Fast sequence-based microsatellite genotyping development workflow

• Published in: bioRxiv
• Main Authors: Lepais, Olivier, Chancerel, Emilie, Boury, Christophe, Salin, Franck, Manicki, Aurélie, Taillebois, Laura, Dutech, Cyril, Aissi, Abdelbjalil, Bacles, Cecile F E, Daverat, Françoise, Launey, Sophie, Guichoux, Erwan
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 16.12.2019; Cold Spring Harbor Laboratory
• Edition: 1.2
• Subjects: Bioinformatics; Fungi; Gene polymorphism; Genetic diversity; Genetics; Genotyping; Haplotypes; Information processing; Next-generation sequencing; Population genetics; Resource availability; HapSTR; haplotype sequence; SSR-seq; SSR-GBS; sequence-based microsatellite genotyping; SNPSTR
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/649772

Application of high-throughput sequencing technologies to microsatellite genotyping (SSRseq) has been shown to remove many of the limitations of electrophoresis-based methods and to refine inference of population genetic diversity and structure. We present here a streamlined SSRseq development workflow that includes microsatellite development, multiplexed marker amplification and sequencing, and automated bioinformatics data analysis. We illustrate its application to five groups of species across phyla (fungi, plant, insect and fish) with different levels of genomic resource availability. We found that relying on previously developed microsatellite assay is not optimal and leads to a resulting low number of reliable locus being genotyped. In contrast, de novo ad hoc primer designs gives highly multiplexed microsatellite assays that can be sequenced to produce high quality genotypes for 20 to 40 loci. We highlight critical upfront development factors to consider for effective SSRseq setup in a wide range of situations. Sequence analysis accounting for all linked polymorphisms along the sequence, quickly generates a powerful multi-allelic haplotype-based genotypic dataset, calling to new theoretical and analytical frameworks to extract more information from multi-nucleotide polymorphism marker systems. Footnotes * https://doi.org/10.15454/HBXKVA