skip to main content


This content will become publicly available on November 27, 2024

Title: Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits

The ease and throughput of single-cell genomics have steadily improved, and its current trajectory suggests that surveying single-cell populations will become routine. We discuss the merger of quantitative genetics with single-cell genomics and emphasize how this synergizes with advantages intrinsic to plants. Single-cell population genomics provides increased detection resolution when mapping variants that control molecular traits, including gene expression or chromatin accessibility. Additionally, single-cell population genomics reveals the cell types in which variants act and, when combined with organism-level phenotype measurements, unveils which cellular contexts impact higher-order traits. Emerging technologies, notably multiomics, can facilitate the measurement of both genetic changes and genomic traits in single cells, enabling single-cell genetic experiments. The implementation of single-cell genetics will advance the investigation of the genetic architecture of complex molecular traits and provide new experimental paradigms to study eukaryotic genetics.

 
more » « less
Award ID(s):
2134912 2120132
NSF-PAR ID:
10488829
Author(s) / Creator(s):
; ;
Publisher / Repository:
Annual Reviews
Date Published:
Journal Name:
Annual Review of Genetics
Volume:
57
Issue:
1
ISSN:
0066-4197
Page Range / eLocation ID:
297 to 319
Subject(s) / Keyword(s):
CREs, single-cell genomics, plant epigenomes
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Genomics has grown exponentially over the last decade. Common variants are associated with physiological changes through statistical strategies such as Genome-Wide Association Studies (GWAS) and quantitative trail loci (QTL). Rare variants are associated with diseases through extensive filtering tools, including population genomics and trio-based sequencing (parents and probands). However, the genomic associations require follow-up analyses to narrow causal variants, identify genes that are influenced, and to determine the physiological changes. Large quantities of data exist that can be used to connect variants to gene changes, cell types, protein pathways, clinical phenotypes, and animal models that establish physiological genomics. This data combined with bioinformatics including evolutionary analysis, structural insights, and gene regulation can yield testable hypotheses for mechanisms of genomic variants. Molecular biology, biochemistry, cell culture, CRISPR editing, and animal models can test the hypotheses to give molecular variant mechanisms. Variant characterizations can be a significant component of educating future professionals at the undergraduate, graduate, or medical training programs through teaching the basic concepts and terminology of genetics while learning independent research hypothesis design. This article goes through the computational and experimental analysis strategies of variant characterization and provides examples of these tools applied in publications. © 2022 American Physiological Society. Compr Physiol 12:3303-3336, 2022. 
    more » « less
  2. Individuals infected with the SARS-CoV-2 virus present with a wide variety of symptoms ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe response to COVID-19. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the genetic predisposition to severe COVID-19 outcomes. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform a locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify four introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. Using reporter assays in the presence/absence of SARS-CoV-2 , we find evidence that these variants respond to viral infection. These variants likely drive the locus’ impact on severity by modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5 . These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes. 
    more » « less
  3. Abstract

    Recently, it has been argued that improving students' genomics literacy could prevent students from developing erroneous beliefs about social identity, such as the belief that racial groups differ cognitively and behaviorally because of their genes; a belief called genetic essentialism. To date, however, little research has explored if or how a conceptual understanding of genomics protects against the development of genetic essentialism. Using a randomized control trial (RCT) (N= 721, 9th–12th graders), we explore if students with more genomics literacy are more able to conceptually change their genetic essentialist beliefs after engaging in a learning experience designed to refute essentialist thinking. The results of the RCT demonstrated that students with higher genomics literacy (relative to those with lower genomics literacy) exhibited greater reductions in the perception of racial differences and greater reductions in belief in genetic essentialism after learning how patterns of human genetic variation refute genetic essentialism. These results suggest that genetics education can protect students from developing a belief in genetic essentialism when it provides them with opportunities to learn multifactorial genetics and population thinking in conjunction with how these concepts refute essentialist thinking.

     
    more » « less
  4. Some genetics educators have recently argued that improving students’ genomics literacy could prevent students from developing erroneous beliefs about social identity, such as the belief that racial groups differ cognitively and behaviorally because of their genes; a belief called genetic essentialism. To date, however, little research has explored if or how a conceptual understanding of genomics protects against the development of genetic essentialism. Using a randomized control trial (RCT) (N = 721, 9th-12th graders), we explore if students with more genomics literacy are more able to conceptually change their genetic essentialist beliefs after engaging in a learning experience designed to refute essentialist thinking. The results of the RCT demonstrated that students with higher genomics literacy (relative to those with lower genomics literacy) exhibited greater reductions in the perception of racial differences and greater reductions in belief in genetic essentialism after learning about patterns of human genetic variation. These results suggest that genetics education can protect students from developing a belief in genetic essentialism when it provides them with opportunities to learn multifactorial genetics and population thinking in conjunction with how these concepts refute essentialist thinking. 
    more » « less
  5. Buchner, David A. (Ed.)
    Several studies have found associations between higher pancreatic fat content and adverse health outcomes, such as diabetes and the metabolic syndrome, but investigations into the genetic contributions to pancreatic fat are limited. This genome-wide association study, comprised of 804 participants with MRI-assessed pancreatic fat measurements, was conducted in the ethnically diverse Multiethnic Cohort-Adiposity Phenotype Study (MEC-APS). Two genetic variants reaching genome-wide significance, rs73449607 on chromosome 13q21.2 (Beta = -0.67, P = 4.50x10 -8 ) and rs7996760 on chromosome 6q14 (Beta = -0.90, P = 4.91x10 -8 ) were associated with percent pancreatic fat on the log scale. Rs73449607 was most common in the African American population (13%) and rs79967607 was most common in the European American population (6%). Rs73449607 was also associated with lower risk of type 2 diabetes (OR = 0.95, 95% CI = 0.89–1.00, P = 0.047) in the Population Architecture Genomics and Epidemiology (PAGE) Study and the DIAbetes Genetics Replication and Meta-analysis (DIAGRAM), which included substantial numbers of non-European ancestry participants (53,102 cases and 193,679 controls). Rs73449607 is located in an intergenic region between GSX1 and PLUTO , and rs79967607 is in intron 1 of EPM2A . PLUTO , a lncRNA , regulates transcription of an adjacent gene, PDX1 , that controls beta-cell function in the mature pancreas, and EPM2A encodes the protein laforin, which plays a critical role in regulating glycogen production. If validated, these variants may suggest a genetic component for pancreatic fat and a common etiologic link between pancreatic fat and type 2 diabetes. 
    more » « less