Genomics and Rare Diseases

Systematic analysis and prediction of genes associated with disorders on chromosome X

The paper systematically analyzes chrX genes to predict disease associations, identifying 235 genes likely involved in disorders and reporting damaging variants in CDK16 and TRPC5 in patients with intellectual disability or autism.

Informing Variant Assessment using Structured Evidence from Prior Classifications (PS1, PM5, and PVS1 Sequence Variant Interpretation Criteria)

The paper uses prior ClinVar variant classifications to inform ACMG/AMP variant interpretation by identifying SNVs with similar functional consequences to pathogenic variants.

Evaluation of in silico pathogenicity prediction tools for the classification of small in-frame indels

The paper evaluates nine in silico pathogenicity prediction tools for small in-frame indels using a dataset from gnomAD, ClinVar, and DDD, finding VEST-indel performs best with AUCs of 0.93 and 0.87.

In Silico Analysis of Novel VHL Germline Mutations in Iranian RCH Patients

The paper reports three novel VHL germline mutations in Iranian RCH patients and analyzes their impact on pVHL structure and function using in silico methods.

PhenoScore: AI-based phenomics to quantify rare disease and genetic variation

PhenoScore quantifies phenotypic similarity using AI and HPO data to improve genetic variant interpretation and genotype-phenotype studies.

SUsPECT: A pipeline for variant effect prediction based on custom long-read transcriptomes for improved clinical variant annotation

SUsPECT improves variant annotation by using custom long-read transcriptomes to better predict variant effects in clinical settings.

Meta-analysis of genotype-phenotype associations in Alström syndrome.

This study performs a meta-analysis of genotype-phenotype associations in Alström syndrome, finding that mutations in exon 10 are linked to higher liver disease prevalence.

Some Mendelian Disorders could be fixed with a pill? A Structural Bioinformatic investigation

The paper investigates Gly mutations in Mendelian disorders using ClinVar data, finding that bulky hydrophobic amino acid substitutions reduce protein stability and that Gly mutations may create binding pockets targetable for drug development.

The penetrance of age-related monogenic disease depends on ascertainment context

The paper estimates penetrance of monogenic diabetes variants across different ascertainment contexts, finding age-related variability for HNF1A/HNF4A variants but consistent penetrance for GCK variants.

The Cancermuts software package for the prioritization of missense cancer variants: a case study of AMBRA1 in melanoma

The paper introduces Cancermuts, a Python tool for prioritizing missense cancer variants, and validates its predictions on AMBRA1 mutations in melanoma.

FAVOR: Functional Annotation of Variants Online Resource and Annotator for Variation across the Human Genome

FAVOR provides an online resource and tool for functional annotation of variants from whole genome sequencing studies to aid in disease gene prioritization.

E-SNPs&GO: Embedding of protein sequence and function improves the annotation of pathogenic variants.

E-SNPs&GO improves pathogenic variant annotation by embedding protein sequences and function, achieving a MCC score of 0.71 on a blind test set.

Mendelian gene identification through mouse embryo viability screening

The paper identifies novel Mendelian genes by analyzing mouse embryo lethality and linking them to human disease phenotypes and genetic variants.

Disease-causing variant recommendation system for clinical genome interpretation with adjusted scores for artefactual variants

The paper develops a system that integrates variant quality control into prioritization to improve the accuracy of identifying disease-causing variants in rare disorders.

SPECIFICATIONS OF THE ACMG/AMP VARIANT CURATION GUIDELINES FOR MYOCILIN: RECOMMENDATIONS FROM THE CLINGEN GLAUCOMA EXPERT PANEL

The paper adapts ACMG/AMP variant curation guidelines for the myocilin gene, leading to changes in variant classification for 38% of tested variants.

Cost and Clinical Utility of WES and WGS in pediatric patients with suspected genetic disease

This study reviews the cost and clinical utility of whole exome sequencing (WES) and whole genome sequencing (WGS) in pediatric genetic disease diagnosis, finding limited evidence of WGS superiority over WES in changing clinical management.

MetaRNN: Differentiating Rare Pathogenic and Rare Benign Missense SNVs and InDels Using Deep Learning

This paper introduces MetaRNN and MetaRNN-indel, deep learning models that differentiate rare pathogenic from benign variants, outperforming existing methods and providing interpretable scores.

Understanding molecular mechanisms and predicting phenotypic effects of pathogenic tubulin mutations

The paper investigates tubulin mutations' molecular mechanisms and their phenotypic effects, finding that current computational methods poorly predict their pathogenicity due to dominant-negative and gain-of-function mechanisms.

A novel syndrome caused by the constitutional gain-of-function variant p.Glu1099Lys in NSD2

The paper identifies a novel syndrome caused by the gain-of-function variant p.Glu1099Lys in NSD2, leading to distinct clinical features compared to loss-of-function variants.

The variant catalogue pipeline: A workflow to generate a background variant library from Whole Genome Sequences

The paper introduces a variant catalogue pipeline to generate high-quality variant libraries from whole genome sequences, applied to 100 human genomes to improve variant cataloguing for diverse populations.

Protein Language Model Predicts Mutation Pathogenicity and Clinical Prognosis

This study shows that pre-trained protein language models can predict mutation pathogenicity and patient survival in cancer, outperforming existing methods.

Sequencing individual genomes with recurrent genomic disorder deletions: an approach to characterize genes for autosomal recessive rare disease traits

The paper demonstrates that recurrent genomic deletions mediated by nonallelic homologous recombination drive recessive disease burden and identifies new disease-contributing variants through exome reanalysis.

Learning with phenotypic similarity improves the prediction of functional effects of missense variants in voltage-gated sodium channels

The paper develops a machine learning framework that uses phenotypic similarity to predict the functional effects of missense variants in voltage-gated sodium channels, achieving high accuracy and robustness.

Overcoming the pitfalls of NGS-based molecular diagnosis of Shwachman-Diamond syndrome

The paper introduces HapICE, a method to improve variant detection in SBDS using NGS, achieving higher diagnostic accuracy than conventional methods.

Exome sequencing as a first-tier test for copy number variant detection : retrospective evaluation and prospective screening in 2418 cases.

This paper evaluates exome sequencing as an alternative to chromosomal microarray for detecting copy number variants in rare disorders, showing improved diagnostic yield in prospective cases.

GenOtoScope: Towards automating ACMG classification of variants associated with congenital hearing loss

GenOtoScope automates ACMG/AMP variant classification for congenital hearing loss, achieving higher accuracy and precision than existing tools.

Low-coverage genome sequencing for the detection of clinically relevant copy-number and mtDNA variants

This study evaluates if low-coverage genome sequencing can detect clinically relevant copy-number and mtDNA variants, finding that 2x coverage is sufficient for most cases.

Prevalence Estimates of Putatively Pathogenic Leptin Variants in the gnomAD Database

The paper estimates the prevalence of putatively pathogenic leptin variants in the gnomAD database, finding low frequencies with higher risk in South Asian populations.

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score

RAVA-FIRST improves rare variant association testing in whole-genome data by using functionally-informed testing units and filtering, identifying a novel intergenic region linked to venous thromboembolism.

Exome re-analysis driven by deep phenotyping increases diagnostic yield

Re-analyzing negative exome sequencing data with deep phenotyping identifies pathogenic variants in two patients with suspected Mendelian diseases.