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      eQTLs Regulating Transcript Variations Associated with Rapid Internode Elongation in Deepwater Rice

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          Abstract

          To avoid low oxygen, oxygen deficiency or oxygen deprivation, deepwater rice cultivated in flood planes can develop elongated internodes in response to submergence. Knowledge of the gene regulatory networks underlying rapid internode elongation is important for an understanding of the evolution and adaptation of major crops in response to flooding. To elucidate the genetic and molecular basis controlling their deepwater response we used microarrays and performed expression quantitative trait loci (eQTL) and phenotypic QTL (phQTL) analyses of internode samples of 85 recombinant inbred line (RIL) populations of non-deepwater (Taichung 65)- and deepwater rice (Bhadua). After evaluating the phenotypic response of the RILs exposed to submergence, confirming the genotypes of the populations, and generating 188 genetic markers, we identified 10,047 significant eQTLs comprised of 2,902 cis-eQTLs and 7,145 trans-eQTLs and three significant eQTL hotspots on chromosomes 1, 4, and 12 that affect the expression of many genes. The hotspots on chromosomes 1 and 4 located at different position from phQTLs detected in this study and other previous studies. We then regarded the eQTL hotspots as key regulatory points to infer causal regulatory networks of deepwater response including rapid internode elongation. Our results suggest that the downstream regulation of the eQTL hotspots on chromosomes 1 and 4 is independent, and that the target genes are partially regulated by SNORKEL1 and SNORKEL2 genes ( SK1/ 2), key ethylene response factors. Subsequent bioinformatic analyses, including gene ontology-based annotation and functional enrichment analysis and promoter enrichment analysis, contribute to enhance our understanding of SK1/2-dependent and independent pathways. One remarkable observation is that the functional categories related to photosynthesis and light signaling are significantly over-represented in the candidate target genes of SK1/2. The combined results of these investigations together with genetical genomics approaches using structured populations with a deepwater response are also discussed in the context of current molecular models concerning the rapid internode elongation in deepwater rice. This study provides new insights into the underlying genetic architecture of gene expression regulating the response to flooding in deepwater rice and will be an important community resource for analyses on the genetic basis of deepwater responses.

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          Most cited references67

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Genetic dissection of transcriptional regulation in budding yeast.

            To begin to understand the genetic architecture of natural variation in gene expression, we carried out genetic linkage analysis of genomewide expression patterns in a cross between a laboratory strain and a wild strain of Saccharomyces cerevisiae. Over 1500 genes were differentially expressed between the parent strains. Expression levels of 570 genes were linked to one or more different loci, with most expression levels showing complex inheritance patterns. The loci detected by linkage fell largely into two categories: cis-acting modulators of single genes and trans-acting modulators of many genes. We found eight such trans-acting loci, each affecting the expression of a group of 7 to 94 genes of related function.
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              A simple regression method for mapping quantitative trait loci in line crosses using flanking markers.

              The use of flanking marker methods has proved to be a powerful tool for the mapping of quantitative trait loci (QTL) in the segregating generations derived from crosses between inbred lines. Methods to analyse these data, based on maximum-likelihood, have been developed and provide good estimates of QTL effects in some situations. Maximum-likelihood methods are, however, relatively complex and can be computationally slow. In this paper we develop methods for mapping QTL based on multiple regression which can be applied using any general statistical package. We use the example of mapping in an F(2) population and show that these regression methods produce very similar results to those obtained using maximum likelihood. The relative simplicity of the regression methods means that models with more than a single QTL can be explored and we give examples of two lined loci and of two interacting loci. Other models, for example with more than two QTL, with environmental fixed effects, with between family variance or for threshold traits, could be fitted in a similar way. The ease, speed of application and generality of regression methods for flanking marker analysis, and the good estimates they obtain, suggest that they should provide the method of choice for the analysis of QTL mapping data from inbred line crosses.
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                Author and article information

                Contributors
                Journal
                Front Plant Sci
                Front Plant Sci
                Front. Plant Sci.
                Frontiers in Plant Science
                Frontiers Media S.A.
                1664-462X
                13 October 2017
                2017
                : 8
                : 1753
                Affiliations
                [1] 1Bioscience and Biotechnology Center, Nagoya University , Nagoya, Japan
                [2] 2Department of Developmental Biology and Neurosciences, Graduate School of Life Sciences, Tohoku University , Sendai, Japan
                [3] 3Genome Resource Unit, National Institute of Agrobiological Sciences , Tsukuba, Japan
                [4] 4RIKEN Center for Sustainable Resource Science , Yokohama, Japan
                [5] 5Graduate School of Life and Environmental Sciences, University of Tsukuba , Tsukuba, Japan
                [6] 6Faculty of Agriculture, Kyushu University , Fukuoka, Japan
                Author notes

                Edited by: Avinash Mishra, Central Salt and Marine Chemicals Research Institute (CSIR), India

                Reviewed by: Xusheng Wang, St. Jude Children’s Research Hospital, United States; Hanwei Mei, Shanghai Agrobiological Gene Center, China; Hiroki Saito, Kyoto University, Japan

                *Correspondence: Takeshi Kuroha, tkuroha@ 123456m.tohoku.ac.jp Atsushi Fukushima, atsushi.fukushima@ 123456riken.jp

                This article was submitted to Plant Abiotic Stress, a section of the journal Frontiers in Plant Science

                Article
                10.3389/fpls.2017.01753
                5645499
                29081784
                3107c45b-05d4-482e-a928-3cd327ec2251
                Copyright © 2017 Kuroha, Nagai, Kurokawa, Nagamura, Kusano, Yasui, Ashikari and Fukushima.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 July 2017
                : 25 September 2017
                Page count
                Figures: 7, Tables: 0, Equations: 0, References: 83, Pages: 16, Words: 0
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                quantitative trait locus,expression qtl,eqtl hotspots,ethylene response factor,submergence,abiotic stress,oryza sativa

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