Multi-locus genome-wide association studies (ML-GWAS) reveal novel genomic regions associated with seedling and adult plant stage leaf rust resistance in bread wheat (Triticum aestivum L.)

Vikas, V. K.; Pradhan, Anjan K.; Budhlakoti, Neeraj; Mishra, Dwijesh Chandra; Chandra, Tilak; Bhardwaj, Subhash; Kumar, Subodh; Sivasamy, M.; Jayaprakash, P.; Rani, Nisha; Shajitha, P.; Peter, John; Geetha, M; Mir, Reyazul Rouf; Singh, Kuldeep; Kumar, Sundeep

doi:10.1038/s41437-022-00525-1

Cited by 33 publications

(25 citation statements)

References 108 publications

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“…The advancement in high-throughput genotyping, next generation sequencing, bioinformatics tools, statistical models, etc., have served as catalyst to access valuable information from genomic databases and a large number of germplasm, allowing effective harnessing of genetic diversity of a crop ( Vikas et al., 2022 ). Such diversity is vital for broadening the genetic base, as it increases the probability of identifying more unique genes for which two parents have different alleles ( Mascher et al., 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…Traditional popular statistical models (single-marker genome-wide scan models), mixed linear model (MLM), and general linear model (GLM), among others, have a number of limitations such as the stringent threshold of significance and mapping power ( Wen et al., 2018 ). To overcome these limitations, several multi-locus models have been developed and utilized for GWAS in several crops ( Zhang et al., 2019 ; Karikari et al., 2020 ; Berhe et al., 2021 ; Vikas et al., 2022 ). Among them include a multi-locus random-SNP-effect mixed linear model (mrMLM) ( Wang et al., 2016 ), a fast mrMLM (FASTmrMLM) ( Zhang et al., 2018 ), a fast mrMLM efficient mixed-model association (FASTmrEMMA) ( Wen et al., 2018 ), polygene-background-control-based least-angle regression plus empirical Bayes (pLARmEB) ( Zhang et al., 2017 ), Kruskal-Wallis test with empirical Bayes under polygenic background control (pKWmEB) ( Ren et al., 2018 ) and integrative sure independence screening expectation maximization Bayesian least absolute shrinkage and selection operator model (ISIS EM-BLASSO) ( Tamba et al., 2017 ).…”

Section: Introductionmentioning

confidence: 99%

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Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Oteng‐Frimpong

Karikari²,

Sie³

et al. 2023

Front. Plant Sci.

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Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Oteng‐Frimpong

Karikari²,

Sie³

et al. 2023

Front. Plant Sci.

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“…Also, QTLs were identified in hostile soils under salt stress conditions for yield and related traits (Hu et al, 2021). Similarly, MTAs were also identified for biotic stresses (Vikas et al, 2022) and quality traits (Sandhu et al, 2021;Rathan et al, 2022) in wheat. Although several marker-trait associations (MTAs) were identified in different GWAS studies for yield and its component traits, there might be several false positives in most of the studies due to a very low threshold (−log 10 p-value ≥ 3.0) fixation to consider the MTA as a significant.…”

Section: Introductionmentioning

confidence: 92%

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

et al. 2022

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Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

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“…Another MTA, scaffold163140-5_613860 against race TNBJS was mapped on the region harboring known gene Lr28 (McIntosh et al 1982) on chromosome 4A. However, TNBJS is virulent on Lr28 which eliminates the possibility of association of Lr28 with scaffold163140-5_613860 .Further, scaffold163140-5_613860 was also mapped in the vicinity of a recently reported MTA ( AX-95106749 ) for adult plant LR resistance (Vikas et al, 2022). Since, scaffold163140-5_613860 was identified for seedling resistance to LR, it is unlikely that this MTA represents AX-95106749 .…”

Section: Discussionmentioning

confidence: 99%

Identification of leaf rust resistance loci in a geographically diverse panel of wheat using genome-wide association analysis

Kaur

Gill

Breiland

et al. 2022

Preprint

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Leaf rust, caused by Puccinia triticina (Pt) is among the most devastating diseases posing a significant threat to global wheat production. The continuously evolving virulent Pt races in North America calls for exploring new sources of leaf rust resistance. A diversity panel of 365 bread wheat accessions selected from a worldwide population of landraces and cultivars was evaluated at the seedling stage against four Pt races (TDBJQ, TBBGS, MNPSD and, TNBJS). A wide distribution of seedling responses against the four Pt races was observed. Majority of the genotypes displayed a susceptible response with only 28 (9.8%), 59 (13.5%), 45 (12.5%), and 29 (8.1%) wheat accessions exhibiting a highly resistant response to TDBJQ, TBBGS, MNPSD and, TNBJS, respectively. Further, we conducted a high-resolution multi-locus genome-wide association study (GWAS) using a set of 302,524 high-quality single nucleotide polymorphisms (SNPs). The GWAS analysis identified 27 marker-trait associations (MTAs) for leaf rust resistance on different wheat chromosomes of which 20 MTAs were found in the vicinity of known Lr genes, MTAs, or quantitative traits loci (QTLs) identified in previous studies. The remaining seven significant MTAs identified represent genomic regions that harbor potentially novel genes for leaf rust resistance. Furthermore, the candidate gene analysis for the significant MTAs identified various genes of interest that may be involved in disease resistance. The identified resistant lines and SNPs linked to the QTLs in this study will serve as valuable resources in wheat rust resistance breeding programs.

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Multi-locus genome-wide association studies (ML-GWAS) reveal novel genomic regions associated with seedling and adult plant stage leaf rust resistance in bread wheat (Triticum aestivum L.)

Cited by 33 publications

References 108 publications

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

Identification of leaf rust resistance loci in a geographically diverse panel of wheat using genome-wide association analysis

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