Searching the Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

 PMID:29858274  

Human long intrinsically disordered protein regions are frequent targets of positive selection.

Arina Afanasyeva | Mathias Bockwoldt | Christopher R Cooney | Ines Heiland | Toni I Gossmann
Genome research | 2018

Intrinsically disordered regions occur frequently in proteins and are characterized by a lack of a well-defined three-dimensional structure. Although these regions do not show a higher order of structural organization, they are known to be functionally important. Disordered regions are rapidly evolving, largely attributed to relaxed purifying selection and an increased role of genetic drift. It has also been suggested that positive selection might contribute to their rapid diversification. However, for our own species, it is currently unknown whether positive selection has played a role during the evolution of these protein regions. Here, we address this question by investigating the evolutionary pattern of more than 6600 human proteins with intrinsically disordered regions and their ordered counterparts. Our comparative approach with data from more than 90 mammalian genomes uses a priori knowledge of disordered protein regions, and we show that this increases the power to detect positive selection by an order of magnitude. We can confirm that human intrinsically disordered regions evolve more rapidly, not only within humans but also across the entire mammalian phylogeny. They have, however, experienced substantial evolutionary constraint, hinting at their fundamental functional importance. We find compelling evidence that disordered protein regions are frequent targets of positive selection and estimate that the relative rate of adaptive substitutions differs fourfold between disordered and ordered protein regions in humans. Our results suggest that disordered protein regions are important targets of genetic innovation and that the contribution of positive selection in these regions is more pronounced than in other protein parts.

Pubmed ID: 29858274

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

None found

Associated grants

None

Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


1000 Genomes Project and AWS (tool)

RRID:SCR_008801

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

View all literature mentions

MobiDB (tool)

RRID:SCR_014542

A database of protein disorder and mobility annotations. The database features three levels of annotation: manually curated data (which are extracted from the DisProt database), indirect data, and predicted data. Additional annotations are included from external sources, including UniProt, Pfam, PDB, and STRING.

View all literature mentions