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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Multiplexed Analysis of Retinal Gene Expression and Chromatin Accessibility Using scRNA-Seq and scATAC-Seq

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Fine-mapping cellular QTLs with RASQUAL and ATAC-seq.

Natsuhiko Kumasaka¹, Andrew J Knights¹, Daniel J Gaffney¹

¹Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, UK.

Nature Genetics

|December 15, 2015

Summary

We developed RASQUAL, a robust statistical method for genetic association mapping that improves accuracy in sequencing data. This approach enabled the first comprehensive map of chromatin accessibility QTLs (caQTLs), revealing insights into gene regulation.

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Area of Science:

Genomics and Bioinformatics
Statistical Genetics
Epigenetics

Background:

High-throughput DNA sequencing measures cellular traits, revealing quantitative trait loci (QTLs) through fragment count and allelic differences.
Existing methods for association mapping in sequencing data face challenges with accuracy and sensitivity due to biases.

Purpose of the Study:

To introduce RASQUAL (Robust Allele-Specific Quantitation and Quality Control), a novel statistical framework for robust association mapping.
To improve fine-mapping accuracy and sensitivity in various sequencing data types (RNA-seq, DNase-seq, ChIP-seq).
To generate the first map of chromatin accessibility QTLs (caQTLs) using ATAC-seq data.

Main Methods:

Developed RASQUAL, a probabilistic framework that models genetic effects and accounts for biases in sequencing data.
Applied RASQUAL to ATAC-seq data to identify chromatin accessibility QTLs (caQTLs).
Utilized a combination of between-individual and allele-specific genetic signals for enhanced functional interpretation.

Main Results:

RASQUAL demonstrated substantial improvements in fine-mapping accuracy and sensitivity compared to existing methods across multiple sequencing data types.
Generated the first map of 2,707 independent caQTLs in a European population using ATAC-seq, despite a modest sample size.
Showcased the power of RASQUAL and ATAC-seq in fine-mapping gene-regulatory variants and linking regulatory elements to gene promoters.

Conclusions:

RASQUAL provides a powerful and accurate statistical approach for association mapping in high-throughput sequencing data.
The generated caQTL map offers valuable insights into the genetic control of chromatin accessibility and gene regulation.
Combining diverse genetic signals significantly enhances the functional interpretation of noncoding genetic variation.