GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and <i>k</i>‐mers

Gupta, P. K.

doi:10.1002/bies.202100109

Cited by 22 publications

(16 citation statements)

References 139 publications

(205 reference statements)

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“…Over a decade of improvements in sequencing technology, whole-genome sequencing and modified reduced genome sequencing (e.g., RAD, RRGS, and GBS) have occurred and SNPs are the most common markers in recent studies [89][90][91]. Currently, multiple genomic variant types, including copy number variations (CNVs) [92][93][94], insertion-deletion (InDel) [84,95], structure variations (SV) [96][97][98], haplotype [99], presence/absence variations (PAVs) based on pan-genome [100], and even epigenomic markers [101] have gained increasing attention through GWAS. Multiple variant profiles have been generated for multiple breeds [102,103].…”

Section: Gwas With Multiple Genomic Variant Typesmentioning

confidence: 99%

Research progress and applications of genome‐wide association study in farm animals

Tan

Fahey

et al. 2023

Animal Research and One Health

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Exploring the genetic loci underlying economic traits is foundational for innovation in modern animal breeding technology. Genome‐wide association studies (GWAS) have been valid and commonly used tools to dissect the genomic variants associated with phenotypes for the past ∼20 years and have contributed to our understanding of genetic and molecular bases of various traits. Here, we comprehensively review the recent research progress on GWAS methods. We highlight the methodological advancements enabled by the combination of new proteome, transcriptome, epigenome, and metagenome information and multi‐omics analysis algorithms. The advances in GWAS investigations of chickens, pigs, cattle, and other animals during the last 5 years are also described. Finally, we discuss the current applications of GWAS in cutting‐edge breeding technologies and overall future perspectives of the post‐GWAS era.

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Section: Gwas With Multiple Genomic Variant Typesmentioning

confidence: 99%

Research progress and applications of genome‐wide association study in farm animals

Tan

Fahey

et al. 2023

Animal Research and One Health

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“…Diverse collections of genes from the different sources/species conferring increased potential for accuracy allelic variants of these genes distinguish carriage from invasive strains. Gene locations identified from Pan-GWAS can tell us the information about even/random spreading of DNA sequences among the chromosomes ( Gori et al., 2020 ; Gupta, 2021 ). Pan-GWAS is mostly used in the microbial study, as the genome of different strains of microorganism can be sequenced easily.…”

Section: Pan-gwasmentioning

confidence: 99%

Two decades of association mapping: Insights on disease resistance in major crops

et al. 2022

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Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

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“…Kmer-db demonstrated the use of k -mer decomposition for efficient analysis of microbial genomes ( [29]). k -mers have many applications in genomics and pangenomics, and they have recently been used as markers for GWAS ( [21,25,26,[30][31][32][33][34][35][36]).…”

Section: Introductionmentioning

confidence: 99%

PanKmer:k-mer based and reference-free pangenome analysis

Aylward

Petrus

Mamerto

et al. 2023

Preprint

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Pangenomes are replacing single reference genomes as the definitive representation of DNA sequence within a species or clade. Pangenome analysis predominantly leverages graph-based methods that require computationally intensive multiple genome alignments, do not scale to highly complex eukaryotic genomes, limit their scope to identifying structural variants (SVs), or incur bias by relying on a reference genome. Here, we present PanKmer, a toolkit designed for reference-free analysis of pangenome datasets consisting of dozens to thousands of individual genomes. PanKmer decomposes a set of input genomes into a table of observed k-mers and their presence-absence values in each genome. These are stored in an efficient k-mer index data format that encodes all forms of variation within the pangenome, including SNPs, INDELs, and SVs. It also includes functions for downstream analysis of the k-mer index, such as calculating sequence similarity statistics between individuals at whole-genome or local scales. For example, k-mers can be "anchored" in any individual genome to quantify sequence variability or conservation at a specific locus. This facilitates workflows with various biological applications, e.g. identifying cases of hybridization between plant species. PanKmer provides researchers with a valuable and convenient means to explore the full scope of genetic variation in a population, without reference bias.

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GWAS for genetics of complex quantitative traits: Genome to pangenome and SNPs to SVs and k‐mers

Cited by 22 publications

References 139 publications

Research progress and applications of genome‐wide association study in farm animals

Research progress and applications of genome‐wide association study in farm animals

Two decades of association mapping: Insights on disease resistance in major crops

PanKmer:k-mer based and reference-free pangenome analysis

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