# New technologies for accurate capture and sequencing of repeat-associated regions

> **NIH NIH R21** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $225,767

## Abstract

Project Summary
While often ignored in analysis, repetitive regions of the genome and their association with disease is becoming
more apparent in recent years. Part of the resurgence of interest in these regions is the availability of new tech-
nologies to sequence them and accurately map their location. Indeed, classes of transposable elements have
been shown to be polymorphic in the population indicating both their continued activity in shaping our genomes
and their propensity to be genetic drivers of phenotype. This has been especially true in neurologic disorders,
where transposable elements are not only polymorphic but actively moving in somatic cells and has driven parts
of projects such as the Brain Somatic Mosaicism Network. However, a major roadblock in identifying these ele-
ments remains as their inherent repetitive nature makes them difficult to place on a genome. In this proposal,
we will develop a technology to capture a set of actively moving transposable elements: L1Hs, AluYa5/8,
AluYb8/9, and SVAs. These represent the vast majority of active transposable elements and thus will allow us
to measure the genetic diversity of polymorphic insertions of these elements. After capture, we will use nanopore
long-read sequencing to capture both the entire insertion as well as thousands of bases of surrounding sequence
which will allow for accurate mapping of these elements to the genome. We will apply this new technology to a
set of three diverse trios that have been well-studied and characterized to allow for follow-up analysis of the
effect of polymorphic insertions of transposable elements.

## Key facts

- **NIH application ID:** 10308722
- **Project number:** 5R21HG011493-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Alan P Boyle
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $225,767
- **Award type:** 5
- **Project period:** 2020-12-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10308722

## Citation

> US National Institutes of Health, RePORTER application 10308722, New technologies for accurate capture and sequencing of repeat-associated regions (5R21HG011493-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10308722. Licensed CC0.

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