芒草产量和成分性状的全基因组关联及基因组预测

IF 5.9 3区 工程技术 Q1 AGRONOMY
Joyce N. Njuguna, Lindsay V. Clark, Alexander E. Lipka, Kossonou G. Anzoua, Larisa Bagmet, Pavel Chebukin, Maria S. Dwiyanti, Elena Dzyubenko, Nicolay Dzyubenko, Bimal Kumar Ghimire, Xiaoli Jin, Douglas A. Johnson, Hironori Nagano, Junhua Peng, Karen Koefoed Petersen, Andrey Sabitov, Eun Soo Seong, Toshihiko Yamada, Ji Hye Yoo, Chang Yeon Yu, Hua Zhao, Stephen P. Long, Erik J. Sacks
{"title":"芒草产量和成分性状的全基因组关联及基因组预测","authors":"Joyce N. Njuguna,&nbsp;Lindsay V. Clark,&nbsp;Alexander E. Lipka,&nbsp;Kossonou G. Anzoua,&nbsp;Larisa Bagmet,&nbsp;Pavel Chebukin,&nbsp;Maria S. Dwiyanti,&nbsp;Elena Dzyubenko,&nbsp;Nicolay Dzyubenko,&nbsp;Bimal Kumar Ghimire,&nbsp;Xiaoli Jin,&nbsp;Douglas A. Johnson,&nbsp;Hironori Nagano,&nbsp;Junhua Peng,&nbsp;Karen Koefoed Petersen,&nbsp;Andrey Sabitov,&nbsp;Eun Soo Seong,&nbsp;Toshihiko Yamada,&nbsp;Ji Hye Yoo,&nbsp;Chang Yeon Yu,&nbsp;Hua Zhao,&nbsp;Stephen P. Long,&nbsp;Erik J. Sacks","doi":"10.1111/gcbb.13097","DOIUrl":null,"url":null,"abstract":"<p>Accelerating biomass improvement is a major goal of <i>Miscanthus</i> breeding. The development and implementation of genomic-enabled breeding tools, like marker-assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of <i>Miscanthus</i> breeding. The present study conducted genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in <i>Miscanthus sacchariflorus</i>. We evaluated a diversity panel with 590 accessions of <i>M. sacchariflorus</i> grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single-nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported <i>Miscanthus</i> studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield-component traits in <i>M. sacchariflorus</i> that may facilitate marker-assisted breeding for biomass yield. Genomic prediction accuracy for the yield-related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of <i>M. sacchariflorus</i> were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (<i>N</i> = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of <i>M. sacchariflorus</i>. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population-improvement of <i>M. sacchariflorus</i>.</p>","PeriodicalId":55126,"journal":{"name":"Global Change Biology Bioenergy","volume":"15 11","pages":"1355-1372"},"PeriodicalIF":5.9000,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.13097","citationCount":"0","resultStr":"{\"title\":\"Genome-wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus\",\"authors\":\"Joyce N. Njuguna,&nbsp;Lindsay V. Clark,&nbsp;Alexander E. Lipka,&nbsp;Kossonou G. Anzoua,&nbsp;Larisa Bagmet,&nbsp;Pavel Chebukin,&nbsp;Maria S. Dwiyanti,&nbsp;Elena Dzyubenko,&nbsp;Nicolay Dzyubenko,&nbsp;Bimal Kumar Ghimire,&nbsp;Xiaoli Jin,&nbsp;Douglas A. Johnson,&nbsp;Hironori Nagano,&nbsp;Junhua Peng,&nbsp;Karen Koefoed Petersen,&nbsp;Andrey Sabitov,&nbsp;Eun Soo Seong,&nbsp;Toshihiko Yamada,&nbsp;Ji Hye Yoo,&nbsp;Chang Yeon Yu,&nbsp;Hua Zhao,&nbsp;Stephen P. Long,&nbsp;Erik J. Sacks\",\"doi\":\"10.1111/gcbb.13097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Accelerating biomass improvement is a major goal of <i>Miscanthus</i> breeding. The development and implementation of genomic-enabled breeding tools, like marker-assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of <i>Miscanthus</i> breeding. The present study conducted genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in <i>Miscanthus sacchariflorus</i>. We evaluated a diversity panel with 590 accessions of <i>M. sacchariflorus</i> grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single-nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported <i>Miscanthus</i> studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield-component traits in <i>M. sacchariflorus</i> that may facilitate marker-assisted breeding for biomass yield. Genomic prediction accuracy for the yield-related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of <i>M. sacchariflorus</i> were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (<i>N</i> = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of <i>M. sacchariflorus</i>. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population-improvement of <i>M. sacchariflorus</i>.</p>\",\"PeriodicalId\":55126,\"journal\":{\"name\":\"Global Change Biology Bioenergy\",\"volume\":\"15 11\",\"pages\":\"1355-1372\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2023-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/gcbb.13097\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Change Biology Bioenergy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/gcbb.13097\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRONOMY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Change Biology Bioenergy","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/gcbb.13097","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0

摘要

加快生物量的提高是芒属植物育种的主要目标。基因组育种工具的开发和实施,如标记辅助选择(MAS)和基因组选择,有可能提高芒属植物育种的效率。本研究对芒草的生物量产量和14个产量组成性状进行了全基因组关联(GWA)和基因组预测。我们评估了一个多样性小组,该小组有590份生长在4个地区的糖化分枝杆菌材料 在一个亚热带和三个温带地区,用268109个单核苷酸多态性(SNPs)进行基因分型。GWA研究在所有性状和位置上总共鉴定了835个显著的SNP和674个候选基因。在已鉴定的重要SNPs中,280个定位在已绘制的定量性状基因座区间中,并接近先前报道的芒属植物研究中为类似性状鉴定的SNPs,为这些基因组区域对生物量产量的重要性提供了额外的支持。我们的研究深入了解了糖化分枝杆菌产量组成性状的遗传基础,这可能有助于生物量产量的标记辅助育种。所有地点和遗传群的产量相关性状的基因组预测准确率在0.15至0.52之间。由于样本量低,糖化分枝杆菌六个基因组的预测准确性有限。尽管如此,韩国/中国东北部/俄罗斯(N = 237)遗传组的预测准确率在所有遗传组中最高(范围为0.26–0.71),这表明在足够的样本量下,糖化分枝杆菌的遗传组中有很强的基因组选择潜力。本研究表明,MAS和基因组预测可能有利于糖化分枝杆菌的种群改良。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Genome-wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

Genome-wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic-enabled breeding tools, like marker-assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in Miscanthus sacchariflorus. We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single-nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield-component traits in M. sacchariflorus that may facilitate marker-assisted breeding for biomass yield. Genomic prediction accuracy for the yield-related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus. This study indicated that MAS and genomic prediction will likely be beneficial for conducting population-improvement of M. sacchariflorus.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Global Change Biology Bioenergy
Global Change Biology Bioenergy AGRONOMY-ENERGY & FUELS
CiteScore
10.30
自引率
7.10%
发文量
96
审稿时长
1.5 months
期刊介绍: GCB Bioenergy is an international journal publishing original research papers, review articles and commentaries that promote understanding of the interface between biological and environmental sciences and the production of fuels directly from plants, algae and waste. The scope of the journal extends to areas outside of biology to policy forum, socioeconomic analyses, technoeconomic analyses and systems analysis. Papers do not need a global change component for consideration for publication, it is viewed as implicit that most bioenergy will be beneficial in avoiding at least a part of the fossil fuel energy that would otherwise be used. Key areas covered by the journal: Bioenergy feedstock and bio-oil production: energy crops and algae their management,, genomics, genetic improvements, planting, harvesting, storage, transportation, integrated logistics, production modeling, composition and its modification, pests, diseases and weeds of feedstocks. Manuscripts concerning alternative energy based on biological mimicry are also encouraged (e.g. artificial photosynthesis). Biological Residues/Co-products: from agricultural production, forestry and plantations (stover, sugar, bio-plastics, etc.), algae processing industries, and municipal sources (MSW). Bioenergy and the Environment: ecosystem services, carbon mitigation, land use change, life cycle assessment, energy and greenhouse gas balances, water use, water quality, assessment of sustainability, and biodiversity issues. Bioenergy Socioeconomics: examining the economic viability or social acceptability of crops, crops systems and their processing, including genetically modified organisms [GMOs], health impacts of bioenergy systems. Bioenergy Policy: legislative developments affecting biofuels and bioenergy. Bioenergy Systems Analysis: examining biological developments in a whole systems context.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信