DOI: 10.5061/dryad.59j3974
title: Data from: CHIIMP: an automated high-throughput microsatellite genotyping approach reveals greater allelic diversity in wild chimpanzees

description: Short tandem repeats (STRs), also known as microsatellites, are commonly
 used to non-invasively genotype wild-living endangered species, including
 African apes. Until recently, capillary electrophoresis has been the
 method of choice to determine the length of polymorphic STR loci. However,
 this technique is labor intensive, difficult to compare across platforms,
 and notoriously imprecise. Here we developed a MiSeq-based approach and
 tested its performance using previously genotyped fecal samples from
 long-term studied chimpanzees in Gombe National Park, Tanzania. Using data
 from eight microsatellite loci as a reference, we designed a
 bioinformatics platform that converts raw MiSeq reads into locus-specific
 files and automatically calls alleles after filtering stutter sequences
 and other PCR artifacts. Applying this method to the entire Gombe
 population, we confirmed previously reported genotypes, but also
 identified 31 new alleles that had been missed due to sequence differences
 and size homoplasy. The new genotypes, which increased the allelic
 diversity and heterozygosity in Gombe by 61% and 8%, respectively, were
 validated by replicate amplification and pedigree analyses. This
 demonstrated inheritance and resolved one case of an ambiguous paternity.
 Using both singleplex and multiplex locus amplification, we also genotyped
 fecal samples from chimpanzees in the Greater Mahale Ecosystem in
 Tanzania, demonstrating the utility of the MiSeq-based approach for
 genotyping non-habituated populations and performing comparative analyses
 across field sites. The new automated high-throughput analysis platform
 (available at https://github.com/ShawHahnLab/chiimp) will allow biologists
 to more accurately and effectively determine wildlife population size and
 structure, and thus obtain information critical for conservation efforts.
description: CHIIMP Analysis Code and
 ResultsThis archive contains
 all analysis code, supporting metadata, and results following execution of
 the included scripts. At least one of the two data archives should be
 supplied as well to re-run the analysis (either the raw, untrimmed
 sequence data or the prepared version), but all other files including
 intermediates and generated figures are provided here. See the contained
 README.md file for a full description of the layout and usage
 instructions.chiimp-paper-analysis.zipchiimp-paper-data-raw.zipThis archive contains the raw, compressed FASTQ files as generated in the original MiSeq runs. This corresponds directly to the data uploaded to the NCBI SRA. Supporting metadata including Illumina adapter and STR primer information are provided in the Analysis Code and Results archive. The adapter-trimmed data files are provided in a separate archive file, whereas these data files will need to be adapter-trimmed before use with CHIIMP. This will be handled automatically by the scripts in the Analysis Code and Results archive. See the contained README.md file in that archive for a full description of the layout and usage instructions.CHIIMP Data Files - Prepared DataThis archive contains the adapter-trimmed FASTQ files ready for use with CHIIMP. These are the raw files, provided separately, after processing with cutadapt. STR primer information is provided in the Analysis Code and Results archive. See the contained README.md file in that archive for a full description of the layout and usage instructions.chiimp-paper-data-prepared.zipLink to CHIIMP in GitHub