Zhixin Zhao

Plant photosynthesis is mainly dependent on leaf color, and this has an impact on yield. Mutants lacking in chlorophyll have been analyzed to gain insight into the genetic processes involved in photosynthesis, chloroplast development, and chlorophyll metabolism. A yellow-to-lethal mutant, ytl, was selected from the M₆ generation of the ⁶⁰Coγ ray irradiation-treated soybean cultivar Nannong 1138-2. The mutant exhibited reduced chlorophyll content, with the thylakoid structure disrupted. Segregation of the cross between Williams 82 (W82) and ytl indicated that a recessive allele controlled yellow-to-lethal traits. The bulked-segregant analysis (BSA)-Seq method performed preliminary mapping, followed by simple sequence repeat (SSR) marker validation and further mapping. The candidate gene was mapped to a 418 Kb region containing 53 genes. High-throughput sequencing and first-generation sequencing results showed a two bp deletion in the second exon of Glyma.08g106500, leading to a frameshift mutation in ytl. As a promising candidate gene, Glyma.08g106500 encoded a chloroplast-localized pentatricopeptide repeat (PPR) domain-containing protein involved in the assembly of chloroplast proteins. These results will contribute to cloning the mutant ytl gene and provide insight into the regulatory processes controlling photosynthesis and chloroplast development and growth in soybean.

Deciphering the genetic basis underlying agronomic traits is of importance for soybean improvement. However, covariation, modulated by genetic correlations between complicated traits via hub QTLs, commonly affects the efficiency and accuracy of soybean improvement. The goals of soybean improvement have nearly all focused on agronomic traits, including yield, plant type traits, and seed-related traits especially. To decipher the hub QTLs of yield, plant type, and seed, nine pertinent traits of an F₂ population (181 plants) derived from a cross between KeXin No.03 and JiDou 17, which were different in multiple traits such as plant height, seed protein, and 100-seed weight, were investigated with a high-density genetic map covering 2708.63 cM. A highly significant negative phenotypic correlation (−0.95) was found between seed protein (Pro) and seed oil (Oil). A total of 35 final QTLs after combining the ones closely linked physically were identified for eight traits explaining from 0.10% to 24.63% of the phenotypic variance explained (PVE) using composite interval mapping (CIM) and inclusive composite interval mapping (ICIM) procedures, and 13 QTLs were novel genes. A genomic region on chromosome 14 (qPro14, qOil14.2, and qSw14) was associated with three seed-related traits based on the relationship within and among the three trait modules. In addition, four genomic regions were detected as hub QTLs which linked to the seed-related module and plant-type model, including the E loci (E1 and E2). From the QTL results, 31 candidate genes were annotated, including the verified genes E1, E2, and QNE1, and they were grouped into three categories of biological processes. These results illustrate the genetic architecture as correlations among various soybean traits, and the hub QTLs should provide insights into the genetic improvement of complex traits in soybean.