Location: Plant Genetics Research
Title: Association mapping for water use efficiency in soybean identifies previously reported and novel loci and permits genomic predictionAuthor
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CHAMARTHI, SIVAKUMAR - University Of Missouri |
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PURCELL, LARRY - University Of Arkansas |
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FRITSCHI, FELIX - University Of Missouri |
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Ray, Jeffery - Jeff |
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Smith, James - Rusty |
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KALER, AVJINDER - University Of Arkansas |
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KING, ANDY - University Of Arkansas |
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Gillman, Jason |
Submitted to: Frontiers in Plant Science
Publication Type: Peer Reviewed Journal Publication Acceptance Date: 11/4/2024 Publication Date: 11/28/2024 Citation: Chamarthi, S., Purcell, L.C., Fritschi, F.B., Ray, J.D., Smith, J.R., Kaler, A.S., King, A.C., Gillman, J.D. 2024. Association mapping for water use efficiency in soybean identifies previously reported and novel loci and permits genomic prediction. Frontiers in Plant Science. 15. https://doi.org/10.3389/fpls.2024.1486736. DOI: https://doi.org/10.3389/fpls.2024.1486736 Interpretive Summary: Soybean is the major legume crop cultivated globally due to the high productivity and quality of its seed protein and oil. However, drought stress is the most significant factor that decreases soybean yield, and more than 90% of US soybean acreage is completely dependent on rainfall. Water use efficiency (WUE) expresses how efficiently water is converted into plant material and is positively correlated with the C13 ratio of carbon isotopes (C13 ratio). The development of soybean varieties with a high C13 ratio could potentially enhance WUE and improve the crop’s tolerance to drought. In this study, we examined a diverse set of 205 soybean accessions across seven distinct environments: five irrigated and two were drought-stressed. Genetic analysis identified 167 significant single nucleotide polymorphisms (SNPs) representing 136 genetic loci which affected the C13 ratio. Genomic regions tagged by 156 significant SNPs contained 873 candidate genes annotated for plant stress responses. We also confirmed that a subset of genomic loci were consistent across multiple studies and could be used to select for higher WUE and drought tolerance in soybean, validated genomic prediction is able to accurately predict C13 ratio, and identified extreme genotypes from the USDA-GRIN germplasm collection to inform drought tolerance physiological studies. Collectively, our results will accelerate efforts to develop more drought tolerant soybean germplasm and cultivars. Technical Abstract: Soybean is a major legume crop cultivated globally due to the high quality and quantity of its seed protein and oil. However, drought stress is the most significant factor that decreases soybean yield, and more than 90% of US soybean acreage is dependent on rainfall. Water use efficiency (WUE) is positively correlated with the carbon isotopic ratio 13C/12C (C13 ratio) and selecting soybean varieties for high C13 ratio may enhance WUE and help improve tolerance to drought. Our study objective was to identify genetic loci associated with C13 ratio using a diverse set of 205 soybean maturity group IV accessions, and to examine the genomic prediction accuracy of C13 ratio across a range of environments. An accession panel was grown and assessed across seven distinct combinations of site, year and treatment, with five site-years under irrigation and two site-years under drought stress. Genome-wide association mapping (GWAM) analysis identified 103 significant single nucleotide polymorphisms (SNPs) representing 93 loci associated with alterations to C13 ratio. Out of these 93 loci, 62 loci coincided with previous studies, and 31 were novel. Regions tagged by 96 significant SNPs overlapped with 550 candidate genes involved in plant stress responses. These confirmed genomic loci could serve as a valuable resource for marker-assisted selection to enhance WUE and drought tolerance in soybean. This study also demonstrated that genomic prediction can accurately predict C13 ratio across different genotypes and environments and by examining only significant SNPs identified by GWAM analysis, higher prediction accuracies (P = 0.05; 0.51 = r = 0.65) were observed. We generated genomic estimated breeding values for each genotype in the entire USDA-GRIN germplasm collection for which there was marker data. This information was used to identify the top ten extreme genotypes for each soybean maturity group, which could serve as valuable genetic and physiological resources for future breeding and physiological studies. |