Construction of a genetic map and QTL mapping of seed size traits in soybean

Jiang, Aohua; Liu, Jiaqi; Gao, Weiran; Ma, Ronghan; Tan, Pingting; Liu, Fang; Zhang, Jian

doi:10.3389/fgene.2023.1248315

Cited by 4 publications

(2 citation statements)

References 45 publications

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“…The genetic map used in this study was constructed by our laboratory in the early stage. The total length of the soybean genetic map was 2799.2 cm, including 455 markers, and the average map distance was 6.15 cm [21]. QTL localization for quality-related traits was analyzed by means of MQM using MapQTL 6.0 software, and phenotypic data were analyzed using 1000 permutation tests with significance p = 0.05 and LOD = 4.0 as the threshold to determine the presence of QTL [22,23].…”

Section: Qtl Mappingmentioning

confidence: 99%

QTL Mapping for Seed Quality Traits under Multiple Environments in Soybean (Glycine max L.)

Liu,

Jiang,

et al. 2023

Agronomy

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Soybeans are the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) for soybean quality traits and mining related candidate genes are of great significance for the molecular breeding of soybean quality traits and understanding the genetic mechanism of protein/fat metabolism. In this study, the F2 population was derived from the high-protein material Changjiang Chun 2 and Jiyu 166. On the basis of a genetic linkage map constructed in our previous study, the QTL of crude protein content, crude oil content and fatty acid fractions were detected using the multiple-QTL model (MQM) mapping method. The results show that a total of 92 QTL were obtained affecting quality traits under three environments, including 14 QTL of crude oil content, 9 QTL of crude protein content, and 20, 20, 11, 10 and 8 QTL for the content of palmitic, stearic, oleic, linoleic and linolenic acids, respectively. Sixteen QTL clusters were identified, among which Loci01.1, Loci06.1 and Loci11.1 were identified as stable QTL clusters with phenotypic contribution rates of 16.5%, 16.4% and 12.1%, respectively, and candidate genes were mined in their regions. A total of 32 candidate genes related to soybean quality were finally screened via GO enrichment and gene annotation. The present study lies the foundations for understanding the genetic mechanism and elite germplasm innovation of seed quality in soybean.

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Section: Qtl Mappingmentioning

confidence: 99%

QTL Mapping for Seed Quality Traits under Multiple Environments in Soybean (Glycine max L.)

Liu,

Jiang,

et al. 2023

Agronomy

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“…In crop breeding, seed size is one of the most important agronomic traits that needs to be considered first. It is an important factor in determining soybean production, seed consumption, and evolutionary fitness [ 8 , 9 , 10 ]. Seed size is a quantitative trait controlled by multiple genes and is constrained by environmental factors [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.)

Gao,

Ma,

et al. 2024

IJMS

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Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

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Genome-Wide Association Study and Candidate Gene Mining of Seed Size Traits in Soybean

Zhang,

Yang,

Jia

et al. 2024

Agronomy

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Seed size traits, including seed length (SL), seed width (SW), and seed thickness (ST), are crucial appearance parameters that determine soybean seed weight, yield, and ultimate utilization. However, there is still a large gap in the understanding of the genetic mechanism of these traits. Here, 281 soybeans were utilized to analyze the genetic architecture of seed size traits in different years through multiple (single-locus and multi-locus) genome-wide association study (GWAS) models, and candidate genes were predicted by integrating information on gene function and transcriptome sequencing data. As a result, two, seven, and three stable quantitative trait nucleotides (QTNs) controlling SL, SW, and ST were detected in multiple environments using the single-locus GWAS model, and concurrently detected by the results of the multi-locus GWAS models. These stable QTNs are located on 10 linkage disequilibrium blocks, with single genome regions ranging in size from 20 to 440 kb, and can serve as the major loci controlling soybean seed size. Furthermore, by combining gene functional annotation and transcriptome sequencing data of seeds at different developmental stages from two extreme soybean accessions, nine candidate genes, including Glyma.05G038000, Glyma.05G244100, Glyma.05G246900, Glyma.07G070200, Glyma.11G010000, Glyma.11G012400, Glyma.17G165500, Glyma.17G166500, and Glyma.20G012600 within the major loci that may regulate soybean seed size, were mined. Overall, these findings offer valuable insights for molecular improvement breeding as well as gene functional studies to unravel the mechanism of soybean seed size.

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Construction of a genetic map and QTL mapping of seed size traits in soybean

Cited by 4 publications

References 45 publications

QTL Mapping for Seed Quality Traits under Multiple Environments in Soybean (Glycine max L.)

QTL Mapping for Seed Quality Traits under Multiple Environments in Soybean (Glycine max L.)

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.)

Genome-Wide Association Study and Candidate Gene Mining of Seed Size Traits in Soybean

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