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      Dissection of genetic architecture of rice plant height and heading date by multiple-strategy-based association studies

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          Abstract

          Xieyou9308 is a certified super hybrid rice cultivar with a high grain yield. To investigate its underlying genetic basis of high yield potential, a recombinant inbred line (RIL) population derived from the cross between the maintainer line XieqingzaoB (XQZB) and the restorer line Zhonghui9308 (ZH9308) was constructed for identification of quantitative trait SNPs (QTSs) associated with two important agronomic traits, plant height (PH) and heading date (HD). By re-sequencing of 138 recombinant inbred lines (RILs), a total of ~0.7 million SNPs were identified for the association studies on the PH and HD. Three association mapping strategies (including hypothesis-free genome-wide association and its two complementary hypothesis-engaged ones, QTL-based association and gene-based association) were adopted for data analysis. Using a saturated mixed linear model including epistasis and environmental interaction, we identified a total of 31 QTSs associated with either the PH or the HD. The total estimated heritability across three analyses ranged from 37.22% to 45.63% and from 37.53% to 55.96% for the PH and HD, respectively. In this study we examined the feasibility of association studies in an experimental population (RIL) and identified several common loci through multiple strategies which could be preferred candidates for further research.

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          What it will take to feed 5.0 billion rice consumers in 2030.

          Major advances have occurred in rice production due to adoption of green revolution technology. Between 1966 and 2000, the population of densely populated low income countries grew by 90% but rice production increased by 130% from 257 million tons in 1966 to 600 million tons in 2000. However, the population of rice consuming countries continues to grow and it is estimated that we will have to produce 40 more rice in 2030. This increased demand will have to be met from less land, with less water, less labor and fewer chemicals. To meet the challenge of producing more rice from suitable lands we need rice varieties with higher yield potential and greater yield stability. Various strategies for increasing the rice yield potential being employed include: (1) conventional hybridization and selection procedures, (2) ideotype breeding, (3) hybrid breeding, (4) wide hybridization and (5) genetic engineering. Various conventional and biotechnology approach are being employed to develop durable resistance to diseases and insect and for tolerance to abiotic stresses. The availability of the rice genome sequence will now permit identification of the function of each of 60,000 rice genes through functional genomics. Once the function of a gene is identified, it will be possible to develop new rice varieties by introduction of the gene through traditional breeding in combination with marker aided selection or direct engineering of genes into rice varieties.
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            The role of QTLs in the breeding of high-yielding rice.

            Food shortages have once again become a serious problem, not only because of world population growth but also as a result of escalating demand for crops as a substrate for biofuels. The production of improved plant varieties, especially major crops such as rice, is urgently required to increase yield. The completion of the sequencing of the rice genome has made it possible to clone and analyze quantitative trait loci (QTLs). Furthermore, the development of high-throughput sequencing and genotyping technologies has improved spectacularly the accuracy of QTL analysis. In this review article, we focus on the potential roles of major QTLs in the selection for agronomic traits in rice and discuss the application of high-throughput technologies for high-resolution genetic analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.
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              DNMT3B interacts with constitutive centromere protein CENP-C to modulate DNA methylation and the histone code at centromeric regions.

              DNA methylation is an epigenetically imposed mark of transcriptional repression that is essential for maintenance of chromatin structure and genomic stability. Genome-wide methylation patterns are mediated by the combined action of three DNA methyltransferases: DNMT1, DNMT3A and DNMT3B. Compelling links exist between DNMT3B and chromosome stability as emphasized by the mitotic defects that are a hallmark of ICF syndrome, a disease arising from germline mutations in DNMT3B. Centromeric and pericentromeric regions are essential for chromosome condensation and the fidelity of segregation. Centromere regions contain distinct epigenetic marks, including dense DNA hypermethylation, yet the mechanisms by which DNA methylation is targeted to these regions remains largely unknown. In the present study, we used a yeast two-hybrid screen and identified a novel interaction between DNMT3B and constitutive centromere protein CENP-C. CENP-C is itself essential for mitosis. We confirm this interaction in mammalian cells and map the domains responsible. Using siRNA knock downs, bisulfite genomic sequencing and ChIP, we demonstrate for the first time that CENP-C recruits DNA methylation and DNMT3B to both centromeric and pericentromeric satellite repeats and that CENP-C and DNMT3B regulate the histone code in these regions, including marks characteristic of centromeric chromatin. Finally, we demonstrate that loss of CENP-C or DNMT3B leads to elevated chromosome misalignment and segregation defects during mitosis and increased transcription of centromeric repeats. Taken together, our data reveal a novel mechanism by which DNA methylation is targeted to discrete regions of the genome and contributes to chromosomal stability.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                13 July 2016
                2016
                : 6
                : 29718
                Affiliations
                [1 ]Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University , Hangzhou 310058, China
                [2 ]State Key Laboratory of Rice Biology and Zhejiang Key Laboratory of Super Rice Research, China National Rice Research Institute , Hangzhou 311401, China
                [3 ]Department of Biostatistics and Bioinformatics, Tulane University , New Orleans, Louisiana, 1440 Canal St., Suite 2001, New Orleans, LA 70112-2632, USA
                Author notes
                Article
                srep29718
                10.1038/srep29718
                4942822
                27406081
                aa05cd28-9425-4e04-b63a-3fd10e68a528
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 23 March 2016
                : 22 June 2016
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