Abstract
Seed weight and shape are important agronomic traits that affect soybean quality and yield. In the present study, we used image analysis software to evaluate 100-seed weight and seed shape traits (length, width, perimeter, projection area, length/width, and weight/projection area) of 155 novel recombinant inbred soybean lines (NJRISX) generated by crossing “Su88-M21” and “XYXHD”. We examined quantitative trait loci (QTLs) associated with the six traits (except seed weight per projection area), and identified 42 additive QTLs (5–8 QTLs per trait) accounting for 24.9–37.5% of the phenotypic variation (PV). Meanwhile, 2–4 epistatic QTL pairs per trait out of a total of 18 accounted for 2.5–7.2% of the PV; and unmapped minor QTLs accounted for the remaining 35.0–56.7% of the PV. A total of 28 additive and 11 epistatic QTL pairs were concentrated in nine joint QTL segments (JQSs), indicating that QTLs associated with seed weight and shape are closely related and interacted. An interaction was also detected between additive and epistatic QTL pairs and environment, which made significant contributions of 1.4–9.5% and 0.4–0.8% to the PV, respectively. We annotated 18 candidate genes in the nine JQSs, which were important for interpreting the close relationships among the six traits. These findings indicate that examining the interactions between closely related traits rather than only analyzing individual trait provides more useful insight into the genetic system of the interrelated traits for which there has been limited QTL information.
Highlights
Soybean (Glycine max [L.] Merr.) is widely cultivated and consumed, accounting for 70% of protein meal and 28% of vegetable oil sources globally in 2018 (SoyStat, 2019)
The heritability of the seven traits ranged from 60.3 to 88.2% (Table 1). These results showed that further quantitative trait loci (QTL) constitution analysis for the traits except seed weight per projection area (SWA) would be meaningful
We examined the QTL system of six seed weight and shape traits (100-seed width (SW), seed length (SL), SW, seed perimeter (SP), seed projection area (SA), and seed length-towidth ratio (SLW)) in the soybean recombinant inbred line (RIL) population NJRISX, and identified 42 additive
Summary
Soybean (Glycine max [L.] Merr.) is widely cultivated and consumed, accounting for 70% of protein meal and 28% of vegetable oil sources globally in 2018 (SoyStat, 2019). A computer imagebased software has been developed that can accurately measure soybean seed morphology traits including seed length (SL), seed width (SW), seed perimeter (SP), and seed projection area (SA) (Ding et al, 2019), which can be used to calculate seed length-towidth ratio (SLW) and seed weight per projection area (SWA). This procedure is simple, accurate, and has high throughput compared to manual measurements using Vernier calipers
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