Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism
Endogenous retroviruses (ERVs) are a class of transposable elements found in all vertebrate genomes that contribute substantially to genomic functional and structural diversity. A host species acquires an ERV when an exogenous retrovirus infects a germ cell of an individual and becomes part of the g...
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| Format: | Article |
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MDPI AG
2014-11-01
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| Series: | Computation |
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| Online Access: | http://www.mdpi.com/2079-3197/2/4/221 |
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| author | Le Bao Daniel Elleder Raunaq Malhotra Michael DeGiorgio Theodora Maravegias Lindsay Horvath Laura Carrel Colin Gillin Tomáš Hron Helena Fábryová David R. Hunter Mary Poss |
| author_facet | Le Bao Daniel Elleder Raunaq Malhotra Michael DeGiorgio Theodora Maravegias Lindsay Horvath Laura Carrel Colin Gillin Tomáš Hron Helena Fábryová David R. Hunter Mary Poss |
| author_sort | Le Bao |
| collection | DOAJ |
| description | Endogenous retroviruses (ERVs) are a class of transposable elements found in all vertebrate genomes that contribute substantially to genomic functional and structural diversity. A host species acquires an ERV when an exogenous retrovirus infects a germ cell of an individual and becomes part of the genome inherited by viable progeny. ERVs that colonized ancestral lineages are fixed in contemporary species. However, in some extant species, ERV colonization is ongoing, which results in variation in ERV frequency in the population. To study the consequences of ERV colonization of a host genome, methods are needed to assign each ERV to a location in a species’ genome and determine which individuals have acquired each ERV by descent. Because well annotated reference genomes are not widely available for all species, de novo clustering approaches provide an alternative to reference mapping that are insensitive to differences between query and reference and that are amenable to mobile element studies in both model and non-model organisms. However, there is substantial uncertainty in both identifying ERV genomic position and assigning each unique ERV integration site to individuals in a population. We present an analysis suitable for detecting ERV integration sites in species without the need for a reference genome. Our approach is based on improved de novo clustering methods and statistical models that take the uncertainty of assignment into account and yield a probability matrix of shared ERV integration sites among individuals. We demonstrate that polymorphic integrations of a recently identified endogenous retrovirus in deer reflect contemporary relationships among individuals and populations. |
| first_indexed | 2024-04-13T00:05:11Z |
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| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-04-13T00:05:11Z |
| publishDate | 2014-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-c8d23ac26268428fa8b85dc08ced99212022-12-22T03:11:15ZengMDPI AGComputation2079-31972014-11-012422124510.3390/computation2040221computation2040221Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model OrganismLe Bao0Daniel Elleder1Raunaq Malhotra2Michael DeGiorgio3Theodora Maravegias4Lindsay Horvath5Laura Carrel6Colin Gillin7Tomáš Hron8Helena Fábryová9David R. Hunter10Mary Poss11Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USAInstitute of Molecular Genetics, Academy of Sciences of the Czech Republic, Videnska 1083, Prague, Czech RepublicDepartment of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USADepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USADepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USADepartment of Pathology, Johns Hopkins University, Baltimore, MD 21287, USADepartment of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA 17033, USADepartment of Fish and Wildlife, 4034 Fairview Industrial Dr. S., Salem, OR 97302, USAInstitute of Molecular Genetics, Academy of Sciences of the Czech Republic, Videnska 1083, Prague, Czech RepublicInstitute of Molecular Genetics, Academy of Sciences of the Czech Republic, Videnska 1083, Prague, Czech RepublicDepartment of Statistics, The Pennsylvania State University, University Park, PA 16802, USADepartment of Biology, The Pennsylvania State University, University Park, PA 16802, USAEndogenous retroviruses (ERVs) are a class of transposable elements found in all vertebrate genomes that contribute substantially to genomic functional and structural diversity. A host species acquires an ERV when an exogenous retrovirus infects a germ cell of an individual and becomes part of the genome inherited by viable progeny. ERVs that colonized ancestral lineages are fixed in contemporary species. However, in some extant species, ERV colonization is ongoing, which results in variation in ERV frequency in the population. To study the consequences of ERV colonization of a host genome, methods are needed to assign each ERV to a location in a species’ genome and determine which individuals have acquired each ERV by descent. Because well annotated reference genomes are not widely available for all species, de novo clustering approaches provide an alternative to reference mapping that are insensitive to differences between query and reference and that are amenable to mobile element studies in both model and non-model organisms. However, there is substantial uncertainty in both identifying ERV genomic position and assigning each unique ERV integration site to individuals in a population. We present an analysis suitable for detecting ERV integration sites in species without the need for a reference genome. Our approach is based on improved de novo clustering methods and statistical models that take the uncertainty of assignment into account and yield a probability matrix of shared ERV integration sites among individuals. We demonstrate that polymorphic integrations of a recently identified endogenous retrovirus in deer reflect contemporary relationships among individuals and populations.http://www.mdpi.com/2079-3197/2/4/221endogenous retrovirusinsertional polymorphismmixture modelsde novo clusteringmule deerpopulation history |
| spellingShingle | Le Bao Daniel Elleder Raunaq Malhotra Michael DeGiorgio Theodora Maravegias Lindsay Horvath Laura Carrel Colin Gillin Tomáš Hron Helena Fábryová David R. Hunter Mary Poss Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism Computation endogenous retrovirus insertional polymorphism mixture models de novo clustering mule deer population history |
| title | Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism |
| title_full | Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism |
| title_fullStr | Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism |
| title_full_unstemmed | Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism |
| title_short | Computational and Statistical Analyses of Insertional Polymorphic Endogenous Retroviruses in a Non-Model Organism |
| title_sort | computational and statistical analyses of insertional polymorphic endogenous retroviruses in a non model organism |
| topic | endogenous retrovirus insertional polymorphism mixture models de novo clustering mule deer population history |
| url | http://www.mdpi.com/2079-3197/2/4/221 |
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