Genomic variations and chromosomal abnormalities

The paper predicts post-pubertal social behavior variability in a mouse model of paternal 15q11-13 duplication using neonatal social communication and gene expression data.

The paper identifies a human-specific genomic structure formed by a joint segmental duplication that drives transcriptional readthrough and expression fine-tuning of NPEPPS-TBC1D3.

The paper identifies a segmental duplication that drives position effect expression of TBC1D3 in the human brain, explaining its high structural heterozygosity.

This study maps structural variation in coppery titi monkeys using whole-genome sequencing, identifying over 13,000 variants, including disease-associated genes and a high de novo mutation rate.

PSVGT is a framework for population-scale structural variant discovery and genotyping that integrates multiple sequencing data types and outperforms existing tools, especially in complex genomes and low-coverage long-read data.

The paper maps ecDNA structures in glioblastoma using long-read sequencing and ecLego3, revealing structural variation, evolutionary dynamics, and transcriptional links to tumor adaptation.

Wakhan reconstructs chromosome-scale copy number profiles of tumor genomes using long-read sequencing, showing better consistency with data than existing methods.

This study shows NAC treatment improves LgDel 22q11.2 deletion syndrome mouse cortical neurons' growth and connectivity without restoring wild-type gene expression or cell states.

The paper introduces StemCNV-check, a pipeline for assessing genomic integrity in human pluripotent stem cells using SNP array data and CNV scoring.

ecDNAInspector identifies high-confidence ecDNA structures from WGS data, linking them to clinical and molecular features in breast cancer.

The paper presents a benchmark for detecting simple and complex genome inversions using Strand-seq and long-read assemblies, revealing method strengths and limitations across sequencing platforms.

SaVor is a reproducible SV calling workflow tested on Arabidopsis thaliana genomes, showing trade-offs between precision and recall based on merge strategies.

ExactCN improves copy number variation estimation from whole-exome sequencing data using deep learning, achieving better accuracy than existing methods.

CHALLENGER improves CNV detection in challenging genomic regions using short-read WGS data, achieving higher F1-scores and capturing CNVs typically requiring long reads.

Svirlpool detects structural variants from ONT data using local consensus assemblies, achieving high Mendelian consistency and outperforming existing methods in certain metrics.

This study compares two WGA kits for single-cell genome analysis, finding that PTA/ResolveDNA outperforms MDA/REPLI-g in quality metrics and CNV detection.

This study evaluates diploid donor-specific assemblies for improving somatic structural variant detection in cancer genomes, finding they identify more variants and reduce artifacts compared to standard references.

The paper presents haplotype-resolved T2T assemblies of two MZ twins, revealing genomic and epigenetic divergence, including structural variation and DNA methylation differences.

The paper uses long-read genome sequencing and multi-omics data to identify structural variants associated with aging and neurodegenerative diseases, finding that SVs are more likely to be causal than SNVs.

ARCLID is a deep learning-based structural variant caller that achieves high accuracy at low sequencing coverages, outperforming existing tools and enabling cost-effective SV discovery.

The paper analyzes genome-wide human chromosomal inversions, showing their impact on genetic diversity and disease, with distinct evolutionary outcomes based on inversion recurrence.

The paper benchmarks somatic structural variant detection at ultra-low allele fractions using synthetic data and evaluates 12 pipelines, finding long-read sequencing provides higher accuracy than short-read methods.

This study evaluates structural variant callers using long-read sequencing data, showing performance variation based on ground truth, reference genome, and genomic regions.

This paper compares long-read sequencing strategies to resolve complex genotypes at FSHD-associated loci, showing that structural variants arise from intrachromosomal recombination and require high-resolution methods for accurate detection.

The paper develops SVrefiner to refine structural variations, enhancing heritability estimates and risk prediction by integrating refined SVs with SNPs and other variants.

This study investigates the role of small extrachromosomal circular DNA (eccDNA) in colorectal cancer, finding that it contributes to gene expression, immune cell recruitment, and poor patient outcomes.

The paper develops a framework to study variable expressivity in genetic disorders using 16p12.1 deletion models, showing how genetic background and secondary variants influence gene expression and phenotypes.

The paper uses long-read sequencing to analyze de novo mutations in autism families, finding higher mutation rates in repetitive DNA and a paternal bias in postzygotic mutations.

The paper identifies novel CNV loci and dose-dependent gene effects across six psychiatric disorders using genome-wide analysis.

The paper identifies shared and divergent genetic mechanisms across psychiatric disorders using gene-set burden analysis of copy number variants.