Jason Ernst

About

Jason Ernst is a Professor of Biological Chemistry, Computer Science, and Computational Medicine at UCLA Samueli School of Engineering. His research interests include computational biology, bioinformatics, and machine learning. He is involved in advancing understanding and development of computational methods in biological and medical sciences, contributing to the fields through his work and publications. His lab, the Ernst Lab, focuses on these areas, and he maintains a professional presence online through his lab's website.

Research topics

• Genetics
• Evolutionary biology
• Biology
• Computational biology

Selected publications

• Universal DNA methylation age across mammalian tissues

  Nature Aging · 2023 · 372 citations

  Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mo…

  PublisherOA PDFDOI

• A mammalian methylation array for profiling methylation levels at conserved sequences

  Nature Communications · 2022 · 212 citations

  Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We ann…

  DOI

• Universal DNA methylation age across mammalian tissues

  bioRxiv (Cold Spring Harbor Laboratory) · 2021 · 149 citations

  ABSTRACT Aging is often perceived as a degenerative process resulting from random accrual of cellular damage over time. Despite this, age can be accurately estimated by epigenetic clocks based on DNA methylation profiles from almost any tissue of the body. Since such pan-tissue epigenetic clocks have been successfully developed for several different species, we hypothesized that one can build pan-mammalian clocks that measure age in all mammalian species. To address this, we generated data using…

  DOI

• DNA methylation networks underlying mammalian traits

  Science · 2023 · 129 citations

  subclass homeobox genes and developmental processes and is potentially regulated by pluripotency transcription factors. The methylation state of some modules responds to perturbations such as caloric restriction, ablation of growth hormone receptors, consumption of high-fat diets, and expression of Yamanaka factors. This study reveals an intertwined evolution of the genome and epigenome that mediates the biological characteristics and traits of different mammalian species.

  PublisherOA PDFDOI

• Distinct mismatch-repair complex genes set neuronal CAG-repeat expansion rate to drive selective pathogenesis in HD mice

  Cell · 2025-02-11 · 47 citations

  articleOpen access

  Huntington's disease (HD) modifiers include mismatch-repair (MMR) genes, but their connections to neuronal pathogenesis remain unclear. Here, we genetically tested 9 HD genome-wide association study (GWAS)/MMR genes in mutant Huntingtin (mHtt) mice with 140 inherited CAG repeats (Q140). Knockout (KO) of genes encoding a distinct MMR complex either strongly (Msh3 and Pms1) or moderately (Msh2 and Mlh1) rescues phenotypes with early onset in striatal medium-spiny neurons (MSNs) and late onset in t…

  PublisherDOI

Recent grants

• Postdoctoral Research Fellowships in Biology for FY 2009

  NSF · $123k · 2009–2011

• Deciphering the Relationship between Substance Use and Psychiatric Disorders from Whole Genome Sequencing Data

  NIH · $2.3M · 2017–2024

• CAREER: Expanding the Dimensions of Computational Epigenomic Modeling and Analysis

  NSF · $991k · 2013–2019

Frequent coauthors

• Manolis Kellis

  Massachusetts Institute of Technology

  74 shared

• Petko Fiziev

  Illumina (United States)

  42 shared

• Ha Vu

  University of California, Los Angeles

  33 shared

• Steve Horvath

  University of California, San Diego

  32 shared

• Pouya Kheradpour

  26 shared

• Julie A. Mattison

  National Institutes of Health

  24 shared

• Kathrin Plath

  21 shared

• B Bernstein

  Broad Institute

  21 shared

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