Genome-Wide Association Study Statistical Models: A Review

Yoosefzadeh-Najafabadi, Mohsen; Eskandari, Milad; Belzile, François; Torkamaneh, Davoud

doi:10.1007/978-1-0716-2237-7_4

Cited by 19 publications

(13 citation statements)

References 134 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The statistical model adopted is one of the setbacks to the power of detection in GWAS ( Gupta et al., 2014 ; Ibrahim et al., 2020 ; Yoosefzadeh-Najafabadi et al., 2022 ). 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 ).…”

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.

View full text Add to dashboard Cite

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.

show abstract

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.

View full text Add to dashboard Cite

show abstract

“…The results indicated that support vector regression-mediated GWAS de-tected more relevant MTAs for the tested traits, supported by the functional annotation of candidate gene analyses (Yoosefzadeh-Najafabadi et al 2021c). Therefore, ML algorithms can be used in GWAS to complement conventional GWAS methods to detect MTAs which can significantly improve the efficiency of genomic-based breeding programs (Yoosefzadeh-Najafabadi et al 2022c).…”

Section: Big Data Analyzing Methodsmentioning

confidence: 78%

Six decades of soybean breeding in Ontario, Canada: a tradition of innovation

Yoosefzadeh-Najafabadi

Rajcan

2023

Can. J. Plant Sci.

Self Cite

View full text Add to dashboard Cite

Soybean has been widely grown by Canadian farmers for more than 80 years, especially in Southern Ontario. In recent decades, the Canadian growing region has and expandingexpanded east and north Canada in recent decades. An average of 1% soybean yield improvement is achieved annually, thanks to efforts by public and private soybean breeding programs. However, in order to meet future food demands, an average 2.4% annual increase in soybean yield is required annually. As sSoybean breeders are mostly dealing with complex traits that are under control by several intrinsic and extrinsic factors, it is necessary to haveso sufficient information about the past and current breeding efforts is required to modify the future breeding programs accordingly. Here, we focused onreview public soybean breeding efforts that have been made inover the past 25 years in Southern Ontario, as one of the most productive regions for Canadian soybean growers. Furthermore, we explain how the recent advances could facilitate the soybean breeding programs by reducing the time and cost and increasing selection accuracy in a large breeding population. Finally, we summarize future directions in three important sections, i.e., multi-omics, environmental, and data-driven approaches, and provide a view vision for future soybean breeding programs.

show abstract

“…Therefore, using Tfit modeling 22 , we systematically inferred and annotated the sites of RNAPII loading and bidirectional transcription initiation, frequently referred to as Mu (μ), within this eRNA set. Next, to discern potential relationships between these eRNA-transcribing genomic regions and asthma risk in the Genetic Epidemiology Research in Adult Health and Aging (GERA) clinical population 23,24 , we leveraged machine learning and fine mapping approaches, which have advantages over traditional statistical inference methods 25 , to create an analysis pipeline (Fig 1A) to discover genetic variants associated with asthma based on proximity to μ. We first screened the GERA dataset to filter SNPs that were annotated within the dynamically regulated enhancer regions, by treatment (dex or TNF).…”

Section: Resultsmentioning

confidence: 99%

“…We used Tfit modeling to systematically infer and annotate the sites of RNAPII loading and bidirectional transcription initiation 24 , frequently referred to as Mu (μ), within this eRNA set. To investigate potential relationships between these eRNA-transcribing genomic regions and asthma risk in the non-Hispanic white population within the Genetic Epidemiology Research in Adult Health and Aging (GERA) clinical cohort 5,25 , we leveraged regression modeling, permutation testing and fine mapping approaches 26 to create an analysis pipeline (Fig 1A ) for discovery of genetic variants associated with asthma based on proximity to μ.…”

Section: Localization Of Snps Within Dynamically Regulated Enhancers ...mentioning

confidence: 99%

Glucocorticoid-regulated bidirectional enhancer RNA transcription pinpoints functional genetic variants linked to asthma

Sasse

Dahlin

Sanford

et al. 2022

Preprint

View full text Add to dashboard Cite

Genome wide association studies of asthma have not explained environmental risk or variable clinical efficacy of glucocorticoids. Bidirectional enhancer RNA (eRNA) transcription is a widespread response to environmental signals and glucocorticoids. Therefore, we investigated whether single nucleotide polymorphisms (SNPs) within dynamically regulated enhancer RNA (eRNA)-transcribing regions contribute to genetic variation in asthma. Through applying machine-learning methods to a large clinical cohort, we identified novel associations between asthma and 36 SNPs located in eRNA-transcribing regions implicated in regulating diverse cellular processes relevant to asthma. Functional validation established that rs258760 (mean allele frequency = 0.35, asthma odds ratio 0.95; P<0.005) eliminates an active aryl hydrocarbon receptor (AHR) response element linked to transcriptional regulation of the glucocorticoid receptor by AHR ligands commonly found in air pollution. Our findings establish eRNA signatures as a tool for discovery of functional genetic variants and define a novel link between air pollution, glucocorticoid signaling and asthma.

show abstract

Genome-Wide Association Study Statistical Models: A Review

Cited by 19 publications

References 134 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

Six decades of soybean breeding in Ontario, Canada: a tradition of innovation

Glucocorticoid-regulated bidirectional enhancer RNA transcription pinpoints functional genetic variants linked to asthma

Contact Info

Product

Resources

About