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Sequencing and exploitation of the genetic diversity in Vietnamese native rice lines to serve research and breeding programs

Sequencing and exploitation of the genetic diversity in Vietnamese native rice lines to serve research and breeding programs
对越南本土水稻品系的遗传多样性进行测序和利用,为研究和育种计划服务
批准号:
BB/N013735/1
负责人:
Mario Caccamo
金额:
$55.01万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

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项目成果

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中文摘要
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英文摘要
We propose to develop a modern platform for rice breeding in Vietnam focused on traits of agronomic interest. Rice is a staple food for a population of 90 million in Vietnam and it is also one of the main exporter commodities of the country. Vietnam is experiencing an exceptional growth in its economic output and population rising as a global leading agricultural country. There is, however, an increasing threat from climate change such as emerging pathogens, periods of droughts and rising sea levels. The areas under greatest risk are the deltas of the Red and Mekong rivers, which represent the major rice growing regions of Vietnam. The rapid selection of rice varieties that are tolerant and resilient to these conditions will help to mitigate some of these challenges and contribute to ensure food security in Vietnam. The Genome Analysis Centre (TGAC) in the UK and the Agricultural Genetics Institute (AGI) in Vietnam initiated a collaboration to sequence the genome of a reduced number of Vietnamese rice varieties with the purpose to characterise the genetic variations in native lines and develop molecular markers that could be used to accelerate rice breeding. The application of new genomics technologies to improve crop breeding is one of the priorities at the National Institute of Agricultural Botany (NIAB) at UK. The proposed project continues the partnership initiated between TGAC and AGI as a collaboration with NIAB. We aim at expanding the pilot project phase I to complete the re-sequencing of around 600 lines. We will complement the generation of these data with the development of databases and the application of bioinformatics pipelines to identify associations of alleles with specific phenotypes. We expect to characterise markers that will enable more efficient rice breeding. The application of modern technologies to rice breeding will also provide an excellent example of how these strategies could be applied to other plant species such as wheat and barley. Rice has a simple genome for which many genomics resources have been already generated and it offers an excellent model for the evaluation and assessment of new strategies for breeding that could later be applied to more complex crops. This collaboration with Vietnam will also open opportunities to work with world leading scientists with experience in rice breeding and agronomy.
期刊论文(10)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1093/gbe/evx135
发表时间: 2017-06-01
期刊: Genome biology and evolution
影响因子: 3.3
作者: [Trung KH, Nguyen TK, Khuat HBT, Nguyen TD, Khanh TD, Xuan TD, Nguyen XH]
通讯作者: Nguyen XH
DOI: 10.1111/eva.13433
发表时间: 2022-07
期刊: Evolutionary applications
影响因子: 4.1
作者: []
通讯作者:
DOI: 10.1186/s12284-021-00481-0
发表时间: 2021-06-10
期刊: Rice (New York, N.Y.)
影响因子: --
作者: [Higgins J, Santos B, Khanh TD, Trung KH, Duong TD, Doai NTP, Khoa NT, Ha DTT, Diep NT, Dung KT, Phi CN, Thuy TT, Tuan NT, Tran HD, Trung NT, Giang HT, Nhung TK, Tran CD, Lang SV, Nghia T, Van Giang N, Xuan TD, Hall A, Dyer S, Ham LH, Caccamo M, De Vega JJ]
通讯作者: De Vega JJ
DOI: 10.1101/2020.07.07.191981
发表时间: 2020-07
期刊: bioRxiv
影响因子: --
作者: [J. Higgins;B. Santos;T. Khanh;K. H. Trung;T. D. Duong;Nguyen Thi Phuong Doai;N. T. Khoa;D. Ha;N. T. Diep;K. T. Dung;Cong Nguyen Phi;T. Thủy;N. T. Tuan;H. Tran;N. Trung;H. T. Giang;Ta Thi Kim Nhung;C. Tran;S. Lang;L. T. Nghia;N. Giảng;T. Xuan;Anthony Hall;S. Dyer;L. Hàm;M. Cáccamo;J. D. Vega]
通讯作者: J. Higgins;B. Santos;T. Khanh;K. H. Trung;T. D. Duong;Nguyen Thi Phuong Doai;N. T. Khoa;D. Ha;N. T. Diep;K. T. Dung;Cong Nguyen Phi;T. Thủy;N. T. Tuan;H. Tran;N. Trung;H. T. Giang;Ta Thi Kim Nhung;C. Tran;S. Lang;L. T. Nghia;N. Giảng;T. Xuan;Anthony Hall;S. Dyer;L. Hàm;M. Cáccamo;J. D. Vega
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