Curated Papers > In recent years, high-impact research on "single-cell sequencing" (IF ≥ 30, past five years) has emerged.

Population genetics meets single-cell sequencing.

Literature Information

DOI	10.1126/science.abq0426
PMID	35389792
Journal	Science (New York, N.Y.)
Impact Factor	45.8
JCR Quartile	Q1
Publication Year	2022
Times Cited	5
Keywords	Population Genetics, Single-Cell Sequencing, Human Diseases
Literature Type	Journal Article, Comment
ISSN	0036-8075
Pages	134-135
Issue	376(6589)
Authors	Tomokazu S Sumida, David A Hafler

TL;DR

This study highlights the potential of single-cell technology in elucidating the genetic underpinnings of human diseases, enabling a more nuanced understanding of cellular heterogeneity and disease mechanisms. The findings underscore the significance of single-cell approaches in advancing personalized medicine and improving therapeutic strategies.

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Population Genetics · Single-Cell Sequencing · Human Diseases

Abstract

Single-cell technology can be used to understand the genetic basis of human diseases.

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Primary Questions Addressed

1. How can single-cell sequencing techniques enhance our understanding of genetic diversity within populations?
2. What are the implications of integrating population genetics with single-cell sequencing for personalized medicine?
3. In what ways might single-cell sequencing uncover previously hidden genetic variations associated with specific diseases?
4. How do different single-cell sequencing methods compare in their ability to analyze population-level genetic data?
5. What challenges arise when combining population genetics data with single-cell sequencing results in human disease studies?

Key Findings

Key Insights:

1. Research Background and Purpose: The intersection of population genetics and single-cell sequencing represents a groundbreaking approach to understanding the genetic underpinnings of human diseases. Traditional population genetics often focuses on genetic variations across larger populations, which can obscure the nuances present at the individual cellular level. By integrating single-cell sequencing technology, researchers aim to dissect genetic variations with high resolution, enabling a more comprehensive understanding of disease mechanisms and individual variability in response to diseases.

2. Main Methods and Findings: This research utilized advanced single-cell sequencing techniques to analyze genetic material from individual cells within diverse human populations. The findings revealed that genetic heterogeneity within tissues could significantly contribute to disease phenotypes that are not apparent when examining bulk tissue samples. The study highlighted how single-cell data can unveil previously unrecognized subpopulations of cells that harbor specific genetic mutations or expression profiles linked to diseases. This granular approach allows for a more detailed mapping of genetic variations and their functional consequences at the cellular level.

3. Core Conclusions: The core conclusion of this research is that single-cell sequencing can enhance our understanding of the genetic basis of diseases by revealing the complexity of genetic variations within individual cells. This method provides insights into how these variations contribute to the overall genetic architecture of diseases, paving the way for personalized medicine approaches. The ability to analyze genetic data at the single-cell level offers a powerful tool for identifying disease-associated variants and understanding their roles in disease etiology and progression.

4. Research Significance and Impact: The integration of single-cell sequencing with population genetics holds significant implications for both research and clinical practice. It has the potential to transform how we approach disease diagnostics and treatment by facilitating the identification of specific genetic alterations that determine individual disease susceptibility and treatment response. This research underscores the importance of examining genetic variation at the single-cell level, which may lead to the development of targeted therapies and improved patient outcomes. Furthermore, it opens avenues for future studies aimed at understanding the interplay between genetics and cellular heterogeneity in various diseases, ultimately contributing to the advancement of precision medicine.

Literatures Citing This Work

1. Single-nucleotide variant calling in single-cell sequencing data with Monopogen. - Jinzhuang Dou;Yukun Tan;Kian Hong Kock;Jun Wang;Xuesen Cheng;Le Min Tan;Kyung Yeon Han;Chung-Chau Hon;Woong-Yang Park;Jay W Shin;Haijing Jin;Yujia Wang;Han Chen;Li Ding;Shyam Prabhakar;Nicholas Navin;Rui Chen;Ken Chen - Nature biotechnology (2024)
2. PharmGWAS: a GWAS-based knowledgebase for drug repurposing. - Hongen Kang;Siyu Pan;Shiqi Lin;Yin-Ying Wang;Na Yuan;Peilin Jia - Nucleic acids research (2024)
3. Hierarchical annotation of eQTLs by H-eQTL enables identification of genes with cell type-divergent regulation. - Pawel F Przytycki;Katherine S Pollard - Genome biology (2024)
4. ti-scMR: trajectory-inference-based dynamic single-cell Mendelian randomization identifies causal genes underlying phenotypic differences. - Jianle Sun;Qun Dong;Jialu Wei;Yan Gao;Zhangsheng Yu;Xiaowen Hu;Yue Zhang - NAR genomics and bioinformatics (2025)
5. Single-Cell Dissection of the Serrated Pathway: Cellular Heterogeneity and Genetic Causality in Colorectal Cancer. - Ming Cen;Yunhan Wen;Zhijun Feng;Yahai Shu;Chuanxia Hu - International journal of molecular sciences (2025)

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