Evidence map›Paper›PMID 37562412›Full record

ReviewAnnual review of genetics2023

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

Mark A A Minow, Alexandre P Marand, Robert J Schmitz

Abstract readReview
In one paragraph

Review in Annual review of genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Genome-wide association studies in forestry.Molecular biology reports · 2025
    Review
  7. Article
  8. Article
  9. Review
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Mark A A MinowDepartment of Genetics, University of Georgia, Athens, Georgia, USA; email: schmitz@uga.edu.
Alexandre P MarandDepartment of Genetics, University of Georgia, Athens, Georgia, USA; email: schmitz@uga.edu.
Robert J SchmitzDepartment of Genetics, University of Georgia, Athens, Georgia, USA; email: schmitz@uga.edu.

Funding

Exploration of cis-regulatory diversity underlying phenotypic innovationR00GM144742 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARAND, ALEXANDRE · 2023 to 2025
$747k
Exploration of cis-regulatory diversity underlying phenotypic innovationK99GM144742 · NIGMS · UNIVERSITY OF GEORGIA · PI MARAND, ALEXANDRE · 2022 to 2023
$142k
NIGMS NIH HHS K99 GM144742NIGMS NIH HHS R00 GM144742
6 · The paper itself

Abstract

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.

Indexed as

GenomicsMultifactorial InheritanceGenomePhenotypePlantschromatin accessibilitygene expressionmutantspopulation geneticsquantitative geneticssingle-cell genomics

Identifiers

PMID37562412
PMCPMC10775913

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.