Evolutionary divergence and limits of conserved non-coding sequence detection in plant genomes

The discovery of regulatory motifs embedded in upstream regions of plants is a particularly challenging bioinformatics task. Previous studies have shown that motifs in plants are short compared with those found in vertebrates. Furthermore, plant genomes have undergone several diversification mechanisms such as genome duplication events which impact the evolution of regulatory motifs. In this article, a systematic phylogenomic comparison of upstream regions is conducted to further identify features of the plant regulatory genomes, the component of genomes regulating gene expression, to enable future de novo discoveries. The findings highlight differences in upstream region properties between major plant groups and the effects of divergence times and duplication events. First, clear differences in upstream region evolution can be detected between monocots and dicots, thus suggesting that a separation of these groups should be made when searching for novel regulatory motifs, particularly since universal motifs such as the TATA box are rare. Second, investigating the decay rate of significantly aligned regions suggests that a divergence time of 100 mya sets a limit for reliable conserved non-coding sequence (CNS) detection. Insights presented here will set a framework to help identify embedded motifs of functional relevance by understanding the limits of bioinformatics detection for CNSs.</p

Evolutionary Dynamics on Protein Bi-stability Landscapes Can Potentially Resolve Adaptive Conflicts

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bistable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed

MDAT- Aligning multiple domain arrangements

Background: Proteins are composed of domains, protein segments that fold independently from the rest of the protein and have a specific function. During evolution the arrangement of domains can change: domains are gained, lost or their order is rearranged. To facilitate the analysis of these changes we propose the use of multiple domain alignments. Results: We developed an alignment program, called MDAT, which aligns multiple domain arrangements. MDAT extends earlier programs which perform pairwise alignments of domain arrangements. MDAT uses a domain similarity matrix to score domain pairs and aligns the domain arrangements using a consistency supported progressive alignment method. Conclusion: MDAT will be useful for analysing changes in domain arrangements within and between protein families and will thus provide valuable insights into the evolution of proteins and their domains. MDAT is coded in C++, and the source code is freely available for download at http://www.bornberglab.org/pages/mda

Domain similarity based orthology detection

Background: Orthologous protein detection software mostly uses pairwise comparisons of amino-acid sequences to assert whether two proteins are orthologous or not. Accordingly, when the number of sequences for comparison increases, the number of comparisons to compute grows in a quadratic order. A current challenge of bioinformatic research, especially when taking into account the increasing number of sequenced organisms available, is to make this ever-growing number of comparisons computationally feasible in a reasonable amount of time. We propose to speed up the detection of orthologous proteins by using strings of domains to characterize the proteins. Results: We present two new protein similarity measures, a cosine and a maximal weight matching score based on domain content similarity, and new software, named porthoDom. The qualities of the cosine and the maximal weight matching similarity measures are compared against curated datasets. The measures show that domain content similarities are able to correctly group proteins into their families. Accordingly, the cosine similarity measure is used inside porthoDom, the wrapper developed for proteinortho. porthoDom makes use of domain content similarity measures to group proteins together before searching for orthologs. By using domains instead of amino acid sequences, the reduction of the search space decreases the computational complexity of an all-against-all sequence comparison. Conclusion: We demonstrate that representing and comparing proteins as strings of discrete domains, i.e. as a concatenation of their unique identifiers, allows a drastic simplification of search space. porthoDom has the advantage of speeding up orthology detection while maintaining a degree of accuracy similar to proteinortho. The implementation of porthoDom is released using python and C++ languages and is available under the GNU GPL licence 3 at http://www.bornberglab.org/pages/porthoda.<br

Genomic divergence between nine- and three-spined sticklebacks

Background: Comparative genomics approaches help to shed light on evolutionary processes that shape differentiation between lineages. The nine-spined stickleback (Pungitius pungitius) is a closely related species of the ecological ‘supermodel’ three-spined stickleback (Gasterosteus aculeatus). It is an emerging model system for evolutionary biology research but has garnered less attention and lacks extensive genomic resources. To expand on these resources and aid the study of sticklebacks in a phylogenetic framework, we characterized nine-spined stickleback transcriptomes from brain and liver using deep sequencing. Results: We obtained nearly eight thousand assembled transcripts, of which 3,091 were assigned as putative oneto- one orthologs to genes found in the three-spined stickleback. These sequences were used for evaluating overall differentiation and substitution rates between nine- and three-spined sticklebacks, and to identify genes that are putatively evolving under positive selection. The synonymous substitution rate was estimated to be 7.1 × 10-9 per site per year between the two species, and a total of 165 genes showed patterns of adaptive evolution in one or both species. A few nine-spined stickleback contigs lacked an obvious ortholog in three-spined sticklebacks but were found to match genes in other fish species, suggesting several gene losses within 13 million years since the divergence of the two stickleback species. We identified 47 SNPs in 25 different genes that differentiate pond and marine ecotypes. We also identified 468 microsatellites that could be further developed as genetic markers in nine-spined sticklebacks. Conclusion: With deep sequencing of nine-spined stickleback cDNA libraries, our study provides a significant increase in the number of gene sequences and microsatellite markers for this species, and identifies a number of genes showing patterns of adaptive evolution between nine- and three-spined sticklebacks. We also report several candidate genes that might be involved in differential adaptation between marine and freshwater nine-spined sticklebacks. This study provides a valuable resource for future studies aiming to identify candidate genes underlying ecological adaptation in this and other stickleback species

Convergent loss of chemoreceptors across independent origins of slave-making in ants

The evolution of an obligate parasitic lifestyle often leads to the reduction of morphological and physiological traits, which may be accompanied by loss of genes and functions. Slave-making ants are social parasites that exploit the work force of closely related ant species for social behaviors such as brood care and foraging. Recent divergence between these social parasites and their hosts enables comparative studies of gene family evolution. We sequenced the genomes of eight ant species, representing three independent origins of ant slavery. During the evolution of eusociality, chemoreceptor genes multiplied due to the importance of chemical communication in insect societies. We investigated the evolutionary fate of these chemoreceptors and found that slave-making ant genomes harbored only half as many gustatory receptors as their hosts’, potentially mirroring the outsourcing of foraging tasks to host workers. In addition, parasites had fewer odorant receptors and their loss shows striking patterns of convergence across independent origins of parasitism, in particular in orthologs often implicated in sociality like the 9-exon odorant receptors. These convergent losses represent a rare case of convergent molecular evolution at the level of individual genes. Thus, evolution can operate in a way that is both repeatable and reversible when independent ant lineages lose important social traits during the transition to a parasitic lifestyle

The Dynamics and Evolutionary Potential of Domain Loss and Emergence

The wealth of available genomic data presents an unrivaled opportunity to study the molecular basis of evolution. Studies on gene family expansions and site-dependent analyses have already helped establish important insights into how proteins facilitate adaptation. However, efforts to conduct full-scale cross-genomic comparisons between species are challenged by both growing amounts of data and the inherent difficulty in accurately inferring homology between deeply rooted species. Proteins, in comparison, evolve by means of domain rearrangements, a process more amenable to study given the strength of profile-based homology inference and the lower rates with which rearrangements occur. However, adapting to a constantly changing environment can require molecular modulations beyond reach of rearrangement alone. Here, we explore rates and functional implications of novel domain emergence in contrast to domain gain and loss in 20 arthropod species of the pancrustacean clade. Emerging domains are more likely disordered in structure and spread more rapidly within their genomes than established domains. Furthermore, although domain turnover occurs at lower rates than gene family turnover, we find strong evidence that the emergence of novel domains is foremost associated with environmental adaptation such as abiotic stress response. The results presented here illustrate the simplicity with which domain-based analyses can unravel key players of nature's adaptational machinery, complementing the classical site-based analyses of adaptation

A protein interaction atlas for the nuclear receptors: properties and quality of a hub-based dimerisation network

BACKGROUND: The nuclear receptors are a large family of eukaryotic transcription factors that constitute major pharmacological targets. They exert their combinatorial control through homotypic heterodimerisation. Elucidation of this dimerisation network is vital in order to understand the complex dynamics and potential cross-talk involved. RESULTS: Phylogeny, protein-protein interactions, protein-DNA interactions and gene expression data have been integrated to provide a comprehensive and up-to-date description of the topology and properties of the nuclear receptor interaction network in humans. We discriminate between DNA-binding and non-DNA-binding dimers, and provide a comprehensive interaction map, that identifies potential cross-talk between the various pathways of nuclear receptors. CONCLUSION: We infer that the topology of this network is hub-based, and much more connected than previously thought. The hub-based topology of the network and the wide tissue expression pattern of NRs create a highly competitive environment for the common heterodimerising partners. Furthermore, a significant number of negative feedback loops is present, with the hub protein SHP [NR0B2] playing a major role. We also compare the evolution, topology and properties of the nuclear receptor network with the hub-based dimerisation network of the bHLH transcription factors in order to identify both unique themes and ubiquitous properties in gene regulation. In terms of methodology, we conclude that such a comprehensive picture can only be assembled by semi-automated text-mining, manual curation and integration of data from various sources