Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Standard

Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data. / Nursyifa, Casia; Brüniche-Olsen, Anna; Garcia-Erill, Genis ; Heller, Rasmus; Albrechtsen, Anders.

I: Molecular Ecology Resources, Bind 22, Nr. 2, 2022, s. 458-467.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Nursyifa, C, Brüniche-Olsen, A, Garcia-Erill, G, Heller, R & Albrechtsen, A 2022, 'Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data', Molecular Ecology Resources, bind 22, nr. 2, s. 458-467. https://doi.org/10.1111/1755-0998.13491

APA

Nursyifa, C., Brüniche-Olsen, A., Garcia-Erill, G., Heller, R., & Albrechtsen, A. (2022). Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data. Molecular Ecology Resources, 22(2), 458-467. https://doi.org/10.1111/1755-0998.13491

Vancouver

Nursyifa C, Brüniche-Olsen A, Garcia-Erill G, Heller R, Albrechtsen A. Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data. Molecular Ecology Resources. 2022;22(2):458-467. https://doi.org/10.1111/1755-0998.13491

Author

Nursyifa, Casia ; Brüniche-Olsen, Anna ; Garcia-Erill, Genis ; Heller, Rasmus ; Albrechtsen, Anders. / Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data. I: Molecular Ecology Resources. 2022 ; Bind 22, Nr. 2. s. 458-467.

Bibtex

@article{f38b0a76808f48baab261692e7df2858,
title = "Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data",
abstract = "Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold-level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on synteny between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here, we present “sex assignment through coverage” (SATC), a method to assign sex to samples and identify sex-linked scaffolds from next generation sequencing (NGS) data. The method works for species with a homogametic/heterogametic sex determination system and only requires a scaffold-level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: (i) male and female individuals, and (ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is freely available at https://github.com/popgenDK/SATC as R code and a graphical user interface (GUI).",
author = "Casia Nursyifa and Anna Br{\"u}niche-Olsen and Genis Garcia-Erill and Rasmus Heller and Anders Albrechtsen",
year = "2022",
doi = "10.1111/1755-0998.13491",
language = "English",
volume = "22",
pages = "458--467",
journal = "Molecular Ecology",
issn = "0962-1083",
publisher = "Wiley-Blackwell",
number = "2",

}

RIS

TY - JOUR

T1 - Joint identification of sex and sex-linked scaffolds in non-model organisms using low depth sequencing data

AU - Nursyifa, Casia

AU - Brüniche-Olsen, Anna

AU - Garcia-Erill, Genis

AU - Heller, Rasmus

AU - Albrechtsen, Anders

PY - 2022

Y1 - 2022

N2 - Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold-level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on synteny between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here, we present “sex assignment through coverage” (SATC), a method to assign sex to samples and identify sex-linked scaffolds from next generation sequencing (NGS) data. The method works for species with a homogametic/heterogametic sex determination system and only requires a scaffold-level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: (i) male and female individuals, and (ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is freely available at https://github.com/popgenDK/SATC as R code and a graphical user interface (GUI).

AB - Being able to assign sex to individuals and identify autosomal and sex-linked scaffolds are essential in most population genomic analyses. Non-model organisms often have genome assemblies at scaffold-level and lack characterization of sex-linked scaffolds. Previous methods to identify sex and sex-linked scaffolds have relied on synteny between the non-model organism and a closely related species or prior knowledge about the sex of the samples to identify sex-linked scaffolds. In the latter case, the difference in depth of coverage between the autosomes and the sex chromosomes are used. Here, we present “sex assignment through coverage” (SATC), a method to assign sex to samples and identify sex-linked scaffolds from next generation sequencing (NGS) data. The method works for species with a homogametic/heterogametic sex determination system and only requires a scaffold-level reference assembly and sampling of both sexes with whole genome sequencing (WGS) data. We use the sequencing depth distribution across scaffolds to jointly identify: (i) male and female individuals, and (ii) sex-linked scaffolds. This is achieved through projecting the scaffold depths into a low-dimensional space using principal component analysis (PCA) and subsequent Gaussian mixture clustering. We demonstrate the applicability of our method using data from five mammal species and a bird species complex. The method is freely available at https://github.com/popgenDK/SATC as R code and a graphical user interface (GUI).

U2 - 10.1111/1755-0998.13491

DO - 10.1111/1755-0998.13491

M3 - Journal article

C2 - 34431216

VL - 22

SP - 458

EP - 467

JO - Molecular Ecology

JF - Molecular Ecology

SN - 0962-1083

IS - 2

ER -

ID: 279348408