Diversity studies on soybean accessions from three countries

Appiah-Kubi, D.; Asibuo, James Yaw; Quain, Marian D.; Oppong, Allen; Akromah, R.

doi:10.1016/j.bcab.2013.11.008

Cited by 4 publications

(3 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The local commercial varieties Faisal soybean and Ajmeri were present in different clusters, indicating that these genotypes were introduced from various origins and assessed throughout the selection process before being made available for commercial cultivation [ 60 ]. Appiah-Kubi et al [ 61 ] assessment of the genetic diversity among the soybean genotypes using 20 SSR markers revealed a close link between genotypes and their geographic origin, which is consistent with these findings. Due to the substantial exchange of genetic resources among farming communities, the poor structure of germplasm may be a reflection of the presence of gene flow between the subpopulations [ 62 ].…”

Section: Discussionsupporting

confidence: 74%

Genetic diversity and population structure analysis in cultivated soybean (Glycine max [L.] Merr.) using SSR and EST-SSR markers

et al. 2023

View full text Add to dashboard Cite

Soybean (Glycine max) is an important legume that is used to fulfill the need of protein and oil of large number of population across the world. There are large numbers of soybean germplasm present in the USDA germplasm resources. Finding and understanding genetically diverse germplasm is a top priority for crop improvement programs. The current study used 20 functional EST-SSR and 80 SSR markers to characterize 96 soybean accessions from diverse geographic backgrounds. Ninety-six of the 100 markers were polymorphic, with 262 alleles (average 2.79 per locus). The molecular markers had an average polymorphic information content (PIC) value of 0.44, with 28 markers ≥ 0.50. The average major allele frequency was 0.57. The observed heterozygosity of the population ranged from 0–0.184 (average 0.02), while the expected heterozygosity ranged from 0.20–0.73 (average 0.51). The lower value for observed heterozygosity than expected heterozygosity suggests the likelihood of a population structure among the germplasm. The phylogenetic analysis and principal coordinate analysis (PCoA) divided the total population into two major groups (G1 and G2), with G1 comprising most of the USA lines and the Australian and Brazilian lines. Furthermore, the phylogenetic analysis and PCoA divided the USA lines into three major clusters without any specific differentiation, supported by the model-based STRUCTURE analysis. Analysis of molecular variance (AMOVA) showed 94% variation among individuals in the total population, with 2% among the populations. For the USA lines, 93% of the variation occurred among individuals, with only 2% among lines from different US states. Pairwise population distance indicated more similarity between the lines from continental America and Australia (189.371) than Asia (199.518). Overall, the 96 soybean lines had a high degree of genetic diversity.

show abstract

Section: Discussionsupporting

confidence: 74%

Genetic diversity and population structure analysis in cultivated soybean (Glycine max [L.] Merr.) using SSR and EST-SSR markers

et al. 2023

View full text Add to dashboard Cite

show abstract

“…One constraint of soybean production in several countries in Africa is the lack of genetic diversity or germplasm available. Only a handful of varieties have been released in Ghana since 1990: Salintuya-1, Quarshie, Jenguma, Salintuya-2 to name a few (Appiah-Kubi et al 2014). The source of genetic materials IITA utilized to build its germplasm collection is unknown, however genotype by sequencing analysis of 298 IITA breeding lines indicate that there exists as much diversity in those lines as varieties from the USA, Canada, and Brazil (PESSOA FILHO et al 2016).…”

Section: Current Breeding Practices In Africamentioning

confidence: 99%

“…The source of genetic materials IITA utilized to build its germplasm collection is unknown, however genotype by sequencing analysis of 298 IITA breeding lines indicate that there exists as much diversity in those lines as varieties from the USA, Canada, and Brazil (PESSOA FILHO et al 2016). Regardless of the limited number of variety releases, newly released varieties continue to see a yield increase (Appiah-Kubi et al 2014).…”

Section: Current Breeding Practices In Africamentioning

confidence: 99%

Adaptation of soybean to tropical environments for smallholder farmers

Miranda¹

View full text Add to dashboard Cite

There are many traits that influence crop adaption to a new environment so that it can perform as a farmer would prefer. In these chapters, I have shown the influence of the genetic mechanisms behind pod shatter, days to flower, days to maturity, and height for soybean in a tropical environment. We developed two molecular tools to identify the allele status of Pdh1, a gene that influences shatter. Using those tools, we discovered that this genetic source of shatter susceptibility is still prevalent in African breeding materials and released varieties. I also contributed knowledge of the effects of the maturity genes E1, E2, E3 and ELF3 on days to flower and days to maturity. It was discovered that season length can be controlled by choice of the long juvenile trait ELF3 allele. Days to flower is influenced by E1 alleles in a j-1 background, and is influenced by E1, E2, and E3 in a j-x background in some cases. I also discovered that the determinate and indeterminate phenotypes do have different influences on height in this environment, but the gene Dt1 does not affect maturity. The next step is to conduct yield testing to understand how these traits influence yield. In addition, other alleles of ELF3 should be bred into different backgrounds to see if they influence different season lengths as well. Finally, the genetic source of the long juvenile trait in the current African released varieties need to be discovered. Taken together the future data combined with the data presented here can assist a local breeder in Africa to choose the germplasm they want to control their season length or protect yields from pod shatter and ultimately create a new, elite African variety.

show abstract