2022
DOI: 10.3389/fevo.2022.970249
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Assessing the performance of historical skins and bones for museomics using wolf specimens as a case study

Abstract: Advances in the field of museomics have promoted a high sampling demand for natural history collections (NHCs), eventually resulting in damage to invaluable resources to understand historical biodiversity. It is thus essential to achieve a consensus about which historical tissues present the best sources of DNA. In this study, we evaluated the performance of different historical tissues from Iberian wolf NHCs in genome-wide assessments. We targeted three tissues—bone (jaw and femur), maxilloturbinal bone, and … Show more

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Cited by 4 publications
(4 citation statements)
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“…Genotype calling was performed using GenomeStudio software (Illumina) following Illumina's recommendations. Additionally, we leveraged the availability of a comprehensive genome‐wide data set of 145 historical putative wolf samples genotyped for 100,000 genome‐wide SNPs targeted based on the Canine SNP chip, using an in‐solution target capture enrichment approach (Pacheco, Lobo, et al., 2022; Table S1). All individuals in our data set are not directly related to each other (identity‐by‐descent <0.5, following Galaverni et al.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Genotype calling was performed using GenomeStudio software (Illumina) following Illumina's recommendations. Additionally, we leveraged the availability of a comprehensive genome‐wide data set of 145 historical putative wolf samples genotyped for 100,000 genome‐wide SNPs targeted based on the Canine SNP chip, using an in‐solution target capture enrichment approach (Pacheco, Lobo, et al., 2022; Table S1). All individuals in our data set are not directly related to each other (identity‐by‐descent <0.5, following Galaverni et al.…”
Section: Methodsmentioning
confidence: 99%
“…Additionally, we leveraged the availability of a comprehensive genome-wide data set of 145 historical putative wolf samples genotyped for 100,000 genome-wide SNPs targeted based on the Canine SNP chip, using an in-solution target capture enrichment approach (Pacheco, Lobo, et al, 2022; Table S1). All individuals in our data set are not directly related to each other (identity-bydescent <0.5, following Galaverni et al (2017); IBD estimated in PLINK v.1.9 using the -genome function following PLINK's guidelines; Purcell et al, 2007).…”
Section: Contemporary and Historical Snp Data Setmentioning
confidence: 99%
“…Thus far, the majority of research investigating how to maximize the recovery of genetic data from non-ancient museum specimens has focused on the influence of DNA source or extraction method on DNA yield (Hahn et al, 2022; Hawkins, Flores, McGowen, & Hinckley, 2022; McDonough et al, 2018; Pacheco et al, 2022; Straube et al, 2021; Tsai et al, 2020; Zacho et al, 2021). However, DNA yield does not necessarily predict sequencing success or efficiency (McDonough et al, 2018; Straube et al, 2021; Zacho et al, 2021) because it is not possible to estimate the proportions of endogenous versus exogenous extracted DNA.…”
Section: Introductionmentioning
confidence: 99%
“…Thus far, the majority of research investigating how to maximize the recovery of genetic data from non‐ancient museum specimens has focused on the influence of DNA source or extraction method on DNA yield (Hahn et al, 2022 ; Hawkins et al, 2022 ; McDonough et al, 2018 ; Pacheco et al, 2022 ; Straube et al, 2021 ; Tsai et al, 2020 ; Zacho et al, 2021 ). However, DNA yield does not necessarily predict sequencing success or efficiency (McDonough et al, 2018 ; Straube et al, 2021 ; Zacho et al, 2021 ) because it is not possible to estimate the proportions of endogenous versus exogenous extracted DNA.…”
Section: Introductionmentioning
confidence: 99%