7 research outputs found
SNP genotypes Russian River 2007-2011
Two column format SNP genotypes from two hatcheries (WSH and CVFF) in the Russian River
smolt-data
Offspring data is in ‘smolt-data.csv’ as follows:
Column 1: PIT: Passive Integrated Transponder number used for individual ID
Column 2: FL: Fork length in mm
Column 3: mass: in grams
Column 4: Sex: Male, Female, or NA (i.e. failed to assign)
Column 5: cross: AA or BB (i.e. pure above-barrier cross or pure below-barrier cross)
Column 6: Ma: Individual ID of mother
Column 7: MOM: A or B (origin of Ma)
Column 8: Pa: Individual ID of father
Column 9: DAD: A or B (origin of Pa)
Column 10: score: smolt condition: 1, 2, 3, 4, or NA (see explanation below)
Column 11: smolt: 0 or 1 (non-smolt or smolt
movement-data
movement-data.csv
Column 1: PIT: Passive Integrated Transponder number used for individual ID
Column 2: cross: AxA, BxB, Hybrid, AxF1, BxF1, F1 (The latter four crosses are from a separate study not discussed in the corresponding manuscript. They were raised in the same manner as the AxA and BxB crosses discussed in the corresponding manuscript)
Column 3: FL: Fork length in mm
Column 4: mass: in grams
Column 5: score: 1, 2, 3, 4 or NA (see explanation below)
Column 6: smolt: 0 or 1 (i.e. non-smolt or smolt)
Column 7: detect: 0 or 1 (i.e. not detected or detected
saltwater-challenge-data
Data from the seawater challenge experiment are in saltwater-challenge-data.csv as follows:
Column 1: PIT: Passive Integrated Transponder number used for individual ID
Column 2: cross: AxA, BxB, Hybrid, AxF1, BxF1, F1 (The latter four crosses are from a separate study not discussed in the corresponding manuscript. They were raised in the same manner as the AxA and BxB crosses discussed in the corresponding manuscript)
Column 3: FL: Fork length in mm
Column 4: mass: in grams
Column 5: score: 1, 2, 3, 4 or NA (see explanation below)
Column 6: smolt: 0 or 1 (non-smolt or smolt)
Column 7: sex: Male, Female, or NA (i.e. failed to assign)
Column 8: fate: 0 or 1: (i.e. dead or alive at the end of the experiment)
Column 9: Date: date individual was declared dead
Column 10: Time: time individual was declared dea
Data_Sheet_2_A New Single Nucleotide Polymorphism Database for Rainbow Trout Generated Through Whole Genome Resequencing.XLSX
<p>Single-nucleotide polymorphisms (SNPs) are highly abundant markers, which are broadly distributed in animal genomes. For rainbow trout (Oncorhynchus mykiss), SNP discovery has been previously done through sequencing of restriction-site associated DNA (RAD) libraries, reduced representation libraries (RRL) and RNA sequencing. Recently we have performed high coverage whole genome resequencing with 61 unrelated samples, representing a wide range of rainbow trout and steelhead populations, with 49 new samples added to 12 aquaculture samples from AquaGen (Norway) that we previously used for SNP discovery. Of the 49 new samples, 11 were double-haploid lines from Washington State University (WSU) and 38 represented wild and hatchery populations from a wide range of geographic distribution and with divergent migratory phenotypes. We then mapped the sequences to the new rainbow trout reference genome assembly (GCA_002163495.1) which is based on the Swanson YY doubled haploid line. Variant calling was conducted with FreeBayes and SAMtools mpileup, followed by filtering of SNPs based on quality score, sequence complexity, read depth on the locus, and number of genotyped samples. Results from the two variant calling programs were compared and genotypes of the double haploid samples were used for detecting and filtering putative paralogous sequence variants (PSVs) and multi-sequence variants (MSVs). Overall, 30,302,087 SNPs were identified on the rainbow trout genome 29 chromosomes and 1,139,018 on unplaced scaffolds, with 4,042,723 SNPs having high minor allele frequency (MAF > 0.25). The average SNP density on the chromosomes was one SNP per 64 bp, or 15.6 SNPs per 1 kb. Results from the phylogenetic analysis that we conducted indicate that the SNP markers contain enough population-specific polymorphisms for recovering population relationships despite the small sample size used. Intra-Population polymorphism assessment revealed high level of polymorphism and heterozygosity within each population. We also provide functional annotation based on the genome position of each SNP and evaluate the use of clonal lines for filtering of PSVs and MSVs. These SNPs form a new database, which provides an important resource for a new high density SNP array design and for other SNP genotyping platforms used for genetic and genomics studies of this iconic salmonid fish species.</p