scispace - formally typeset
Open AccessJournal ArticleDOI

A neutral model of transcriptome evolution.

Reads0
Chats0
TLDR
The results suggest that the majority of expression differences observed between species are selectively neutral or nearly neutral and likely to be of little or no functional significance, which should be based on null hypotheses assuming functional neutrality.
Abstract
Microarray technologies allow the identification of large numbers of expression differences within and between species. Although environmental and physiological stimuli are clearly responsible for changes in the expression levels of many genes, it is not known whether the majority of changes of gene expression fixed during evolution between species and between various tissues within a species are caused by Darwinian selection or by stochastic processes. We find the following: (1) expression differences between species accumulate approximately linearly with time; (2) gene expression variation among individuals within a species correlates positively with expression divergence between species; (3) rates of expression divergence between species do not differ significantly between intact genes and expressed pseudogenes; (4) expression differences between brain regions within a species have accumulated approximately linearly with time since these regions emerged during evolution. These results suggest that the majority of expression differences observed between species are selectively neutral or nearly neutral and likely to be of little or no functional significance. Therefore, the identification of gene expression differences between species fixed by selection should be based on null hypotheses assuming functional neutrality. Furthermore, it may be possible to apply a molecular clock based on expression differences to infer the evolutionary history of tissues.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Genome-wide midrange transcription profiles reveal expression level relationships in human tissue specification

TL;DR: The analyses provide a novel route to infer expression profiles for presumed ancestral nodes in the tissue dendrogram, whereby de novo enhancement and diminution of gene expression go hand in hand, and highlight the importance of gene suppression events.
Journal ArticleDOI

Functional organization of the transcriptome in human brain

TL;DR: This work analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astroCytes and microglia, providing an initial description of the transcriptional programs that distinguish the major cell classes of the human brain.
Journal ArticleDOI

Conservation and evolution of gene coexpression networks in human and chimpanzee brains

TL;DR: This work identifies modules of coexpressed genes that correspond to discrete brain regions and quantify their conservation between the species and introduces a method for identifying species-specific network connections and demonstrates how differential network connectivity can be used to identify key drivers of evolutionary change.
Journal ArticleDOI

Comparative studies of gene expression and the evolution of gene regulation.

TL;DR: Comparative studies in primates and how they are complemented by studies in model organisms are focused on to link gene regulatory changes to adaptive evolution of complex phenotypes.
Journal ArticleDOI

Neutral and adaptive variation in gene expression.

TL;DR: These analyses measure the expression of metabolic genes in common-gardened populations of the fish Fundulus heteroclitus whose habitat is distributed along a steep thermal gradient and identify genes evolving by natural selection.
References
More filters
Journal ArticleDOI

Initial sequencing and analysis of the human genome.

Eric S. Lander, +248 more
- 15 Feb 2001 - 
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Journal ArticleDOI

R: A Language for Data Analysis and Graphics

TL;DR: In this article, the authors discuss their experience designing and implementing a statistical computing language, which combines what they felt were useful features from two existing computer languages, and they feel that the new language provides advantages in the areas of portability, computational efficiency, memory management, and scope.
Book

Principles of Neural Science

TL;DR: The principles of neural science as mentioned in this paper have been used in neural networks for the purpose of neural network engineering and neural networks have been applied in the field of neural networks, such as:
Journal ArticleDOI

BLAT—The BLAST-Like Alignment Tool

TL;DR: How BLAT was optimized is described, which is more accurate and 500 times faster than popular existing tools for mRNA/DNA alignments and 50 times faster for protein alignments at sensitivity settings typically used when comparing vertebrate sequences.
Journal ArticleDOI

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

TL;DR: Three methods of performing normalization at the probe intensity level are presented: a one number scaling based algorithm and a method that uses a non-linear normalizing relation by comparing the variability and bias of an expression measure and the simplest and quickest complete data method is found to perform favorably.
Related Papers (5)