Automating microsatellite screening and primer design from multi-individual libraries using Micro-Primers.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

Biological Variation, Individual* ; Biological Variation, Population* ; DNA Primers* ; Gene Library* ; Genetic Variation* ; High-Throughput Nucleotide Sequencing* ; Microsatellite Repeats* ; Polymerase Chain Reaction* ; Software*; Automation, Laboratory ; Humans ; Reproducibility of Results ; Time Factors ; Workflow

Analysis of intra- and inter-population diversity has become important for defining the genetic status and distribution patterns of a species and a powerful tool for conservation programs, as high levels of inbreeding could lead into whole population extinction in few generations. Microsatellites (SSR) are commonly used in population studies but discovering highly variable regions across species' genomes requires demanding computation and laboratorial optimization. In this work, we combine next generation sequencing (NGS) with automatic computing to develop a genomic-oriented tool for characterizing SSRs at the population level. Herein, we describe a new Python pipeline, named Micro-Primers, designed to identify, and design PCR primers for amplification of SSR loci from a multi-individual microsatellite library. By combining commonly used programs for data cleaning and microsatellite mining, this pipeline easily generates, from a fastq file produced by high-throughput sequencing, standard information about the selected microsatellite loci, including the number of alleles in the population subset, and the melting temperature and respective PCR product of each primer set. Additionally, potential polymorphic loci can be identified based on the allele ranges observed in the population, to easily guide the selection of optimal markers for the species. Experimental results show that Micro-Primers significantly reduces processing time in comparison to manual analysis while keeping the same quality of the results. The elapsed times at each step can be longer depending on the number of sequences to analyze and, if not assisted, the selection of polymorphic loci from multiple individuals can represent a major bottleneck in population studies.
(© 2022. The Author(s).)

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PTDC/AAGMAA/2261/2014 FRESHING; POCI010145FEDER356016824 COMPETE; SFRH/BD/104703/2014 Fundação para a Ciência e a Tecnologia; SFRH/BPD/108018/2015 Fundação para a Ciência e a Tecnologia; POCI010145FEDER022184 GenomePT

0 (DNA Primers)

Date Created: 20220108 Date Completed: 20220224 Latest Revision: 20220224

20221213

PMC8741888

10.1038/s41598-021-04275-8

34997147