Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics

Parameters of reproductive success are critical to the management of wildlife populations. Genetic monitoring can provide this demographic information when traditional methods aren’t tractable. This study demonstrates a novel application of genetic data to estimate a minimum annual count of breeding...

Full description

Bibliographic Details
Main Author: Clendenin, Heather Rose
Other Authors: Waits, Lisette Rose; Hohenlohe, Paul Rose
Format: Text
Language:English
Published: 2019
Subjects:
Online Access:http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/1262
id ftunividahodc:oai:digital.lib.uidaho.edu:etd/1262
record_format openpolar
spelling ftunividahodc:oai:digital.lib.uidaho.edu:etd/1262 2023-11-12T04:15:45+01:00 Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics Clendenin, Heather Rose Waits, Lisette Rose; Hohenlohe, Paul Rose 2019-05 PDF http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/1262 en eng Clendenin_idaho_0089N_11493 http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/1262 http://rightsstatements.org/vocab/InC-EDU/1.0/ genetics genomics harvest management sibship reconstruction wolves Bioinformatics Text 2019 ftunividahodc 2023-10-27T10:31:02Z Parameters of reproductive success are critical to the management of wildlife populations. Genetic monitoring can provide this demographic information when traditional methods aren’t tractable. This study demonstrates a novel application of genetic data to estimate a minimum annual count of breeding packs of gray wolves (Canis lupus). Using tissue samples from wolves harvested in Idaho, 98 young of the year from 2015 and 205 from 2016 were genotyped at 18 microsatellite loci. Sibling groups for each cohort were reconstructed using COLONY, with full-sibling litters corresponding to unique packs. To assess the accuracy of relationship assignments, young of the year of known relationship from long-term study packs were added to the dataset (61 individuals from 2015 and 45 from 2016). Varied input parameters were used to evaluate the power of relationship assignments under real-world data constraints, providing insight into the use of sibship reconstruction as a tool to meet monitoring goals. Though all known relationship were correctly identified under these conditions, the number and size of assigned subgroups varied. Notably, the ability to discern between closely related non-siblings was diminished when the number of loci was reduced from 18 to 10. To further explore the impacts of different genotype data, we used RADseq to identify thousands of single nucleotide polymorphism (SNP) loci and repeated sibship analyses for 50 gray wolf YOY from 2014. Our results indicated that sibship analyses using SNP loci may be limited by missing data caused by DNA quality and quantity, and that strict filtering may yield inconsistent results. SNP and microsatellite datasets were generally concordant but produced some discrepancies in sibship assignments. To compare SNP-based sibship estimates against known relationships, we have also generated RADseq-derived SNPs in an analogous group of 86 red wolf (Canis rufus) YOY of known pedigree. Though the use of SNPs is increasing in genetic monitoring of wildlife, the strengths and ... Text Canis lupus gray wolf University of Idaho Library: Digital Initiatives
institution Open Polar
collection University of Idaho Library: Digital Initiatives
op_collection_id ftunividahodc
language English
topic genetics
genomics
harvest
management
sibship reconstruction
wolves
Bioinformatics
spellingShingle genetics
genomics
harvest
management
sibship reconstruction
wolves
Bioinformatics
Clendenin, Heather Rose
Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
topic_facet genetics
genomics
harvest
management
sibship reconstruction
wolves
Bioinformatics
description Parameters of reproductive success are critical to the management of wildlife populations. Genetic monitoring can provide this demographic information when traditional methods aren’t tractable. This study demonstrates a novel application of genetic data to estimate a minimum annual count of breeding packs of gray wolves (Canis lupus). Using tissue samples from wolves harvested in Idaho, 98 young of the year from 2015 and 205 from 2016 were genotyped at 18 microsatellite loci. Sibling groups for each cohort were reconstructed using COLONY, with full-sibling litters corresponding to unique packs. To assess the accuracy of relationship assignments, young of the year of known relationship from long-term study packs were added to the dataset (61 individuals from 2015 and 45 from 2016). Varied input parameters were used to evaluate the power of relationship assignments under real-world data constraints, providing insight into the use of sibship reconstruction as a tool to meet monitoring goals. Though all known relationship were correctly identified under these conditions, the number and size of assigned subgroups varied. Notably, the ability to discern between closely related non-siblings was diminished when the number of loci was reduced from 18 to 10. To further explore the impacts of different genotype data, we used RADseq to identify thousands of single nucleotide polymorphism (SNP) loci and repeated sibship analyses for 50 gray wolf YOY from 2014. Our results indicated that sibship analyses using SNP loci may be limited by missing data caused by DNA quality and quantity, and that strict filtering may yield inconsistent results. SNP and microsatellite datasets were generally concordant but produced some discrepancies in sibship assignments. To compare SNP-based sibship estimates against known relationships, we have also generated RADseq-derived SNPs in an analogous group of 86 red wolf (Canis rufus) YOY of known pedigree. Though the use of SNPs is increasing in genetic monitoring of wildlife, the strengths and ...
author2 Waits, Lisette Rose; Hohenlohe, Paul Rose
format Text
author Clendenin, Heather Rose
author_facet Clendenin, Heather Rose
author_sort Clendenin, Heather Rose
title Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
title_short Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
title_full Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
title_fullStr Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
title_full_unstemmed Monitoring Wolf Packs by Counting Litters: Sibling Reconstruction from Genetics to Genomics
title_sort monitoring wolf packs by counting litters: sibling reconstruction from genetics to genomics
publishDate 2019
url http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/1262
genre Canis lupus
gray wolf
genre_facet Canis lupus
gray wolf
op_relation Clendenin_idaho_0089N_11493
http://digital.lib.uidaho.edu/cdm/ref/collection/etd/id/1262
op_rights http://rightsstatements.org/vocab/InC-EDU/1.0/
_version_ 1782333023958597632