Systematic clustering of transcription start site landscapes.

Genome-wide, high-throughput methods for transcription start site (TSS) detection have shown that most promoters have an array of neighboring TSSs where some are used more than others, forming a distribution of initiation propensities. TSS distributions (TSSDs) vary widely between promoters and earl...

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Autores principales:	Xiaobei Zhao, Eivind Valen, Brian J Parker, Albin Sandelin
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8143a7e7bf684957be8cdc3c01b7aa82
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spelling	oai:doaj.org-article:8143a7e7bf684957be8cdc3c01b7aa822021-11-18T06:47:24ZSystematic clustering of transcription start site landscapes.1932-620310.1371/journal.pone.0023409https://doaj.org/article/8143a7e7bf684957be8cdc3c01b7aa822011-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21887249/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Genome-wide, high-throughput methods for transcription start site (TSS) detection have shown that most promoters have an array of neighboring TSSs where some are used more than others, forming a distribution of initiation propensities. TSS distributions (TSSDs) vary widely between promoters and earlier studies have shown that the TSSDs have biological implications in both regulation and function. However, no systematic study has been made to explore how many types of TSSDs and by extension core promoters exist and to understand which biological features distinguish them. In this study, we developed a new non-parametric dissimilarity measure and clustering approach to explore the similarities and stabilities of clusters of TSSDs. Previous studies have used arbitrary thresholds to arrive at two general classes: broad and sharp. We demonstrated that in addition to the previous broad/sharp dichotomy an additional category of promoters exists. Unlike typical TATA-driven sharp TSSDs where the TSS position can vary a few nucleotides, in this category virtually all TSSs originate from the same genomic position. These promoters lack epigenetic signatures of typical mRNA promoters and a substantial subset of them are mapping upstream of ribosomal protein pseudogenes. We present evidence that these are likely mapping errors, which have confounded earlier analyses, due to the high similarity of ribosomal gene promoters in combination with known G addition bias in the CAGE libraries. Thus, previous two-class separations of promoter based on TSS distributions are motivated, but the ultra-sharp TSS distributions will confound downstream analyses if not removed.Xiaobei ZhaoEivind ValenBrian J ParkerAlbin SandelinPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 8, p e23409 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xiaobei Zhao Eivind Valen Brian J Parker Albin Sandelin Systematic clustering of transcription start site landscapes.
description	Genome-wide, high-throughput methods for transcription start site (TSS) detection have shown that most promoters have an array of neighboring TSSs where some are used more than others, forming a distribution of initiation propensities. TSS distributions (TSSDs) vary widely between promoters and earlier studies have shown that the TSSDs have biological implications in both regulation and function. However, no systematic study has been made to explore how many types of TSSDs and by extension core promoters exist and to understand which biological features distinguish them. In this study, we developed a new non-parametric dissimilarity measure and clustering approach to explore the similarities and stabilities of clusters of TSSDs. Previous studies have used arbitrary thresholds to arrive at two general classes: broad and sharp. We demonstrated that in addition to the previous broad/sharp dichotomy an additional category of promoters exists. Unlike typical TATA-driven sharp TSSDs where the TSS position can vary a few nucleotides, in this category virtually all TSSs originate from the same genomic position. These promoters lack epigenetic signatures of typical mRNA promoters and a substantial subset of them are mapping upstream of ribosomal protein pseudogenes. We present evidence that these are likely mapping errors, which have confounded earlier analyses, due to the high similarity of ribosomal gene promoters in combination with known G addition bias in the CAGE libraries. Thus, previous two-class separations of promoter based on TSS distributions are motivated, but the ultra-sharp TSS distributions will confound downstream analyses if not removed.
format	article
author	Xiaobei Zhao Eivind Valen Brian J Parker Albin Sandelin
author_facet	Xiaobei Zhao Eivind Valen Brian J Parker Albin Sandelin
author_sort	Xiaobei Zhao
title	Systematic clustering of transcription start site landscapes.
title_short	Systematic clustering of transcription start site landscapes.
title_full	Systematic clustering of transcription start site landscapes.
title_fullStr	Systematic clustering of transcription start site landscapes.
title_full_unstemmed	Systematic clustering of transcription start site landscapes.
title_sort	systematic clustering of transcription start site landscapes.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/8143a7e7bf684957be8cdc3c01b7aa82
work_keys_str_mv	AT xiaobeizhao systematicclusteringoftranscriptionstartsitelandscapes AT eivindvalen systematicclusteringoftranscriptionstartsitelandscapes AT brianjparker systematicclusteringoftranscriptionstartsitelandscapes AT albinsandelin systematicclusteringoftranscriptionstartsitelandscapes
_version_	1718424425304424448

Systematic clustering of transcription start site landscapes.

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