William R Rolling, Shelby Ellison, Kevin Coe, Massimo Iorizzo, Julie Dawson, Douglas Senalik, Philipp W Simon
{"title":"结合全基因组关联和基因组预测揭示胡萝卜类胡萝卜素积累的遗传结构。","authors":"William R Rolling, Shelby Ellison, Kevin Coe, Massimo Iorizzo, Julie Dawson, Douglas Senalik, Philipp W Simon","doi":"10.1002/tpg2.20560","DOIUrl":null,"url":null,"abstract":"<p><p>Carrots (Daucus carota L.) are a rich source of provitamin A, namely, α- and β-carotene. Breeding programs prioritize increasing β-carotene content for improved color and nutrition. Understanding the genetic basis of carotenoid accumulation is crucial for implementing genomic-assisted selection to develop high-carotenoid lines. While previous studies identified loci (Y2, Y, Or, and REC) associated with carrot color and carotenoid content, this study employed genome-wide association (GWA) in a diverse panel of 738 carrot accessions. We discovered a novel locus with a candidate gene encoding phytoene synthase, a key enzyme in carotenoid biosynthesis. The Y2, Y, Or, and REC loci are mostly fixed in orange varieties, yet considerable variation in carotenoid concentration persists. This suggests a multigenic trait influenced by the environment. GWA of carotenoid concentration identified a quantitative trait locus for total carotenoids and α-carotene. We explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. We determined the optimal number of plants and plots required for accurate carotenoid phenotyping, finding ≥5 plants per plot and three plots per site as the minimum effective sample per accession. GP models achieved accuracies ranging from 0.06 to 0.40 depending on the carotenoid measured and environment the carrots were assayed. Additional studies in breeding programs will clarify the potential of genomic-assisted selection for high-carotenoid carrots.</p>","PeriodicalId":49002,"journal":{"name":"Plant Genome","volume":"18 1","pages":"e20560"},"PeriodicalIF":3.9000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11782711/pdf/","citationCount":"0","resultStr":"{\"title\":\"Combining genome-wide association and genomic prediction to unravel the genetic architecture of carotenoid accumulation in carrot.\",\"authors\":\"William R Rolling, Shelby Ellison, Kevin Coe, Massimo Iorizzo, Julie Dawson, Douglas Senalik, Philipp W Simon\",\"doi\":\"10.1002/tpg2.20560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Carrots (Daucus carota L.) are a rich source of provitamin A, namely, α- and β-carotene. Breeding programs prioritize increasing β-carotene content for improved color and nutrition. Understanding the genetic basis of carotenoid accumulation is crucial for implementing genomic-assisted selection to develop high-carotenoid lines. While previous studies identified loci (Y2, Y, Or, and REC) associated with carrot color and carotenoid content, this study employed genome-wide association (GWA) in a diverse panel of 738 carrot accessions. We discovered a novel locus with a candidate gene encoding phytoene synthase, a key enzyme in carotenoid biosynthesis. The Y2, Y, Or, and REC loci are mostly fixed in orange varieties, yet considerable variation in carotenoid concentration persists. This suggests a multigenic trait influenced by the environment. GWA of carotenoid concentration identified a quantitative trait locus for total carotenoids and α-carotene. We explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. We determined the optimal number of plants and plots required for accurate carotenoid phenotyping, finding ≥5 plants per plot and three plots per site as the minimum effective sample per accession. GP models achieved accuracies ranging from 0.06 to 0.40 depending on the carotenoid measured and environment the carrots were assayed. Additional studies in breeding programs will clarify the potential of genomic-assisted selection for high-carotenoid carrots.</p>\",\"PeriodicalId\":49002,\"journal\":{\"name\":\"Plant Genome\",\"volume\":\"18 1\",\"pages\":\"e20560\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2025-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11782711/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Plant Genome\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1002/tpg2.20560\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Genome","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/tpg2.20560","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
Combining genome-wide association and genomic prediction to unravel the genetic architecture of carotenoid accumulation in carrot.
Carrots (Daucus carota L.) are a rich source of provitamin A, namely, α- and β-carotene. Breeding programs prioritize increasing β-carotene content for improved color and nutrition. Understanding the genetic basis of carotenoid accumulation is crucial for implementing genomic-assisted selection to develop high-carotenoid lines. While previous studies identified loci (Y2, Y, Or, and REC) associated with carrot color and carotenoid content, this study employed genome-wide association (GWA) in a diverse panel of 738 carrot accessions. We discovered a novel locus with a candidate gene encoding phytoene synthase, a key enzyme in carotenoid biosynthesis. The Y2, Y, Or, and REC loci are mostly fixed in orange varieties, yet considerable variation in carotenoid concentration persists. This suggests a multigenic trait influenced by the environment. GWA of carotenoid concentration identified a quantitative trait locus for total carotenoids and α-carotene. We explored the accuracy of genomic prediction (GP) models to predict carotenoid concentration. We determined the optimal number of plants and plots required for accurate carotenoid phenotyping, finding ≥5 plants per plot and three plots per site as the minimum effective sample per accession. GP models achieved accuracies ranging from 0.06 to 0.40 depending on the carotenoid measured and environment the carrots were assayed. Additional studies in breeding programs will clarify the potential of genomic-assisted selection for high-carotenoid carrots.
期刊介绍:
The Plant Genome publishes original research investigating all aspects of plant genomics. Technical breakthroughs reporting improvements in the efficiency and speed of acquiring and interpreting plant genomics data are welcome. The editorial board gives preference to novel reports that use innovative genomic applications that advance our understanding of plant biology that may have applications to crop improvement. The journal also publishes invited review articles and perspectives that offer insight and commentary on recent advances in genomics and their potential for agronomic improvement.