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Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes
BACKGROUND: Soybean is a valuable crop that provides protein and oil. Soybean requires a large amount of nitrogen (N) to accumulate high levels of N in the seed. The yield and protein content of soybean seeds are directly affected by the N-use efficiency (NUE) of the plant, and improvements in NUE w...
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/PMC3210170/ https://www.ncbi.nlm.nih.gov/pubmed/22029603 http://dx.doi.org/10.1186/1471-2164-12-525 |
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author | Hao, Qing N Zhou, Xin A Sha, Ai H Wang, Cheng Zhou, Rong Chen, Shui L |
author_facet | Hao, Qing N Zhou, Xin A Sha, Ai H Wang, Cheng Zhou, Rong Chen, Shui L |
author_sort | Hao, Qing N |
collection | PubMed |
description | BACKGROUND: Soybean is a valuable crop that provides protein and oil. Soybean requires a large amount of nitrogen (N) to accumulate high levels of N in the seed. The yield and protein content of soybean seeds are directly affected by the N-use efficiency (NUE) of the plant, and improvements in NUE will improve yields and quality of soybean products. Genetic engineering is one of the approaches to improve NUE, but at present, it is hampered by the lack of information on genes associated with NUE. Solexa sequencing is a new method for estimating gene expression in the transcription level. Here, the expression profiles were analyzed between two soybean varieties in N-limited conditions to identify genes related to NUE. RESULTS: Two soybean genotypes were grown under N-limited conditions; a low-N-tolerant variety (No.116) and a low-N-sensitive variety (No.84-70). The shoots and roots of soybeans were used for sequencing. Eight libraries were generated for analysis: 2 genotypes × 2 tissues (roots and shoots) × 2 time periods [short-term (0.5 to 12 h) and long-term (3 to 12 d) responses] and compared the transcriptomes by high-throughput tag-sequencing analysis. 5,739,999, 5,846,807, 5,731,901, 5,970,775, 5,476,878, 5,900,343, 5,930,716, and 5,862,642 clean tags were obtained for the eight libraries: L1, 116-shoot short-term; L2 84-70-shoot short-term; L3 116-shoot long-term; L4 84-70-shoot long-term; L5 116-root short-term; L6 84-70-root short-term; L7 116-root long-term;L8 84-70-root long-term; these corresponded to 224,154, 162,415, 191,994, 181,792, 204,639, 206,998, 233,839 and 257,077 distinct tags, respectively. The clean tags were mapped to the reference sequences for annotation of expressed genes. Many genes showed substantial differences in expression among the libraries. In total, 3,231genes involved in twenty-two metabolic and signal transduction pathways were up- or down-regulated. Twenty-four genes were randomly selected and confirmed their expression patterns by quantitative RT-PCR; Twenty-one of the twenty-four genes showed expression patterns consistent with the Digital Gene Expression (DGE) data. CONCLUSIONS: A number of soybean genes were differentially expressed between the low-N-tolerant and low-N-sensitive varieties under N-limited conditions. Some of these genes may be candidates for improving NUE. These findings will help to provide a detailed understanding of NUE mechanisms, and also provide a basis for breeding soybean varieties that are tolerant to low-N conditions. |
format | Online Article Text |
id | pubmed-3210170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32101702011-11-08 Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes Hao, Qing N Zhou, Xin A Sha, Ai H Wang, Cheng Zhou, Rong Chen, Shui L BMC Genomics Research Article BACKGROUND: Soybean is a valuable crop that provides protein and oil. Soybean requires a large amount of nitrogen (N) to accumulate high levels of N in the seed. The yield and protein content of soybean seeds are directly affected by the N-use efficiency (NUE) of the plant, and improvements in NUE will improve yields and quality of soybean products. Genetic engineering is one of the approaches to improve NUE, but at present, it is hampered by the lack of information on genes associated with NUE. Solexa sequencing is a new method for estimating gene expression in the transcription level. Here, the expression profiles were analyzed between two soybean varieties in N-limited conditions to identify genes related to NUE. RESULTS: Two soybean genotypes were grown under N-limited conditions; a low-N-tolerant variety (No.116) and a low-N-sensitive variety (No.84-70). The shoots and roots of soybeans were used for sequencing. Eight libraries were generated for analysis: 2 genotypes × 2 tissues (roots and shoots) × 2 time periods [short-term (0.5 to 12 h) and long-term (3 to 12 d) responses] and compared the transcriptomes by high-throughput tag-sequencing analysis. 5,739,999, 5,846,807, 5,731,901, 5,970,775, 5,476,878, 5,900,343, 5,930,716, and 5,862,642 clean tags were obtained for the eight libraries: L1, 116-shoot short-term; L2 84-70-shoot short-term; L3 116-shoot long-term; L4 84-70-shoot long-term; L5 116-root short-term; L6 84-70-root short-term; L7 116-root long-term;L8 84-70-root long-term; these corresponded to 224,154, 162,415, 191,994, 181,792, 204,639, 206,998, 233,839 and 257,077 distinct tags, respectively. The clean tags were mapped to the reference sequences for annotation of expressed genes. Many genes showed substantial differences in expression among the libraries. In total, 3,231genes involved in twenty-two metabolic and signal transduction pathways were up- or down-regulated. Twenty-four genes were randomly selected and confirmed their expression patterns by quantitative RT-PCR; Twenty-one of the twenty-four genes showed expression patterns consistent with the Digital Gene Expression (DGE) data. CONCLUSIONS: A number of soybean genes were differentially expressed between the low-N-tolerant and low-N-sensitive varieties under N-limited conditions. Some of these genes may be candidates for improving NUE. These findings will help to provide a detailed understanding of NUE mechanisms, and also provide a basis for breeding soybean varieties that are tolerant to low-N conditions. BioMed Central 2011-10-26 /pmc/articles/PMC3210170/ /pubmed/22029603 http://dx.doi.org/10.1186/1471-2164-12-525 Text en Copyright ©2011 Hao 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 Hao, Qing N Zhou, Xin A Sha, Ai H Wang, Cheng Zhou, Rong Chen, Shui L Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title | Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title_full | Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title_fullStr | Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title_full_unstemmed | Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title_short | Identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
title_sort | identification of genes associated with nitrogen-use efficiency by genome-wide transcriptional analysis of two soybean genotypes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3210170/ https://www.ncbi.nlm.nih.gov/pubmed/22029603 http://dx.doi.org/10.1186/1471-2164-12-525 |
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