Analyses of Genome Regulatory Evolution Following Whole-Genome Duplication Using the Phylogenetic EVE Model

Whole-genome duplications (WGDs) are important in shaping the evolution of complex genomes, including rewiring of genome regulation. To address key questions about how WGDs impact the evolution of genome regulation, we need to understand the relative importance of selection versus drift and temporal evolutionary dynamics. One promising class of statistical models that can help address such questions are phylogenetic Ornstein-Uhlenbeck (OU) models.Here we present a computational pipeline for the comparative phylogenetic analyses of genome regulation using an OU model. We have implemented this model in R and provide a step-by-step protocol for the use of this model, including example scripts and simulated test data. We provide the nonspecialist a brief overview of how this model works and how to perform tests for signatures of selection on genome regulation as well as power simulations to aid in experimental design and interpretation of results. We believe that these resources could help polyploidy research move forward in an era of rapidly increasing functional genomics data across the tree of life.

Evolution of mouse circadian enhancers from transposable elements

BACKGROUND

Transposable elements are increasingly recognized as a source of cis-regulatory variation. Previous studies have revealed that transposons are often bound by transcription factors and some have been co-opted into functional enhancers regulating host gene expression. However, the process by which transposons mature into complex regulatory elements, like enhancers, remains poorly understood. To investigate this process, we examined the contribution of transposons to the cis-regulatory network controlling circadian gene expression in the mouse liver, a well-characterized network serving an important physiological function.

RESULTS

ChIP-seq analyses reveal that transposons and other repeats contribute ~ 14% of the binding sites for core circadian regulators (CRs) including BMAL1, CLOCK, PER1/2, and CRY1/2, in the mouse liver. RSINE1, an abundant murine-specific SINE, is the only transposon family enriched for CR binding sites across all datasets. Sequence analyses and reporter assays reveal that the circadian regulatory activity of RSINE1 stems from the presence of imperfect CR binding motifs in the ancestral RSINE1 sequence. These motifs matured into canonical motifs through point mutations after transposition. Furthermore, maturation occurred preferentially within elements inserted in the proximity of ancestral CR binding sites. RSINE1 also acquired motifs that recruit nuclear receptors known to cooperate with CRs to regulate circadian gene expression specifically in the liver.

CONCLUSIONS

Our results suggest that the birth of enhancers from transposons is predicated both by the sequence of the transposon and by the cis-regulatory landscape surrounding their genomic integration site.

LINE retrotransposons characterize mammalian tissue-specific and evolutionarily dynamic regulatory regions

BACKGROUND

To investigate the mechanisms driving regulatory evolution across tissues, we experimentally mapped promoters, enhancers, and gene expression in the liver, brain, muscle, and testis from ten diverse mammals.

RESULTS

The regulatory landscape around genes included both tissue-shared and tissue-specific regulatory regions, where tissue-specific promoters and enhancers evolved most rapidly. Genomic regions switching between promoters and enhancers were more common across species, and less common across tissues within a single species. Long Interspersed Nuclear Elements (LINEs) played recurrent evolutionary roles: LINE L1s were associated with tissue-specific regulatory regions, whereas more ancient LINE L2s were associated with tissue-shared regulatory regions and with those switching between promoter and enhancer signatures across species.

CONCLUSIONS

Our analyses of the tissue-specificity and evolutionary stability among promoters and enhancers reveal how specific LINE families have helped shape the dynamic mammalian regulome.

Sex steroids as mediators of phenotypic integration, genetic correlations, and evolutionary transitions

In recent decades, endocrinologists have increasingly adopted evolutionary methods and perspectives to characterize the evolution of the vertebrate endocrine system and leverage it as a model for developing and testing evolutionary theories. This review summarizes recent research on sex steroids (androgens and estrogens) to illustrate three ways in which a detailed understanding of the molecular and cellular architecture of hormonally mediated gene expression can enhance our understanding of general evolutionary principles. By virtue of their massively pleiotropic effects on the expression of genes and phenotypes, sex steroids and their receptors can (1) structure the patterns of phenotypic variance and covariance that are available to natural selection, (2) alter the underlying genetic correlations that determine a population's evolutionary response to selection, and (3) facilitate evolutionary transitions in fitness-related phenotypes via subtle regulatory shifts in underlying tissues and genes. These principles are illustrated by the author's research on testosterone and sexual dimorphism in lizards, and by recent examples drawn from other vertebrate systems. Mechanistically, these examples call attention to the importance of evolutionary changes in (1) androgen- and estrogen-mediated gene expression, (2) androgen and estrogen receptor expression, and (3) the distribution of androgen and estrogen response elements in target genes throughout the genome. A central theme to emerge from this review is that the rapidly increasing availability of genomic and transcriptomic data from non-model organisms places evolutionary endocrinologist in an excellent position to address the hormonal regulation of the key evolutionary interface between genes and phenotypes.

Molecular drivers of human cerebral cortical evolution

One of the most important questions in human evolutionary biology is how our ancestor has acquired an expanded volume of the cerebral cortex, which may have significantly impacted on improving our cognitive abilities. Recent comparative approaches have identified developmental features unique to the human or hominid cerebral cortex, not shared with other animals including conventional experimental models. In addition, genomic, transcriptomic, and epigenomic signatures associated with human- or hominid-specific processes of the cortical development are becoming identified by virtue of technical progress in the deep nucleotide sequencing. This review discusses ontogenic and phylogenetic processes of the human cerebral cortex, followed by the introduction of recent comprehensive approaches identifying molecular mechanisms potentially driving the evolutionary changes in the cortical development.

Transcriptomic buffering of cryptic genetic variation contributes to meningococcal virulence

Background

Commensal bacteria like Neisseria meningitidis sometimes cause serious disease. However, genomic comparison of hyperinvasive and apathogenic lineages did not reveal unambiguous hints towards indispensable virulence factors. Here, in a systems biological approach we compared gene expression of the invasive strain MC58 and the carriage strain α522 under different ex vivo conditions mimicking commensal and virulence compartments to assess the strain-specific impact of gene regulation on meningococcal virulence.

Results

Despite indistinguishable ex vivo phenotypes, both strains differed in the expression of over 500 genes under infection mimicking conditions. These differences comprised in particular metabolic and information processing genes as well as genes known to be involved in host-damage such as the nitrite reductase and numerous LOS biosynthesis genes. A model based analysis of the transcriptomic differences in human blood suggested ensuing metabolic flux differences in energy, glutamine and cysteine metabolic pathways along with differences in the activation of the stringent response in both strains. In support of the computational findings, experimental analyses revealed differences in cysteine and glutamine auxotrophy in both strains as well as a strain and condition dependent essentiality of the (p)ppGpp synthetase gene relA and of a short non-coding AT-rich repeat element in its promoter region.

Conclusions

Our data suggest that meningococcal virulence is linked to transcriptional buffering of cryptic genetic variation in metabolic genes including global stress responses. They further highlight the role of regulatory elements for bacterial virulence and the limitations of model strain approaches when studying such genetically diverse species as N. meningitidis.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3616-7) contains supplementary material, which is available to authorized users.

motifDiverge: a model for assessing the statistical significance of gene regulatory motif divergence between two DNA sequences

Next-generation sequencing technology enables the identification of thousands of gene regulatory sequences in many cell types and organisms. We consider the problem of testing if two such sequences differ in their number of binding site motifs for a given transcription factor (TF) protein. Binding site motifs impart regulatory function by providing TFs the opportunity to bind to genomic elements and thereby affect the expression of nearby genes. Evolutionary changes to such functional DNA are hypothesized to be major contributors to phenotypic diversity within and between species; but despite the importance of TF motifs for gene expression, no method exists to test for motif loss or gain. Assuming that motif counts are Binomially distributed, and allowing for dependencies between motif instances in evolutionarily related sequences, we derive the probability mass function of the difference in motif counts between two nucleotide sequences. We provide a method to numerically estimate this distribution from genomic data and show through simulations that our estimator is accurate. Finally, we introduce the R package motifDiverge that implements our methodology and illustrate its application to gene regulatory enhancers identified by a mouse developmental time course experiment. While this study was motivated by analysis of regulatory motifs, our results can be applied to any problem involving two correlated Bernoulli trials.