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      Genome-Wide Association Studies for Pasmo Resistance in Flax ( Linum usitatissimum L.)

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          Abstract

          Pasmo is one of the most widespread diseases threatening flax production. To identify genetic regions associated with pasmo resistance (PR), a genome-wide association study was performed on 370 accessions from the flax core collection. Evaluation of pasmo severity was performed in the field from 2012 to 2016 in Morden, MB, Canada. Genotyping-by-sequencing has identified 258,873 single nucleotide polymorphisms (SNPs) distributed on all 15 flax chromosomes. Marker-trait associations were identified using ten different statistical models. A total of 692 unique quantitative trait nucleotides (QTNs) associated with 500 putative quantitative trait loci (QTL) were detected from six phenotypic PR datasets (five individual years and average across years). Different QTNs were identified with various statistical models and from individual PR datasets, indicative of the complementation between analytical methods and/or genotype × environment interactions of the QTL effects. The single-locus models tended to identify large-effect QTNs while the multi-loci models were able to detect QTNs with smaller effects. Among the putative QTL, 67 had large effects (3–23%), were stable across all datasets and explained 32–64% of the total variation for PR in the various datasets. Forty-five of these QTL spanned 85 resistance gene analogs including a large toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (TNL) type gene cluster on chromosome 8. The number of QTL with positive-effect or favorite alleles (NPQTL) in accessions was significantly correlated with PR ( R 2 = 0.55), suggesting that these QTL effects are mainly additive. NPQTL was also significantly associated with morphotype ( R 2 = 0.52) and major QTL with positive effect alleles were present in the fiber type accessions. The 67 large effect QTL are suited for marker-assisted selection and the 500 QTL for effective genomic prediction in PR molecular breeding.

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          An efficient multi-locus mixed model approach for genome-wide association studies in structured populations

          Population structure causes genome-wide linkage disequilibrium between unlinked loci, leading to statistical confounding in genome-wide association studies. Mixed models have been shown to handle the confounding effects of a diffuse background of large numbers of loci of small effect well, but do not always account for loci of larger effect. Here we propose a multi-locus mixed model as a general method for mapping complex traits in structured populations. Simulations suggest that our method outperforms existing methods, in terms of power as well as false discovery rate. We apply our method to human and Arabidopsis thaliana data, identifying novel associations in known candidates as well as evidence for allelic heterogeneity. We also demonstrate how a priori knowledge from an A. thaliana linkage mapping study can be integrated into our method using a Bayesian approach. Our implementation is computationally efficient, making the analysis of large datasets (n > 10000) practicable.
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            QTL mapping and marker-assisted selection forFusariumhead blight resistance in wheat: a review

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              Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

              Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.
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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
                14 January 2019
                2018
                : 9
                : 1982
                Affiliations
                [1] 1Ottawa Research and Development Centre, Agriculture and Agri-Food Canada , Ottawa, ON, Canada
                [2] 2Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University/JCIC-MCP , Nanjing, China
                [3] 3Morden Research and Development Centre, Agriculture and Agri-Food Canada , Morden, MB, Canada
                [4] 4Crop Development Centre, University of Saskatchewan , Saskatoon, SK, Canada
                Author notes

                Edited by: Yuan-Ming Zhang, Huazhong Agricultural University, China

                Reviewed by: Hailong Ning, Northeast Agricultural University, China; Dan Zhang, Henan Agricultural University, China

                *Correspondence: Sylvie Cloutier sylvie.j.cloutier@ 123456canada.ca

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

                Article
                10.3389/fpls.2018.01982
                6339956
                30693010
                14673e85-2ad2-4f51-8518-bc301ac0eb31
                Copyright © 2019 He, Xiao, Rashid, Yao, Li, Jia, Wang, Cloutier and You.

                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) and the copyright owner(s) 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
                : 07 November 2018
                : 20 December 2018
                Page count
                Figures: 7, Tables: 8, Equations: 1, References: 57, Pages: 15, Words: 9473
                Categories
                Plant Science
                Original Research

                Plant science & Botany
                pasmo resistance,quantitative trait loci (qtl),quantitative trait nucleotides (qtns),fiber,linseed,core collection,flax,linum usitatissimum

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