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Automated genotyping of microsatellite loci from feces with high throughput sequences
Ecological and conservation genetic studies often use noninvasive sampling, especially with elusive or endangered species. Because microsatellites are generally short in length, they can be amplified from low quality samples such as feces. Microsatellites are highly polymorphic so few markers are en...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8544849/ https://www.ncbi.nlm.nih.gov/pubmed/34695152 http://dx.doi.org/10.1371/journal.pone.0258906 |
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author | Salado, Isabel Fernández-Gil, Alberto Vilà, Carles Leonard, Jennifer A. |
author_facet | Salado, Isabel Fernández-Gil, Alberto Vilà, Carles Leonard, Jennifer A. |
author_sort | Salado, Isabel |
collection | PubMed |
description | Ecological and conservation genetic studies often use noninvasive sampling, especially with elusive or endangered species. Because microsatellites are generally short in length, they can be amplified from low quality samples such as feces. Microsatellites are highly polymorphic so few markers are enough for reliable individual identification, kinship determination, or population characterization. However, the genotyping process from feces is expensive and time consuming. Given next-generation sequencing (NGS) and recent software developments, automated microsatellite genotyping from NGS data may now be possible. These software packages infer the genotypes directly from sequence reads, increasing throughput. Here we evaluate the performance of four software packages to genotype microsatellite loci from Iberian wolf (Canis lupus) feces using NGS. We initially combined 46 markers in a single multiplex reaction for the first time, of which 19 were included in the final analyses. Megasat was the software that provided genotypes with fewer errors. Coverage over 100X provided little additional information, but a relatively high number of PCR replicates were necessary to obtain a high quality genotype from highly unoptimized, multiplexed reactions (10 replicates for 18 of the 19 loci analyzed here). This could be reduced through optimization. The use of new bioinformatic tools and next-generation sequencing data to genotype these highly informative markers may increase throughput at a reasonable cost and with a smaller amount of laboratory work. Thus, high throughput sequencing approaches could facilitate the use of microsatellites with fecal DNA to address ecological and conservation questions. |
format | Online Article Text |
id | pubmed-8544849 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85448492021-10-26 Automated genotyping of microsatellite loci from feces with high throughput sequences Salado, Isabel Fernández-Gil, Alberto Vilà, Carles Leonard, Jennifer A. PLoS One Research Article Ecological and conservation genetic studies often use noninvasive sampling, especially with elusive or endangered species. Because microsatellites are generally short in length, they can be amplified from low quality samples such as feces. Microsatellites are highly polymorphic so few markers are enough for reliable individual identification, kinship determination, or population characterization. However, the genotyping process from feces is expensive and time consuming. Given next-generation sequencing (NGS) and recent software developments, automated microsatellite genotyping from NGS data may now be possible. These software packages infer the genotypes directly from sequence reads, increasing throughput. Here we evaluate the performance of four software packages to genotype microsatellite loci from Iberian wolf (Canis lupus) feces using NGS. We initially combined 46 markers in a single multiplex reaction for the first time, of which 19 were included in the final analyses. Megasat was the software that provided genotypes with fewer errors. Coverage over 100X provided little additional information, but a relatively high number of PCR replicates were necessary to obtain a high quality genotype from highly unoptimized, multiplexed reactions (10 replicates for 18 of the 19 loci analyzed here). This could be reduced through optimization. The use of new bioinformatic tools and next-generation sequencing data to genotype these highly informative markers may increase throughput at a reasonable cost and with a smaller amount of laboratory work. Thus, high throughput sequencing approaches could facilitate the use of microsatellites with fecal DNA to address ecological and conservation questions. Public Library of Science 2021-10-25 /pmc/articles/PMC8544849/ /pubmed/34695152 http://dx.doi.org/10.1371/journal.pone.0258906 Text en © 2021 Salado et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Salado, Isabel Fernández-Gil, Alberto Vilà, Carles Leonard, Jennifer A. Automated genotyping of microsatellite loci from feces with high throughput sequences |
title | Automated genotyping of microsatellite loci from feces with high throughput sequences |
title_full | Automated genotyping of microsatellite loci from feces with high throughput sequences |
title_fullStr | Automated genotyping of microsatellite loci from feces with high throughput sequences |
title_full_unstemmed | Automated genotyping of microsatellite loci from feces with high throughput sequences |
title_short | Automated genotyping of microsatellite loci from feces with high throughput sequences |
title_sort | automated genotyping of microsatellite loci from feces with high throughput sequences |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8544849/ https://www.ncbi.nlm.nih.gov/pubmed/34695152 http://dx.doi.org/10.1371/journal.pone.0258906 |
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