Evidence map›Paper›PMID 29870119›Full record

ArticleMolecular ecology resources2018

A bioinformatic pipeline for identifying informative SNP panels for parentage assignment from RADseq data.

Kimberly R Andrews, Jennifer R Adams, E Frances Cassirer, Raina K Plowright, Colby Gardner, Maggie Dwire, Paul A Hohenlohe, Lisette P Waits

Abstract read
In one paragraph

Article in Molecular ecology resources, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kimberly R AndrewsDepartment of Fish and Wildlife Sciences, University of Idaho, Moscow, Idaho.ORCID http://orcid.org/0000-0003-4721-1924
Jennifer R AdamsDepartment of Fish and Wildlife Sciences, University of Idaho, Moscow, Idaho.
E Frances CassirerIdaho Department of Fish and Game, Lewiston, Idaho.
Raina K PlowrightDepartment of Microbiology and Immunology, Montana State University, Bozeman, Montana.
Colby GardnerU.S. Fish and Wildlife Service, Albuquerque, New Mexico.
Maggie DwireU.S. Fish and Wildlife Service, Albuquerque, New Mexico.
Paul A HohenloheDepartment of Biological Sciences, Institute for Bioinformatics and Evolutionary Studies, University of Idaho, Moscow, Idaho.
Lisette P WaitsDepartment of Fish and Wildlife Sciences, University of Idaho, Moscow, Idaho.

Funding

Research Core (Developmental Research Project Program)P20GM103474 · NIGMS · MONTANA STATE UNIVERSITY - BOZEMAN · PI Jeffrey Good · 2012 to 2026
$60.0M
Pilot Grants ProgramP30GM110732 · NIGMS · MONTANA STATE UNIVERSITY - BOZEMAN · PI QUINN, MARK T · 2014 to 2018
$5.4M
Genomics Resources Core (GRC)P30GM103324 · NIGMS · UNIVERSITY OF IDAHO · PI FORNEY, LARRY J · 2013 to 2017
$5.0M
Mexican Wolf Interagency Field TeamMontana University System Research Initiative 51040-MUSRI2015-03Morris Animal Foundation D13ZO-081National Institutes of Health (NIH) P20GM103474National Institutes of Health (NIH) P30GM103324National Institutes of Health (NIH) P30GM110732National Science Foundation (NSF) DEB-1316549NIGMS NIH HHS P20 GM103474NIGMS NIH HHS P30 GM103324NIGMS NIH HHS P30 GM110732Oregon Department of Fish and WildlifeUniversity of Idaho College of Natural ResourcesUniversity of Idaho IBESTU.S. Fish and Wildlife Service
6 · The paper itself

Abstract

The development of high-throughput sequencing technologies is dramatically increasing the use of single nucleotide polymorphisms (SNPs) across the field of genetics, but most parentage studies of wild populations still rely on microsatellites. We developed a bioinformatic pipeline for identifying SNP panels that are informative for parentage analysis from restriction site-associated DNA sequencing (RADseq) data. This pipeline includes options for analysis with or without a reference genome, and provides methods to maximize genotyping accuracy and select sets of unlinked loci that have high statistical power. We test this pipeline on small populations of Mexican gray wolf and bighorn sheep, for which parentage analyses are expected to be challenging due to low genetic diversity and the presence of many closely related individuals. We compare the results of parentage analysis across SNP panels generated with or without the use of a reference genome, and between SNPs and microsatellites. For Mexican gray wolf, we conducted parentage analyses for 30 pups from a single cohort where samples were available from 64% of possible mothers and 53% of possible fathers, and the accuracy of parentage assignments could be estimated because true identities of parents were known a priori based on field data. For bighorn sheep, we conducted maternity analyses for 39 lambs from five cohorts where 77% of possible mothers were sampled, but true identities of parents were unknown. Analyses with and without a reference genome produced SNP panels with ≥95% parentage assignment accuracy for Mexican gray wolf, outperforming microsatellites at 78% accuracy. Maternity assignments were completely consistent across all SNP panels for the bighorn sheep, and were 74.4% consistent with assignments from microsatellites. Accuracy and consistency of parentage analysis were not reduced when using as few as 284 SNPs for Mexican gray wolf and 142 SNPs for bighorn sheep, indicating our pipeline can be used to develop SNP genotyping assays for parentage analysis with relatively small numbers of loci.

Indexed as

PedigreePolymorphism, Single NucleotideAnimalsComputational BiologyGenotypeGenotyping TechniquesMicrosatellite RepeatsSequence Analysis, DNASheep, BighornWolvesCanis lupus baileyicervusmaternityOvis canadensispaternityrestriction site-associated DNA sequencingsingle nucleotide polymorphism

Identifiers

PMID29870119
PMCPMC6207459

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.