Cargando…

An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile

RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing covera...

Descripción completa

Detalles Bibliográficos
Autores principales: Prakash, Celine, Haeseler, Arndt Von
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Mary Ann Liebert, Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346924/
https://www.ncbi.nlm.nih.gov/pubmed/27661099
http://dx.doi.org/10.1089/cmb.2016.0096
_version_ 1782513975876911104
author Prakash, Celine
Haeseler, Arndt Von
author_facet Prakash, Celine
Haeseler, Arndt Von
author_sort Prakash, Celine
collection PubMed
description RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing coverage across a genomic feature has been a concern in RNA-seq and is attributed to biases for certain fragments in RNA-seq library preparation and sequencing. To investigate the expected coverage obtained from fragmentation, we develop a simple fragmentation model that is independent of bias from the experimental method and is not specific to the transcript sequence. Essentially, we enumerate all configurations for maximal placement of a given fragment length, F, on transcript length, T, to represent every possible fragmentation pattern, from which we compute the expected coverage profile across a transcript. We extend this model to incorporate general empirical attributes such as read length, fragment length distribution, and number of molecules of the transcript. We further introduce the fragment starting-point, fragment coverage, and read coverage profiles. We find that the expected profiles are not uniform and that factors such as fragment length to transcript length ratio, read length to fragment length ratio, fragment length distribution, and number of molecules influence the variability of coverage across a transcript. Finally, we explore a potential application of the model where, with simulations, we show that it is possible to correctly estimate the transcript copy number for any transcript in the RNA-seq experiment.
format Online
Article
Text
id pubmed-5346924
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Mary Ann Liebert, Inc.
record_format MEDLINE/PubMed
spelling pubmed-53469242017-03-13 An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile Prakash, Celine Haeseler, Arndt Von J Comput Biol Research Articles RNA sequencing (RNA-seq) has emerged as the method of choice for measuring the expression of RNAs in a given cell population. In most RNA-seq technologies, sequencing the full length of RNA molecules requires fragmentation into smaller pieces. Unfortunately, the issue of nonuniform sequencing coverage across a genomic feature has been a concern in RNA-seq and is attributed to biases for certain fragments in RNA-seq library preparation and sequencing. To investigate the expected coverage obtained from fragmentation, we develop a simple fragmentation model that is independent of bias from the experimental method and is not specific to the transcript sequence. Essentially, we enumerate all configurations for maximal placement of a given fragment length, F, on transcript length, T, to represent every possible fragmentation pattern, from which we compute the expected coverage profile across a transcript. We extend this model to incorporate general empirical attributes such as read length, fragment length distribution, and number of molecules of the transcript. We further introduce the fragment starting-point, fragment coverage, and read coverage profiles. We find that the expected profiles are not uniform and that factors such as fragment length to transcript length ratio, read length to fragment length ratio, fragment length distribution, and number of molecules influence the variability of coverage across a transcript. Finally, we explore a potential application of the model where, with simulations, we show that it is possible to correctly estimate the transcript copy number for any transcript in the RNA-seq experiment. Mary Ann Liebert, Inc. 2017-03-01 2017-03-01 /pmc/articles/PMC5346924/ /pubmed/27661099 http://dx.doi.org/10.1089/cmb.2016.0096 Text en © Celine Prakash and Arndt Von Haeseler, 2016. Published by Mary Ann Liebert, Inc. This Open Access article is distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.
spellingShingle Research Articles
Prakash, Celine
Haeseler, Arndt Von
An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title_full An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title_fullStr An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title_full_unstemmed An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title_short An Enumerative Combinatorics Model for Fragmentation Patterns in RNA Sequencing Provides Insights into Nonuniformity of the Expected Fragment Starting-Point and Coverage Profile
title_sort enumerative combinatorics model for fragmentation patterns in rna sequencing provides insights into nonuniformity of the expected fragment starting-point and coverage profile
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346924/
https://www.ncbi.nlm.nih.gov/pubmed/27661099
http://dx.doi.org/10.1089/cmb.2016.0096
work_keys_str_mv AT prakashceline anenumerativecombinatoricsmodelforfragmentationpatternsinrnasequencingprovidesinsightsintononuniformityoftheexpectedfragmentstartingpointandcoverageprofile
AT haeselerarndtvon anenumerativecombinatoricsmodelforfragmentationpatternsinrnasequencingprovidesinsightsintononuniformityoftheexpectedfragmentstartingpointandcoverageprofile
AT prakashceline enumerativecombinatoricsmodelforfragmentationpatternsinrnasequencingprovidesinsightsintononuniformityoftheexpectedfragmentstartingpointandcoverageprofile
AT haeselerarndtvon enumerativecombinatoricsmodelforfragmentationpatternsinrnasequencingprovidesinsightsintononuniformityoftheexpectedfragmentstartingpointandcoverageprofile