Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-13T10:20:33.780Z Has data issue: false hasContentIssue false
  • English
  • Français

Assessment of diversity in tropical soybean (Glycine max (L.) Merr.) varieties and elite breeding lines using single nucleotide polymorphism markers

Published online by Cambridge University Press:  17 February 2021

Abush Tesfaye Abebe Open the ORCID record for Abush Tesfaye Abebe [Opens in a new window] ,
Adesike Oladoyin Kolawole ,
Nnanna Unachukwu ,
Godfree Chigeza ,
Hailu Tefera  and
Melaku Gedil
Abush Tesfaye Abebe
Affiliation:
International Institute of Tropical Agriculture, Ibadan, Nigeria
Adesike Oladoyin Kolawole
Affiliation:
Ladoke Akintola University of Technology, Ogbomoso, Nigeria
Nnanna Unachukwu
Affiliation:
International Institute of Tropical Agriculture, Ibadan, Nigeria
Godfree Chigeza
Affiliation:
International Institute of Tropical Agriculture, Lusaka, Zambia
Hailu Tefera
Affiliation:
Private Consultant, 2384 Rolling Fork Circle, #403, Herndon, VA20171, USA
Melaku Gedil*
Affiliation:
International Institute of Tropical Agriculture, Ibadan, Nigeria
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Soybean (Glycine max (L.) Merr.) is an important legume crop with high commercial value widely cultivated globally. Thus, the genetic characterization of the existing soybean germplasm will provide useful information for enhanced conservation, improvement and future utilization. This study aimed to assess the extent of genetic diversity of soybean elite breeding lines and varieties developed by the soybean breeding programme of the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. The genetic diversity of 65 soybean genotypes was studied using single-nucleotide polymorphism (SNP) markers. The result revealed that 2446 alleles were detected, and the indicators for allelic richness and diversity had good differentiating power in assessing the diversity of the genotypes. The three complementary approaches used in the study grouped the germplasm into three major clusters based on genetic relatedness. The analysis of molecular variance revealed that 71% (P < 0.001) variation was due to among individual genotypes, while 11% (P < 0.001) was ascribed to differences among the three clusters, and the fixation index (FST) was 0.11 for the SNP loci, signifying moderate genetic differentiation among the genotypes. The identified private alleles indicate that the soybean germplasm contains diverse variability that is yet to be exploited. The SNP markers revealed high diversity in the studied germplasm and found to be efficient for assessing genetic diversity in the crop. These results provide valuable information that might be utilized for assessing the genetic variability of soybean and other legume crops germplasm by breeding programmes.

Keywords

allelic diversitybreeding programmesgenetic relatednessSNPsoybean germplasm
Type
Research Article
Information
Plant Genetic Resources , Volume 19 , Issue 1 , February 2021 , pp. 20 - 28
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of NIAB

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, DH and Lange, K (2011) Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics 12: 246.CrossRefGoogle ScholarPubMed
Alexander, DH, Novembre, J and Lange, K (2009) Fast model based estimation of ancestry in unrelated individuals. Genome Research 19: 1655–1664.CrossRefGoogle ScholarPubMed
Chen, Y and Nelson, RL (2005) Relationship between origin and genetic diversity in Chinese soybean germplasm. Crop Science 45: 1645–1652.CrossRefGoogle Scholar
Chen, W, Hou, L, Zhang, Z, Pang, X and Li, Y (2017) Genetic diversity, population structure, and linkage disequilibrium of a core collection of Ziziphus jujuba assessed with genome-wide SNPs developed by genotyping by-sequencing and SSR markers. Frontiers in Plant Science 8: 575.Google ScholarPubMed
Chigeza, G, Boahen, S, Gedil, M, Agoyi, E, Mushoriwa, H, Denwar, N, Gondwe, T, Tesfaye, A, Kamara, A, Alamu, OE and Chikoye, D (2019) Public sector soybean (Glycine max) breeding: advances in cultivar development in the African tropics. Plant Breeding 2019: 1–10.Google Scholar
Cornelious, BK and Sneller, CH (2002) Yield and molecular diversity of soybean lines derived from crosses of northern and southern elite parents. Crop Science 42: 642–647.CrossRefGoogle Scholar
Dellaporta, SL, Wood, J and Hicks, JB (1983) A plant DNA mini preparation: version II. Plant Molecular Biology Reporter 1: 19–21.CrossRefGoogle Scholar
Eltaher, S, Sallam, A, Belamkar, V, Emara, HA, Nower, AA, Salem, KF, Poland, J and Baenziger, PS (2018) Genetic diversity and population structure of F3:6 Nebraska winter wheat genotypes using genotyping-by-sequencing. Frontiers in genetics 9: 76.CrossRefGoogle ScholarPubMed
FAO (2020) FAOSTAT. URL: http://www.fao.org/faostat/en/#data. Accessed date and time: 12/10/202, 9:40 am.Google Scholar
Frichot, E, Mathieu, F, Trouillon, T, Bouchard, G and François, O (2014) Fast and efficient estimation of individual ancestry coefficients. Genetics 196: 973–983.CrossRefGoogle ScholarPubMed
Gizlice, Z, Carter, TE Jr and Burton, JW (1993) Genetic diversity in North American soybean: I. Multivariate analysis of founding stock and relation to coefficient of parentage. Crop Science 33: 614–620.CrossRefGoogle Scholar
Gizlice, Z, Carter, TE Jr and Burton, JW (1994) Genetic base for North American public soybean cultivars released between 1947 and 1988. Crop Science 34: 1143–1151.CrossRefGoogle Scholar
Gizlice, Z, Carter, TE Jr, Gerig, TM and Burton, JW (1996) Genetic diversity patterns in North American public soybean cultivars based on coefficient of parentage. Crop Science 36: 753– 765.CrossRefGoogle Scholar
Hamblin, MT, Warburton, ML and Buckler, ES (2007) Empirical comparison of simple sequence repeats and single nucleotide polymorphisms in assessment of maize diversity and relatedness. PLoS One 2: 1367.CrossRefGoogle ScholarPubMed
Helms, T, Orf, J, Vallad, G and McClean, P (1997) Genetic variance, coefficient of parentage, and genetic distance of six soybean populations. Theoretical and Applied Genetics 94: 20–26.CrossRefGoogle ScholarPubMed
Hymowitz, T and Shurtleff, WR (2005) Debunking soybean myths and legends in the historical and popular literature. Crop Science 45: 473–476.CrossRefGoogle Scholar
Hyten, DL, Song, Q, Choi, IY, Yoon, MS, Specht, JE, Matukumalli, LK, Nelson, RL, Shoemaker, RC, Young, ND and Cregan, PB (2008) High-throughput genotyping with the GoldenGate assay in the complex genome of soybean. Theoretical and Applied Genetics 116: 945–952.CrossRefGoogle ScholarPubMed
Jombart, T (2008) Adegenet an R package for the multivariate analysis of genetic markers. Bioinformatics (Oxford, England) 24: 1403–1405.CrossRefGoogle Scholar
Keim, P, Beavis, GW, Schupp, J and Freestone, R (1992) Evaluation of soybean RFLP marker diversity in adapted germplasm. Theoretical and Applied Genetics 85: 205–212.CrossRefGoogle Scholar
Kisha, T, Sneller, CH and Diers, BW (1997) Relationship of genetic distance and genetic variance in populations of soybean. Crop Science 37: 1317–1325.CrossRefGoogle Scholar
Kisha, T, Diers, BW, Hoyt, JM and Sneller, CH (1998) Genetic diversity among soybean plant introductions and North American germplasm. Crop Science 38: 1669–1680.CrossRefGoogle Scholar
Lee, JD, Yu, JK, Hwang, YH, Blake, S, So, YS, Lee, GJ, Nguyen, HT and Shannon, JG (2008) Genetic diversity of wild soybean (Glycine soja Sieb. and Zucc.) accessions from South Korea and other countries. Crop Science 48: 606–616.CrossRefGoogle Scholar
Liu, K and Muse, SV (2005) Power marker: an integrated analysis environment for genetic marker analysis. Bioinformatics (Oxford, England) 21: 2128–2129.CrossRefGoogle Scholar
Lu, H and Bernardo, R (2001) Molecular marker diversity among current and historical maize inbreds. Theoretical and Applied Genetics 103: 613–617.CrossRefGoogle Scholar
Narvel, JM, Fehr, WR, Chu, WC and Grant, D (2000) Simple sequence repeat diversity among soybean plant introductions and elite genotypes. Crop Science 40: 1452–1458.CrossRefGoogle Scholar
Nelson, LA, Elmore, RW, Klein, RN and Shapiro, C (1998) Nebraska Soybean Variety Tests. Nebraska Coop. Ext. E. C. 98-104-A. Lincoln: University of Nebraska.Google Scholar
Paradis, E, Claude, J and Strimmer, K (2004) APE: analyses of phylogenetics and evolution in R language. Bioinformatics (Oxford, England) 20: 289–290.CrossRefGoogle ScholarPubMed
Peakall, R and Smouse, P (2012) Genalex 6.5: genetic analysis in Excel. Population genetic software for teaching and research – an update. Bioinformatics (Oxford, England) 28: 2537–2539.CrossRefGoogle ScholarPubMed
Purcell, S, Neale, B, Todd-brown, K, Thomas, L, Bender, D, Maller, J, Sklar, P, de Bakker, PIW, Daly, MJ and Sham, PC (2007) PLINK: a toolset for whole-genome association and population-based linkage analyses. American Journal of Human Genetics 81: 559–575.CrossRefGoogle Scholar
Qiu, L, Chen, P, Liu, Z, Li, Y, Guan, R, Wang, L and Chang, R (2011) The worldwide utilization of the Chinese soybean germplasm collection. Plant Genetic Resources: Characterization and Utilization 9: 109–122.CrossRefGoogle Scholar
R Core Team (2015) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.Google Scholar
Roldàn-Ruiz, I, Dendauw, J, Van Bockstaele, E, Depicker, A and De Loose, MA (2000) AFLP markers reveal high polymorphic rates in ryegrasses (Lolium spp.). Molecular breeding 6: 125–134.CrossRefGoogle Scholar
Salado-Navarro, LR, Sinclair, TR and Hinson, K (1993) Changes in yield and seed growth traits in soybean cultivars released in the southern U.S.A. from 1945 to 1983. Crop Science 33: 1204–1209.CrossRefGoogle Scholar
Semagn, K, Babu, R, Hearne, S and Olsen, M (2014) Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement. Molecular Breeding 33: 1–14.CrossRefGoogle Scholar
Singh, RJ and Hymowitz, T (1999) Soybean genetic resources and crop improvement. Genome 42: 605–616.CrossRefGoogle Scholar
Singh, N, Choudhury, DR, Singh, AK, Kumar, S, Srinivasan, K, Tyagi, RK, Singh, NK and Singh, R (2013) Comparison of SSR and SNP markers in estimation of genetic diversity and population structure of Indian rice varieties. PLoS One 8: e84136.CrossRefGoogle ScholarPubMed
Sneller, CH (1994) Pedigree analysis of elite soybean lines. Crop Science 34: 1515–1522.CrossRefGoogle Scholar
Sneller, CH, Miles, J and Hoyt, JM (1997) Agronomic performance of soybean plant introduction and their genetic similarity to elite lines. Crop Science 37: 1595–1600.CrossRefGoogle Scholar
Soybase (2020) Soybean genetic resources and genetic enhancements white paper. URL: https://soybase.org/Genetic_Resources/Soybean_Genetic_Resources.html accessed date: 16/08/2020.Google Scholar
Tantasawat, P, Trongchuen, J, Prajongjai, T, Jenweerawat, S and Chaowiset, W (2011) SSR analysis of soybean (Glycine max (L.) Merr.) genetic relationship and variety identification in Thailand. Australian Journal of Crop Science 5: 283–290.Google Scholar
Tefera, H, Kamara, AY and Asafo-Adjei, B (2009) Improvement in grain and fodder yields of early maturing promiscuous soybean varieties in the Guinea savanna of Nigeria. Crop Science 49: 2037–2042.CrossRefGoogle Scholar
Wright, S (1921) Systems of mating. II. The effects of inbreeding on the genetic composition of a population. Genetics 6: 124–143.CrossRefGoogle ScholarPubMed
Wright, S (1978) Evolution and the Genetics of Populations Vol. 4. Variability Within and among Natural Populations, Chicago: University of Chicago Press, p. 58.Google Scholar