Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals

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Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals. / Hellmann, Ines; Mang, Yuan; Gu, Zhiping; Li, Peter; de la Vega, Francisco M; Clark, Andrew G; Nielsen, Rasmus.

I: Genome Research, Bind 18, Nr. 7, 2008, s. 1020-9.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Hellmann, I, Mang, Y, Gu, Z, Li, P, de la Vega, FM, Clark, AG & Nielsen, R 2008, 'Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals', Genome Research, bind 18, nr. 7, s. 1020-9. https://doi.org/10.1101/gr.074187.107

APA

Hellmann, I., Mang, Y., Gu, Z., Li, P., de la Vega, F. M., Clark, A. G., & Nielsen, R. (2008). Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals. Genome Research, 18(7), 1020-9. https://doi.org/10.1101/gr.074187.107

Vancouver

Hellmann I, Mang Y, Gu Z, Li P, de la Vega FM, Clark AG o.a. Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals. Genome Research. 2008;18(7):1020-9. https://doi.org/10.1101/gr.074187.107

Author

Hellmann, Ines ; Mang, Yuan ; Gu, Zhiping ; Li, Peter ; de la Vega, Francisco M ; Clark, Andrew G ; Nielsen, Rasmus. / Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals. I: Genome Research. 2008 ; Bind 18, Nr. 7. s. 1020-9.

Bibtex

@article{94e74370e6eb11ddbf70000ea68e967b,
title = "Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals",
abstract = "We introduce a simple, broadly applicable method for obtaining estimates of nucleotide diversity from genomic shotgun sequencing data. The method takes into account the special nature of these data: random sampling of genomic segments from one or more individuals and a relatively high error rate for individual reads. Applying this method to data from the Celera human genome sequencing and SNP discovery project, we obtain estimates of nucleotide diversity in windows spanning the human genome and show that the diversity to divergence ratio is reduced in regions of low recombination. Furthermore, we show that the elevated diversity in telomeric regions is mainly due to elevated mutation rates and not due to decreased levels of background selection. However, we find indications that telomeres as well as centromeres experience greater impact from natural selection than intrachromosomal regions. Finally, we identify a number of genomic regions with increased or reduced diversity compared with the local level of human-chimpanzee divergence and the local recombination rate.",
author = "Ines Hellmann and Yuan Mang and Zhiping Gu and Peter Li and {de la Vega}, {Francisco M} and Clark, {Andrew G} and Rasmus Nielsen",
note = "Keywords: Animals; Genetic Variation; Genetics, Population; Genome, Human; Humans; Likelihood Functions; Models, Genetic; Pan troglodytes; Polymorphism, Single Nucleotide; Sequence Analysis, DNA",
year = "2008",
doi = "10.1101/gr.074187.107",
language = "English",
volume = "18",
pages = "1020--9",
journal = "Genome Research",
issn = "1088-9051",
publisher = "Cold Spring Harbor Laboratory Press",
number = "7",

}

RIS

TY - JOUR

T1 - Population genetic analysis of shotgun assemblies of genomic sequences from multiple individuals

AU - Hellmann, Ines

AU - Mang, Yuan

AU - Gu, Zhiping

AU - Li, Peter

AU - de la Vega, Francisco M

AU - Clark, Andrew G

AU - Nielsen, Rasmus

N1 - Keywords: Animals; Genetic Variation; Genetics, Population; Genome, Human; Humans; Likelihood Functions; Models, Genetic; Pan troglodytes; Polymorphism, Single Nucleotide; Sequence Analysis, DNA

PY - 2008

Y1 - 2008

N2 - We introduce a simple, broadly applicable method for obtaining estimates of nucleotide diversity from genomic shotgun sequencing data. The method takes into account the special nature of these data: random sampling of genomic segments from one or more individuals and a relatively high error rate for individual reads. Applying this method to data from the Celera human genome sequencing and SNP discovery project, we obtain estimates of nucleotide diversity in windows spanning the human genome and show that the diversity to divergence ratio is reduced in regions of low recombination. Furthermore, we show that the elevated diversity in telomeric regions is mainly due to elevated mutation rates and not due to decreased levels of background selection. However, we find indications that telomeres as well as centromeres experience greater impact from natural selection than intrachromosomal regions. Finally, we identify a number of genomic regions with increased or reduced diversity compared with the local level of human-chimpanzee divergence and the local recombination rate.

AB - We introduce a simple, broadly applicable method for obtaining estimates of nucleotide diversity from genomic shotgun sequencing data. The method takes into account the special nature of these data: random sampling of genomic segments from one or more individuals and a relatively high error rate for individual reads. Applying this method to data from the Celera human genome sequencing and SNP discovery project, we obtain estimates of nucleotide diversity in windows spanning the human genome and show that the diversity to divergence ratio is reduced in regions of low recombination. Furthermore, we show that the elevated diversity in telomeric regions is mainly due to elevated mutation rates and not due to decreased levels of background selection. However, we find indications that telomeres as well as centromeres experience greater impact from natural selection than intrachromosomal regions. Finally, we identify a number of genomic regions with increased or reduced diversity compared with the local level of human-chimpanzee divergence and the local recombination rate.

U2 - 10.1101/gr.074187.107

DO - 10.1101/gr.074187.107

M3 - Journal article

C2 - 18411405

VL - 18

SP - 1020

EP - 1029

JO - Genome Research

JF - Genome Research

SN - 1088-9051

IS - 7

ER -

ID: 9855418