Juan F Macias-Velasco

This study develops pangenome-based frameworks to analyze DNA methylome variation across diverse human genomes, identifying genetic factors influencing methylation patterns and their associations with complex traits.

The paper analyzes polymorphic transposable elements in human pangenomes to reveal regulatory evolution mechanisms before fixation.

The paper presents a human panepigenome map of DNA methylation, revealing epigenomic diversity across populations and highlighting the role of genetic variation in CpG presence and absence.

Pansoma improves somatic variant calling using pangenome graphs, enhancing accuracy by avoiding reference bias and preserving graph-specific variant representations.

460 haplotypes from 230 genomes, selected to maximize common-variant coverage, capture 99.43% of All of Us common small variants and halve structurally unreliable regions and base errors versus HPRC1.

The paper investigates methylation patterns of polymorphic transposable elements using long-read sequencing and the Human Pangenome Reference, revealing distinct methylation profiles and context-dependent interactions.

The paper uses fully phased telomere-to-telomere assemblies and long-read epigenomes to study centromere genetic and epigenetic dynamics across inheritance and cell-fate transitions, finding positional stability of CDRs and dynamic epigenetic changes.

This paper presents a chromosome-level genome assembly and annotation for the degu, improving contiguity, completeness, and gene annotation compared to previous assemblies.

This study shows that using graph-based pangenomes and inferred donor-specific assemblies improves somatic variant detection compared to GRCh38.

The paper develops a pangenomic method to create a benchmark resource for somatic variant detection using HapMap mixtures, identifying millions of variants across different genomic regions.

The paper investigates how genetic, epigenetic, and environmental factors influence allele-specific gene expression in mice, identifying tissue- and context-dependent patterns and inconsistent ASE biases.

The paper identifies a network of imprinted and non-imprinted genes that propagate parent-of-origin effects on metabolic traits through epistatic interactions in mice.

This study integrates single-cell and bulk RNA sequencing data from SM/J mice to identify β-cell subpopulations and genetic networks linked to obesity and glycemic control.

The paper uses TRAP to analyze allelic translation efficiency imbalance in mouse astrocytes, finding that some genetic variants affect ribosome occupancy independently of transcript abundance.

The paper identifies epistatic gene interactions underlying parent-of-origin effects on metabolic traits in mice using reciprocal crosses and tissue-specific expression analysis.