Theresa Makawa Phiri, Haizheng Xiong, Yong‐Bao Pan, Ryan William Dickson, Neelendra Joshi, Alejandro Rojas, Ainong Shi
{"title":"Genomic Association and Prediction Study for Yield Traits in a Sugarcane (Saccharum spp. Hybrids) Mapping Population ‘LCP 85‐384’","authors":"Theresa Makawa Phiri, Haizheng Xiong, Yong‐Bao Pan, Ryan William Dickson, Neelendra Joshi, Alejandro Rojas, Ainong Shi","doi":"10.1111/pbr.13221","DOIUrl":null,"url":null,"abstract":"Sugarcane (<jats:italic>Saccharum</jats:italic> spp. hybrids) are complex polyploid and aneuploid interspecific hybrids with 110–130 chromosomes. A traditional sugarcane breeding cycle takes 13–15 years and involves multiple years and locations testing of yield. To identify molecular markers associated with yield‐related traits, the LCP 85‐384 cultivar and its mapping population of 263 self‐progenies were planted in two randomly replicated field plots. The mapping population was genotyped with amplified fragment length polymorphism (AFLP), simple sequence repeats (SSR) and target region amplification polymorphism (TRAP) markers. Data on plant height, stalk number, stalk diameter and stalk weight were collected. A large variation was observed for each trait. A genome‐wide association study (GWAS) was conducted using mixed linear model (MLM), generalized linear model (GLM) and single marker regression (SMR) programmes of TASSEL 5 and FarmCPU of GAPIT 3. A total of 64 yield trait‐associated alleles were identified, including 11 for stalk number, 36 for stalk weight, 21 for stalk diameter and 5 for plant height. Of the 64 alleles, seven were linked to two traits and one to three traits. Genomic prediction (GP) was also performed by cross‐prediction with five models, namely, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL). Prediction accuracy (<jats:italic>r</jats:italic> value) reached 0.40 for plant height, 0.36 for stalk number, 0.44 for stalk diameter and 0.54 for stalk weight with the standard errors from 0.009 to 0.012. Once verified, these markers will be a valuable tool to aid in the selection of yield‐related traits in sugarcane improvement programmes.","PeriodicalId":20228,"journal":{"name":"Plant Breeding","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Breeding","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1111/pbr.13221","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
Sugarcane (Saccharum spp. hybrids) are complex polyploid and aneuploid interspecific hybrids with 110–130 chromosomes. A traditional sugarcane breeding cycle takes 13–15 years and involves multiple years and locations testing of yield. To identify molecular markers associated with yield‐related traits, the LCP 85‐384 cultivar and its mapping population of 263 self‐progenies were planted in two randomly replicated field plots. The mapping population was genotyped with amplified fragment length polymorphism (AFLP), simple sequence repeats (SSR) and target region amplification polymorphism (TRAP) markers. Data on plant height, stalk number, stalk diameter and stalk weight were collected. A large variation was observed for each trait. A genome‐wide association study (GWAS) was conducted using mixed linear model (MLM), generalized linear model (GLM) and single marker regression (SMR) programmes of TASSEL 5 and FarmCPU of GAPIT 3. A total of 64 yield trait‐associated alleles were identified, including 11 for stalk number, 36 for stalk weight, 21 for stalk diameter and 5 for plant height. Of the 64 alleles, seven were linked to two traits and one to three traits. Genomic prediction (GP) was also performed by cross‐prediction with five models, namely, ridge regression best linear unbiased prediction (rrBLUP), Bayesian ridge regression (BRR), Bayesian A (BA), Bayesian B (BB), and Bayesian least absolute shrinkage and selection operator (BL). Prediction accuracy (r value) reached 0.40 for plant height, 0.36 for stalk number, 0.44 for stalk diameter and 0.54 for stalk weight with the standard errors from 0.009 to 0.012. Once verified, these markers will be a valuable tool to aid in the selection of yield‐related traits in sugarcane improvement programmes.
期刊介绍:
PLANT BREEDING publishes full-length original manuscripts and review articles on all aspects of plant improvement, breeding methodologies, and genetics to include qualitative and quantitative inheritance and genomics of major crop species. PLANT BREEDING provides readers with cutting-edge information on use of molecular techniques and genomics as they relate to improving gain from selection. Since its subject matter embraces all aspects of crop improvement, its content is sought after by both industry and academia. Fields of interest: Genetics of cultivated plants as well as research in practical plant breeding.