Jeffrey M. Kidd

This study uses Ancestral Recombination Graphs to identify 285 outlier loci in dogs showing signs of selection, enriched near genes linked to domestication.

The paper estimates retrotransposition rates in dogs using genome assembly comparisons, finding higher SINEC rates than human Alu elements but LINE-1 rates within human ranges.

This study shows that HIV-1 silencing in polyclonal cell populations arises from clone-specific behaviors, not uniform repression, with many clones maintaining stable bimodal expression over time.

The paper infers fine-scale recombination maps in dogs using the canFam4 assembly and shows strong correlations with previous maps.

The paper integrates long-read and short-read data to analyze structural variation in canines, identifying new variants and selection signatures.

The paper characterizes nuclear mitochondrial insertions (Numts) in canine genome assemblies, identifying their distribution, evolutionary history, and population variation.

The paper analyzes allele sharing among wolves, village dogs, and breed dogs using GeoVar, finding significant genetic variation and shared variants across these groups.

The paper reanalyzes canine genetic data using a Greenland wolf outgroup reference to reduce bias, revealing population size changes in village dogs.

The paper analyzes duplication content in nine canine genome assemblies, finding high rates of retrocopies and highlighting issues with assembly accuracy.

The paper shows HeLa strains differ in Alu retrotransposition efficiency, with distinct mechanisms for SINE RNA mobilization involving ORF2p.

The paper identifies and validates copy number variants in single human neurons using a new method, revealing nonrandom CNV locations and complex karyotypes in a subset of neurons.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper presents an improved long-read assembly of the dog reference genome, significantly enhancing contiguity and gene annotation.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

The paper assembles a Great Dane genome using long-read sequencing, revealing improvements over the Boxer-derived reference and highlighting retrotransposon activity in canine genetic variation.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

TypeTE improves Alu insertion genotype accuracy from 83% to 92% in the 1000 Genomes dataset by reassembling and re-mapping sequencing data.

The paper analyzes whole genome sequences of canids to trace the origin and recent expansion of an active gammaretroviral lineage, identifying new insertions and polymorphisms across multiple species.

This study sequenced ancient dog genomes from the Neolithic period in Europe, finding continuity with modern dogs and rejecting a population replacement model and dual origins hypothesis for dog domestication.

SVelter reconstructs complex structural genomic rearrangements by iteratively rearranging genome regions and scoring them against sequencing data.

This study uses whole genome sequences from gorillas to infer demographic history and selective sweeps, finding population expansions and contractions and signatures of positive selection in specific biological processes.