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BSA-Seq for the Identification of Major Genes for EPN in Rice
Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573429/ https://www.ncbi.nlm.nih.gov/pubmed/37834285 http://dx.doi.org/10.3390/ijms241914838 |
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author | Shen, Shen Xu, Shanbin Wang, Mengge Ma, Tianze Chen, Ning Wang, Jingguo Zheng, Hongliang Yang, Luomiao Zou, Detang Xin, Wei Liu, Hualong |
author_facet | Shen, Shen Xu, Shanbin Wang, Mengge Ma, Tianze Chen, Ning Wang, Jingguo Zheng, Hongliang Yang, Luomiao Zou, Detang Xin, Wei Liu, Hualong |
author_sort | Shen, Shen |
collection | PubMed |
description | Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative trait locus (QTL) for EPN in rice is limited, and there is also limited research on the gene for EPN in rice. Therefore, the excavation and analysis of major genes related to EPN in rice is of great significance for molecular breeding and yield improvement. This study used japonica rice varieties Dongfu 114 and Longyang 11 to construct an F(5) population consisting of 309 individual plants. Two extreme phenotypic pools were constructed by identifying the EPN of the population, and QTL-seq analysis was performed to obtain three main effective QTL intervals for EPN. This analysis also helped to screen out 34 candidate genes. Then, EPN time expression pattern analysis was performed on these 34 genes to screen out six candidate genes with higher expression levels. Using a 3K database to perform haplotype analysis on these six genes, we selected haplotypes with significant differences in EPN. Finally, five candidate genes related to EPN were obtained. |
format | Online Article Text |
id | pubmed-10573429 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105734292023-10-14 BSA-Seq for the Identification of Major Genes for EPN in Rice Shen, Shen Xu, Shanbin Wang, Mengge Ma, Tianze Chen, Ning Wang, Jingguo Zheng, Hongliang Yang, Luomiao Zou, Detang Xin, Wei Liu, Hualong Int J Mol Sci Article Improving rice yield is one of the most important food issues internationally. It is an undeniable goal of rice breeding, and the effective panicle number (EPN) is a key factor determining rice yield. Increasing the EPN in rice is a major way to increase rice yield. Currently, the main quantitative trait locus (QTL) for EPN in rice is limited, and there is also limited research on the gene for EPN in rice. Therefore, the excavation and analysis of major genes related to EPN in rice is of great significance for molecular breeding and yield improvement. This study used japonica rice varieties Dongfu 114 and Longyang 11 to construct an F(5) population consisting of 309 individual plants. Two extreme phenotypic pools were constructed by identifying the EPN of the population, and QTL-seq analysis was performed to obtain three main effective QTL intervals for EPN. This analysis also helped to screen out 34 candidate genes. Then, EPN time expression pattern analysis was performed on these 34 genes to screen out six candidate genes with higher expression levels. Using a 3K database to perform haplotype analysis on these six genes, we selected haplotypes with significant differences in EPN. Finally, five candidate genes related to EPN were obtained. MDPI 2023-10-02 /pmc/articles/PMC10573429/ /pubmed/37834285 http://dx.doi.org/10.3390/ijms241914838 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Shen, Shen Xu, Shanbin Wang, Mengge Ma, Tianze Chen, Ning Wang, Jingguo Zheng, Hongliang Yang, Luomiao Zou, Detang Xin, Wei Liu, Hualong BSA-Seq for the Identification of Major Genes for EPN in Rice |
title | BSA-Seq for the Identification of Major Genes for EPN in Rice |
title_full | BSA-Seq for the Identification of Major Genes for EPN in Rice |
title_fullStr | BSA-Seq for the Identification of Major Genes for EPN in Rice |
title_full_unstemmed | BSA-Seq for the Identification of Major Genes for EPN in Rice |
title_short | BSA-Seq for the Identification of Major Genes for EPN in Rice |
title_sort | bsa-seq for the identification of major genes for epn in rice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10573429/ https://www.ncbi.nlm.nih.gov/pubmed/37834285 http://dx.doi.org/10.3390/ijms241914838 |
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