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QTL underlying some agronomic traits in barley detected by SNP markers
BACKGROUND: Increasing the yield of barley (Hordeum vulgare L.) is a main breeding goal in developing barley cultivars. A high density genetic linkage map containing 1894 SNP and 68 SSR markers covering 1375.8 cM was constructed and used for mapping quantitative traits. A late-generation double hapl...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936321/ https://www.ncbi.nlm.nih.gov/pubmed/27388211 http://dx.doi.org/10.1186/s12863-016-0409-y |
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author | Wang, Jibin Sun, Genlou Ren, Xifeng Li, Chengdao Liu, Lipan Wang, Qifei Du, Binbin Sun, Dongfa |
author_facet | Wang, Jibin Sun, Genlou Ren, Xifeng Li, Chengdao Liu, Lipan Wang, Qifei Du, Binbin Sun, Dongfa |
author_sort | Wang, Jibin |
collection | PubMed |
description | BACKGROUND: Increasing the yield of barley (Hordeum vulgare L.) is a main breeding goal in developing barley cultivars. A high density genetic linkage map containing 1894 SNP and 68 SSR markers covering 1375.8 cM was constructed and used for mapping quantitative traits. A late-generation double haploid population (DH) derived from the Huaai 11 × Huadamai 6 cross was used to identify QTLs and QTL × environment interactions for ten traits affecting grain yield including length of main spike (MSL), spikelet number on main spike (SMS), spikelet number per plant (SLP), grain number per plant (GP), grain weight per plant (GWP), grain number per spike (GS), thousand grain weight (TGW), grain weight per spike (GWS), spike density (SPD) and spike number per plant (SP). RESULTS: In single environment analysis using composite interval mapping (CIM), a total of 221 QTLs underlying the ten traits were detected in five consecutive years (2009–2013). The QTLs detected in each year were 50, 48, 41, 41 and 41 for the year 2009 to 2013. The QTLs associated with these traits were generally clustered on chromosome 2H, 4H and 7H. In multi-environment analysis, a total of 111 significant QTLs including 18 for MSL, 16 for SMS, 15 for SPD, 5 for SP, 4 for SLP, 14 for TGW, 5 for GP, 11 for GS, 8 for GWP, and 15 for GWS were detected in the five years. Most QTLs showed significant QTL × environment interactions (QEI), nine QTLs (qIMSL3-1, qIMSL4-1, qIMSL4-2, qIMSL6-1, qISMS7-1, qISPD2-7, qISPD7-1, qITGW3-1 and qIGWS4-3) were detected with minimal QEI effects and stable in different years. Among 111 QTLs,71 (63.40 %) QTLs were detected in both single and multiple environments. CONCLUSIONS: Three main QTL cluster regions associated with the 10 agronomic traits on chromosome 2H, 4H and 7H were detected. The QTLs for SMS, SLP, GP and GWP were located in the region near Vrs1 on chromosome 2H. The QTLs underlying SMS, SPD and SLP were clustered on chromosome 4H. On the terminal of chromosome 7H, there was a QTL cluster associated with TGW, SPD, GWP and GWS. The information will be useful for marker-assisted selection (MAS) in barley breeding. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0409-y) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4936321 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-49363212016-07-08 QTL underlying some agronomic traits in barley detected by SNP markers Wang, Jibin Sun, Genlou Ren, Xifeng Li, Chengdao Liu, Lipan Wang, Qifei Du, Binbin Sun, Dongfa BMC Genet Research Article BACKGROUND: Increasing the yield of barley (Hordeum vulgare L.) is a main breeding goal in developing barley cultivars. A high density genetic linkage map containing 1894 SNP and 68 SSR markers covering 1375.8 cM was constructed and used for mapping quantitative traits. A late-generation double haploid population (DH) derived from the Huaai 11 × Huadamai 6 cross was used to identify QTLs and QTL × environment interactions for ten traits affecting grain yield including length of main spike (MSL), spikelet number on main spike (SMS), spikelet number per plant (SLP), grain number per plant (GP), grain weight per plant (GWP), grain number per spike (GS), thousand grain weight (TGW), grain weight per spike (GWS), spike density (SPD) and spike number per plant (SP). RESULTS: In single environment analysis using composite interval mapping (CIM), a total of 221 QTLs underlying the ten traits were detected in five consecutive years (2009–2013). The QTLs detected in each year were 50, 48, 41, 41 and 41 for the year 2009 to 2013. The QTLs associated with these traits were generally clustered on chromosome 2H, 4H and 7H. In multi-environment analysis, a total of 111 significant QTLs including 18 for MSL, 16 for SMS, 15 for SPD, 5 for SP, 4 for SLP, 14 for TGW, 5 for GP, 11 for GS, 8 for GWP, and 15 for GWS were detected in the five years. Most QTLs showed significant QTL × environment interactions (QEI), nine QTLs (qIMSL3-1, qIMSL4-1, qIMSL4-2, qIMSL6-1, qISMS7-1, qISPD2-7, qISPD7-1, qITGW3-1 and qIGWS4-3) were detected with minimal QEI effects and stable in different years. Among 111 QTLs,71 (63.40 %) QTLs were detected in both single and multiple environments. CONCLUSIONS: Three main QTL cluster regions associated with the 10 agronomic traits on chromosome 2H, 4H and 7H were detected. The QTLs for SMS, SLP, GP and GWP were located in the region near Vrs1 on chromosome 2H. The QTLs underlying SMS, SPD and SLP were clustered on chromosome 4H. On the terminal of chromosome 7H, there was a QTL cluster associated with TGW, SPD, GWP and GWS. The information will be useful for marker-assisted selection (MAS) in barley breeding. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12863-016-0409-y) contains supplementary material, which is available to authorized users. BioMed Central 2016-07-07 /pmc/articles/PMC4936321/ /pubmed/27388211 http://dx.doi.org/10.1186/s12863-016-0409-y Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Wang, Jibin Sun, Genlou Ren, Xifeng Li, Chengdao Liu, Lipan Wang, Qifei Du, Binbin Sun, Dongfa QTL underlying some agronomic traits in barley detected by SNP markers |
title | QTL underlying some agronomic traits in barley detected by SNP markers |
title_full | QTL underlying some agronomic traits in barley detected by SNP markers |
title_fullStr | QTL underlying some agronomic traits in barley detected by SNP markers |
title_full_unstemmed | QTL underlying some agronomic traits in barley detected by SNP markers |
title_short | QTL underlying some agronomic traits in barley detected by SNP markers |
title_sort | qtl underlying some agronomic traits in barley detected by snp markers |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4936321/ https://www.ncbi.nlm.nih.gov/pubmed/27388211 http://dx.doi.org/10.1186/s12863-016-0409-y |
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