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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

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Published on: June 21, 2018

Genotyping-by-Sequencing SNP Identification for Crops without a Reference Genome: Using Transcriptome Based Mapping

Cécile Berthouly-Salazar¹, Cédric Mariac¹, Marie Couderc¹

¹UMR Diversité, Adaptation et Développement des Plantes, Institut de Recherche pour le Développement Montpellier, France.

Frontiers in Plant Science

|July 6, 2016

Summary

Genome reduction techniques like UNEAK are useful for studying crop diversity. Mapping sequencing reads to transcriptomes offers a promising alternative for analyzing genetic diversity in non-model organisms.

Keywords:

GBS SNP UNEAK pearl millet site frequency spectrum transcriptome

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Published on: May 21, 2020

Area of Science:

Population Genetics
Genomics
Bioinformatics

Background:

Next-generation sequencing enables genomic diversity studies in non-model organisms.
Genome reduction techniques (e.g., UNEAK) are popular for exploring diversity without a reference genome.
Transcriptomes are often more accessible than reference genomes for non-model species.

Purpose of the Study:

To compare single nucleotide variants (SNVs) from the UNEAK pipeline with those from direct transcriptome mapping.
To assess the feasibility of both SNV datasets for analyzing genetic diversity in wild pearl millet.
To evaluate the impact of different variant calling strategies on diversity and selection analyses.

Main Methods:

Genotyping-by-sequencing (GBS) was performed on 91 wild pearl millet samples.
Single nucleotide variants (SNVs) were identified using the UNEAK pipeline.
SNVs were also identified by directly mapping GBS reads to a pearl millet transcriptome.

Main Results:

Both UNEAK and transcriptome mapping generated tens of thousands of SNVs.
Differences in variant identification led to distinct frequency spectrums and biased diversity assessments.
Both methods yielded similar inferences of genetic structure, revealing three main groups across Africa.

Conclusions:

Directly mapping sequencing reads to transcriptomes is a viable and promising strategy for non-model organisms.
Transcriptome-based analysis can provide a more thorough investigation of genome reduction datasets.
Careful consideration of variant calling methods is crucial for accurate diversity and selection analyses.