Genomics and Rare Diseases

RAGE protein: COPD biomarker and case study for variant pathogenicity prediction

The paper uses RAGE as a case study to demonstrate how structural biology and variant databases can inform pathogenicity prediction, highlighting challenges in interpreting variant effects.

Integrating AlphaFold2 Models and Clinical Data to Improve the Assessment of Short Linear Motifs (SLiMs) and Their Variants' Pathogenicity

This paper improves SLiM variant pathogenicity assessment by integrating AlphaFold2-generated structures into MotSASi, enhancing prediction accuracy over existing tools.

Interpreting the Effects of DNA Polymerase Variants at the Structural Level Using MAVISp and Molecular Dynamics Simulations

The paper uses MAVISp and molecular dynamics simulations to analyze DNA polymerase variants, classifying VUS and predicting functional consequences of POLE and POLD1 variants.

Analysis of Premature Termination Codons Predicted to Escape Nonsense Mediated Decay Identifies Novel Genes, Pathways, and Networks Contributing to an Oligogenic Etiology of Congenital Heart Disease

The paper analyzes PTCs in CHD patients to identify genes and pathways contributing to an oligogenic etiology of congenital heart disease.

A structure-based tool to interpret the significance of kinase mutations in clinical next generation sequencing in cancer

The paper develops a structure-based tool to evaluate kinase mutations in cancer by aligning them with known activating mutations using structural and functional data.

varCADD: large sets of standing genetic variation enable genome-wide pathogenicity prediction

The paper introduces varCADD, a method using standing genetic variation to predict variant pathogenicity, showing improved accuracy over existing tools in certain genomic regions.

The performance of in silico prediction tools for variant curation in a panel of cancer genes.

This study evaluates in silico variant prediction tools for cancer genes, finding gene-specific performance issues and recommending validation for individual genes.

Enhancing Clinical Classification of Protein Variants using ESM2 and UMAP

This paper improves the classification of uncertain protein variants using ESM2 and UMAP for better variant prioritization in precision medicine.

Comparative analysis of WGS and WES for genetic diagnosis in a pediatric Albanian population.

This study compares whole-genome sequencing (WGS) and whole-exome sequencing (WES) in a pediatric Albanian population, finding WGS more effective in diagnosing rare genetic disorders and identifying complex variants.

Developing best practice rare disease diagnostic care models in a real-world rural/regional setting

The paper identifies challenges in rare disease diagnosis in Tasmania through stakeholder consultations and suggests establishing a Rare Care Centre to improve care.

Disease-associated genetic variants can cause mutations in tissue-specific protein isoforms

The paper shows that disease-associated variants in alternative protein isoforms can cause structural mutations, emphasizing the need to consider tissue-specific expression and full-length transcripts in variant interpretation.

A knowledge-based distance metric highlights underperformance of variant effect predictors on gain-of-function missense variants

This paper introduces SPDV, a spatial distance metric that outperforms half of existing variant effect predictors in identifying dominant disease variants, particularly for gain-of-function missense variants.

Variant Scientists in Genomic Medicine: Survey of Demographics, Training, Duties, and Professional Development

The paper surveys Variant Scientists in clinical genomics labs, finding they are predominantly female, highly educated, and involved in diverse tasks with adequate employer support but lacking professional recognition.

Missense3D-PTMdb an interactive web resource to explore and visualize genetic variants and post-translational modifications sites (PTMs) using AlphaFold 3D models

Missense3D-PTMdb maps missense variants and PTM sites to AlphaFold 3D models to explore their structural and functional impacts.

Characteristics predicting reduced penetrance variants in the high-risk cancer predisposition gene TP53

The paper identifies characteristics of TP53 variants with reduced penetrance using ClinVar data and a random forest model, finding they have intermediate function, higher frequency, and delayed disease onset.

Assessment of the variant prioritisation strategy for genomic newborn screening in the Generation Study

The paper assesses an automated variant prioritisation strategy for genomic newborn screening in the Generation Study, finding that 3-5% of samples require manual review and <1% need confirmatory testing.

Aberrant splicing prediction during human organ development

The paper improves aberrant splicing variant prediction across developmental stages and identifies developmentally restricted variants linked to neurodevelopmental disorders.

Extracting and calibrating evidence of variant pathogenicity from population biobank data

The paper uses population biobank data to identify and calibrate evidence of variant pathogenicity for 41 genes, finding that 2.6% of participants have rare variants with moderate or stronger evidence of pathogenicity.

Comprehensively Testing the Function of Missense Variation in the STK11 Tumour Suppressor

This study functionally tests STK11 missense variants in mammalian cells, identifying pathogenic variants and providing insights for clinical interpretation.

A simple, cost efficient assay for assessing the functional impact of single and multi-gene variant combinations

The paper introduces a cost-effective in vitro assay to assess the functional impact of single and multi-gene variants in obesity, identifying putatively pathogenic variants and digenic combinations.

Pangenome-based identification of cryptic pathogenic variants in undiagnosed rare disease patients

This study uses long-read sequencing and pangenome analysis to identify pathogenic variants in undiagnosed rare disease patients, finding novel mutations and epigenomic changes.

Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants

This paper predicts the pathogenicity of missense variants using graph embeddings of protein structures generated by ESMFold and XGBoost.

The Refined Recurrence Risk of De Novo variants Due to Parental Mosaicism

The paper assesses parental mosaicism in families with de novo variants, finding 4.4% parental mosaicism and proposing amplicon-based sequencing for improved recurrence risk assessment.

Assessing the diagnostic impact of blood transcriptome profiling in a pediatric cohort previously assessed by genome sequencing

This study evaluates how blood transcriptome profiling adds value to genome sequencing in diagnosing rare genetic disorders in a pediatric cohort.

AutoPM3: Enhancing Variant Interpretation via LLM-driven PM3 Evidence Extraction from Scientific Literature

AutoPM3 automates PM3 evidence extraction from scientific literature using LLMs, improving variant interpretation for rare diseases.

Mapping MAVE data for use in human genomics applications

The paper maps MAVE data to human reference sequences to improve variant functional assay utility for genomics applications.

Genetic disease risks of under-represented founder populations in New York City

The paper identifies founder populations in New York City using genomic data and finds 202 likely disease-causing variants enriched in these under-represented groups, many of which are new discoveries.

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases

SHEPHERD uses few-shot learning and a knowledge graph to improve diagnosis of rare genetic diseases using simulated data and real-world patient cohorts.

AdaGenes: A streaming processor for high-throughput annotation and filtering of sequence variant data

AdaGenes processes and filters sequence variant data from WES/WGS efficiently, enabling scalable and interactive analysis for genomics applications.

GOLF: A Generative AI Framework for Pathogenicity Prediction of Myocilin OLF Variants

GOLF predicts the pathogenicity of myocilin OLF domain variants using generative AI and interpretable models, achieving accurate classification of known pathogenic and benign variants.