AIMC Topic: Genome-Wide Association Study

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Precision breeding in a changing climate: unlocking resilience through omics and gene editing.

Functional & integrative genomics
Climate change, rising global food demand, and shrinking resources require transformative innovations in crop breeding. This review outlines recent advances in new breeding technologies (NBTs), including molecular markers, genome-wide association stu...

Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Mammalian genome : official journal of the International Mammalian Genome Society
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...

Genetic relationships between the gut microbiota and prostate cancer: Mendelian randomization combined with bioinformatics analysis.

The aging male : the official journal of the International Society for the Study of the Aging Male
BACKGROUND: Prostate cancer (PCa) is a leading cause of male cancer-related death globally. While the gut microbiota is linked to PCa, its genetic association remains unclear.

Bayesian neural networks for genomic prediction: uncertainty quantification and SNP interpretation with SHAP and GWAS.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
This study presents a Bayesian neural networks framework with LASSO regularization and the GSMeSP interpretability tool, enabling accurate, uncertainty-aware, and biologically interpretable genomic prediction. Deep learning offers significant potenti...

Genome-wide association study reveals genetic architecture and evolution of human retinal pigmentation.

Science advances
Pigmentation varies widely across humans and is shaped by melanin quantity, type, and spatial distribution. Retinal pigmentation protects against light-induced damage, yet its genetic and evolutionary bases remain unclear. We developed a deep learnin...

Decoding the germline genetic architecture of prostate cancer at a single cell resolution.

PLoS genetics
Prostate cancer exhibits a strong familial association, and its heritability indicates a significant contribution from germline variants. While genome-wide association studies (GWAS) have identified common germline variants associated with prostate c...

Candidate genes for anthracnose resistance in Senegalese sorghum: a machine learning-based exploration.

Functional & integrative genomics
Anthracnose, caused by the hemibiotrophic fungal pathogen Colletotrichum sublineola, is a significant constraint to sorghum production worldwide. Developing resistant cultivars is the most sustainable control strategy, but it requires constant additi...

Transformer-based deep learning enhances discovery in migraine GWAS.

Nature communications
Migraine is a complex neurological disorder with substantial heritability, yet genome-wide association studies (GWAS) have explained only a fraction of its genetic component. We developed InsightGWAS, a Transformer-based model, to enhance genetic dis...

ML-MAGES enables multivariate genetic association analyses with genes and effect size shrinkage.

Genome research
A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges account for inflation in GWA ...

BayesRVAT enhances rare-variant association testing through Bayesian aggregation of functional annotations.

Genome research
Gene-level rare variant association tests (RVATs) are essential for uncovering disease mechanisms and identifying therapeutic targets. Advances in sequence-based machine learning have generated diverse variant pathogenicity scores, creating opportuni...