17
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Genetic architecture of grain yield in bread wheat based on genome-wide association studies

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits.

          Results

          A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4–725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS.

          Conclusions

          The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

          Electronic supplementary material

          The online version of this article (10.1186/s12870-019-1781-3) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references46

          • Record: found
          • Abstract: found
          • Article: not found

          Genome-wide association study for grain yield and related traits in an elite spring wheat population grown in temperate irrigated environments.

          Through genome-wide association study, loci for grain yield and yield components were identified in chromosomes 5A and 6A in spring wheat (Triticum aestivum). Genome-wide association study (GWAS) was conducted for grain yield (YLD) and yield components on a wheat association mapping initiative (WAMI) population of 287 elite, spring wheat lines grown under temperate irrigated high-yield potential condition in Ciudad Obregón, Mexico, during four crop cycles (from 2009-2010 to 2012-2013). The population was genotyped with high-density Illumina iSelect 90K single nucleotide polymorphisms (SNPs) assay. An analysis of traits across subpopulations indicated that lines with 1B/1R translocation had higher YLD, grain weight, and taller plants than lines without the translocation. GWAS using 18,704 SNPs identified 31 loci that explained 5-14 % of the variation in individual traits. We identified SNPs in chromosome 5A and 6A that were significantly associated with yield and yield components. Four loci were detected for YLD in chromosomes 3B, 5A, 5B, and 6A and the locus in 5A explained 5 % of the variation for grain number/m(2). The locus for YLD in chromosome 6A also explained 6 % of the variation in grain weight. Loci significantly associated with maturity were identified in chromosomes 2B, 3B, 4B, 4D, and 6A and for plant height in 1A and 6A. Loci were also detected for canopy temperature at grain filling (2D, 4D, 6A), chlorophyll index at grain filling (3B and 6A), biomass (3D and 6A) and harvest index (1D, 1B, and 3B) that explained 5-10 % variation. These markers will be further validated.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            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.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              High-Throughput SNP Genotyping to Accelerate Crop Improvement

                Bookmark

                Author and article information

                Contributors
                lifajily@163.com
                wenweie@live.com
                liujindong_1990@163.com
                zhangyong05@caas.cn
                caoshuanghe@caas.cn
                zhhecaas@163.com
                awais_rasheed@yahoo.com
                jinhuicaas@126.com
                chz@kth.se
                yanjuncn@163.com
                pzzha@yahoo.com
                wanyingxiu@163.com
                xiaxianchun@caas.cn
                Journal
                BMC Plant Biol
                BMC Plant Biol
                BMC Plant Biology
                BioMed Central (London )
                1471-2229
                29 April 2019
                29 April 2019
                2019
                : 19
                : 168
                Affiliations
                [1 ]ISNI 0000 0000 9354 9799, GRID grid.413251.0, College of Agronomy, , Xinjiang Agricultural University, ; Urumqi, 830052 Xinjiang China
                [2 ]ISNI 0000 0001 0526 1937, GRID grid.410727.7, Institute of Crop Sciences, National Wheat Improvement Center, , Chinese Academy of Agricultural Sciences (CAAS), ; 12 Zhongguancun South Street, Beijing, 100081 China
                [3 ]International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o CAAS, 12 Zhongguancun South Street, Beijing, 100081 China
                [4 ]GRID grid.452609.c, Sino-Russia Agricultural Scientific and Technological Cooperation Center, , Heilongjiang Academy of Agricultural Sciences, ; 368 Xuefu Street, Harbin, 150086 Heilongjiang China
                [5 ]ISNI 0000000121581746, GRID grid.5037.1, School of Chemical Science and Engineering, , Royal Institute of Technology, ; Teknikringen 42, SE-100 44 Stockholm, Sweden
                [6 ]ISNI 0000 0001 0526 1937, GRID grid.410727.7, Institute of Cotton Research, , Chinese Academy of Agricultural Sciences (CAAS), ; 38 Huanghe Street, Anyang, 455000 Henan China
                [7 ]ISNI 0000 0004 1756 0127, GRID grid.469521.d, Crop Research Institute, , Anhui Academy of Agricultural Sciences, ; 40 Nongke South Street, Hefei, 230001 Anhui China
                Author information
                http://orcid.org/0000-0003-2071-197X
                Article
                1781
                10.1186/s12870-019-1781-3
                6489268
                31035920
                8ecc0924-bcdc-4d7b-831e-8820a4ee7057
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 October 2018
                : 16 April 2019
                Funding
                Funded by: National Basic Research Program of China
                Award ID: 2014CB138105
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31461143021
                Award Recipient :
                Funded by: National Key Research and Development Programs of China
                Award ID: 2016YFD0101802
                Award ID: 2016YFE0108600
                Award Recipient :
                Funded by: CAAS Science and Technology Innovation Program
                Award ID: No
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Plant science & Botany
                gwas,marker-assisted selection,single nucleotide polymorphism,triticum aestivum

                Comments

                Comment on this article