Genotyping by RNA Sequencing

Last updated on 2024-09-06 | Edit this page

Overview

Questions

  • What is Genotyping by RNA Sequencing (GBRS)?
  • What analyses does GBRS provide?
  • What are the steps in a GBRS analysis?

Objectives

  • Explain what GBRS does.
  • Understand when and why you would use GBRS for transcript quantification.
  • List the steps in a GBRS analysis.

Introduction

Genotyping by RNA Sequencing (GBRS) is a suite of tools which estimates allele-specific transcript expression and performs haplotype reconstruction in multi-founder mouse crosses. GBRS can also by used to analyze transcript expression in other organisms, but this tutorial will focus on mouse crosses. We have configured GBRS to use the Nextflow workflow software and Singularity containers.

Prerequisites

This tutorial assumes that you have a background in genetics and are familiar with bash command-line programming.

In the area of genetics, we assume that:

  1. you understand the folloiwng terms: inbred strain, recombinant inbred strain, multi-founder advanced generation intercross;
  2. you are familiar with the Diversity Outbred (J:DO) mouse population;
  3. you understand the concepts of haplotype reconstruction and allele- specific expression;
  4. you understand what RNASeq analysis is used for and what type of data it produces.

In the area of bash programming, we assume that:

  1. you can navigate the UNIX/Linux file system;
  2. you understand the difference between absolute and relative file paths;
  3. you can create and use bash variables;
  4. you understand what a software container is and know how to use one.

Background

There are many tool chains that can align RNASeq reads and quantify transcript expression. The alignment tools (i.e. bowtie or STAR) generally align the reads to the reference genome or transcriptome, allowing for gaps and mismatches. These methods work well for reads derived from mice with genomes that are similar to the reference, but may not provide accurate alignments for mouse genome that diverge from the reference genome. This may be particularly important when users need allele-specific expression estimates. Allele-specific expression provides an estimate of the expression of each of the two alleles in a diploid sample.

GBRS provides a suite of tools which aligns reads to pseudogenomes and then quantifies allele-specific expression in multi-founder mouse crosses. A “pseudo-genome” is a reference genome with SNPs and indels inserted from the genome of a non-reference mouse strain. By analogy, we can also create a “pseudo-transcriptome” for a non-reference inbred strain, which involves inserting SNPs and indels into the reference transcriptome. We then align RNASeq reads to multiple pseudo-transriptomes and use expectation maximization to estimate allele-specific transcript counts and total gene counts. In the process, we also reconstruct the haplotypes of each mouse in terms of the founder strain haplotypes.

The GBRS suite consists of three tools:

  1. g2gtools: given a reference genome and a VCF containing SNPs and indels, creates pseudo-genomes by inserting the SNPs and indels into the reference genome.
  2. EMASE: given a set of pseudogenomes and a transcriptome, create a multi-way transcriptome. EMASE also produces estimates of allele-specific transcript counts.
  3. GBRS: Genotyping-by-RNA-Sequencing uses the pesudo-genomes created by g2gtools and the RNASeq read alignments from EMASE to reconstruct the haplotypes of each sample in terms of the founder strain haplotypes.

GBRS is designed to work well with bulk RNASeq off with sufficient read depth to confidently call genetic variants. It does not work well with single-cell RNASeq because of the low sequencing depth in each cell.

Organization of this Tutorial

This tutorial is intended to cover all aspects of GBRS, from building reference genomes and transcriptomes through haplotype reconstruction and estimation of allele-specific transcript expression. All users may not need to perform all steps.

We envision four types of users:

  1. Users who are analyzing J:DO data
  • inside of The Jackson Laboratory This is the simplest case. The Next-Generation Sequencing Operations group has created the reference files and a pipeline to execute this workflow. This case is covered in the “Running GBRS” lesson.
  • outside of The Jackson Laboratory In this case, users will need to download and store the DO-related reference files and have Nextflow installed on their computing cluster. This case is covered in the “Running GBRS” lesson.
  1. Users who are analyzing other mouse crosses
  • inside of The Jackson Laboratory Users will need to create reference files for the founder strains in their cross and point to them in their GBRS scripts. This is described in the “Preparing GBRS Reference Genomes” and “Preparing GBRS Reference Transcriptomes” lessons.
  • outside of The Jackson Laboratory Users will need to create reference files for the founder strains in their cross and point to them in their GBRS scripts. This is described in the “Preparing GBRS Reference Genomes” and “Preparing GBRS Reference Transcriptomes” lessons.

Key Points

  • GBRS is a suite of tools which includes pseudo-genome creation, allele- specific transcript estimation, and haplotype reconstruction.
  • Users who have J:DO data and work at The Jackson Laboratory can use reference data stored on the high-performance computing cluster.
  • Users outside of The Jackson Laboratory will need to create or download the reference files.