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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Optimizing ddRAD sequencing for population genomic studies with ddgRADer.

Aparna Lajmi¹, Felix Glinka¹, Eyal Privman¹

¹Department of Evolutionary and Environmental Biology, Institute of Evolution, University of Haifa, Haifa, Israel.

Molecular Ecology Resources

|September 21, 2023

Summary

This summary is machine-generated.

Designing double-digest Restriction-site Associated DNA sequencing (ddRADseq) experiments is simplified with ddgRADer. This tool optimizes enzyme choice and size selection for improved sequencing efficiency in population genomics.

Keywords:

RAD sequencing genomic sequencing population genomics reduced representation genome sequencing size selection user friendly webtool

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Area of Science:

Genomics
Evolutionary Biology
Ecological Studies

Background:

Double-digest Restriction-site Associated DNA sequencing (ddRADseq) is a popular method for generating genomic data in non-model organisms.
Challenges exist in experimental design, leading to issues like read overlaps and adaptor contamination, reducing sequencing efficiency and data quality.

Purpose of the Study:

To analyze factors affecting ddRADseq efficiency, specifically enzyme choice and size selection.
To develop a predictive model and user-friendly tool to aid in ddRADseq experimental design.

Main Methods:

Analysis of diverse literature datasets and controlled experiments.
Empirical investigation of enzyme choice and size selection impacts on sequencing efficiency.
Development of a predictive model for genomic fragments, SNP genotyping, multiplexing, and sequencing efficiency.

Main Results:

Size selection is often imprecise and has limited efficacy, with short fragments frequently bypassing lower cut-offs.
Enzyme choice can significantly reduce the inclusion of unwanted short fragments, improving efficiency.
A predictive model was created and implemented in the ddgRADer webtool.

Conclusions:

The ddgRADer webtool assists in designing ddRADseq experiments by recommending enzyme pairs and optimizing size selection criteria.
This tool enhances accessibility and success rates for population genomic studies, especially for new users.
ddgRADer is also applicable to single-enzyme protocols like Genotyping-by-Sequencing.