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Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus
BACKGROUND: In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3155843/ https://www.ncbi.nlm.nih.gov/pubmed/21679437 http://dx.doi.org/10.1186/1471-2164-12-319 |
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author | Swamy, BP Mallikarjuna Vikram, Prashant Dixit, Shalabh Ahmed, HU Kumar, Arvind |
author_facet | Swamy, BP Mallikarjuna Vikram, Prashant Dixit, Shalabh Ahmed, HU Kumar, Arvind |
author_sort | Swamy, BP Mallikarjuna |
collection | PubMed |
description | BACKGROUND: In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach. RESULTS: The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL(1.2), MQTL(1.3), MQTL(1.4), and MQTL(12.1 )were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY(12.1 )was present in 85% of the lines, followed by DTY(4.1 )in 79% and DTY(1.1 )in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL(1.4 )and MQTL(3.2 )had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL. CONCLUSIONS: Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought. |
format | Online Article Text |
id | pubmed-3155843 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-31558432011-08-15 Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus Swamy, BP Mallikarjuna Vikram, Prashant Dixit, Shalabh Ahmed, HU Kumar, Arvind BMC Genomics Research Article BACKGROUND: In the last few years, efforts have been made to identify large effect QTL for grain yield under drought in rice. However, identification of most precise and consistent QTL across the environments and genetics backgrounds is essential for their successful use in Marker-assisted Selection. In this study, an attempt was made to locate consistent QTL regions associated with yield increase under drought by applying a genome-wide QTL meta-analysis approach. RESULTS: The integration of 15 maps resulted in a consensus map with 531 markers and a total map length of 1821 cM. Fifty-three yield QTL reported in 15 studies were projected on a consensus map and meta-analysis was performed. Fourteen meta-QTL were obtained on seven chromosomes. MQTL(1.2), MQTL(1.3), MQTL(1.4), and MQTL(12.1 )were around 700 kb and corresponded to a reasonably small genetic distance of 1.8 to 5 cM and they are suitable for use in marker-assisted selection (MAS). The meta-QTL for grain yield under drought coincided with at least one of the meta-QTL identified for root and leaf morphology traits under drought in earlier reports. Validation of major-effect QTL on a panel of random drought-tolerant lines revealed the presence of at least one major QTL in each line. DTY(12.1 )was present in 85% of the lines, followed by DTY(4.1 )in 79% and DTY(1.1 )in 64% of the lines. Comparative genomics of meta-QTL with other cereals revealed that the homologous regions of MQTL(1.4 )and MQTL(3.2 )had QTL for grain yield under drought in maize, wheat, and barley respectively. The genes in the meta-QTL regions were analyzed by a comparative genomics approach and candidate genes were deduced for grain yield under drought. Three groups of genes such as stress-inducible genes, growth and development-related genes, and sugar transport-related genes were found in clusters in most of the meta-QTL. CONCLUSIONS: Meta-QTL with small genetic and physical intervals could be useful in Marker-assisted selection individually and in combinations. Validation and comparative genomics of the major-effect QTL confirmed their consistency within and across the species. The shortlisted candidate genes can be cloned to unravel the molecular mechanism regulating grain yield under drought. BioMed Central 2011-06-16 /pmc/articles/PMC3155843/ /pubmed/21679437 http://dx.doi.org/10.1186/1471-2164-12-319 Text en Copyright ©2011 Swamy et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Swamy, BP Mallikarjuna Vikram, Prashant Dixit, Shalabh Ahmed, HU Kumar, Arvind Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title_full | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title_fullStr | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title_full_unstemmed | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title_short | Meta-analysis of grain yield QTL identified during agricultural drought in grasses showed consensus |
title_sort | meta-analysis of grain yield qtl identified during agricultural drought in grasses showed consensus |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3155843/ https://www.ncbi.nlm.nih.gov/pubmed/21679437 http://dx.doi.org/10.1186/1471-2164-12-319 |
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