Utilization of Interspecific High-Density Genetic Map of RIL Population for the QTL Detection and Candidate Gene Mining for 100-Seed Weight in Soybean

Abstract

Seed-weight is one of the most important traits determining soybean yield. Hence, it is prerequisite to have detailed understanding of the genetic basis regulating seed-weight for the development of improved cultivars. In this regard, the present study used high-density interspecific linkage map of NJIR4P recombinant inbred population evaluated in four different environments to detect stable Quantitative trait loci (QTLs) as well as mine candidate genes for 100-seed weight. In total, 19 QTLs distributed on 12 chromosomes were identified in all individual environments plus combined environment, out of which seven were novel and eight are stable identified in more than one environment. However, all the novel QTLs were minor (R2 < 10%). The remaining 12 QTLs detected in this study were co-localized with the earlier reported QTLs with narrow genomic regions, and out of these only 2 QTLs were major (R2 > 10%) viz., qSW-17-1 and qSW-17-4. Beneficial alleles of all identified QTLs were derived from cultivated soybean parent (Nannong493-1). Based on Protein ANalysis THrough Evolutionary Relationships, gene annotation information, and literature search, 29 genes within 5 stable QTLs were predicted to be possible candidate genes that might regulate seed-weight/size in soybean. However, it needs further validation to confirm their role in seed development. In conclusion, the present study provides better understanding of trait genetics and candidate gene information through the use high-density inter-specific bin map, and also revealed considerable scope for genetic improvement of 100-seed weight in soybean using marker-assisted breeding.

Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean (Glycine max L.) at Seedling Stages Using SLAF-Seq

“…Many studies have been performed to elucidate the genetic foundation and underlying root genetic function in soybean, and several root-related QTLs have been reported in various populations using various environments ( Liang et al, 2010 , 2014 ; Lü et al, 2010 ; Rong et al, 2011 ). Nevertheless, most of these QTL mapping studies were carried out using low-density genetic linkage maps ( Karikari et al, 2019 ). In soybean, roots have previously been indicated to be controlled by multigenes, and are strongly affected by environmental changes ( Lü et al, 2010 ).…”

GmKIX8‐1 regulates organ size in soybean and is the causative gene for the major seed weight QTL qSw17‐1

“…qSw17-1 is a well-known QTL associated with seed weight in soybean (Hoeck et al, 2003;Panthee et al, 2005;Liu et al, 2007Liu et al, , 2013Liu et al, , 2018Teng et al, 2008;Kim et al, 2010;Kato et al, 2014;Zhou et al, 2015;Yan et al, 2017;Karikari et al, 2019). Considerable effort has been invested in fine-mapping the QTL, and so far the smallest region identified corresponded to a c. 700 kb region on chromosome 17 (Fig.…”

Identification of Additive–Epistatic QTLs Conferring Seed Traits in Soybean Using Recombinant Inbred Lines

“…Linkage mapping has been widely used in detecting quantitative trait loci (QTL) of soybean 100-SW ( Stombaugh et al, 2004 ; Kato et al, 2014 ; Yang et al, 2019 ). To date, 304 QTLs have been identified for 100-SW in soybean; most are minor QTLs and the candidate genes have yet to be validated ( Karikari et al, 2019 ). There are 29 QTLs for SL mapped to 13 chromosomes, 25 for SW on 13 chromosomes, and 18 for SLW on 11 chromosomes in SoyBase 1 .…”

“…Given the lower marker density in early genetic linkage maps, chromosome regions potentially harboring 100-SW and seed shape QTLs were too broad and often overlooked, leading to imprecise mapping that was not useful for identifying candidate genes for marker-assisted breeding. Recent advances in sequencing technology have led to the discovery of new markers and the generation of high-density molecular genetic linkage maps to detect 100-SW QTLs for annotated candidate genes in soybean ( Karikari et al, 2019 ). Thus, a high-density molecular genetic map is a basic requirement for QTL fine mapping and candidate gene discovery ( Zhang et al, 2016a ; Wei et al, 2019 ).…”