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Meta-analysis of QTL associated with tolerance to abiotic stresses in barley
A meta-analysis of quantitative trait loci (QTL) associated with tolerance to abiotic stresses in barley was carried out using results from 35 different experiments. “MetaQTL” software was used to project QTL positions on a reference map. Three hundred and thirty-seven QTL for traits associated with...
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Published in: | Euphytica 2013, Vol.189 (1), p.31-49 |
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description | A meta-analysis of quantitative trait loci (QTL) associated with tolerance to abiotic stresses in barley was carried out using results from 35 different experiments. “MetaQTL” software was used to project QTL positions on a reference map. Three hundred and thirty-seven QTL for traits associated with tolerance to abiotic stresses were included in this analysis which identified 79 metaQTL (MQTL) including 26 for drought, 11 for low temperature, 22 for salinity, 17 for water-logging, and 3 for mineral toxicity and deficiency. The distribution of MQTL was similar to that of the initial QTL. Many of these MQTL were located on chromosomes 2H (mainly for water-logging and drought) and 5H (mainly for salinity and low temperature). It inferred that chromosomes 2H and 5H were important for researches on barley abiotic tolerance, and the genes associated with abiotic stresses were concentrated relatively. As expected from trait correlations, 22.8 % of these MQTL displayed overlapping CIs. These overlapping regions were mainly on chromosomes 1H, 2H and 4H. The results indicated that the tolerance to diverse abiotic stresses were associated with each other in barley. Additionally, 67 candidate genes responsive to abiotic stresses were co-located with the abiotic-stress MQTL. Of them, a total of 55 had different conserved motifs. It inferred that the tolerance to abiotic stresses was contributed by multi-genes with diverse functions, though there might be some important genes associated with the tolerance to abiotic stresses in barley. Additionally, of these candidate genes, scsnp02622, scsnp01644 and scsnp19641 could be better for further studies of abiotic stresses tolerance. |
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Three hundred and thirty-seven QTL for traits associated with tolerance to abiotic stresses were included in this analysis which identified 79 metaQTL (MQTL) including 26 for drought, 11 for low temperature, 22 for salinity, 17 for water-logging, and 3 for mineral toxicity and deficiency. The distribution of MQTL was similar to that of the initial QTL. Many of these MQTL were located on chromosomes 2H (mainly for water-logging and drought) and 5H (mainly for salinity and low temperature). It inferred that chromosomes 2H and 5H were important for researches on barley abiotic tolerance, and the genes associated with abiotic stresses were concentrated relatively. As expected from trait correlations, 22.8 % of these MQTL displayed overlapping CIs. These overlapping regions were mainly on chromosomes 1H, 2H and 4H. The results indicated that the tolerance to diverse abiotic stresses were associated with each other in barley. Additionally, 67 candidate genes responsive to abiotic stresses were co-located with the abiotic-stress MQTL. Of them, a total of 55 had different conserved motifs. It inferred that the tolerance to abiotic stresses was contributed by multi-genes with diverse functions, though there might be some important genes associated with the tolerance to abiotic stresses in barley. Additionally, of these candidate genes, scsnp02622, scsnp01644 and scsnp19641 could be better for further studies of abiotic stresses tolerance.</description><identifier>ISSN: 0014-2336</identifier><identifier>EISSN: 1573-5060</identifier><identifier>DOI: 10.1007/s10681-012-0683-3</identifier><identifier>CODEN: EUPHAA</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Abiotic stress ; Agronomy. Soil science and plant productions ; Analysis ; Barley ; Biological and medical sciences ; Biomedical and Life Sciences ; Biotechnology ; Chromosomes ; Drought ; Droughts ; Fundamental and applied biological sciences. Psychology ; Gene loci ; Gene mapping ; Genes ; Genetics and breeding of economic plants ; Life Sciences ; Low temperature ; Meta-analysis ; Plant Genetics and Genomics ; Plant Pathology ; Plant Physiology ; Plant Sciences ; Quantitative genetics ; Salinity ; Waterlogging</subject><ispartof>Euphytica, 2013, Vol.189 (1), p.31-49</ispartof><rights>Springer Science+Business Media B.V. 2012</rights><rights>2014 INIST-CNRS</rights><rights>COPYRIGHT 2013 Springer</rights><rights>Springer Science+Business Media Dordrecht 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c385t-97dfe5aa41e36efd3d921d4535ffcd2b460ac65d374e88ad43475f5e797fa2c83</citedby><cites>FETCH-LOGICAL-c385t-97dfe5aa41e36efd3d921d4535ffcd2b460ac65d374e88ad43475f5e797fa2c83</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,4010,27904,27905,27906</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=27610243$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Wei-Tao</creatorcontrib><creatorcontrib>Liu, Chunji</creatorcontrib><creatorcontrib>Liu, Ya-Xi</creatorcontrib><creatorcontrib>Pu, Zhi-En</creatorcontrib><creatorcontrib>Dai, Shou-Fen</creatorcontrib><creatorcontrib>Wang, Ji-Rui</creatorcontrib><creatorcontrib>Lan, Xiu-Jin</creatorcontrib><creatorcontrib>Zheng, You-Liang</creatorcontrib><creatorcontrib>Wei, Yu-Ming</creatorcontrib><title>Meta-analysis of QTL associated with tolerance to abiotic stresses in barley</title><title>Euphytica</title><addtitle>Euphytica</addtitle><description>A meta-analysis of quantitative trait loci (QTL) associated with tolerance to abiotic stresses in barley was carried out using results from 35 different experiments. “MetaQTL” software was used to project QTL positions on a reference map. Three hundred and thirty-seven QTL for traits associated with tolerance to abiotic stresses were included in this analysis which identified 79 metaQTL (MQTL) including 26 for drought, 11 for low temperature, 22 for salinity, 17 for water-logging, and 3 for mineral toxicity and deficiency. The distribution of MQTL was similar to that of the initial QTL. Many of these MQTL were located on chromosomes 2H (mainly for water-logging and drought) and 5H (mainly for salinity and low temperature). It inferred that chromosomes 2H and 5H were important for researches on barley abiotic tolerance, and the genes associated with abiotic stresses were concentrated relatively. As expected from trait correlations, 22.8 % of these MQTL displayed overlapping CIs. These overlapping regions were mainly on chromosomes 1H, 2H and 4H. The results indicated that the tolerance to diverse abiotic stresses were associated with each other in barley. Additionally, 67 candidate genes responsive to abiotic stresses were co-located with the abiotic-stress MQTL. Of them, a total of 55 had different conserved motifs. It inferred that the tolerance to abiotic stresses was contributed by multi-genes with diverse functions, though there might be some important genes associated with the tolerance to abiotic stresses in barley. Additionally, of these candidate genes, scsnp02622, scsnp01644 and scsnp19641 could be better for further studies of abiotic stresses tolerance.</description><subject>Abiotic stress</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Analysis</subject><subject>Barley</subject><subject>Biological and medical sciences</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Chromosomes</subject><subject>Drought</subject><subject>Droughts</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Gene loci</subject><subject>Gene mapping</subject><subject>Genes</subject><subject>Genetics and breeding of economic plants</subject><subject>Life Sciences</subject><subject>Low temperature</subject><subject>Meta-analysis</subject><subject>Plant Genetics and Genomics</subject><subject>Plant Pathology</subject><subject>Plant Physiology</subject><subject>Plant Sciences</subject><subject>Quantitative genetics</subject><subject>Salinity</subject><subject>Waterlogging</subject><issn>0014-2336</issn><issn>1573-5060</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp1kF1rFTEQhoMoeKz-AO8WxMu0-dzsXpaiVThFhHod5iSTmrLd1EyKnH9vDlvEG5mLGWbed5h5GHsvxbkUwl2QFOMkuZCK90Jz_YLtpHWaWzGKl2wnhDRcaT2-Zm-I7oUQs7Nix_Y32IDDCsuRMg0lDd9v9wMQlZChYRx-5_ZzaGXBCmvAXg1wyKXlMFCrSIQ05HU4QF3w-Ja9SrAQvnvOZ-zH50-3V1_4_tv116vLPQ96so3PLia0AEaiHjFFHWclo7HaphSiOphRQBht1M7gNEE02jibLLrZJVBh0mfsw7b3sZZfT0jN35en2n8gL5UwqhMZ564631R3sKDPayqtQugR8SGHsmLKvX_ppBFuMpPsBrkZQi1EFZN_rPkB6tFL4U-U_UbZd8r-RNnr7vn4fApQgCWdKGX6a1RulEKZk05tOuqj9Q7rPyf_d_kfSp2Lmg</recordid><startdate>2013</startdate><enddate>2013</enddate><creator>Li, Wei-Tao</creator><creator>Liu, Chunji</creator><creator>Liu, Ya-Xi</creator><creator>Pu, Zhi-En</creator><creator>Dai, Shou-Fen</creator><creator>Wang, Ji-Rui</creator><creator>Lan, Xiu-Jin</creator><creator>Zheng, You-Liang</creator><creator>Wei, Yu-Ming</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>7TM</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>M2P</scope><scope>M7N</scope><scope>P64</scope><scope>PATMY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>RC3</scope></search><sort><creationdate>2013</creationdate><title>Meta-analysis of QTL associated with tolerance to abiotic stresses in barley</title><author>Li, Wei-Tao ; Liu, Chunji ; Liu, Ya-Xi ; Pu, Zhi-En ; Dai, Shou-Fen ; Wang, Ji-Rui ; Lan, Xiu-Jin ; Zheng, You-Liang ; Wei, Yu-Ming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c385t-97dfe5aa41e36efd3d921d4535ffcd2b460ac65d374e88ad43475f5e797fa2c83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Abiotic stress</topic><topic>Agronomy. Soil science and plant productions</topic><topic>Analysis</topic><topic>Barley</topic><topic>Biological and medical sciences</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Chromosomes</topic><topic>Drought</topic><topic>Droughts</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Gene loci</topic><topic>Gene mapping</topic><topic>Genes</topic><topic>Genetics and breeding of economic plants</topic><topic>Life Sciences</topic><topic>Low temperature</topic><topic>Meta-analysis</topic><topic>Plant Genetics and Genomics</topic><topic>Plant Pathology</topic><topic>Plant Physiology</topic><topic>Plant Sciences</topic><topic>Quantitative genetics</topic><topic>Salinity</topic><topic>Waterlogging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Wei-Tao</creatorcontrib><creatorcontrib>Liu, Chunji</creatorcontrib><creatorcontrib>Liu, Ya-Xi</creatorcontrib><creatorcontrib>Pu, Zhi-En</creatorcontrib><creatorcontrib>Dai, Shou-Fen</creatorcontrib><creatorcontrib>Wang, Ji-Rui</creatorcontrib><creatorcontrib>Lan, Xiu-Jin</creatorcontrib><creatorcontrib>Zheng, You-Liang</creatorcontrib><creatorcontrib>Wei, Yu-Ming</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Nucleic Acids Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Agricultural Science Database</collection><collection>ProQuest Science Journals</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><jtitle>Euphytica</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Wei-Tao</au><au>Liu, Chunji</au><au>Liu, Ya-Xi</au><au>Pu, Zhi-En</au><au>Dai, Shou-Fen</au><au>Wang, Ji-Rui</au><au>Lan, Xiu-Jin</au><au>Zheng, You-Liang</au><au>Wei, Yu-Ming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Meta-analysis of QTL associated with tolerance to abiotic stresses in barley</atitle><jtitle>Euphytica</jtitle><stitle>Euphytica</stitle><date>2013</date><risdate>2013</risdate><volume>189</volume><issue>1</issue><spage>31</spage><epage>49</epage><pages>31-49</pages><issn>0014-2336</issn><eissn>1573-5060</eissn><coden>EUPHAA</coden><abstract>A meta-analysis of quantitative trait loci (QTL) associated with tolerance to abiotic stresses in barley was carried out using results from 35 different experiments. “MetaQTL” software was used to project QTL positions on a reference map. Three hundred and thirty-seven QTL for traits associated with tolerance to abiotic stresses were included in this analysis which identified 79 metaQTL (MQTL) including 26 for drought, 11 for low temperature, 22 for salinity, 17 for water-logging, and 3 for mineral toxicity and deficiency. The distribution of MQTL was similar to that of the initial QTL. Many of these MQTL were located on chromosomes 2H (mainly for water-logging and drought) and 5H (mainly for salinity and low temperature). It inferred that chromosomes 2H and 5H were important for researches on barley abiotic tolerance, and the genes associated with abiotic stresses were concentrated relatively. As expected from trait correlations, 22.8 % of these MQTL displayed overlapping CIs. These overlapping regions were mainly on chromosomes 1H, 2H and 4H. The results indicated that the tolerance to diverse abiotic stresses were associated with each other in barley. Additionally, 67 candidate genes responsive to abiotic stresses were co-located with the abiotic-stress MQTL. Of them, a total of 55 had different conserved motifs. It inferred that the tolerance to abiotic stresses was contributed by multi-genes with diverse functions, though there might be some important genes associated with the tolerance to abiotic stresses in barley. Additionally, of these candidate genes, scsnp02622, scsnp01644 and scsnp19641 could be better for further studies of abiotic stresses tolerance.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10681-012-0683-3</doi><tpages>19</tpages></addata></record> |
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subjects | Abiotic stress Agronomy. Soil science and plant productions Analysis Barley Biological and medical sciences Biomedical and Life Sciences Biotechnology Chromosomes Drought Droughts Fundamental and applied biological sciences. Psychology Gene loci Gene mapping Genes Genetics and breeding of economic plants Life Sciences Low temperature Meta-analysis Plant Genetics and Genomics Plant Pathology Plant Physiology Plant Sciences Quantitative genetics Salinity Waterlogging |
title | Meta-analysis of QTL associated with tolerance to abiotic stresses in barley |
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