Genetic dissection of ten photosynthesis-related traits based on InDel- and SNP-GWAS in soybean.
Dezhou HuYajun ZhaoLixun ZhuXiao LiJinyu ZhangXuan CuiWenlong LiDerong HaoZhongyi YangFei WuShupeng DongXiaoyue SuFang HuangDe-Yue YuPublished in: TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik (2024)
A total of 416 InDels and 112 SNPs were significantly associated with soybean photosynthesis-related traits. GmIWS1 and GmCDC48 might be related to chlorophyll fluorescence and gas-exchange parameters, respectively. Photosynthesis is one of the main factors determining crop yield. A better understanding of the genetic architecture for photosynthesis is of great significance for soybean yield improvement. Our previous studies identified 5,410,112 single nucleotide polymorphisms (SNPs) from the resequencing data of 219 natural soybean accessions. Here, we identified 634,106 insertions and deletions (InDels) from these 219 accessions and used these InDel variations to perform principal component and linkage disequilibrium analysis of this population. The genome-wide association study (GWAS) were conducted on six chlorophyll fluorescence parameters (chlorophyll content, light energy absorbed per reaction center, quantum yield for electron transport, probability that a trapped exciton moves an electron into the electron transport chain beyond primary quinone acceptor, maximum quantum yield of photosystem II primary photochemistry in the dark-adapted state, performance index on absorption basis) and four gas-exchange parameters (intercellular carbon dioxide concentration, stomatal conductance, net photosynthesis rate, transpiration rate) and revealed 416 significant InDels and 112 significant SNPs. Based on GWAS results, GmIWS1 (encoding a transcription elongation factor) and GmCDC48 (encoding a cell division cycle protein) with the highest expression in the mapping region were determined as the candidate genes responsible for chlorophyll fluorescence and gas-exchange parameters, respectively. Further identification of favorable haplotypes with higher photosynthesis, seed weight and seed yield were carried out for GmIWS1 and GmCDC48. Overall, this study revealed the natural variations and candidate genes underlying the photosynthesis-related traits based on abundant phenotypic and genetic data, providing valuable insights into the genetic mechanisms controlling photosynthesis and yield in soybean.
Keyphrases
- genome wide
- energy transfer
- carbon dioxide
- dna methylation
- genome wide association study
- copy number
- quantum dots
- molecular dynamics
- solar cells
- poor prognosis
- room temperature
- water soluble
- body mass index
- small molecule
- transcription factor
- deep learning
- mesenchymal stem cells
- artificial intelligence
- high density
- hiv testing