Literature DB >> 35915266

Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps.

Danting Shan1,2, Mohsin Ali1,2, Mohammed Shahid3, Anjuman Arif4, Muhammad Qandeel Waheed4, Xianchun Xia1, Richard Trethowan5, Mark Tester6, Jesse Poland6,7, Francis C Ogbonnaya8, Awais Rasheed9, Zhonghu He1, Huihui Li10,11.   

Abstract

KEY MESSAGE: A genetic framework underpinning salinity tolerance at reproductive stage was revealed by genome-wide SNP markers and major adaptability genes in synthetic-derived wheats, and trait-associated loci were used to predict phenotypes. Using wild relatives of crops to identify genes related to improved productivity and resilience to climate extremes is a prioritized area of crop genetic improvement. High salinity is a widespread crop production constraint, and development of salt-tolerant cultivars is a sustainable solution. We evaluated a panel of 294 wheat accessions comprising synthetic-derived wheat lines (SYN-DERs) and modern bread wheat advanced lines under control and high salinity conditions at two locations. The GWAS analysis revealed a quantitative genetic framework of more than 200 loci with minor effect underlying salinity tolerance at reproductive stage. The significant trait-associated SNPs were used to predict phenotypes using a GBLUP model, and the prediction accuracy (r2) ranged between 0.57 and 0.74. The r2 values for flag leaf weight, days to flowering, biomass, and number of spikes per plant were all above 0.70, validating the phenotypic effects of the loci discovered in this study. Furthermore, the germplasm sets were compared to identify selection sweeps associated with salt tolerance loci in SYN-DERs. Six loci associated with salinity tolerance were found to be differentially selected in the SYN-DERs (12.4 Mb on chromosome (chr)1B, 7.1 Mb on chr2A, 11.2 Mb on chr2D, 200 Mb on chr3D, 600 Mb on chr6B, and 700.9 Mb on chr7B). A total of 228 reported markers and genes, including 17 well-characterized genes, were uncovered using GWAS and EigenGWAS. A linkage disequilibrium (LD) block on chr5A, including the Vrn-A1 gene at 575 Mb and its homeologs on chr5D, were strongly associated with multiple yield-related traits and flowering time under salinity stress conditions. The diversity panel was screened with more than 68 kompetitive allele-specific PCR (KASP) markers of functional genes in wheat, and the pleiotropic effects of superior alleles of Rht-1, TaGASR-A1, and TaCwi-A1 were revealed under salinity stress. To effectively utilize the extensive genetic information obtained from the GWAS analysis, a genetic interaction network was constructed to reveal correlations among the investigated traits. The genetic network data combined with GWAS, selective sweeps, and the functional gene survey provided a quantitative genetic framework for identifying differentially retained loci associated with salinity tolerance in wheat.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

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Year:  2022        PMID: 35915266     DOI: 10.1007/s00122-022-04153-5

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.574


  45 in total

1.  Algorithms for identifying Boolean networks and related biological networks based on matrix multiplication and fingerprint function.

Authors:  T Akutsu; S Miyano; S Kuhara
Journal:  J Comput Biol       Date:  2000       Impact factor: 1.479

2.  Genomic control for association studies.

Authors:  B Devlin; K Roeder
Journal:  Biometrics       Date:  1999-12       Impact factor: 2.571

Review 3.  Genomic insights into positive selection.

Authors:  Shameek Biswas; Joshua M Akey
Journal:  Trends Genet       Date:  2006-06-30       Impact factor: 11.639

4.  TASSEL: software for association mapping of complex traits in diverse samples.

Authors:  Peter J Bradbury; Zhiwu Zhang; Dallas E Kroon; Terry M Casstevens; Yogesh Ramdoss; Edward S Buckler
Journal:  Bioinformatics       Date:  2007-06-22       Impact factor: 6.937

5.  A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals.

Authors:  Brian L Browning; Sharon R Browning
Journal:  Am J Hum Genet       Date:  2009-02-05       Impact factor: 11.025

6.  Fast model-based estimation of ancestry in unrelated individuals.

Authors:  David H Alexander; John Novembre; Kenneth Lange
Journal:  Genome Res       Date:  2009-07-31       Impact factor: 9.043

7.  Genome-wide comparative diversity uncovers multiple targets of selection for improvement in hexaploid wheat landraces and cultivars.

Authors:  Colin R Cavanagh; Shiaoman Chao; Shichen Wang; Bevan Emma Huang; Stuart Stephen; Seifollah Kiani; Kerrie Forrest; Cyrille Saintenac; Gina L Brown-Guedira; Alina Akhunova; Deven See; Guihua Bai; Michael Pumphrey; Luxmi Tomar; Debbie Wong; Stephan Kong; Matthew Reynolds; Marta Lopez da Silva; Harold Bockelman; Luther Talbert; James A Anderson; Susanne Dreisigacker; Stephen Baenziger; Arron Carter; Viktor Korzun; Peter Laurent Morrell; Jorge Dubcovsky; Matthew K Morell; Mark E Sorrells; Matthew J Hayden; Eduard Akhunov
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-29       Impact factor: 11.205

8.  EigenGWAS: finding loci under selection through genome-wide association studies of eigenvectors in structured populations.

Authors:  G-B Chen; S H Lee; Z-X Zhu; B Benyamin; M R Robinson
Journal:  Heredity (Edinb)       Date:  2016-05-04       Impact factor: 3.821

9.  A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species.

Authors:  Robert J Elshire; Jeffrey C Glaubitz; Qi Sun; Jesse A Poland; Ken Kawamoto; Edward S Buckler; Sharon E Mitchell
Journal:  PLoS One       Date:  2011-05-04       Impact factor: 3.240

10.  Mapping of novel salt tolerance QTL in an Excalibur × Kukri doubled haploid wheat population.

Authors:  Muhammad A Asif; Rhiannon K Schilling; Joanne Tilbrook; Chris Brien; Kate Dowling; Huwaida Rabie; Laura Short; Christine Trittermann; Alexandre Garcia; Edward G Barrett-Lennard; Bettina Berger; Diane E Mather; Matthew Gilliham; Delphine Fleury; Mark Tester; Stuart J Roy; Allison S Pearson
Journal:  Theor Appl Genet       Date:  2018-07-30       Impact factor: 5.699

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