Genome-wide association analysis permits characterization of Stagonospora nodorum blotch (SNB) resistance in hard winter wheat

Altameemi, Rami; Gill, Harsimardeep S.; Ali, Shaukat; Ayana, Girma; Halder, Jyotirmoy; Sidhu, Jagdeep Singh; Gill, U. S.; Turnipseed, Brent; Gonzalez-Hernandez, Jose L.; Sehgal, Sunish K.

doi:10.1038/s41598-021-91515-6

Cited by 17 publications

(10 citation statements)

References 73 publications

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“…Furthermore, QTLs for the same abiotic stress tolerance from different mapping populations were projected onto the same chromosomal region, confirming that those regions exist. The meta-analysis conducted in this study refined the CIs and compared the genomic positions of different QTLs detected in individual studies associated Further, GWAS is an alternative high-precision technique to QTL mapping which is based on high-throughput sequencing or array technologies [57][58][59] . Interestingly, more than 57% (76/134) of MQTLs were validated with GWAS-MTAs associated with different abiotic stress tolerance traits identified in wheat.…”

Section: Discussionmentioning

confidence: 99%

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

Tanin

Saini

Sandhu

et al. 2022

Sci Rep

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In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress (DS), heat stress (HS), salinity stress (SS), water-logging stress (WS), pre-harvest sprouting (PHS), and aluminium stress (AS) which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 189 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

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Section: Discussionmentioning

confidence: 99%

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

Tanin

Saini

Sandhu

et al. 2022

Sci Rep

View full text Add to dashboard Cite

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“…Genome-wide association studies (GWAS) is one of the most widely used methods of gene discovery nowadays and in use in almost all important crop plants (e.g., Choudhary et al, 2018b ; Sidhu et al, 2020 ; AlTameemi et al, 2021 ). This method allows for high-resolution mapping of genes/QTLs utilizing recent as well as historical recombination events in natural populations ( Saini et al, 2022b ).…”

Section: Discussionmentioning

confidence: 99%

“…Similarly, different meta-QTL studies have identified promising CGs associated with MQTLs with differential expression patterns for the traits under studies, such as drought tolerance in wheat (Kumar et al, 2020), root traits in wheat (Saini et al, 2021) and yield-related traits and seed protein content in pea (Klein et al, 2020(Klein et al, ). 10.3389/fpls.2022 Validating meta-quantitative trait loci from genome-wide association studies Genome-wide association studies (GWAS) is one of the most widely used methods of gene discovery nowadays and in use in almost all important crop plants (e.g., Choudhary et al, 2018b;Sidhu et al, 2020;AlTameemi et al, 2021). This method allows for high-resolution mapping of genes/QTLs utilizing recent as well as historical recombination events in natural populations (Saini et al, 2022b).…”

Section: Candidate Gene Identification and Expression Analysismentioning

confidence: 99%

Delineating meta-quantitative trait loci for anthracnose resistance in common bean (Phaseolus vulgaris L.)

et al. 2022

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Anthracnose, caused by the fungus Colletotrichum lindemuthianum, is one of the devastating disease affecting common bean production and productivity worldwide. Several quantitative trait loci (QTLs) for anthracnose resistance have been identified. In order to make use of these QTLs in common bean breeding programs, a detailed meta-QTL (MQTL) analysis has been conducted. For the MQTL analysis, 92 QTLs related to anthracnose disease reported in 18 different earlier studies involving 16 mapping populations were compiled and projected on to the consensus map. This meta-analysis led to the identification of 11 MQTLs (each involving QTLs from at least two different studies) on 06 bean chromosomes and 10 QTL hotspots each involving multiple QTLs from an individual study on 07 chromosomes. The confidence interval (CI) of the identified MQTLs was found 3.51 times lower than the CI of initial QTLs. Marker-trait associations (MTAs) reported in published genome-wide association studies (GWAS) were used to validate nine of the 11 identified MQTLs, with MQTL4.1 overlapping with as many as 40 MTAs. Functional annotation of the 11 MQTL regions revealed 1,251 genes including several R genes (such as those encoding for NBS-LRR domain-containing proteins, protein kinases, etc.) and other defense related genes. The MQTLs, QTL hotspots and the potential candidate genes identified during the present study will prove useful in common bean marker-assisted breeding programs and in basic studies involving fine mapping and cloning of genomic regions associated with anthracnose resistance in common beans.

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“…Genome-wide association study (GWAS) provides a good alternative by providing a much higher resolution to capture insights into the genetic architecture of complex traits because of historically accumulated mutations or recombination events ( Scherer and Christensen, 2016 ; Sidhu et al, 2020 ). GWAS has been successfully used to dissect many traits of economic importance in wheat ( Sukumaran et al, 2014 ; Sidhu et al, 2020 ; AlTameemi et al, 2021 ) including a several studies on FHB resistance ( Kollers et al, 2013 ; Arruda et al, 2016 ; Wang et al, 2017 ; Tessmann et al, 2019 ; Larkin et al, 2020 ; Zhu et al, 2020 ). However, GWAS on FHB resistance has not been reported for the US hard winter wheat.…”

Section: Introductionmentioning

confidence: 99%

Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat

et al. 2022

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Fusarium head blight (FHB), caused by the fungus Fusarium graminearum Schwabe is an important disease of wheat that causes severe yield losses along with serious quality concerns. Incorporating the host resistance from either wild relatives, landraces, or exotic materials remains challenging and has shown limited success. Therefore, a better understanding of the genetic basis of native FHB resistance in hard winter wheat (HWW) and combining it with major quantitative trait loci (QTLs) can facilitate the development of FHB-resistant cultivars. In this study, we evaluated a set of 257 breeding lines from the South Dakota State University (SDSU) breeding program to uncover the genetic basis of native FHB resistance in the US hard winter wheat. We conducted a multi-locus genome-wide association study (ML-GWAS) with 9,321 high-quality single-nucleotide polymorphisms (SNPs). A total of six distinct marker-trait associations (MTAs) were identified for the FHB disease index (DIS) on five different chromosomes including 2A, 2B, 3B, 4B, and 7A. Further, eight MTAs were identified for Fusarium-damaged kernels (FDK) on six chromosomes including 3B, 5A, 6B, 6D, 7A, and 7B. Out of the 14 significant MTAs, 10 were found in the proximity of previously reported regions for FHB resistance in different wheat classes and were validated in HWW, while four MTAs represent likely novel loci for FHB resistance. Accumulation of favorable alleles of reported MTAs resulted in significantly lower mean DIS and FDK score, demonstrating the additive effect of FHB resistance alleles. Candidate gene analysis for two important MTAs identified several genes with putative proteins of interest; however, further investigation of these regions is needed to identify genes conferring FHB resistance. The current study sheds light on the genetic basis of native FHB resistance in the US HWW germplasm and the resistant lines and MTAs identified in this study will be useful resources for FHB resistance breeding via marker-assisted selection.

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Genome-wide association analysis permits characterization of Stagonospora nodorum blotch (SNB) resistance in hard winter wheat

Cited by 17 publications

References 73 publications

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

Delineating meta-quantitative trait loci for anthracnose resistance in common bean (Phaseolus vulgaris L.)

Multi-Locus Genome-Wide Association Studies to Characterize Fusarium Head Blight (FHB) Resistance in Hard Winter Wheat

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