Functional Evolution of a cis-Regulatory Module

Ludwig, Michael Z.; Pálsson, Arnar; Alekseeva, Elena; Bergman, Casey M.; Nathan, Janaki; Kreitman, Martin

doi:10.1371/journal.pbio.0030093

ScienceOpen: research and publishing network

For Publishers

For Researchers

Blog
About

Search
Advanced search

views

recommends

Record: found
Abstract: found
Article: not found

Functional Evolution of a cis-Regulatory Module

research-article

Author(s): Michael Z Ludwig ¹ ^, , Arnar Palsson ¹ , Elena Alekseeva ¹ , Casey M Bergman ² , Janaki Nathan ¹ , Martin Kreitman ¹

Editor(s): Michael Levine

Publication date (Electronic): 15 March 2005

Journal: PLoS Biology

Publisher: Public Library of Science

Read this article at

ScienceOpenPublisher PMC

Bookmark

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Lack of knowledge about how regulatory regions evolve in relation to their structure–function may limit the utility of comparative sequence analysis in deciphering cis-regulatory sequences. To address this we applied reverse genetics to carry out a functional genetic complementation analysis of a eukaryotic cis-regulatory module—the even-skipped stripe 2 enhancer—from four Drosophila species. The evolution of this enhancer is non-clock-like, with important functional differences between closely related species and functional convergence between distantly related species. Functional divergence is attributable to differences in activation levels rather than spatiotemporal control of gene expression. Our findings have implications for understanding enhancer structure–function, mechanisms of speciation and computational identification of regulatory modules.

Abstract

Analysis of the even-skipped stripe 2 enhancer from four Drosophila species revealed that functional divergence is attributable to differences in activation levels rather than spatiotemporal control of gene expression

Related collections

Most cited references 38

Record: found
Abstract: not found
Book: not found

Introduction to Quantitative Genetics

D. S. Falconer (1996)

0 comments Cited 1093 times – based on 0 reviews

Bookmark

Record: found
Abstract: found
Article: not found

Evolutionary changes in cis and trans gene regulation.

Patricia J. Wittkopp, Belinda K Haerum, Andrew Clark (2004)

Differences in gene expression are central to evolution. Such differences can arise from cis-regulatory changes that affect transcription initiation, transcription rate and/or transcript stability in an allele-specific manner, or from trans-regulatory changes that modify the activity or expression of factors that interact with cis-regulatory sequences. Both cis- and trans-regulatory changes contribute to divergent gene expression, but their respective contributions remain largely unknown. Here we examine the distribution of cis- and trans-regulatory changes underlying expression differences between closely related Drosophila species, D. melanogaster and D. simulans, and show functional cis-regulatory differences by comparing the relative abundance of species-specific transcripts in F1 hybrids. Differences in trans-regulatory activity were inferred by comparing the ratio of allelic expression in hybrids with the ratio of gene expression between species. Of 29 genes with interspecific expression differences, 28 had differences in cis-regulation, and these changes were sufficient to explain expression divergence for about half of the genes. Trans-regulatory differences affected 55% (16 of 29) of genes, and were always accompanied by cis-regulatory changes. These data indicate that interspecific expression differences are not caused by select trans-regulatory changes with widespread effects, but rather by many cis-acting changes spread throughout the genome.

0 comments Cited 362 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.

G Hertz, G Stormo (2015)

Molecular biologists frequently can obtain interesting insight by aligning a set of related DNA, RNA or protein sequences. Such alignments can be used to determine either evolutionary or functional relationships. Our interest is in identifying functional relationships. Unless the sequences are very similar, it is necessary to have a specific strategy for measuring-or scoring-the relatedness of the aligned sequences. If the alignment is not known, one can be determined by finding an alignment that optimizes the scoring scheme. We describe four components to our approach for determining alignments of multiple sequences. First, we review a log-likelihood scoring scheme we call information content. Second, we describe two methods for estimating the P value of an individual information content score: (i) a method that combines a technique from large-deviation statistics with numerical calculations; (ii) a method that is exclusively numerical. Third, we describe how we count the number of possible alignments given the overall amount of sequence data. This count is multiplied by the P value to determine the expected frequency of an information content score and, thus, the statistical significance of the corresponding alignment. Statistical significance can be used to compare alignments having differing widths and containing differing numbers of sequences. Fourth, we describe a greedy algorithm for determining alignments of functionally related sequences. Finally, we test the accuracy of our P value calculations, and give an example of using our algorithm to identify binding sites for the Escherichia coli CRP protein. Programs were developed under the UNIX operating system and are available by anonymous ftp from ftp://beagle.colorado.edu/pub/consensus.

0 comments Cited 267 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

: Role: Academic Editor

Journal

Journal ID (nlm-ta): PLoS Biol

Journal ID (publisher-id): pbio

Title: PLoS Biology

Publisher: Public Library of Science (San Francisco, USA )

ISSN (Print): 1544-9173

ISSN (Electronic): 1545-7885

Publication date (Print): April 2005

Publication date (Electronic): 15 March 2005

Volume: 3

Issue: 4

Electronic Location Identifier: e93

Affiliations

[1] 1Department of Ecology and Evolution, University of Chicago IllinoisUnited States of America

[2] 2Department of Genetics University of CambridgeUnited Kingdom

University of California, Berkeley United States of America

Article

DOI: 10.1371/journal.pbio.0030093

PMC ID: 1064851

PubMed ID: 15757364

SO-VID: 91af2de3-af73-4bc9-a974-da4052dbdf93

Copyright © Copyright: © 2005 Ludwig et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

History

Date received : 23 August 2004

Date accepted : 13 January 2005

Comments

Comment on this article

scite_

Smart Citations

Citing PublicationsSupportingMentioningContrasting

View Citations

See how this article has been cited at scite.ai

scite shows how a scientific paper has been cited by providing the context of the citation, a classification describing whether it supports, mentions, or contrasts the cited claim, and a label indicating in which section the citation was made.