Article(id=1308459086278841078, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1308459084781482033, articleNumber=null, orderNo=null, doi=10.7606/j.issn.1009-1041.2025.05.02, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1716825600000, receivedDateStr=2024-05-28, revisedDate=1732032000000, revisedDateStr=2024-11-20, acceptedDate=null, acceptedDateStr=null, onlineDate=1789890556162, onlineDateStr=2026-09-20, pubDate=1747238400000, pubDateStr=2025-05-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789890556162, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789890556162, creator=13701087609, updateTime=1789890556162, updator=13701087609, issue=Issue{id=1308459084781482033, tenantId=1146029695717560320, journalId=1303687221787852879, year='2025', volume='45', issue='5', pageStart='F2', pageEnd='710', issueExtLink='null', onlineDate='null', pubDate='1747238400000', pubDateStr='2025-05-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789890555806, creator='13701087609', updateTime=1789890630422, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308459397810778987, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1308459084781482033, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308459397810778988, tenantId=1146029695717560320, journalId=1303687221787852879, issueId=1308459084781482033, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=576, endPage=586, ext={EN=ArticleExt(id=1308459087092536055, articleId=1308459086278841078, tenantId=1146029695717560320, journalId=1303687221787852879, language=EN, title=QTL Meta-Analysis and Candidate Gene Prediction for Leaf Morphological and Physiological Traits in Barley, columnId=1305133119129023428, journalTitle=Journal of Triticeae Crops, columnName=Genetics & Breeding, runingTitle=null, highlight=null, articleAbstract=

Leaf is an important organ for photosynthesis and a key factor affecting yield in barley. In this study, a total of 23 papers on quantitative trait loci (QTL) mapping for leaf morphological and physiological traits in barley, published from 1999 to 2023, were collected to explore the genetic mechanisms of leaf-related traits in barley. The 356 initial QTLs from different genetic populations were integrated into a high-density consensus map of barley and subjected to QTL meta-analysis. A total of 31 meta-QTLs (MQTLs) were identified. These MQTLs were unevenly distributed across the seven chromosomes, with the majority (54.8%) consisting of 3-5 initial QTLs and three MQTLs containing at least 13 initial QTLs. The average confidence interval (CI) width of these MQTLs was 1.54 cM, which is 6.73 times narrower than the average CI width of the initial QTLs. Among these 31 MQTLs, 10 breeder's MQTLs were selected for further candidate gene mining. Using the barley-rice homology comparative strategy, a total of 12 barley orthologs associated with rice leaf morphology or physiological traits were identified within the breeder's MQTL regions, which may be candidate genes for regulating leaf morphology and physiological traits in barley.

, authors=Binbin DU1, Jie ZHOU2, Huaping HU2, Qifei WANG3, Xuejun CUI2, authorsList=Binbin DU, Jie ZHOU, Huaping HU, Qifei WANG, Xuejun CUI, authorCompany=null, correspAuthors=Xuejun CUI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1308459089315517176, articleId=1308459086278841078, tenantId=1146029695717560320, journalId=1303687221787852879, language=CN, title=大麦叶片形态和生理性状QTL元分析及候选基因预测, columnId=1305133119284212678, journalTitle=麦类作物学报, columnName=遗传育种, runingTitle=null, highlight=null, articleAbstract=

叶片是大麦植株进行光合作用的重要器官,也是影响大麦产量的关键因素。本研究收集了1999至2023年发表的23篇大麦叶片形态和生理性状的数量性状基因座(quantitative trait loci, QTL)定位的文献,以研究大麦叶片相关性状的遗传机制。将来自不同遗传群体的356个初始QTL整合到大麦高密度一致性图谱中,并进行QTL元分析,鉴定到31个元QTL(meta-QTL, MQTL)。这些MQTL不均匀地分布在7条染色体上,多数MQTL(54.8%)由3~5个初始QTL组成,其中3个MQTL包含至少13个初始QTL。这些MQTL的平均置信区间(confidence interval, CI)宽度为1.54 cM,比初始QTL的平均CI宽度缩减了6.73倍。在31个MQTL中,筛选出了10个育种者MQTL,进一步进行候选基因的挖掘。基于大麦-水稻同源比较策略,在育种者MQTL区域内共鉴定到12个与水稻叶片形态或生理性状相关的大麦直系同源基因,这些可能是调控大麦叶片形态和生理性状的候选基因。

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E-mail: (都斌斌)

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大麦叶片形态和生理性状QTL元分析及候选基因预测
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都斌斌 1 , 周洁 2 , 胡华萍 2 , 王其飞 3 , 崔学军 2
麦类作物学报 | 遗传育种 2025,45(5): 576-586
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麦类作物学报 |遗传育种 2025 , 45 (5) : 576 -586
大麦叶片形态和生理性状QTL元分析及候选基因预测
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都斌斌1 , 周洁2 , 胡华萍2, 王其飞3, 崔学军2
作者信息
  • 1.皖西学院 生物与制药工程学院,安徽 六安 237012
  • 2.六安市农业科学研究院,安徽 六安 237000
  • 3.浙江省农业科学院 作物与核技术利用研究所,浙江 杭州 310021
通讯作者:
E-mail: (崔学军)
作者简介:

E-mail: (都斌斌)

(周洁)

QTL Meta-Analysis and Candidate Gene Prediction for Leaf Morphological and Physiological Traits in Barley
Binbin DU1 , Jie ZHOU2 , Huaping HU2, Qifei WANG3, Xuejun CUI2
Affiliations
  • 1.College of Biotechnology and Pharmaceutical Engineering, West Anhui University, Lu’an, Anhui 237012, China
  • 2.Lu’an Academy of Agricultural Science, Lu’an, Anhui 237000, China
  • 3. Institute of Crop and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang 310021, China
出版时间: 2025-05-15 doi: 10.7606/j.issn.1009-1041.2025.05.02
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叶片是大麦植株进行光合作用的重要器官,也是影响大麦产量的关键因素。本研究收集了1999至2023年发表的23篇大麦叶片形态和生理性状的数量性状基因座(quantitative trait loci, QTL)定位的文献,以研究大麦叶片相关性状的遗传机制。将来自不同遗传群体的356个初始QTL整合到大麦高密度一致性图谱中,并进行QTL元分析,鉴定到31个元QTL(meta-QTL, MQTL)。这些MQTL不均匀地分布在7条染色体上,多数MQTL(54.8%)由3~5个初始QTL组成,其中3个MQTL包含至少13个初始QTL。这些MQTL的平均置信区间(confidence interval, CI)宽度为1.54 cM,比初始QTL的平均CI宽度缩减了6.73倍。在31个MQTL中,筛选出了10个育种者MQTL,进一步进行候选基因的挖掘。基于大麦-水稻同源比较策略,在育种者MQTL区域内共鉴定到12个与水稻叶片形态或生理性状相关的大麦直系同源基因,这些可能是调控大麦叶片形态和生理性状的候选基因。

大麦  /  叶片形态性状和生理性状  /  MQTL  /  候选基因

Leaf is an important organ for photosynthesis and a key factor affecting yield in barley. In this study, a total of 23 papers on quantitative trait loci (QTL) mapping for leaf morphological and physiological traits in barley, published from 1999 to 2023, were collected to explore the genetic mechanisms of leaf-related traits in barley. The 356 initial QTLs from different genetic populations were integrated into a high-density consensus map of barley and subjected to QTL meta-analysis. A total of 31 meta-QTLs (MQTLs) were identified. These MQTLs were unevenly distributed across the seven chromosomes, with the majority (54.8%) consisting of 3-5 initial QTLs and three MQTLs containing at least 13 initial QTLs. The average confidence interval (CI) width of these MQTLs was 1.54 cM, which is 6.73 times narrower than the average CI width of the initial QTLs. Among these 31 MQTLs, 10 breeder's MQTLs were selected for further candidate gene mining. Using the barley-rice homology comparative strategy, a total of 12 barley orthologs associated with rice leaf morphology or physiological traits were identified within the breeder's MQTL regions, which may be candidate genes for regulating leaf morphology and physiological traits in barley.

Barley  /  Leaf morphological and physiological traits  /  MQTL  /  Candidate gene
都斌斌, 周洁, 胡华萍, 王其飞, 崔学军. 大麦叶片形态和生理性状QTL元分析及候选基因预测. 麦类作物学报, 2025 , 45 (5) : 576 -586 . DOI: 10.7606/j.issn.1009-1041.2025.05.02
Binbin DU, Jie ZHOU, Huaping HU, Qifei WANG, Xuejun CUI. QTL Meta-Analysis and Candidate Gene Prediction for Leaf Morphological and Physiological Traits in Barley[J]. Journal of Triticeae Crops, 2025 , 45 (5) : 576 -586 . DOI: 10.7606/j.issn.1009-1041.2025.05.02
  • 国家自然科学基金项目(32001493)
  • 皖西学院高层次人才科研启动项目(WGKQ2022029)
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doi: 10.7606/j.issn.1009-1041.2025.05.02
  • 接收时间:2024-05-28
  • 首发时间:2026-09-20
  • 出版时间:2025-05-15
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  • 收稿日期:2024-05-28
  • 修回日期:2024-11-20
基金
国家自然科学基金项目(32001493)
皖西学院高层次人才科研启动项目(WGKQ2022029)
作者信息
    1.皖西学院 生物与制药工程学院,安徽 六安 237012
    2.六安市农业科学研究院,安徽 六安 237000
    3.浙江省农业科学院 作物与核技术利用研究所,浙江 杭州 310021

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E-mail: (崔学军)
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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