variant effect prediction

The paper examines GT>GC 5' splice-site variants, showing they can retain wild-type transcript and challenge variant classification.

This study identifies a SNP in CaPAT1 that enables full-length GRAS domain formation, enhancing shoot regeneration in pepper through dimerization and overexpression.

This study benchmarks somatic mutation detection using the human pangenome reference and finds improved accuracy, especially in East Asian individuals.

The paper integrates AMGs and phage assembly into a genome-scale metabolic model to predict their impact on host metabolism and phage production, revealing synergistic and antagonistic effects.

BioWorldModel predicts phenotype from genotype across four kingdoms by modeling biological processes, achieving higher accuracy than traditional methods.

This study uses genomic prediction to select resilient sessile oak genotypes based on foliar physiological traits, showing high heritability and across-provenance predictability.

This paper introduces a Bayesian marker-based principal component ridge regression framework for estimating quantitative genetic parameters in wild study systems, showing efficient estimation of additive genetic variance and accurate breeding value prediction.

SILO improves detection of disease susceptible variants in short IBD segments, outperforming existing models in simulated and real data.

This paper introduces GroupSig, a framework to overcome sparsity in clinical targeted-panel sequencing data, identifying inherited determinants of mutational signatures in cancer.

This paper improves variant effect predictors by calibrating them gene- and domain-aware, increasing evidence assignment and accuracy for variant classification.

The paper introduces BlueSTARR, a predictive modeling framework trained on whole-genome STARR-seq data to assess variant effects on regulatory functions, revealing purifying selection against loss-of-function and gain-of-function variants.

The paper identifies biallelic variants in RNU2-2 as a common cause of recessive neurodevelopmental disorders, showing higher prevalence than the dominant form in England.

The paper introduces methbiome, a tool for reference-based DNA methylation profiling of long-read metagenomic data, enabling cross-platform and between-sample comparison of methylation signals in microbiomes.

The paper shows that humanized Traf6 promoter sequences in mice affect immune responses but not fertility, revealing distinct roles for germ and immune cells in gene regulatory evolution.

This paper introduces StructureDCA, a method that improves mutational landscape predictions by integrating structural information into direct coupling analysis.

The paper uses a convolutional neural network to predict chromatin organization disruptions caused by somatic structural variants in pediatric tumors, identifying high-impact SVs and regions associated with cancer.

This study evaluates bulk ATAC-seq's ability to detect genomic variants, CNVs, and telomere repeats, showing its potential as an integrative tool for cancer research.

The paper performs whole exome sequencing on 44,028 British South Asians to identify gene-phenotype associations and knockout genes, finding novel links and implications for drug development.

The paper develops a method to estimate variance components and predict genetic values using ancestral recombination graphs (ARGs) and linear mixed models on large datasets.

WINDEX improves detection of positive selective sweeps by integrating site- and window-based statistics in population genetic data, showing improved localization and genome-wide estimates of selective pressures.

This paper evaluates Evo 2's ability to predict variant effects in plant genes using Arabidopsis thaliana data, showing it can identify functionally impactful variants.

BARMIX quantifies treatment resistance in gastrointestinal stromal tumor cell mixtures using barcoded experiments and probabilistic modeling, accurately reflecting clinical resistance patterns.

gnomAD v4 (730,947 exomes) brings LOFTEE-2 loss-of-function annotation (0.90 precision, strict mode), missense-aware constraint, and LLM-mined literature evidence combined with constraint to rank disease genes.

CanVar-UK is a web platform that supports collaborative interpretation of germline variants in cancer susceptibility genes by integrating variant data, clinical information, and expert discussions.

The paper identifies noncoding variants that alter gene regulatory networks using a combination of single-molecule deaminase footprinting and variant effect prediction, applied to UK Biobank genomes.

The paper identifies and analyzes human intrinsically disordered regions (IDRs) in transcription factors, revealing their unique functional, phenotypic, and evolutionary characteristics compared to non-TF IDRs.

This study implements whole-exome sequencing in Algeria for neurodevelopmental disorders, achieving molecular diagnoses in 8/14 cases and highlighting challenges in variant interpretation and database underrepresentation.

This study shows chronic morphine exposure represses Smchd1, disrupting X-chromosome inactivation and genomic imprinting through epigenetic changes in mouse and human cells.

COBT is a gene-based rare variant burden test for case-only studies that outperforms existing methods and identifies novel candidate variants in rare diseases.

This paper introduces REGEN, a GNN framework for learning gene interaction networks from bulk transcriptomic data and predicting patient outcomes, showing improved performance across cancer types.