DOI: 10.5061/dryad.4mw6m90mv
title: Data from: Time is of the essence: using archived samples to develop a GT-seq panel to preserve continuity of ongoing genetic monitoring

description: For the past 25 years, genetic monitoring of Rio Grande silvery minnow
 (Hybognathus amarus) has been conducted annually. The monitoring program
 has been carried out using nine microsatellite loci. Recently a temporal
 genome-wide microhaplotype dataset obtained from nextRAD-seq (a reduced
 representation sequencing approach) was obtained from archived samples
 spanning 20 years and allowed to compare results from both datasets
 (Osborne et al. 2022). To develop a GT-seq panel that was able to track
 past genomic changes across the time-series, ensuring this way the
 continuity of the ongoing genetic monitoring, we first identified loci
 from that nextRAD-seq but using a new conspecific reference genome. The
 final dataset included 2,983 loci and 379 individuals (nextRAD_complete
 dataset). From those, we selected a subset of 500 loci with the highest
 power to track the changes identified with the genome-wide data for GT-seq
 PCR multiplex optimization. We also included the sex-linked marker HAM06
 from Caeiro-Dias et al. (2023) in the panel optimization. After four
 rounds of panel optimization, we retained 284 loci. The optimized panel
 was used to genotype 118 samples from eight temporal collections (a subset
 of the nextRAD_complete) for validation of the 283 loci in the GT-seq
 panel; other 20 samples of known sex were used for sex assignment accuracy
 using the sex-marker genotyped with the GT-seq panel. The nextRAD_complete
 is provided as a VCF (single SNPs) and GENEPOP file (microhaplotypes). The
 GT-seq_283 is provided as a GENEPOP file (microhaplotypes).
description: Genome-wide SNP identification was performed using
 Nextera-tagmented reductively-amplified DNA sequencing (nextRAD-seq;
 Russello et al., 2015) data from 379 individuals reported in Osborne et
 al. (2023),
 comprising 12 temporal collections that spanned 20 years. Microhaplotypes
 were identified using the methods also described in Osborne et al. (2023), but
 with four modifications. First, NextRAD loci were identified using the
 draft genome sequenced for this study; no depth of coverage filter was
 applied to nextRAD loci before variant calling; loci were discarded if
 mean depth of coverage was lower than 20; and only individuals with less
 than 25% missing data were retained. Microhaplotypes and individuals
 retained after all filtering steps are referred to as nextRAD_complete
 dataset. The nextRAD_complete is provided as a VCF containing single SNPs
 and as GENEPOP file containing the haplotyped SNPs
 (microhaplotypes). The optimized GT-seq panel excluding
 the sex-linked marker (GT-seq_283) was used to genotype 118 samples from
 eight temporal collections. Those samples are also included in the
 nextRAD_complete dataset. The GTscore pipeline v. 1.3 (https://github.com/gjmckinney/GTscore) was used to identify genotypes. In-silico probes were designed for each SNPs to include eight nucleotides flanking for each SNP and to include variants when overlapping identified SNPs (see manual for details on probe design https://github.com/gjmckinney/GTscore/blob/master/GTScoreDocumentation%20V1.3.docx). <em>AmpliconRadCounter.pl</em> script was used to count the number of unique reads per individual, to identify on-target reads, and to count the number of reads containing each SNP allele for every individual. Then counts of reads containing a SNP allele for each individual were used for microhaplotype genotyping with the maximum likelihood algorithm described by McKinney et al. (2018) and implemented in <em>GTscore.R</em> script. Only individuals genotyped for at least 70% of the loci were kept in the dataset, resulting in 72 individuals from five temporal collections retained. Missing data across loci was not higher than 30%. The GT-seq_283 dataset is provided as a GENEPOP file (microhaplotypes).
description: # Data from: Time is of the essence: using archived samples to develop a
 GT-seq panel to preserve continuity of ongoing genetic monitoring
 [https://doi.org/10.5061/dryad.4mw6m90mv](https://doi.org/10.5061/dryad.4mw6m90mv) ## Description of the data and file structure Filtered genotype data obtained from Rio Grande silvery minnow nextRAD-seq time-series and genotypes from an optimized GT-seq panel developed from that nextRAD-seq data.  ### Files and variables #### File: GT-seq\_283loc\_72ind.gen **Description:** GENEPOP file containing genotype (microhaplotypes) data from 283 loci for 72 Rio Grande silvery minnow samples from five temporal collections (1999, 2002, 2004, 2017,2018; separated as populations in this order). #### File: nextRAD\_complete\_2983loc\_373ind.gen **Description:** GENEPOP file containing genotype (microhaplotypes) data from 2983 loci for 373 Rio Grande silvery minnow samples from 12 temporal collections (1999, 2000, 2002, 2004, 2006, 2008, 2009, 2010, 2012, 2015, 2017, 2018; separated as populations in this order). #### File: nextRAD\_complete\_2983loc\_373ind.vcf **Description:** VCF file containing biallelic SNP data from the 5315 SNPs retained after microhaplotype identification (microhaplotype data in the file nextRAD_complete_2983loc_373ind.gen) for 373 Rio Grande silvery minnow samples from 12 temporal collections (1999, 2000, 2002, 2004, 2006, 2008, 2009, 2010, 2012, 2015, 2017, 2018). ## Access information Other publicly accessible locations of the data: * n/a Data was derived from the following sources: * Raw reads from nextRAD-seq (BioSample accession numbers SAMN31170359 - SAMN311737) and GT-seq (BioSample accession numbers XXXXXXXX - XXXXXXXXXX) used to obtained these datasets are deposited in the NCBI Sequence Read Archive (SRA), with the BioProject accession number PRJNA887477.