The Experts below are selected from a list of 1755 Experts worldwide ranked by ideXlab platform

Aaron B A Shafer - One of the best experts on this subject based on the ideXlab platform.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single nucleotide polymorphism (SNP) data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from >10,000 SNPs: hind foot length, dressed body mass and Peroneus Muscle mass had high h2 values of 0.62, 0.44 and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33 and had high standard errors. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits should respond to selection.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and Peroneus Muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.

Joseph M Northrup - One of the best experts on this subject based on the ideXlab platform.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single nucleotide polymorphism (SNP) data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from >10,000 SNPs: hind foot length, dressed body mass and Peroneus Muscle mass had high h2 values of 0.62, 0.44 and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33 and had high standard errors. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits should respond to selection.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and Peroneus Muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.

Aidan Jamieson - One of the best experts on this subject based on the ideXlab platform.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single nucleotide polymorphism (SNP) data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from >10,000 SNPs: hind foot length, dressed body mass and Peroneus Muscle mass had high h2 values of 0.62, 0.44 and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33 and had high standard errors. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits should respond to selection.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and Peroneus Muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.

Jeremie Fuller - One of the best experts on this subject based on the ideXlab platform.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single nucleotide polymorphism (SNP) data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from >10,000 SNPs: hind foot length, dressed body mass and Peroneus Muscle mass had high h2 values of 0.62, 0.44 and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33 and had high standard errors. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits should respond to selection.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and Peroneus Muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.

Steeve D Cote - One of the best experts on this subject based on the ideXlab platform.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and genome-wide single nucleotide polymorphism (SNP) data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated classic and robust GRMs from >10,000 SNPs: hind foot length, dressed body mass and Peroneus Muscle mass had high h2 values of 0.62, 0.44 and 0.55, respectively. Heritability in male-only antler features ranged from 0.07 to 0.33 and had high standard errors. We explored the influence of filtering by minor allele frequency and data completion on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs, specifically many unrelated individuals, can increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management as these traits should respond to selection.

  • heritability estimates of antler and body traits in white tailed deer odocoileus virginianus from genomic relatedness matrices
    2020
    Co-Authors: Aidan Jamieson, Spencer J Anderson, Jeremie Fuller, Steeve D Cote, Joseph M Northrup, Aaron B A Shafer
    Abstract:

    Estimating heritability (h2) is required to predict the response to selection and is useful in species that are managed or farmed using trait information. Estimating h2 in free-ranging populations is challenging due to the need for pedigrees; genomic-relatedness matrices (GRMs) circumvent this need and can be implemented in nearly any system where phenotypic and SNP data are available. We estimated the heritability of five body and three antler traits in a free-ranging population of white-tailed deer (Odocoileus virginianus) on Anticosti Island, Quebec, Canada. We generated GRMs from >10,000 SNPs: dressed body mass and Peroneus Muscle mass had moderate h2 values of 0.49 and 0.56, respectively. Heritability in male-only antler features ranged from 0.00 to 0.51 and had high standard errors. We explored the influence of minor allele frequency and data completion filters on h2: GRMs derived from fewer SNPs had reduced h2 estimates and the relatedness coefficients significantly deviated from those generated with more SNPs. As a corollary, we discussed limitations to the application of GRMs in the wild, notably how skewed GRMs increase variance around h2 estimates. This is the first study to estimate h2 on a free-ranging population of white-tailed deer and should be informative for breeding designs and management.