# Rarely Common: Uncovering the dominant role of rare variants in the genetic architecture of complex human traits.

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2022 · $545,748

## Abstract

ABSTRACT:
The vast majority of human mutations have minor allele frequencies (MAF) under 1%, with the plurality
observed only once (i.e., “singletons”). While Mendelian diseases are predominantly caused by rare alleles,
the cumulative contribution of rare variants to complex phenotypes remains hotly debated. In our recent
work, we demonstrated that ultrarare variants (MAF<0.01%) make a substantial contribution to the genetic
architecture of human transcriptional regulation (an intermediate between genetic variation and complex
disease)1, and low frequency variants constitute nearly half the heritability of several complex traits (on
average)2. In this study, we will functionally validate the role that ultrarare variants play in human gene
expression using massively parallel reporter assays (MPRAs). MPRA have revolutionized the way
enhancers can be assayed for activity. We will utilize MPRAs to functionally validate our finding that
ultrarare variants dominate the genetic architecture of human gene expression. We will use insights from
this technology to drive statistical and bioinformatic improvements in the way genetic variation data are
analyzed. We will then expand our analysis to quantify the genetic architecture of gene expression across
tissues. All tissues in the human body derive from essentially the same DNA but exhibit remarkably different
patterns of gene expression. We will extend our Haseman-Elston (HE) regression approach for modeling
the genetic architecture of gene expression to multiple traits to uncover cross-tissue and tissue-specific
genetic effects using WGS and multi-tissue RNA-sequencing data from the GTEx project5. Finally, we will
improve genomic-based precision medicine efforts for all by characterizing the population-specific genetic
architecture of complex traits. Every human population has experienced a different evolutionary history in
the recent past (different pathogens, different limits on reproductive growth, etc). Each population therefore
has a different distribution of genetic variation. As a consequence, different populations likely have different
genetic architectures for complex traits. Further, many understudied populations are admixed (with ancestry
deriving from multiple populations). We will extend our HE regression approach to model shared and
population-specific genetic effects using >140 thousand samples from multiple populations with whole
genome sequencing data and complex trait data from the TOPMed Project6.

## Key facts

- **NIH application ID:** 10366074
- **Project number:** 5R01GM142112-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Ryan D. Hernandez
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $545,748
- **Award type:** 5
- **Project period:** 2021-04-01 → 2024-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10366074

## Citation

> US National Institutes of Health, RePORTER application 10366074, Rarely Common: Uncovering the dominant role of rare variants in the genetic architecture of complex human traits. (5R01GM142112-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10366074. Licensed CC0.

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