Genomics and Rare Diseases

Site saturation mutagenesis of 500 human protein domains reveals the contribution of protein destabilization to genetic disease

The paper performs site saturation mutagenesis on 500 human protein domains to assess the impact of missense variants on protein stability and disease.

Nanopore sequencing-based episignature detection

This study demonstrates that nanopore sequencing can detect episignatures in developmental disorders, matching microarray results and identifying pathogenic variants.

Sanger validation of WGS variants - when to?

This study evaluates concordance between whole genome sequencing variants and Sanger validation to establish thresholds for high-quality variant filtering.

Machine learning of three-dimensional protein structures to predict the functional impacts of genome variation

This paper develops a machine learning method using protein structures to predict the functional impacts of genetic variants on transcriptional pathways of Nrf2 and c-MYC.

A variant prioritization tool leveraging multiple instance learning for rare Mendelian disease genomic testing

This paper introduces a deep learning model using multiple instance learning and learning to rank to prioritize variants in rare Mendelian disease genomic testing, achieving high accuracy in identifying disease-causing variants.

FiTMuSiC: Leveraging structural and (co)evolutionary data for protein fitness prediction

FiTMuSiC predicts protein fitness effects using structural and coevolutionary data, achieving high accuracy and providing mechanistic insights through functional and structural scores.

Lethal phenotypes in Mendelian disorders

This paper curates human essential genes based on lethality in Mendelian disorders and explores their relationships with constraint metrics and viability data.

VarPPUD: Variant post prioritization developed for undiagnosed genetic disorders

VarPPUD improves the prioritization of pathogenic variants in undiagnosed genetic disorders by distinguishing likely from unlikely disease-causing variants using machine learning.

The landscape of regional missense mutational intolerance quantified from 730,947 exomes

The paper quantifies regional missense mutational intolerance using 730,947 exomes to identify constrained gene regions and improve variant interpretation.

DNA binding analysis of rare variants in homeodomains reveals novel homeodomain specificity-determining residues

The paper analyzes DNA binding effects of 92 human homeodomain mutants, identifying 14 novel specificity-determining residues and highlighting limitations of variant effect prediction tools.

VariPred: Enhancing Pathogenicity Prediction of Missense Variants Using Protein Language Models

VariPred uses a protein language model to predict missense variant pathogenicity, outperforming existing methods on the ClinVar dataset.

Exome copy number variant detection, analysis and classification in a large cohort of families with undiagnosed rare genetic disease

The paper detects and classifies copy number variants in exome data from 6,633 families, identifying causal CNVs in 173 families and improving classification standards.

DrivR-Base: A Feature Extraction Toolkit For Variant Effect Prediction Model Construction

DrivR-Base extracts and integrates molecular features for variant effect prediction models using data from AlphaFold, ENCODE, and Variant Effect Predictor.

Clinical application of Complete Long Read genome sequencing identifies a 16kb intragenic duplication in EHMT1 in a patient with suspected Kleefstra syndrome

The paper applies complete long read sequencing to undiagnosed patients, identifying a 16kb intragenic duplication in EHMT1 causing Kleefstra syndrome.

When rare meets common: Treatable genetic diseases are enriched in the general psychiatric population

This study identifies a four-fold enrichment of treatable genetic disorders in psychiatric patients compared to the general population through targeted sequencing of 129 genes.

A comparative medical genomics approach may facilitate the interpretation of rare missense variation

The paper compares pathogenicity features of missense variants in non-human livestock to human genomic data, finding higher odds of pathogenic classification in cross-species variants.

Mapping structural variants to rare disease genes using long-read whole genome sequencing and trait-relevant polygenic scores

The paper uses long-read whole genome sequencing and polygenic scores to identify structural variants linked to rare diseases and prioritize candidate genes for functional validation.

Closing the gap: Solving complex medically relevant genes at scale

The paper introduces a targeted sequencing framework, TADGP, that accurately calls variants in complex medically relevant genes at lower cost than HiFi-WGS, enabling scalable analysis of dark genomic regions.

Universal Exome Sequencing in Critically Ill Adults: A Diagnostic Yield of 25% and Race-Based Disparities in Access to Genetic Testing

This study finds that universal exome sequencing in critically ill adults yields a 25% diagnostic rate and highlights race-based disparities in genetic diagnosis documentation.

Leveraging cancer mutation data to predict the pathogenicity of germline missense variants

This study uses cancer mutation data and machine learning to predict the pathogenicity of germline missense variants, showing strong performance in identifying disease-causing variants.

Cerebral Visual Impairment: genetic diagnoses and phenotypic associations

This study identifies genetic variants associated with cerebral visual impairment (CVI) in two cohorts and highlights phenotypic associations with neurodevelopmental disorders.

Automated Identification of Germline de novo Mutations in Family Trios: A Consensus-Based Informatic Approach

This paper presents an informatic method to identify germline de novo mutations in family trios using consensus across variant callers, achieving high precision and recall.

Medically relevant tandem repeats in nanopore sequencing of control cohorts

The paper introduces PathSTR, a tool for analyzing tandem repeats using long-read sequencing, and demonstrates its application in a Myotonic Dystrophy type 1 case.

The performance of AlphaMissense to identify genes causing disease

This study evaluates AlphaMissense's impact on gene-based testing for disease causation using UK Biobank exome data, finding no significant improvement in identifying disease-causing genes.

Bioinformatic analysis of human ZPR1 gene pathogenic exome mutation

The paper analyzes ZPR1 exome variants using computational methods to assess their pathogenicity and identifies ethnic differences in variant frequency.

AutoGVP: a dockerized workflow integrating ClinVar and InterVar germline sequence variant classification

AutoGVP classifies germline variants using ClinVar and modified InterVar criteria, enabling large-scale variant pathogenicity assessment in research.

The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities

The paper analyzes pathogenic variant frequencies in the All of Us cohort by ancestry, revealing disparities and potential biases in genomic data.

Mimicking Human EED Variants in Drosophila: A Promising Strategy to Analyze Human EED Variant Function

The paper uses Drosophila to functionally assess human EED variants, showing that pathogenic variants cause loss of function while benign variants function normally.

A rare splice-site variant in cardiac troponin-T (TNNT2): The need for ancestral diversity in genomic reference datasets

The paper reports a rare splice-site variant in TNNT2 found in Oceanian ancestry individuals, highlighting the need for diverse genomic datasets to avoid misclassification of variants.

WEGS: a cost-effective sequencing method for genetic studies combining high-depth whole exome and low-depth whole genome

WEGS combines low-depth whole genome and high-depth whole exome sequencing to reduce costs while maintaining variant detection accuracy in genetic studies.