Recent advances on genome-wide association studies (GWAS) and genomic selection (GS); prospects for Fusarium head blight research in Durum wheat

Mir, Zahoor Ahmad; Chandra, Tilak; Saharan, Anurag; Budhlakoti, Neeraj; Mishra, Dwijesh Chandra; Saharan, M. S.; Mir, Reyazul Rouf; Singh, Amit Kumar; Sharma, Soumya; Vikas, V. K.; Kumar, Sundeep

doi:10.1007/s11033-023-08309-4

Cited by 5 publications

(3 citation statements)

References 112 publications

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“…Comparative genomics approaches using these model species have also been pursued in order to understand the evolution of diverse ecologies among the Sordariomycetes, especially those that are related to pathogenesis ( Figure 2 ). Among the pathogenic Sordariomycetes, species of Fusarium have been intensively studied for their diverse genome structures ( Brown and Proctor, 2013 ; Ma et al., 2013 ; Zhang, 2019 ; Mir et al., 2023 ). Research on entomopathogenic Sordariomycetes, represented by Cordyceps , Beauveria , and Metarhizium species, has been greatly enhanced by the availability of genomes of these species ( Gao et al., 2011 ; Pattemore et al., 2014 ; Valero-Jiménez et al., 2016 ; Kato et al., 2022 ; Liu and Dong, 2023 ; Sant Anna Iwanicki et al., 2023 ).…”

Section: New Details and New Omics Data On The Sordariomycetes Contin...mentioning

confidence: 99%

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Wang

Kim

Wang

et al. 2023

Front. Fungal Biol.

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Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium, Neurospora, and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom.

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Section: New Details and New Omics Data On The Sordariomycetes Contin...mentioning

confidence: 99%

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Wang

Kim

Wang

et al. 2023

Front. Fungal Biol.

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show abstract

“…The development of high-yielding, thermo-tolerant cultivars is anticipated to be accelerated through the discovery of new genes and genomic regions linked to speci c bread wheat traits. Given that all-marker effects are concurrently assessed in ML-GWAS models, these are thought to be superior to SL-GWAS methods for mapping of complex traits [54], [51], [39] and were utilized for the current GWAS study. In current study, six different GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, ISIS EM-BLASSO, and pKWmEB) were used to examine the marker-trait association to nd out markers associated to the target trait [40], [45], [43], [44], [51].…”

Section: Discussionmentioning

confidence: 99%

“…In many GWAS studies, the single locus model is commonly used, relying on single marker associations at a time throughout genome-wide scans. However, these models have certain drawbacks, such as repeated test adjustments for critical values and not considering the overall impact of multiple loci [39]. This is due to their onedimensional genome scan nature.…”

Section: Genome-wide Association Analysesmentioning

confidence: 99%

Unlocking the Grain Quality Enigma: A KASP-Driven Voyage Through Bread Wheat's Quantitative Trait Nucleotides Under Heat Adversity

Bashir,

Budhlakoti,

Pradhan

et al. 2024

Preprint

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Heat stress is a critical factor affecting global wheat production and productivity. In this study, out of 500 studied accessions a diverse panel of 126 wheat genotypes grown under twelve distinct environmental conditions was analyzed. Using 35K single-nucleotide polymorphism (SNP) genotyping assays and trait data on five biochemical parameters, including grain protein content (GPC), grain amylose content (GAC), grain total soluble sugars (TSS), grain iron (Fe), and zinc (Zn) content, six multi-locus GWAS models were employed for association analysis. This revealed 67 significantly associated QTNs linked to grain quality parameters, explaining phenotypic variations ranging from 3–44% under heat stress conditions. By considering the results in consensus to at least three GWAS models and three locations, the final QTNs were reduced to 17, with 14 being novel findings. Notably, two novel markers, AX-94461119 (chromosome 6A) and AX-95220192 (chromosome 7D), associated with grain iron and zinc, respectively, were validated through KASP approach. Candidate genes, such as chaperonin Cpn60/GroEL/TCP-1 family, P-loop containing nucleoside triphosphate hydrolases (NTPases), Bowman-Birk type proteinase inhibitor (BBI), and NPSN13 protein, were identified from the associated genomic regions, which could be potentially targeted for improving quality traits and heat tolerance in wheat.

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Integrating Marker-Assisted (MAS) and Genomic Selection (GS) for Plant Functional Trait Improvement

Verma,

Gupta,

Yalla

et al. 2024

Plant Functional Traits for Improving Productivity

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Recent advances on genome-wide association studies (GWAS) and genomic selection (GS); prospects for Fusarium head blight research in Durum wheat

Cited by 5 publications

References 112 publications

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

Unlocking the Grain Quality Enigma: A KASP-Driven Voyage Through Bread Wheat's Quantitative Trait Nucleotides Under Heat Adversity

Integrating Marker-Assisted (MAS) and Genomic Selection (GS) for Plant Functional Trait Improvement

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