# DMS/NIGMS 1: Multilayer network approach to tandem repeat variation in genomes

> **NIH NIH R01** · STATE UNIVERSITY OF NEW YORK AT BUFFALO · 2022 · $148,350

## Abstract

Understanding the genetic bases of biological function is a fundamental quest ion in biological sciences.
Traditionally, the conservation of genetic sequences across species and populations has been a primary
concept with which to measure functionality. However, recent biochemical characterizations of the DNA
have challenged this definition of functionality and argued up to 80% of the human genome to be
functional. Several studies have pursued the possibility that biological function evolves as an adaptive
response to rapid changes under environmental pressures whe reby sequence conservation does not
directly predict function. By integrating -omics datasets and multilayer network approaches, we will
specifically test the following four hypotheses: (1) Among the millions of tandem repeats, a small portion,
still corresponding to thousands of loci, are functionally relevant. We further hypothesize that majority of
these functional tandem repeats will be evolving under negative selection and pr imarily cluster together in
multilayer networks of tandem repeat units. (2) Exonic tandem repeats have evolved as molecular tools to
regulate the dosage of a particular functional motif. Thus, we expect that these functional tandem repeats
will retain sequence conservation among paralogs as well as among species. (3) There are hundreds of
tandem repeats in the mammalian genome that evolve under lineage-specific positive selection. We
expect that such positively selected tandem re peats show unusual species-specific copy number
expansions or contractions, and may affect gene expression and phenotypic traits more often than
neutrally evolving tandem repeats. (4) Tandem-repeat copy numbe r variation, if functional, primarily
effects phenotypic variation related to immunity and metabolism in humans. We expect that these repeat
loci evolve under positive selection. To test these hypotheses, we will develop
mathematical/computational methods to find groups of core nodes in multilayer genetic networks, and
then apply them to multilayer networks that we will build, in which each network layer is based on a
specific type of relationships between tandem repeat units.
RELEVANCE (See instructions):
Understanding genetic bases of biological function can alleviate ou r ability to understand and treat human
disease. However, variable tandem repeats in the human genome have been difficult to characterize for
functional and biomedical relevance. This research will leverage recently available long-read sequencing
datasets to develop mathematical methods to investigate tandemly repeated sequences in the human
genome, thus providing potentially transformative insights into genetic basis of human disease.
P ROJ ECT/ P E R FO R M A N C E SI T E(S) (if ad di tional space is need ed , use

## Key facts

- **NIH application ID:** 10592458
- **Project number:** 1R01GM148973-01
- **Recipient organization:** STATE UNIVERSITY OF NEW YORK AT BUFFALO
- **Principal Investigator:** Naoki Masuda
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $148,350
- **Award type:** 1
- **Project period:** 2022-09-24 → 2025-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10592458

## Citation

> US National Institutes of Health, RePORTER application 10592458, DMS/NIGMS 1: Multilayer network approach to tandem repeat variation in genomes (1R01GM148973-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10592458. Licensed CC0.

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