RNA-Seq in the Collaborative Cross.

Area of Science:

• Genomics
• Transcriptomics
• Bioinformatics

Background:

• The Collaborative Cross (CC) is a resource of diverse inbred mouse strains for studying complex diseases.
• Integrated omics approaches are crucial for understanding disease mechanisms.
• RNA-sequencing (RNA-seq) offers superior sensitivity and resolution for transcriptomic analysis compared to microarrays, especially for novel genomes.

Purpose of the Study:

• To provide an overview of effective RNA-sequencing (RNA-seq) analysis methods tailored for Collaborative Cross (CC) mouse data.
• To address the specific challenges posed by significant genomic variation within CC mouse strains.

Main Methods:

• Discussing RNA-sequencing (RNA-seq) as the preferred transcriptomic analysis method.
• Highlighting the need for specialized approaches due to substantial genetic differences across CC mouse strains.
• Overview of data analysis strategies for CC mouse RNA-seq datasets.

Main Results:

• RNA-sequencing (RNA-seq) is increasingly favored over microarrays for transcriptomic studies.
• Traditional RNA-seq methods require adaptation for the high genetic diversity found in Collaborative Cross (CC) mouse populations.
• Effective analysis strategies are essential for accurate transcriptomic profiling in CC mice.

Conclusions:

• This chapter offers guidance on performing robust RNA-sequencing (RNA-seq) analysis on Collaborative Cross (CC) mouse data.
• Adapting RNA-seq methodologies is critical for leveraging the genetic diversity of CC mice in research.
• The presented overview facilitates deeper understanding of biological mechanisms underlying disease phenotypes in CC mice.