Dataset Information

High-Density Genetic Mapping Identifies New Major Loci for Tolerance to Low-Phosphorus Stress in Soybean.

ABSTRACT: Phosphorus (P) is essential for all living cells and organisms, and low-P stress represents a major constraint on plant growth and yield worldwide. Soybean is an important economical resource of protein and oil for human and animals, and soybean is also a high-P demand species that is sensitive to low-P stress, which is considered a major constraint on soybean production. However, P efficiency is an important complex quantitative trait involving multiple genes, and the mechanisms underlying soybean P efficiency are largely unknown. Here, we reported the construction of a high-density genetic map using a specific-locus amplified fragment sequencing (SLAF-seq) strategy in soybean. This map, spanning 3020.59 cM in length, contained 6159 markers on 20 chromosomes, with an average distance of 0.49 cM between adjacent markers. Based on this map, 20 loci, including eight novel loci, associated with P efficiency-related traits were identified across multiple years and treatments. The confidence intervals of almost all QTLs were refined significantly, and the accuracy of this map was evidenced by coincident detections of the previously identified P efficiency-related genes GmACP1 and GmPT1. Notably, a highly significant novel QTL located on chromosome 4, q4-2, was identified across traits, years and treatments. Several candidate genes, such as a pectin methylesterase-encoding gene (Glyma.04G214000) and a protein kinase gene (Glyma.13G161900), with significantly differential expression upon low-P stress were considered as promising candidates involved in regulating soybean P efficiency. Markers that tightly associated with P efficiency could be used for marker-assisted selection in a soybean P efficient breeding program. Further, dissection of these QTLs will facilitate gene cloning underlying P efficiency in soybean, and increase our understanding of efficient use of P in enhancing crop yield.

SUBMITTER: Zhang D

PROVIDER: S-EPMC4811872 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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High-Density Genetic Mapping Identifies New Major Loci for Tolerance to Low-Phosphorus Stress in Soybean.

Zhang Dan D Li Hongyan H Wang Jinshe J Zhang Hengyou H Hu Zhenbin Z Chu Shanshan S Lv Haiyan H Yu Deyue D

Frontiers in plant science 20160330

Phosphorus (P) is essential for all living cells and organisms, and low-P stress represents a major constraint on plant growth and yield worldwide. Soybean is an important economical resource of protein and oil for human and animals, and soybean is also a high-P demand species that is sensitive to low-P stress, which is considered a major constraint on soybean production. However, P efficiency is an important complex quantitative trait involving multiple genes, and the mechanisms underlying soyb ...[more]

PMID: 27065041

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Project description:Pythium root rot is one of the significant diseases of soybean (Glycine max (L.) Merr.) in the United States. The causal agent of the disease is a soil-borne oomycete pathogen Pythium irregulare, the most prevalent and aggressive species of Pythium in North Central United States. However, few studies have been conducted in soybean for the identification of quantitative trait loci (QTL) for tolerance to P. irregulare In this study, two recombinant inbred line (RIL) populations (designated as POP1 and POP2) were challenged with P. irregulare (isolate CMISO2-5-14) in a greenhouse assay. POP1 and POP2 were derived from 'E09014' × 'E05226-T' and 'E05226-T' × 'E09088', and contained 113 and 79 lines, respectively. Parental tests indicated that 'E05226-T' and 'E09014' were more tolerant than 'E09088', while 'E09088' was highly susceptible to the pathogen. The disease indices, root weight of inoculation (RWI) and ratio of root weight (RRW) of both populations showed near normal distributions, with transgressive segregation, suggesting the involvement of multiple QTL from both parents contributed to the tolerance. All the lines were genotyped using Illumina Infinium BARCSoySNP6K iSelect BeadChip and yielded 1373 and 1384 polymorphic markers for POP1 and POP2, respectively. Notably, despite high density, polymorphic markers coverage was incomplete in some genomic regions. As such, 28 and 37 linkage groups were obtained in POP1 and POP2, respectively corresponding to the 20 soybean chromosomes. Using RRW, one QTL was identified in POP1 on Chromosome 20 that explained 12.7-13.3% of phenotypic variation. The desirable allele of this QTL was from 'E05226-T'. Another QTL was found in POP2 on Chromosome 11. It explained 15.4% of the phenotypic variation and the desirable allele was from 'E09088'. However, no QTL were identified using RWI in either population. These results supported that RRW was more suitable to be used to evaluate P. irregulare tolerance in soybean.

Project description:BackgroundSeed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage.ResultsIn the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation.ConclusionsOur findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

Dataset Information

High-Density Genetic Mapping Identifies New Major Loci for Tolerance to Low-Phosphorus Stress in Soybean.

Publications

High-Density Genetic Mapping Identifies New Major Loci for Tolerance to Low-Phosphorus Stress in Soybean.

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