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      Genome-Wide Association Study Uncovers Novel Genomic Regions Associated With Coleoptile Length in Hard Winter Wheat

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          Abstract

          Successful seedling establishment depends on the optimum depth of seed placement especially in drought-prone conditions, providing an opportunity to exploit subsoil water and increase winter survival in winter wheat. Coleoptile length is a key determinant for the appropriate depth at which seed can be sown. Thus, understanding the genetic basis of coleoptile length is necessary and important for wheat breeding. We conducted a genome-wide association study (GWAS) using a diverse panel of 298 winter wheat genotypes to dissect the genetic architecture of coleoptile length. We identified nine genomic regions associated with the coleoptile length on seven different chromosomes. Of the nine genomic regions, five have been previously reported in various studies, including one mapped to previously known Rht-B1 region. Three novel quantitative trait loci (QTLs), QCL.sdsu-2AS, QCL.sdsu-4BL, and QCL.sdsu-5BL were identified in our study. QCL.sdsu-5BL has a large substitution effect which is comparable to Rht-B1's effect and could be used to compensate for the negative effect of Rht-B1 on coleoptile length. In total, the nine QTLs explained 59% of the total phenotypic variation. Cultivars ‘Agate’ and ‘MT06103’ have the longest coleoptile length and interestingly, have favorable alleles at nine and eight coleoptile loci, respectively. These lines could be a valuable germplasm for longer coleoptile breeding. Gene annotations in the candidate regions revealed several putative proteins of specific interest including cytochrome P450-like, expansins, and phytochrome A. The QTLs for coleoptile length linked to single-nucleotide polymorphism (SNP) markers reported in this study could be employed in marker-assisted breeding for longer coleoptile in wheat. Thus, our study provides valuable insights into the genetic and molecular regulation of the coleoptile length in winter wheat.

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          Conversion of tryptophan to indole-3-acetic acid by TRYPTOPHAN AMINOTRANSFERASES OF ARABIDOPSIS and YUCCAs in Arabidopsis.

          Auxin is an essential hormone, but its biosynthetic routes in plants have not been fully defined. In this paper, we show that the TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS (TAA) family of amino transferases converts tryptophan to indole-3-pyruvate (IPA) and that the YUCCA (YUC) family of flavin monooxygenases participates in converting IPA to indole-3-acetic acid, the main auxin in plants. Both the YUCs and the TAAs have been shown to play essential roles in auxin biosynthesis, but it has been suggested that they participate in two independent pathways. Here, we show that all of the taa mutant phenotypes, including defects in shade avoidance, root resistance to ethylene and N-1-naphthylphthalamic acid (NPA), are phenocopied by inactivating YUC genes. On the other hand, we show that the taa mutants in several known auxin mutant backgrounds, including pid and npy1, mimic all of the well-characterized developmental defects caused by combining yuc mutants with the auxin mutants. Furthermore, we show that overexpression of YUC1 partially suppresses the shade avoidance defects of taa1 and the sterile phenotypes of the weak but not the strong taa mutants. In addition, we discovered that the auxin overproduction phenotypes of YUC overexpression lines are dependent on active TAA genes. Our genetic data show that YUC and TAA work in the same pathway and that YUC is downstream of TAA. The yuc mutants accumulate IPA, and the taa mutants are partially IPA-deficient, indicating that TAAs are responsible for converting tryptophan to IPA, whereas YUCs play an important role in converting IPA to indole-3-acetic acid.
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            Shrinkage Estimation of the Realized Relationship Matrix

            The additive relationship matrix plays an important role in mixed model prediction of breeding values. For genotype matrix X (loci in columns), the product XX′ is widely used as a realized relationship matrix, but the scaling of this matrix is ambiguous. Our first objective was to derive a proper scaling such that the mean diagonal element equals 1+f, where f is the inbreeding coefficient of the current population. The result is a formula involving the covariance matrix for sampling genomic loci, which must be estimated with markers. Our second objective was to investigate whether shrinkage estimation of this covariance matrix can improve the accuracy of breeding value (GEBV) predictions with low-density markers. Using an analytical formula for shrinkage intensity that is optimal with respect to mean-squared error, simulations revealed that shrinkage can significantly increase GEBV accuracy in unstructured populations, but only for phenotyped lines; there was no benefit for unphenotyped lines. The accuracy gain from shrinkage increased with heritability, but at high heritability (> 0.6) this benefit was irrelevant because phenotypic accuracy was comparable. These trends were confirmed in a commercial pig population with progeny-test-estimated breeding values. For an anonymous trait where phenotypic accuracy was 0.58, shrinkage increased the average GEBV accuracy from 0.56 to 0.62 (SE < 0.00) when using random sets of 384 markers from a 60K array. We conclude that when moderate-accuracy phenotypes and low-density markers are available for the candidates of genomic selection, shrinkage estimation of the relationship matrix can improve genetic gain.
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              Development and validation of KASP assays for genes underpinning key economic traits in bread wheat.

              We developed and validated a robust marker toolkit for high-throughput and cost-effective screening of a large number of functional genes in wheat. Functional markers (FMs) are the most valuable markers for crop breeding programs, and high-throughput genotyping for FMs could provide an excellent opportunity to effectively practice marker-assisted selection while breeding cultivars. Here we developed and validated kompetitive allele-specific PCR (KASP) assays for genes that underpin economically important traits in bread wheat including adaptability, grain yield, quality, and biotic and abiotic stress resistances. In total, 70 KASP assays either developed in this study or obtained from public databases were validated for reliability in application. The validation of KASP assays were conducted by (a) comparing the assays with available gel-based PCR markers on 23 diverse wheat accessions, (b) validation of the derived allelic information using phenotypes of a panel comprised of 300 diverse cultivars from China and 13 other countries, and (c) additional testing, where possible, of the assays in four segregating populations. All KASP assays being reported were significantly associated with the relevant phenotypes in the cultivars panel and bi-parental populations, thus revealing potential application in wheat breeding programs. The results revealed 45 times superiority of the KASP assays in speed than gel-based PCR markers. KASP has recently emerged as single-plex high-throughput genotyping technology; this is the first report on high-throughput screening of a large number of functional genes in a major crop. Such assays could greatly accelerate the characterization of crossing parents and advanced lines for marker-assisted selection and can complement the inflexible, high-density SNP arrays. Our results offer a robust and reliable molecular marker toolkit that can contribute towards maximizing genetic gains in wheat breeding programs.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                05 February 2020
                2019
                : 10
                : 1345
                Affiliations
                [1] 1 Department of Agronomy, Horticulture & Plant Science, South Dakota State University , Brookings, SD, United States
                [2] 2 Department of Biology and Microbiology, South Dakota State University , Brookings, SD, United States
                Author notes

                Edited by: Nunzio D'Agostino, Università degli Studi di Napoli Federico II, Italy

                Reviewed by: Francesca Taranto, Council for Agricultural and Economics Research, Italy; Alessandro Tondelli, Council for Agricultural and Economics Research, Italy

                *Correspondence: Sunish Kumar Sehgal, sunish.sehgal@ 123456sdstate.edu

                †These authors have contributed equally to this work

                This article was submitted to Evolutionary and Population Genetics, a section of the journal Frontiers in Genetics

                Article
                10.3389/fgene.2019.01345
                7025573
                32117410
                4e0a3bd9-75ba-46b0-8cee-b438dd6c25d6
                Copyright © 2020 Sidhu, Singh, Gill, Brar, Qiu, Halder, Al Tameemi, Turnipseed and Sehgal

                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
                : 20 September 2019
                : 09 December 2019
                Page count
                Figures: 5, Tables: 3, Equations: 3, References: 64, Pages: 13, Words: 7472
                Funding
                Funded by: U.S. Department of Agriculture 10.13039/100000199
                Award ID: SD00H538-15, SD00H695-20, 2011-68002-30029 (Triticeae-CAP), 2017-67007-25939 (Wheat-CAP)
                Categories
                Genetics
                Original Research

                Genetics
                triticum aestivum,coleoptile length,semi-dwarf wheat,genome-wide association study,quantitative trait loci,snp (single-nucleotide polymorphism),marker-assisted selection

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