当前位置: X-MOL 学术Annu. Rev. Genomics Hum. Genet. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Population Diversity at the Single-Cell Level
Annual Review of Genomics and Human Genetics ( IF 8.7 ) Pub Date : 2024-02-21 , DOI: 10.1146/annurev-genom-021623-083207
M. Grace Gordon 1 , Pooja Kathail 2 , Bryson Choy 3, 4 , Min Cheol Kim 3, 4 , Thomas Mazumder 3, 4 , Melissa Gearing 3, 4 , Chun Jimmie Ye 3, 4, 5
Affiliation  

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease.Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 25 is August 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

中文翻译:

单细胞水平的群体多样性

群体规模的单细胞基因组学是一种揭示遗传和细胞变异之间复杂联系的变革性方法。这种方法得到了尖端实验方法的促进,包括高通量单细胞多组学的发展以及多重环境和遗传扰动的进展。检查跨细胞环境的天然或合成遗传变异的影响,可以深入了解遗传和环境在塑造细胞异质性方面的相互影响。计算方法的发展进一步实现了分子变异的详细定量分析,为研究随机变异、细胞间变异和个体变异各自的作用提供了机会。未来的机会在于利用长读长测序、完善与疾病相关的细胞模型以及采用预测和生成机器学习模型。这些进展有可能更深入地了解人类分子特征的遗传结构,这反过来又对了解人类疾病的遗传原因具有重要意义。《基因组学和人类遗传学年度评论》第 25 卷的预计最终在线出版日期是 2024 年 8 月。请参阅 http://www.annualreviews.org/page/journal/pubdates 了解修订后的估算。
更新日期:2024-02-21
down
wechat
bug