Soybean(Glycine max)is an important and valuable crop,providing oil and proteins for both humans and animals.Seed weight is a key trait that determines soybean yields;however,the genes and mechanisms controlling seed ...Soybean(Glycine max)is an important and valuable crop,providing oil and proteins for both humans and animals.Seed weight is a key trait that determines soybean yields;however,the genes and mechanisms controlling seed weight remain poorly understood.Here,we used genome-wide association study(GWAS)and joint linkage mapping to identify a ubiquitin-specific protease,GmSW17.1,which regulates 100-seed weight in soybean.Two natural allelic variants of GmSW17.1 resulted in significantly different 100-seed weight,with GmSW17.1T conferring heavier seeds.We used CRISPR/Cas9 technology to knock out GmSW17.1,resulting in lighter and smaller seeds;however,these mutants produced more seeds than the wild type,resulting in similar overall yields.Owing to the increased number of seeds,we determined that GmSW17.1 is highly transcribed in developing seeds,and its encoded protein physically interacts in the nucleus with GmSGF11,which plays a crucial role in the deubiquitinating pathway.Analysis of genomic sequences from more than 1714 soybean accessions suggested that the natural allele GmSW17.1T was selected during the domestication and genetic improvement,resulting in its rapid expansion in cultivated soybean.These findings provide important insights into the role of GmSW17.1 in 100-seed weight and offer valuable clues for the molecular breeding of soybean.展开更多
100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, ...100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, the public map should be chosen which was suitable for the published results integrated, and to improve yield. In this research, an integrated map of 100-seed weight QTLs in soybean had been established with soymap2 published in 2004 as a reference map. QTLs of 100-seed weight in soybean were collected in recent 20 yr. With the software BioMercator 2.1, QTLs from their own maps were projected to the reference map. From published papers, 65 QTLs of 100-seed weight were collected and 53 QTLs were integrated, including 17 reductive effect QTLs and 36 additive effect QTLs. 12 clusters of QTLs were found in the integrated map. A method of meta-analysis was used to narrow down the confidence interval, and 6 additive QTLs and 6 reductive QTLs and their corresponding markers were obtained respectively. The minimum confidence interval （C.I.） was shrunk to 1.52 cM. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, as well as QTL gene cloning in soybean.展开更多
基金supported by Research and Application of Technological Innovation in Inner Mongolia Soybean Industry (2023DXZD0002)the National Natural Science Foundation of China (32201756)+4 种基金the National Key Research and Development Program of China (2021YFD1201600)the Agricultural Science and Technology Innovation Program (ASTIP)of Chinese Academy of Agricultural Sciences (CAAS-ZDRW202109,01-ICS-05)the earmarked fund for CARS (CARS-04-PS01)Scientific Innovation 2030 Project (2022ZD0401703)the National Science Foundation for Post-doctoral Scientists of China (2021 M703554).
文摘Soybean(Glycine max)is an important and valuable crop,providing oil and proteins for both humans and animals.Seed weight is a key trait that determines soybean yields;however,the genes and mechanisms controlling seed weight remain poorly understood.Here,we used genome-wide association study(GWAS)and joint linkage mapping to identify a ubiquitin-specific protease,GmSW17.1,which regulates 100-seed weight in soybean.Two natural allelic variants of GmSW17.1 resulted in significantly different 100-seed weight,with GmSW17.1T conferring heavier seeds.We used CRISPR/Cas9 technology to knock out GmSW17.1,resulting in lighter and smaller seeds;however,these mutants produced more seeds than the wild type,resulting in similar overall yields.Owing to the increased number of seeds,we determined that GmSW17.1 is highly transcribed in developing seeds,and its encoded protein physically interacts in the nucleus with GmSGF11,which plays a crucial role in the deubiquitinating pathway.Analysis of genomic sequences from more than 1714 soybean accessions suggested that the natural allele GmSW17.1T was selected during the domestication and genetic improvement,resulting in its rapid expansion in cultivated soybean.These findings provide important insights into the role of GmSW17.1 in 100-seed weight and offer valuable clues for the molecular breeding of soybean.
基金supported by the Chinese Transgenic Specific Technology Programs (2009ZX08009-013B)
文摘100-seed weight is a very complicated quantitative trait of yield. The study of gene mapping for yield trait in soybean is very important for application. However, the mapping result of 100-seed weight was dispersed, the public map should be chosen which was suitable for the published results integrated, and to improve yield. In this research, an integrated map of 100-seed weight QTLs in soybean had been established with soymap2 published in 2004 as a reference map. QTLs of 100-seed weight in soybean were collected in recent 20 yr. With the software BioMercator 2.1, QTLs from their own maps were projected to the reference map. From published papers, 65 QTLs of 100-seed weight were collected and 53 QTLs were integrated, including 17 reductive effect QTLs and 36 additive effect QTLs. 12 clusters of QTLs were found in the integrated map. A method of meta-analysis was used to narrow down the confidence interval, and 6 additive QTLs and 6 reductive QTLs and their corresponding markers were obtained respectively. The minimum confidence interval （C.I.） was shrunk to 1.52 cM. These results would lay the foundation for marker-assisted selection and mapping QTL precisely, as well as QTL gene cloning in soybean.
