Genomic variations and chromosomal abnormalities

LEVIATHAN is a structural variant caller that improves scalability and applicability across organisms using Linked-Reads data.

The paper investigates how gene expression changes from a 16p12.1 deletion and second-hit variants contribute to phenotypic variability in developmental delay.

The paper analyzes structural variation in inbred mouse strains to identify genetic factors associated with autism-related traits.

This study identifies de novo and polymorphic retrotransposon insertions in ASD families, finding increased exonic and intronic insertions in ASD cases compared to controls.

The paper reports a comprehensive map of 36,699 non-reference mobile element insertions (MEIs) from 5,675 human genomes and builds a database for public use.

The paper uses Drosophila deficiency lines to analyze multigenic deletions and their implications in human diseases related to epithelial morphogenesis and cytoskeletal processes.

This study evaluates optical genome mapping's ability to detect chromosomal variants in MDS patients, showing high concordance with standard methods and identifying additional clinically relevant aberrations.

The paper analyzes whole genome sequences from OSCC-GB patients to detect NUMTs but finds no somatic NUMTs confirmed by PCR and no germline NUMTs specific to OSCC-GB.

The paper investigates the inter- and intra-species variability of LCR22s in non-human primates and finds that LCR22 expansions are unique to humans.

The paper introduces CTLR-Seq, a method to resolve complex genomic regions with high accuracy, and applies it to study CNVs associated with schizophrenia and autism.

This study shows that the 3q29 deletion causes sex-specific metabolic changes in mice, which are not linked to behavioral issues, and that a high-fat diet can improve weight in females without worsening behavior.

The paper identifies DNA sequences associated with TOP2 poisoning that are linked to genetic variations contributing to multiple diseases.

The paper identifies dispersed duplications and de novo structural mutations using whole-genome sequencing data from 706 families by analyzing IBD relationships and copy number variations.

The paper analyzes chromoanagenesis breakpoints in constitutional and cancer cases, finding enrichment in late-replicating chromatin and suggesting similar mechanisms for both.

This study evaluates high-resolution optical mapping for detecting chromosomal aberrations in 85 samples, achieving 100% concordance with standard tests for non-centromeric breakpoints.

GRIDSS2 identifies somatic structural variants by analyzing single breakends and phasing, achieving a 3.1% false negative rate in metastatic cancers and uncovering a novel duplication signature.

The paper investigates the correlation between 45S and 5S rDNA copy numbers in humans and finds no meaningful correlation, challenging previous claims of concerted variation.

The paper compares structural variant detection using short-read and long-read sequencing in three trios, showing lrWGS finds more SVs but srWGS has high concordance in non-repetitive regions.

This paper develops a yeast experimental system to study meiotic NAHR and CNV formation, finding that larger LCRs increase CNV frequency and interhomolog NAHR is overrepresented.

The paper integrates genetic, transcriptomic, and clinical data to identify CNV gene associations with brain-related and health traits, finding pleiotropy and multigenicity in CNV biology.

This paper develops Samplot-ML, a CNN that reduces false positives in structural variant detection by 47% while retaining 97% of true positives using visualization-based training.

DECoNT improves CNV detection accuracy on WES data by learning from matched WES and WGS data, tripling duplication precision and doubling deletion precision.

The paper catalogs structural variants across 19,652 genomes and identifies their associations with proteomic measurements and disease phenotypes.

The paper presents a high-throughput optical mapping technique to genotype structural variation in segmental duplications, identifying novel variants and refining breakpoints in microdeletion syndromes across diverse populations.

The paper introduces a structural variant calling pipeline called BioGraph, which achieves higher sensitivity for detecting SVs compared to existing pipelines, though with lower precision.

The paper generates 65 hiPSC clones with 16p11.2 CNVs and identifies transcriptional changes in neural development using RNA-Seq.

This study quantifies non-allelic homologous recombination (NAHR) frequency at the Xq28 inversion site using digital PCR, finding a higher rate than previously believed.

This study benchmarks WGS-based structural variant callers using a PCR-confirmed gold standard, finding wide performance variation and identifying tools best suited for low and ultra-low pass data.

The paper examines the effects of neuropsychiatric CNVs on brain structure using neuroimaging data and identifies shared anatomical patterns across multiple CNVs.