Jackson Laboratory

The Dumont Lab

Principal Investigator: Beth Dumont, Ph.D.

The Jackson Laboratory
Bar Harbor, ME

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Researching the mechanisms that generate genetic diversity through the lens of evolution

Our Research Focus

The broad objective of my research program is to understand the causes and consequences of variation in the cellular mechanisms that govern DNA inheritance: genetic recombination, chromosome segregation, and de novo mutation. To date, my work has combined wet-bench and computational approaches in multiple mammalian model systems to investigate variation in two recombination mechanisms, crossing-over and gene conversion. Over the next several years, my research group will work at the leading edge of genomics, evolutionary genetics, and cytogenetics to advance our understanding of recombination rate variation from diverse biological perspectives.

Full Scientific Report

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Open Positions

Job	Job Title	Location	Description

Lab Staff

Uma Arora

PhD Student

Investigating the composition and diversity of centromeric sequence amongst Mus musculus subspecies and autosomes vs sex chromosomes to understand their significance in evolution.
Laura Blanco-Berdugo, MS

Research Assistant II

Interested in genetic diversity and evolution of wild and wild-derived mice
Beth Dumont, Ph.D.

Assistant Professor

Researching the mechanisms that generate genetic diversity through the lens of evolution
Brett Haines, B.S.

Research Assistant

Developing novel CRISPR protocols to isolate and sequence recalcitrant regions of the genome.
Raman Akinyanju Lawal, Ph.D.

Postdoctoral Associate

Unraveling the evolutionary forces that give rise to the observed genetic diversity in the house mouse
Glenn Smallidge

Research Administrative Assistant II

Provide Research Administrative Support for several faculty members.
Lydia Wooldridge, Ph.D.

Postdoctoral Associate

To study the evolution of genes related to fertility and sexual reproduction, and to use this information to understand infertility in humans.

Selected Publications

Highlighted Abstract

Knowledge of the rate and pattern of new mutation is critical to the understanding of human disease and evolution. We used extensive autozygosity in a genealogically well-defined population of Hutterites to estimate the human sequence mutation rate over multiple generations. We sequenced whole genomes from 5 parent-offspring trios and identified 44 segments of autozygosity. Using the number of meioses separating each pair of autozygous alleles and the 72 validated heterozygous single-nucleotide variants (SNVs) from 512 Mb of autozygous DNA, we obtained an SNV mutation rate of 1.20 × 10(-8) (95% confidence interval 0.89-1.43 × 10(-8)) mutations per base pair per generation. The mutation rate for bases within CpG dinucleotides (9.72 × 10(-8)) was 9.5-fold that of non-CpG bases, and there was strong evidence (P = 2.67 × 10(-4)) for a paternal bias in the origin of new mutations (85% paternal). We observed a non-uniform distribution of heterozygous SNVs (both newly identified and known) in the autozygous segments (P = 0.001), which is suggestive of mutational hotspots or sites of long-range gene conversion.

View full list of publications

Blog PostMarch 01, 2021
When should you seek clinical confirmation of consumer genomic test results?
For many, testing provides a window into their innermost self, their genome, and a new way to learn about themselves.
Tech CornerFebruary 01, 2021
New coronavirus variants spark concerns
Mutations in SARS-CoV-2 are generating viral variants that change the properties of the virus and affect the response to the COVID-19 pandemic.
Tech CornerFebruary 01, 2021
Machine learning: Shining a light on genomic function
Machine learning platforms can be fed data to "teach" them to learn patterns and predict outcomes, and they are becoming more important all the time in biomedical research. But what are they? How do they work? And can we peer into the black box of their inner functions to make them more powerful for prediction and discovery?
Research HighlightJanuary 12, 2021
Few mutations, important difference in cancer cells
JAX Professor Sheng Li, Ph.D., presents a tool, epihet, that automates the epigenetic analysis of AML cells. epihet allows researchers to assess epigenetic differences between cells, identify genomic locations where the differences occur, and associate cellular epigenetic profiles with cancer-related biological function.

Press ReleaseFebruary 25, 2021
A new reference for global genomic diversity
Exactly 20 years after the successful completion of the "Human Genome Project," an international group of researchers, the Human Genome Structural Variation Consortium (HGSVC), has now sequenced 32 human genomes at high resolution.
Research HighlightFebruary 01, 2021
Novel antibody tests reveal complexity of immune response to covid-19
The interaction of SARS-CoV-2, the novel coronavirus causing the global COVID-19 pandemic, and the human immune system has been the focus of intensive research.
Research HighlightJanuary 18, 2021
JAX uses genetic models to fight CUP
A JAX team developed CUP-AI-Dx, a machine learning tool that uses RNA sequence data for analysis. The researchers show that CUP-AI-Dx provides an important clinical tool to help guide therapies for CUP patients.
Press ReleaseJanuary 07, 2021
Using the mouse model to fight against heart attacks
British Heart Foundation funds research aimed at supporting the lymphatic system to prevent heart failure.

The Dumont Lab

Principal Investigator: Beth Dumont, Ph.D.

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Contact The Dumont Lab

Our Research Focus

Open Positions

Selected Publications

Highlighted Abstract

When should you seek clinical confirmation of consumer genomic test results?

New coronavirus variants spark concerns

Machine learning: Shining a light on genomic function

Few mutations, important difference in cancer cells

A new reference for global genomic diversity

Novel antibody tests reveal complexity of immune response to covid-19

JAX uses genetic models to fight CUP

Using the mouse model to fight against heart attacks