Genomics and Rare Diseases

ClinVar and HGMD genomic variant classification accuracy has improved over time, as measured by implied disease burden

The paper assesses improvements in genomic variant classification accuracy over time in ClinVar and HGMD by analyzing misclassification rates in inborn errors of metabolism across ancestry groups.

Deep Mutational Scanning in Disease-related Genes with Saturation Mutagenesis-Reinforced Functional Assays (SMuRF)

This paper introduces SMuRF, a framework for deep mutational scanning in disease-related genes, generating functional scores for all coding variants and aiding in variant interpretation.

The NYCKidSeq randomized controlled trial: Impact of GUIA digitally enhanced genetic counseling in racially and ethnically diverse families

The paper evaluates the impact of GUIA, a digital genetic counseling tool, on understanding of genetic test results in diverse families, finding improved understanding in the intervention group.

RNA-sequencing first approach generates new diagnostic candidates in Mendelian disorders

This study uses RNA-sequencing to identify novel diagnoses in Mendelian disorders by detecting aberrant splicing and expression abnormalities, particularly in patients without candidate sequence variants.

A SYSTEMATIC RE-ANALYSIS OF COPY NUMBER LOSSES OF UNCERTAIN CLINICAL SIGNIFICANCE

The paper re-analyzes clinical aCGH data to identify pathogenic copy number losses, finding that 7.2% of class 3 variants were reclassified as pathogenic or likely pathogenic.

A systematic assessment of the impact of rare canonical splice site variants on splicing using functional and in silico methods

The paper assesses the impact of rare canonical splice site variants on splicing using functional and in silico methods, finding that 24% of variants do not cause loss-of-function.

Combination of Expert Guidelines-based and MachineLearning-based Approaches Leads to Superior Accuracy ofAutomated Prediction of Clinical Effect of Copy Number Variations

The paper combines expert guideline-based and machine learning approaches to improve automated prediction of the clinical effect of copy number variations.

Non-coding variants are a rare cause of recessive developmental disorders in trans with coding variants

The paper identifies non-coding variants in trans with coding variants in patients with developmental disorders, finding them to be a rare cause of recessive disorders.

A Novel Autosomal Dominant Childhood-Onset Disorder Associated with Pathogenic Variants in VCP

The paper identifies novel VCP variants causing a childhood-onset neurodevelopmental disorder through exome sequencing and functional analysis.

Clinical genome sequencing: three years experience at a tertiary childrens hospital

This study evaluates clinical genome sequencing (GS) over three years at a children's hospital, finding a 35% diagnostic yield and frequent misordering, with higher yields in patients without prior exome sequencing.

Updated benchmarking of variant effect predictors using deep mutational scanning

This study benchmarks 55 variant effect predictors using deep mutational scanning data from 26 human proteins, finding that unsupervised methods like EVE and ESM-1v perform best, while supervised methods like VARITY show improved handling of data circularity.

Carrier Frequencies Estimation of Pathogenic Variants of Autosomal Recessive and X-linked Recessive Mendelian Disorders using exome sequencing data in 1,642 Thais

The paper estimates carrier frequencies of pathogenic variants in 113 ACMG-recommended genes using exome sequencing data from 1,642 Thai individuals, finding high carrier rates for several disorders.

Neuropathy target esterase activity predicts retinopathy among PNPLA6 disorders

The paper identifies NTE activity as a biomarker for retinopathy and endocrinopathy in PNPLA6 disorders, using clinical and preclinical data to establish a genotype-activity-phenotype relationship.

SPRI: Structure-Based Pathogenicity Relationship Identifier for Predicting Effects of Single Missense Variants and Discovery of Higher-Order Cancer Susceptibility Clusters of Mutations

SPRI predicts the pathogenicity of missense variants and identifies spatially organized mutational clusters linked to cancer and Mendelian diseases.

The landscape of tolerated genetic variation in humans and primates

The paper uses primate genetic data to predict human variant pathogenicity with a deep learning classifier trained on 4.3 million common missense variants.

Discordant calls across genotype discovery approaches elucidate variants with systematic errors

The paper identifies discordant genotype calls across sequencing methods in gnomAD, provides a blacklist of problematic variants, and introduces a classifier to detect such variants in other datasets.

Buffering of genetic dominance by allele-specific protein complex assembly

The paper shows that cotranslational protein complex assembly is less common for subunits with dominant-negative mutations and develops a model to predict such mutations.

Pangenome graphs improve the analysis of rare genetic diseases

The paper uses pangenome graphs to improve detection of rare structural variants in a rare disease cohort, identifying novel diagnostic variants.

Functional clustering of splice-altering variants in whole genome sequencing data reveals hidden heritability in rare variant disorder

SpliPath identifies pathogenic splice-altering variants in ALS by integrating SpliceAI predictions with transcriptomics data, revealing hidden heritability in rare variant disorders.

Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of multiple cardiovascular disease risk factors

A comprehensive workflow for target adaptive sampling long-read sequencing applied to hereditary cancer patient genomes

This study develops a computational workflow for target adaptive sampling long-read sequencing and applies it to hereditary cancer genomes to identify genetic variants and epigenetic changes.

Correspondence between functional scores from deep mutational scans and predicted effects on protein stability

The paper compares protein stability predictors with DMS-derived functional scores, finding FoldX and Rosetta show strong correlations, especially when considering intermolecular interactions.

A tissue-aware machine learning framework enhances the mechanistic understanding and genetic diagnosis of Mendelian and rare diseases

This paper introduces a tissue-aware machine learning framework to improve understanding and diagnosis of Mendelian and rare diseases by leveraging tissue-specific gene mechanisms.

Estimating clinical risk in gene regions from population sequencing cohort data

The paper introduces REGatta, a method to estimate clinical risk in gene regions using population sequencing data, identifying significant risk differences in breast cancer genes for rare missense variants.

Challenges in screening for de novo noncoding variants contributing to genetically complex phenotypes

The paper investigates why studies fail to find associations between de novo noncoding variants and complex disorders like ASD, identifying annotation quality and variant reliability as key issues.

Functional filter for whole genome sequence data identifies stress impact, non-coding, alternate polyadenylation site variants >5kb from coding DNA

GROFFFY filters whole genome sequence data to identify non-coding and polyadenylation site variants, improving detection of disease-causing variants in unsolved cases.

A deep catalog of protein-coding variation in 985,830 individuals

This paper presents the largest catalog of human protein-coding variation from 985,830 individuals, identifying rare variants and their functional implications for precision medicine.

High-throughput deep learning variant effect prediction with Sequence UNET

This paper introduces Sequence UNET, a deep learning model for variant effect prediction that is highly scalable and computationally efficient, achieving comparable performance to existing methods on ClinVar data.

Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing

The paper identifies clinically relevant variants in poison exons (PEs) that improve diagnostic yield for neurodevelopmental disorders by uncovering variants previously overlooked in standard analyses.

Molecular diagnostic yield of genome sequencing versus targeted gene panel testing in racially and ethnically diverse pediatric patients

This study compares the diagnostic yield of genome sequencing and targeted gene panel testing in diverse pediatric patients, finding higher yields with genome sequencing in most groups but not all.