Tu Huynh, Kyujung Van, M A Rouf Mian, Leah K McHale
{"title":"具有先进育种品系背景的大豆群体种子油脂和蛋白质含量的单性状和多性状定量性状位点分析。","authors":"Tu Huynh, Kyujung Van, M A Rouf Mian, Leah K McHale","doi":"10.1007/s11032-024-01489-2","DOIUrl":null,"url":null,"abstract":"<p><p>Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H<sup>2</sup> > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPV<sub>NOPA</sub> and EPV<sub>HY+Q</sub> when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPV<sub>NOPA</sub> and decreased EPV<sub>HY+Q</sub>, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11032-024-01489-2.</p>","PeriodicalId":18769,"journal":{"name":"Molecular Breeding","volume":"44 8","pages":"51"},"PeriodicalIF":2.6000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11306453/pdf/","citationCount":"0","resultStr":"{\"title\":\"Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background.\",\"authors\":\"Tu Huynh, Kyujung Van, M A Rouf Mian, Leah K McHale\",\"doi\":\"10.1007/s11032-024-01489-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H<sup>2</sup> > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPV<sub>NOPA</sub> and EPV<sub>HY+Q</sub> when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPV<sub>NOPA</sub> and decreased EPV<sub>HY+Q</sub>, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s11032-024-01489-2.</p>\",\"PeriodicalId\":18769,\"journal\":{\"name\":\"Molecular Breeding\",\"volume\":\"44 8\",\"pages\":\"51\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11306453/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Breeding\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.1007/s11032-024-01489-2\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Breeding","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1007/s11032-024-01489-2","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
Single- and multiple-trait quantitative trait locus analyses for seed oil and protein contents of soybean populations with advanced breeding line background.
Soybean seed oil and protein contents are negatively correlated, posing challenges to enhance both traits simultaneously. Previous studies have identified numerous oil and protein QTLs via single-trait QTL analysis. Multiple-trait QTL methods were shown to be superior but have not been applied to seed oil and protein contents. Our study aimed to evaluate the effectiveness of single- and multiple-trait multiple interval mapping (ST-MIM and MT-MIM, respectively) for these traits using three recombinant inbred line populations from advanced breeding line crosses tested in four environments. Using original and simulated data, we found that MT-MIM did not outperform ST-MIM for our traits with high heritability (H2 > 0.84). Empirically, MT-MIM confirmed only five out of the seven QTLs detected by ST-MIM, indicating single-trait analysis was sufficient for these traits. All QTLs exerted opposite effects on oil and protein contents with varying protein-to-oil additive effect ratios (-0.4 to -4.8). We calculated the economic impact of the allelic variations via estimated processed values (EPV) using the National Oilseed Processors Association (NOPA) and High Yield + Quality (HY + Q) methods. Oil-increasing alleles had positive effects on both EPVNOPA and EPVHY+Q when the protein-to-oil ratio was low (-0.4 to -0.7). However, when the ratio was high (-4.1 to -4.8), oil-increasing alleles increased EPVNOPA and decreased EPVHY+Q, which penalizes low protein meal. In conclusion, single-trait QTL analysis is adequately effective for high heritability traits like seed oil and protein contents. Additionally, the populations' elite pedigrees and varying protein-to-oil ratios provide potential lines for further yield assessment and direct integration into breeding programs.
Supplementary information: The online version contains supplementary material available at 10.1007/s11032-024-01489-2.
期刊介绍：
Molecular Breeding is an international journal publishing papers on applications of plant molecular biology, i.e., research most likely leading to practical applications. The practical applications might relate to the Developing as well as the industrialised World and have demonstrable benefits for the seed industry, farmers, processing industry, the environment and the consumer.
All papers published should contribute to the understanding and progress of modern plant breeding, encompassing the scientific disciplines of molecular biology, biochemistry, genetics, physiology, pathology, plant breeding, and ecology among others.
Molecular Breeding welcomes the following categories of papers: full papers, short communications, papers describing novel methods and review papers. All submission will be subject to peer review ensuring the highest possible scientific quality standards.
Molecular Breeding core areas:
Molecular Breeding will consider manuscripts describing contemporary methods of molecular genetics and genomic analysis, structural and functional genomics in crops, proteomics and metabolic profiling, abiotic stress and field evaluation of transgenic crops containing particular traits. Manuscripts on marker assisted breeding are also of major interest, in particular novel approaches and new results of marker assisted breeding, QTL cloning, integration of conventional and marker assisted breeding, and QTL studies in crop plants.
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