Finding Needles in the Haystack: Strategies for Uncovering Noncoding Regulatory Variants-Reference-Cited by-同舟云学术

Finding Needles in the Haystack: Strategies for Uncovering Noncoding Regulatory Variants

Published:2023-11-27 Issue:1 Volume:57 Page:201-222
ISSN:0066-4197
Container-title:Annual Review of Genetics
language:en
Short-container-title:Annu. Rev. Genet.

Author:

Chen You¹²,Paramo Mauricio I.¹²,Zhang Yingying¹²,Yao Li²³,Shah Sagar R.¹²,Jin Yiyang¹²,Zhang Junke²³,Pan Xiuqi¹²,Yu Haiyuan²³

Affiliation:

1. Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York, USA

2. Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, USA;

3. Department of Computational Biology, Cornell University, Ithaca, New York, USA

Abstract

Despite accumulating evidence implicating noncoding variants in human diseases, unraveling their functionality remains a significant challenge. Systematic annotations of the regulatory landscape and the growth of sequence variant data sets have fueled the development of tools and methods to identify causal noncoding variants and evaluate their regulatory effects. Here, we review the latest advances in the field and discuss potential future research avenues to gain a more in-depth understanding of noncoding regulatory variants.

Publisher

Annual Reviews

Subject

Genetics

Link

https://www.annualreviews.org/doi/pdf/10.1146/annurev-genet-030723-120717

Reference149 articles.

1. A global reference for human genetic variation

2. A method and server for predicting damaging missense mutations

3. Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks

4. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

5. An atlas of active enhancers across human cell types and tissues