Ubiaja 23 TR 1808 IBA 070539 Ubiaja 123 TR 1004 IBA 070520 Ubiaja 24 TR 0172 IBA 011404 Ubiaja 124 TR 0679 SM 3434 Ubiaja 25 TR 0382 IBA 010732 Ubiaja 125 TR 1515 IBA 980505 Ubiaja 26 TR 0384 IBA 011404 Ubiaja 126 TR 1735 IBA 071393 Ubiaja 27 TR 1688 TME B2026 Ubiaja 127 TR 0700 IBA 102286 Ubiaja 28 TR 1437 TME B2026 Ubiaja 128 TR 1463 IBA 980581 Ubiaja 29 TR 0696 IBA 102612 Ubiaja 129 TR 0365 IBA 011663 Ubiaja 30 TR 0033 IBA 102286 Ubiaja 130 TR 1620 TMEB 693 Ubiaja 31 TR 1034 IBA 050327 Ubiaja 131 TR 0289 IBA 961632 Ubiaja 32 O334 SM 3444- 2 Ubiaja 132 TR 1603 IBA 30572 Ubiaja 33 TR 1610 IBA 070525 Ubiaja 133 TR 1505 IBA 102429 Ubiaja 34 35 TR 0631 TR 1233 IBA 101040 IBA 070675 Ubiaja Ubiaja 134 135 TR 1849 TR 0031 TME B778 IBA 050311 Ubiaja Ubiaja 36 TR 0998 IBA 30572 Ubiaja 136 TR 0319 IBA 050099 Ubiaja 37 TR 1744 MM 090564 Ubiaja 137 TR 1198 SM 3374 Ubiaja 38 TR 1153 SM 3374 Ubiaja 138 TR 1256 IBA 070738 Ubiaja 39 TR 0886 SM 3666 Ubiaja 139 TR 1557 IBA 082708 Ubiaja 40 TR 0446 IBA 070749 Ubiaja 140 TR 0535 IBA 020091 Ubiaja 41 TR 0974 IBA 101438 Ubiaja 141 TR 0856 KIBAHA Ubiaja 42 TR 1565 IBA 102480 Ubiaja 142 TR 1359 IBA 070520 Ubiaja 43 TR 0785 IBA 070620 Ubiaja 143 TR 0881 IBA 102480 Ubiaja 44 TR 1569 GM 3594 Ubiaja 144 TR 1405 IBA 083724 Ubiaja 45 TR 0713 IBA 082708 Ubiaja 145 TR 0385 SM 3374 Ubiaja 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1196 Genet Resour Crop Evol (2020) 67:1193–1208 Table 1 continued No. Accession name Pedigree Origin No. Accession name Pedigree Origin 46 47 TR 0423 TR 0887 IBA 011206 IBA 082708 Ubiaja Ubiaja 146 147 TR 1223 TR 0680 SM 3374 KIBAHA Ubiaja Ubiaja 48 TR 1785 SM 3434 Ubiaja 148 TR 1313 IBA 070520 Ubiaja 49 TR 0025 IBA 071393 Ubiaja 149 TR 0480 IBA 015654 Ubiaja 50 TR 1374 IBA 102480 Ubiaja 150 TR 1266 IBA 070738 Ubiaja 51 TR 1562 IBA 980505 Ubiaja 151 TR 1071 IBA 100649 Ubiaja 52 TR 1236 Z 960012 Ubiaja 152 TR 0703 SM 3434 Ubiaja 53 TR 0838 IBA 070557 Ubiaja 153 TR 0893 IBA 102480 Ubiaja 54 TR 1480 IBA 082708 Ubiaja 154 TR 1689 TMEB 2026 Ubiaja 55 TR 0937 IBA 082708 Ubiaja 155 TR 0707 SM 3434 Ubiaja 56 TR 0743 IBA 101094 Ubiaja 156 TR 1556 IBA 070749 Ubiaja 57 TR 1540 BA 011371 Ubiaja 157 TR 0927 IBA 070337 Ubiaja 58 TR 0747 IBA 102286 Ubiaja 158 TR 0688 SM 3374 Ubiaja 59 TR 1348 IBA 980501 Ubiaja 159 TR 1007 IBA 100645 Ubiaja 60 TR 1438 SM 3434 Ubiaja 160 TR 0299 IBA 051625 Ubiaja 61 62 TR 1477 TR 1243 IBA 070520 IBA 070738 Ubiaja Ubiaja 161 162 TR 1289 TR 0851 IBA 011412 SM 3444 Ubiaja Ubiaja 63 TR 0807 BA 011206 Ubiaja 163 TR 0295 IBA 051625 Ubiaja 64 TR 1389 IBA 083849 Ubiaja 164 TR 1590 IBA 30572 Ubiaja 65 TR 1259 IBA 070738 Ubiaja 165 TR 0918 IBA 101803 Ubiaja 66 TR 1182 IBA 100649 Ubiaja 166 TR 1133 IBA 100198 Ubiaja 67 TR 1543 KIBAHA Ubiaja 167 TR 1331 IBA 070520 Ubiaja 68 TR 0975 IBA 083724 Ubiaja 168 TR 0461 IBA 051654 Ubiaja 69 TR 1155 IBA 070738 Ubiaja 169 TR 1419 IBA 102612 Ubiaja 70 TR 1404 SM 3374 Ubiaja 170 TR 0368 IBA 011663 Ubiaja 71 TR 1202 IBA 102429 Ubiaja 171 TR 0299 IBA 071393 Ubiaja 72 TR 0955 GM3594- 12 Ubiaja 172 TR 1448 IBA 083724 Ubiaja 73 TR 0520 IBA 101438 Ubiaja 173 TR 1322 IBA 070520 Ubiaja 74 TR 1208 IBA 083724 Ubiaja 174 TR 0399 IBA 071393 Ubiaja 75 TR 0843 SM 3374 Ubiaja 175 TR 1525 BA 011371 Ubiaja 76 TR 1113 IBA 101645 Ubiaja 176 TR 1753 IBA 070749 Ubiaja 77 78 TR 1316 TR 0693 IBA 071313 SM 3374 Ubiaja Ubiaja 177 178 TR 1501 TR 0019 IBA 102429 IBA 990313 Ubiaja Ubiaja 79 TR 1593 SM 3444 Ubiaja 179 TR 0296 IBA 961551 Ubiaja 80 TR 1598 IBA 982101 Ubiaja 180 TR 1360 IBA 070557 Ubiaja 81 TR 0282 IBA 070520 Ubiaja 181 TR 1527 IBA 102429 Ubiaja 82 TR 1350 IBA 102286 Ubiaja 182 TR 0560 MM 980747 Ubiaja 83 TR 0957 IBA 30572 Ubiaja 183 TR 1502 IBA 070557 Ubiaja 84 TR 1422 IBA 30572 Ubiaja 184 SLICASS 11 IBA 070749 Sierra Leone 85 TR 0932 IBA 050303 Ubiaja 185 SLICASS 4 Can’t be traced Sierra Leone 86 TR 1349 IBA 083849 Ubiaja 186 SLICASS 6 Can’t be traced Sierra Leone 87 TR 0810 IBA 101645 Ubiaja 187 SLICASS 7 Can’t be traced Sierra Leone 88 TR 0718 IBA 102612 Ubiaja 188 COCOA Local Cultivar Sierra Leone 89 TR 0907 IBA 030007 Ubiaja 90 TR 335 IBA 030007 Ubiaja 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 1197 Table 1 continued No. Accession name Pedigree Origin 91 92 TR 1327 TR 1666 IBA 070520 IBA 070703 Ubiaja Ubiaja 93 TR 1748 IBA 070749 Ubiaja 94 TR 1361 IBA 070557 Ubiaja 95 TR 0189 IBA 011206 Ubiaja 96 TR 1269 IBA 070738 Ubiaja 97 TR 1533 SM 3434 Ubiaja 98 TR 1762 IBA 070557 Ubiaja 99 TR 0015 IBA 990313 Ubiaja 100 TR 0018 IBA 070593 Ubiaja Table 2 Parameters evaluated at 1, 3, 6 and 9 month after planting No. Accession name Pedigree Origin Traits Traits Leaf color Color of stem epidermis Number of leaf lobes Color of stem cortex Length of leaf lobe Growth habit of stem Width of leaf lobe Prominence of foliar scars Lobe margin Leaf retention Pubescence of apical leaves Level of branching Color of apical leaves Height at 1st branching Orientation of petiole Petiole color Height at 2nd branching Height at 3rd branching Leaf area Color of end branches of adult plant Length of stipule Percentage sprout Stipule margin African cassava mosaic disease Stem color Cassava green mite Stem diameter base Cassava anthracnose disease Stem diameter-1foot below percentage was determined by selecting three representative storage roots. Slices of the fresh root were randomly selected and weighed to obtain a 100 g fresh mass sample per genotype, before being dried for 48 h in an oven at 80 °C. The dried samples were then reweighed to obtain the dry mass. Disease occurrence and intensity were mostly measured in the 1st, 3rd, 6th and 9th month after planting. Molecular characterization The Dellaporta method of DNA extraction (Dellaporta et al. 1983) was carried out at the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. For genotyping-by-sequencing library preparation, the ApekI restriction enzyme (recognition site: G|CWCG) that produces less variable distributions of read depth, and therefore, a larger number of scorable SNPs in cassava (Hamblin and Rabbi 2014) was used. Two 96-plex GBS libraries were constructed as 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1198 Genet Resour Crop Evol (2020) 67:1193–1208 described by Elshire et al. (2011) and sequenced at the Institute of Genomic Diversity at Cornell University, using the Illumina HiSeq 2500. Raw read sequences were processed through cassava GBS production pipelines developed using TASSEL 5.0V2. The GBS-derived SNPs were further filtered using the TASSEL software (Bradbury et al. 2007) to retain only polymorphic SNPs. Initially, filtered for minor allele frequency (MAF \ 0.05), the generated 5634 SNPs were processed under the Next Generation Cassava project. The resulting SNP dataset was used for the diversity analysis study among the 188 cassava accessions already phenotyped and analyzed. Results from both the phenotype and genotype analyses were compared to check the correspondence between the two. Data analysis Agro-morphological data sets from this study were subjected to selected statistical packages for analysis. Analytical procedures comprised the following softwares and statistical procedures: descriptive statistics using XLSTAT (2010), MINITAB 15 and STATA 13. Principal Component Analysis (PCA) were performed using Princomp software to examine the structure of the correlations between the variables using SAS 9.3. Cluster analyses, based on Agro-morphological and SNP markers data sets, were performed to group observations together using the method of Ward’s minimum variance distance using SAS 9.4. A dendrogram was plotted from the computed similarity values for each Agro-morphological traits and SNP markers to show the relationship among the accessions. The provitamin-A studied accessions and varieties were grouped based on the varying levels of total carotenoid content. Basic diversity indices for the 183 provitamin-A studied accessions and varieties were calculated using Power marker (Liu and Muse 2005) and GenAlex version 6.41 (Peakall and Mouse 2006). The Power maker software was used to generate the following statistics: number of alleles per locus, major allele frequency, observed heterozygosity (Ho), expected heterozygosity (He) and polymorphic information content (PIC) (Bostein et al. 1980). PIC values were calculated with the equation: PIC ¼ 1 RP2 i R2P2 i where: RP2i = sum of each squared ith haplotype frequency. A Mantel matrix test (Mantel 1967) was carried out to compare the extent of agreement between dendrograms derived from morphological and molecular data using the distance matrices. The pairwise genetic distance (identity-by-state, IBS) matrix was calculated among all individuals using PLINK (Purcell et al. 2007). A Ward’s minimum variance hierarchical cluster dendrogram was built from the IBS matrix, using the analyses of phylogenetic and evolution (ape) package in R. Results and discussion Summary statistics of morpho-agronomic traits of 183 provitamin-A studied accession and varieties Table 3 shows summary statistics of some morphoagronomic traits of 183 provitamin-A studied accessions and varieties. Sprouting was only recorded in the first month after planting (MAP) and ranged from 65 to 100% among the 183 provitamin-A studied accessions and varieties with an average of 9.56 seeds sprouted in the first month. Severity scores for African Cassava Mosaic Disease Cassava Bacterial Blight and Cassava Green Mite variably ranged from 0 to nine in the studied collection consisting of the 183 provitamin-A cassava collection and the five varieties. Percent incidence for African Cassava Mosaic Disease, Cassava Bacterial Blight and Cassava Green Mite variably ranged from 0 to 9. Most of the morphological characters both quantitative and qualitative were taken in the 3rd, 6th, 9th and 12th MAP. Color of apical lobe ranged from 3 to 9 about a mean of 6.8 ± 1.61 3 MAP; whereas the same traits scored ranged from 0 to 9 about a mean of 6.71 ± 1.74 9 MAP. Plant height ranged from 65.5 to 284.5 cm at 6 MAP about a mean of 155.69 ± 26.12 cm. Leaf area ranged from 10.24 to 73.93 cm2 at 6 MAP; whereas leaf retention ranged from 1.75 to 4.5 at the same time. All yield related traits were recorded at 12 MAP. Yield per hectare ranged from 0.2 to 42.5 t/ha; while dry matter content ranged from 4.0 to 44.5% (Table 3). These parameters which were good indicators of growth showed considerable variation for the morpho- 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 1199 Table 3 Summary statistics of some morpho-agronomic traits of the studied accessions and varieties Trait Descriptive statistics Time of data collection (MAP) Sprouting (%) 1 Minimum 6.5 Maximum 10 Mean Standard deviation 9.56 0.6 ACMD Incidence (%) 1, 3, 6 and 9 0 4.25 0.08 0.42 ACMD Severity (score) 1, 3, 6 and 9 0.75 2 1.04 0.13 CAD Incidence (%) 1, 3, 6 and 9 0 2.75 0.11 0.41 CAD Severity (score) 1, 3, 6 and 9 0.5 2.75 1.05 0.23 CBB Incidence (%) 1, 3, 6 and 9 0 4 0.41 0.6 CBB Severity (score) 1, 3, 6 and 9 0.5 4.5 1.15 0.34 Mealybug incidence (%) 9 0 9 3.22 2.17 Mealybug severity (score) 9 1 6.5 2.54 0.84 CGM Incidence (%) 9 2 8 5.27 1.66 CGM Severity (score) Colour of apical lobe (score) 9 3 2 3 9 9 3.31 6.8 0.72 1.61 Colour of apical lobe (score) 6 0 5 2.90 0.99 Colour of apical lobe (score) 9 0 9 6.71 1.74 Plant height (cm) 6 65.5 284.5 155.69 26.12 Height of branching (cm) 6 37 196.5 85.83 29.38 Stem diameter base (cm) 6 1.07 3.94 1.51 0.26 Stem diameter (mid height) (cm) 6 1.03 2.25 1.53 0.2 Leaf area (cm2) 6 10.24 73.93 34.13 11.04 Leaf retention (score) 6 1.75 4.5 2.87 0.5 Shape of central leaflet (score) 6 1.75 6.25 3.13 0.94 Petiole colour (score) 6 0.5 7 1.94 1.48 Petiole colour (score) 9 1 8 3.2 1.54 Leaf colour (score) 6 1.5 5 3.69 0.87 Leaf colour (score) 9 3 Colour of leave vein (score) Petiole length (cm) 6 6 3 3 6 18.75 32.95 3.94 0.77 3.85 14.79 1.73 6.09 Orientation of petiole (score) 6 0.5 7 2.55 1.13 Number of leaf lobes (no) 6 3.75 8 6.18 0.89 Length of leaf lobe (cm) 6 3.13 15.15 11.15 1.61 Width of leaf lobe (cm) 6 1.08 7.05 3.05 0.81 Lobe margin (score) 6 1.5 8 4.38 1.87 Length of stipules (cm) 9 1 4 2.97 0.22 Stipule margin (score) 9 1 5 1.31 0.59 Prominence of foliar scars colour (score) 9 3 6 4.93 0.39 Stem colour (score) 6 4 8 6.47 0.79 Colour of stem exterior (score) 6 1 7 2.55 0.71 Colour of stem epidermis (score) 9 4 8.5 6.52 1.1 Colour of end branches of adult plants (score) 9 1 32.5 4.62 2.47 7.5 88 44.83 14.21 12.09 5.69 0.47 2.62 Mean number of storage root (no) 12 Yield (t/ha) 12 0.24 42.5 Mean weight per storage root (kg) 12 0.09 28 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1200 Genet Resour Crop Evol (2020) 67:1193–1208 Table 3 continued Trait Descriptive statistics Time of data collection (MAP) Minimum Maximum Mean Standard deviation Dry matter content (%) 12 4 44.5 29.56 Root size (score) 12 2 7 4.93 6 1.07 Root shape (score) 12 1 5 2.76 0.62 Outer root colour (score) 12 1 4 3.4 0.72 Inner root colour (score) 12 1 3 1.9 0.36 Pulp colour (score) 12 1 3 2.01 0.19 Ease of peeling (score) 12 2 7 2.83 0.53 Biomass (kg) 12 2.5 13.5 9.99 1.91 MAP, month after planting; ACMD, African cassava mosaic Disease; CAD, cassava anthracnose disease; CBB, cassava bacterial blight; CGM, cassava green mite agronomic traits evaluated in the study, and the findings were in concordance with previous studies by Mbah et al. (2019) who reported that agro morphological parameters exert strong influence on cassava root yield. In the present study, descriptive analysis of the 183 provitamin-A studied accessions and varieties based on various traits showed high variability among the accessions. The significant variation observed among the 183 provitamin-A studied accessions and varieties studied for these economically important traits, such as African cassava mosaic disease, yield and dry matter content (DMC) offers a prospect for progress in cassava breeding program in Sierra Leone. Diversity studies of cassava germplasm has been widely undertaken worldwide (Bolanos 2001; Chavez et al. 2005; Morillo 2009; Fregene 2007; Parkes 2011; Njoku 2012; Thompson 2013) with little or no attention in Sierra Leone. These findings agree with the findings by Carvalho and Schaal (2001) who reported, in Brazil, a high degree of variability among 94 cassava accessions of Brazilian origin. Raghu et al. (2007) in a similar study, in India, also identified a high level of diversity among 58 cassava accessions from South Indian cassava germplasm based on 29 morphological traits. Lyimo et al. (2012) reported significant variability among 39 cassava accessions of Tanzanian origin using 14 morphological traits. Thompson (2013) observed a moderate to high diversity among 150 Ghanaian landraces and introduced accessions from IITA, Ibadan, Nigeria using 25 morphological traits in Ghana. Summary statistics of the genetic variation among the 183 provitamin-A studied accessions and varieties using SNP markers Summary statistics for number of alleles observed, expected heterozygosity and polymorphic information content are presented in Table 4. The number of observed alleles ranged from 1.30 to 1.47, with an average of 1.38 alleles per locus. The expected heterozygosity was the lowest for TR 1233 (0.15) and SLICASS 6 (0.15) and highest in TR 1525 (0.23), with a mean of 0.19. The observed heterozygosity per individual observation ranged from 0.30 (TR 1233) to 0.47 (TR 1525) with a mean of 0.38. The mean of Table 4 Summary statistics for number of alleles observed, expected heterozygosity and polymorphic information content stats Mafa no of allele Heb Hoc Picd Mean 0.81 1.38 0.19 0.38 0.14 Maximum 0.85 1.47 0.23 0.47 0.18 Minimum 0.77 1.30 0.15 0.30 0.11 a Maf, majority of allele frequency; bHe, heterozygosity; cHo, momozygosity; dPic, polymorphic information 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 observed heterozygosity (0.38) was moderately higher than the expected heterozygosity (0.19). This substantiates the difference in the relatedness of most of the provitamin-A studied accessions which were developed from varieties of half sib families with different female know parental sources (Female plants) been pollinated by different sources. However, the major allele frequency (MAF) of all the ‘markers used in the observations was generally, below 0.95, indicating that they were all polymorphic. PIC values ranged from 0.11 in TR 1233 to 0.18 in TR 1199 and TR 1525 with a PIC mean of 0.14. The higher the PIC value the more informative is the marker. Since morphological traits are influenced by the environment, molecular markers which are not influenced or controlled by the environment are preferable in genetic diversity studies (Kaemmer et al. 1992; Gepts 1993; Njoku 2012; Thompson 2013). The study carried out by Kawuki et al. (2009) was the first published report where SNPs were used for genetic diversity studies in cassava. They characterized and identified some SNP markers and assessed their utilization in cassava genetic diversity analysis assessment. The present study seems to be the first reported case in Sierra Leone, where SNP markers were used in cassava diversity study of provitamin-A cassava accessions. Using the 5634 SNP markers, 95% of them were polymorphic. The informativeness of a genetic marker is measured by the polymorphic information content (PIC). The mean PIC value observed in this study (0.14) is relatively lower than previously reported. Indeed, Kawuki et al. (2009) reported a PIC value of 0.29 in 74 cassava accessions using 26 SNP: while Thompson (2013) also reported PIC value of 0.29 using 150 cassava accessions. PIC values for SNP markers in cassava are generally lower than observed in genetic diversity studies in other crops. For instance, Yang et al. (2011) reported PIC value of 0.34 in maize genotypes using 884 SNP markers. Principal component analysis among yield and yield related traits of 183 provitamin-A cassava studied accessions and varieties The first five PCs together accounted for 70.44% of the total phenotypic variation among the 183 provitaminA cassava studied accessions and five varieites (Table 5). PC1 axis had an eigenvalue of 4.44 and acounted for 27.74% of the total variation, whereas 1201 Table 5 Principal component analysis of yield and yield related traits Variable Eigenvectors Comp1 Comp2 Comp3 Comp4 Comp5 mrot 0.40 0.05 - 0.15 - 0.02 0.02 unmrot 0.09 0.24 - 0.63 - 0.04 0.06 tsr 0.37 0.00 - 0.47 - 0.06 0.05 mwet 0.44 0.05 0.23 0.00 0.00 nmwet 0.06 0.46 0.12 0.00 0.15 twet 0.39 0.25 0.25 0.01 0.05 yld 0.44 0.05 0.23 - 0.03 0.06 - 0.06 - 0.12 0.50 0.09 0.10 dmc 0.14 - 0.28 0.14 - 0.31 0.03 rz 0.30 - 0.08 0.02 0.26 - 0.24 - 0.03 - 0.01 0.12 - 0.17 - 0.13 0.29 - 0.32 0.00 0.67 0.39 wsrot rs ocol incol - 0.06 - 0.01 0.01 0.68 0.45 pcol - 0.09 0.10 0.16 - 0.45 0.13 epeel - 0.09 0.46 0.10 0.10 - 0.07 biomas 0.11 - 0.25 - 0.06 0.20 0.28 Eigenvalue 4.44 3.18 1.45 1.11 1.09 Difference 1.26 1.74 0.33 0.02 0.18 Proportion 27.74 19.89 9.03 6.95 6.82 Cumulative 27.74 47.64 56.67 63.62 70.44 The bold column in tables signifies the traits that contributed higher negative or positive loadings to the percent variance explained mrot, marketable roots; unmrot, non-marketable roots; tsr, total number of storage roots; mwet, marketable weight; nmwet, Non-marketable weight; twet, total weight; yld, yield; wsrot, storage root weight; dmc, dry matter content; rz, root size; rs, root shape; ocol, Outer color; epeel, ease of peel PC, PC3, PC4 and PC5 axes had eigenvalues of 3.1, 1.45, 1.11% and 1.09% acounted for 19.8%, 9.03%, 6.95% and 6.82% of the total variation, respectively. Marketable root, marketable weight and yield had positive loadings on PC1. Non-marketable weight, storage root weight and ease of peel had positive loadings on PC2. Unmarketable root and total number of storage roots had negative loadings in PC3. Root Size had a positive loading in PC4 and Inner color had a positive loading in PC5. Principal Component Analysis is a technique which identifies plant traits that contribute most to the observed variation within a group of 183 provitamin- 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1202 Genet Resour Crop Evol (2020) 67:1193–1208 A studied accessions and five varieties. The tool has a practical application in the selection of parent lines for breeding purposes and varietal development. The cumulative variance of 70.44% by the first five axes with eigen values [ 1.0 indicates that the identified traits within these axes exhibited great influence on the phenotype of these accessions, and could effectively be used for selection among them. This study agrees with findings of Afuape and Nwachukwu (2005; Afuape et al. 2010), who reported a cumulative variance of 70.09% for the first three axes in the dry evaluation of nine sweetpotato genotypes, weight of total roots, weight of biomass, and dry matter as the important traits that distinguished the elite materials been researched on. Cluster groupings of the studied accessions and varieties based on morpho-agronomic traits using ward’s minimum variance and SNP markers Agro-morphological traits diversity analysis: The dendrogram constructed based on the data generated from the agro-morphological traits divided the provitamin-A studied accessions and five varieties into six major clusters (A to F), and at a genetic distance of 0.30, and each had sub clusters apart from Cluster A (Table 6). Cluster A consisted of only two cassava accession germplasm with no sub clusters. Cluster B, had two sub cluster, Cluster D recorded the highest number of accessions, 57 in total, followed by Cluster E and F, grouping 53 and 34 accessions, respectively. In general, most of the accessions in this study were grouped according to their morpho-agronomic traits and geographical location. For example, the accessions in major Cluster E scored similar values for most of the morph-agronomic traits studied. Three out the five Sierra Leonean varieties developed in Sierra Leone were grouped into cluster F: while cluster B and D contained only provitamin-A studied accessions introduced to Sierra Leone in the form of seeds from IITA, Nigeria, and had a discrete pattern of clustering, which have been grouped more or less per their state, geographical distribution or country. SNP markers diversity analysis: The 181 Provitamin-A cassava accession germplasm and 4 Sierra Leonean varieties were grouped into nine clusters based on the 5643 SNP markers (Fig. 1). Clusters A, B, C, D and E, had 21, 7, 11, 8, and 16 accessions, respectively; while cluster F, G, H and I consisted of 10, 47, 50 and 17 accessions, respectively (Table 7). Clusters A, B, C, E, G, H and I had 3, 1, 2, 4, 9, 10, and 1 accessions with varying levels of total carotenoid content. Cluster I consisted of only one provitamin-A studied accessions. Correlation Analysis between Clusters from AgroMorphological Traits and SNP Makers: A comparison of the two dendrogram based on Mantel matrix test showed a significant positive, but weak correlation between the morphological and molecular data sets (r = 0.104, p \ 0.034). In a similar study, Raghu et al. (2007) mentioned that 24 morphological traits out of 28, contributed to the total variation observed. Here, our clustering study showed six and nine distinct clusters based on morphological and molecular analyses, respectively, indicating a large variability in the collection. In a similar study, Carvalho and Schaal (2001) identified 22 distinct clusters using 94 cassava accessions in Brazil, whereas Raghu et al. (2007) identified six distinct groups using 58 accessions. Our study is, therefore, in agreement with all these studies. Although the morphological and SNP data grouped the accessions into six and nine distinct clusters, respectively, some similarities were observed. Accessions TR 0747 and TR 0365 which were selected as provitamin-A studied accessions were found to be closely similar using both morphological and genetic markers. This could explain why the morphological and molecular analysis showed similar accessions between the two clusters. There are no reports on the genetic diversity of provitamin-A cassava accessions using morphological traits, molecular markers and total carotenoid content so far. This remains the first study using morphological, genetic diversity characterization and total carotenoid content levels of our provitamin-A cassava accessions in Sierra Leone. The study reveals a moderate degree of diversity among the provitamin-A cassava accessions and varieties which can be further used for crop improvement. This may provide an opportunity to enhance and boost the breeding strategy. Thirty provitamin-A studied accessions with varying levels of total carotenoid content, yield and dry matter content The 30 accessions grouped in the different clusters were selected as provitamin-A studied accessions for formation of core collection, conservation and 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 1203 Table 6 Cluster groupings of the 182 provitamin-a studied accessions and five sierra leonean varieties based on morpho-agronomic traits using ward’s minimum variance Cluster A Cluster B Cluster C Cluster D Cluster D Cluster E Cluster E Cluster F TR1808 TR0560 TR1590 TR0700 TR0033 TR1578 TR0396 TR1603 TR1259 TR1207 TR1133 TR1202 TR1313 TR1735 TR1233 TR1788 TR1128 TR0703 TR1031 TR0019 TR0743 TR0631 TR0890 TR1004 TR0421 TR1563 TR1744 TR0983 TR0535 TR1533 TR1007 TR1144 TR1337 TR1208 TR0520 TR1610 TR0480 TR0894 TR0707 TR1201 TR0810 TR1515 TR0446 TR1666 TR0990 TR0918 TR0696 TR1501 TR1279 TR0974 TR0851 TR1034 TR0688 TR1350 TR1289 TR0881 TR0998 TR1155 TR0296 TR1269 TR1316 TR1244 TR0868 TR0385 TR1051 TR9689 TR0365 TR1556 TR1071 TR0282 TR1405 TR0854 TR1113 TR0368 TR0893 TR1557 TR1753 TR0085 TR0955 TR0295 TR1748 TR0856 TR1525 TR1349 TR1565 TR0399 TR1480 TR0316 TR1198 TR1569 TR1404 TR1562 TR1688 TR1223 TR1477 TR0907 TR1502 TR1598 TR1302 TR0384 TR0747 TR1361 TR0838 TR0172 TR1199 TR0840 TR1448 TR1419 TR1295 TR0887 TR1153 TR1540 TR1374 TR1327 TR0382 TR0679 TR0807 TR0289 TR0713 TR1755 TR1849 TR0319 I1635/Slicass 11 TR0861 TR0118 TR1073 TR1543 TR1422 TR0431 TR0772 TR335 TR0957 TR1182 TR1360 TR0267 TR0693 TR1505 TR0222 TR0232 TMEB419/Slicass 7 TR0927 TR0886 TR1322 TR1229 TR1256 TR1463 TR1437 TR0718 TR1620 TR0785 Slicass4 TR1348 TR0025 TR0461 TR1331 TR1762 TR1359 TR1627 TR1008 TR0299 TR0485 TR1438 TR1527 TR0031 TR1389 TR1236 TR0018 TR0957 TR1785 TR1243 TR0015 TR0937 TR1152 TR1593 TR0224 TR0932 TR0015 TR0423 TR0982 TR0683 TR1593 TR0626 TR0189 O334 Slicass6 TR0843 Cocoa improvement in the breeding program. These accessions were selected based on the higher levels of total carotene content after laboratory analysis using color chat and the i-check device. The core selected provitamin-A cassava accessions across different clusters revealed significant variation of total carotenoid content, yield and dry matter. These provitamin- A cassava accessions TR 0998, TR 0222, TR 1337 and TR 0461 contained higher levels of total carotenoid content with TR 0365 been the lowest. Dry matter content ranged from 12.5 (TR 0696) to 39.5 (TR 1208) with yield ranging from 2.0 (TR 0461) to 22.8 (TR 0232) in the study provitamin-A accessions. TR 0747, TR 1337, TR 0232, TR 0998 and TR1755 clustered 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1204 Genet Resour Crop Evol (2020) 67:1193–1208 C D E B F A I G H Fig. 1 Dendrogram of 182 Provitamin-A studied accessions and Sierra Leonean varieties based on SNP markers similarly morphologically and genetically (B, D, E, E and E). The wide range of total carotenoid content, dry matter content, yield, and distribution of morphological variability revealed in the study might provide a broader scope for the crop’s improvement through hybridization and selection. The higher dry matter content and significant variability observed in some provitamin-A cassava accessions in this study contradict findings reported by Esuma et al. (2012) who reported high DMC and low total carotenoid content for local white cassava root varieties using the Ugandan landraces. Conclusion The present morphological and molecular assessment studies reported that provitamin-A cassava accessions in Sierra Leone have moderate to high diversity based on total carotenoid content, morphological, and molecular assessment (Table 8). The inter-relationships of morpho- agronomic factors in determining cassava fresh root yield based on provitamin-A cassava accessions require additional research to fully understand concept of improving total carotenoid content and yield on provitamin-A 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 1205 Table 7 Cluster groupings of the 181 Provitamin-A Studied Accessions and Sierra Leonean Cassava varieties based on SNP Markers Cluster I Cluster H Cluster A Cluster B Cluster C Cluster D Cluster E Cluster F Cluster G Cluster G Cluster H TR0018 TR0679 TR0918 TR1643 TR1348 TR0299 TR0626 TR0707 TR1389 TR0480 TR0222 TR0282 TR0172 TR1419 TR1008 TR0718 TR0118 TR1448 TR1244 TR1438 TR0485 TR1788 Slicass 4 TR1590 TR1233 TR0015 TR1808 TR1229 TR1543 Slicass6 TR1350 TR1201 TR1155 TR1505 TR1620 TR1501 TR0446 TR1666 TR0683 TR0172 TR1327 TR1480 TR1610 TR1556 TR1534 TR0295 TR0368 TR1071 TR0713 TR1256 TR0840 TR0932 TR0269 TR1313 TR3168 TR1735 TR1753 TR1515 TR0843 1/1635/Slicass 11 TR1128 TR1259 TR0856 TR0681 TR1223 TR0894 TR0747 TR0703 TR0306 TR1313 TR335 TR0399 TR0461 TR0224 TR0890 TR0085 TR0982 TR0868 TR0975 TR1593 TR0189 TR1322 TR1295 TR0033 TR0744 TR1688 TR1302 TR1152 TR0025 TR0881 TR1207 TR1198 TR1243 TR1557 TR0854 TR0261 TR1034 TR0365 TR0700 TR0019 TR0535 TR1562 TR1502 TR1031 TR1349 TR1266 TR0990 Cocoa TR1437 TR1269 TR1603 TR0886 TR1527 TR0998 TR1289 TR0693 TR0983 TR1627 TR1236 TR1762 TR0957 TR1202 TR1533 TMEB419/ Slicass 7 TR0421 TR0893 TR1689 TR0520 TR0560 TR0851 TR1360 TR1337 TR0319 TR1361 TR1004 TR1569 TR1182 TR0631 TR1755 TR0316 TR1563 TR1279 TR0688 TR1840 TR0031 TR0955 TR1540 TR1004 TR1359 TR1477 TR1113 TR0785 TR1785 TR1279 TR1073 TR0974 TR0887 TR1133 TR1598 TR1374 TR1748 TR1744 TR1007 TR1565 TR0232 TR1144 TR0384 TR0907 TR1208 TR1422 TR1405 O334 TR1578 TR1404 TR0423 cassava accession germplasm. Even though the agromorphological traits are generally employed to estimate genetic diversity in crop plants, such a method has its own limitations as the traits are heavily influenced by the environmental conditions and climate being the main factor influencing the growth and development of the species (Cadena Iniguez and Arevalo Galarza 2011). This also confirms the importance of molecular techniques and markers on Provitamin-A cassava accession germplasm to carry out successful research and improvement studies. The present study has revealed that during provitamin-A cassava variety development, high dry matter content TR0927 TR0267 TR1051 TR0801 TR1199 TR0810 TR0696 TR0382 (quality trait) is a priority trait that should be considered at both primary and advance (yield evaluation) stages with good root qualities to facilitate adoption after varietal release. Finally, the genetic diversity revealed from this study would provide the cassava breeding program in Sierra Leone an opportunity to boost the breeding strategy on crop genetic improvement for ProvitaminA cassava varieties with end-use preferred traits (total carotenoid content, dry matter, yield and African cassava mosaic disease resistance). 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. 1206 Genet Resour Crop Evol (2020) 67:1193–1208 Table 8 Thirty provitamin-A studied accessions with varying levels of total carotenoid content, dry matter content and yield Yield Dry matter content Accession Total carotenoid content (lg/g fresh weight) Phenotypic cluster name Genotypic cluster name TR 0747 10.9 B B 4.3 29.5 TR 0365 7.0 B C 2.3 25.5 TR 0560 9.7 B H 7.5 25.5 TR 1208 8.9 D G 7.5 39.5 TR 0461 11.5 D G 2.0 23.0 TR 1337 11.8 D D 14.6 25.5 TR 1569 10.3 D H 21.8 26.5 TR 0683 10.2 D G 5.0 28.5 TR 1198 10.8 D E 7.0 28.5 TR 1313 11.7 D E 11.0 35.0 TR 0696 11.1 D G 6.5 12.5 TR 1322 9.9 D H 13.0 29.5 TR 1350 9.0 D G 8.0 29.5 TR 0907 9.1 D G 6.0 31.5 TR 1557 TR 1152 11.2 8.08 D D A G 10.6 4.8 18.0 33.0 TR 0232 9.9 E E 22.8 27.0 TR 1279 9.1 E H 6.3 35.6 TR 0031 10.3 E A 6.9 29.5 TR 0222 13.1 E A 7.8 37.0 TR 0998 13.7 E E 2.8 38.1 TR 1755 10.7 E E 5.3 24.0 TR 1182 10.4 E I 10.8 24.0 TR 1753 8.6 E C 16.8 35.0 TR 0713 8.2 E F 7.5 28.0 TR 0423 8.7 G F 6.5 25.5 TR 0384 10.6 G F 5.5 27.0 TR 1327 11.1 F H 4.5 21.0 TR 0399 11.1 F G 11.8 25.5 Acknowledgements Support for this research was provided by the West Africa Agricultural Productivity Programme Sierra Leone (WAAPP-1C) through a Grant acquired from the Word Bank. We are grateful to Sierra Leone Agricultural Research Institute, West Africa Centre for Crop Improvement (WACCI), University of Ghana, Legon and the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria for providing free access to their facilities. Funding West Africa Agricultural Productivity Programme Sierra Leone (WAAPP). Compliance with ethical standards Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Conflict of interest We the authors of this manuscript declare that we have no conflict of interest. 123 Content courtesy of Springer Nature, terms of use apply. Rights reserved. Genet Resour Crop Evol (2020) 67:1193–1208 References Afuape SO, Nwachukwu EC (2005) Variability and correlation studies in some quantitative characters in selected sweetpotato (Ipomea batatas (L.) Lam) genotypes. Genetics and Sustainable Agriculture. 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