Expand+Functional selection and systematic analysis of intronic splicing elements identify active sequence motifs and associated splicing factors

Despite the critical role of pre-mRNA splicing in generating proteomic diversity and regulating gene expression, the sequence composition and function of intronic splicing regulatory elements (ISREs) have not been well elucidated. Here, we employed a high-throughput in vivo Screening PLatform for Intronic Control Elements (SPLICE) to identify 125 unique ISRE sequences from a random nucleotide library in human cells. Bioinformatic analyses reveal consensus motifs that resemble splicing regulatory elements and binding sites for characterized splicing factors and that are enriched in the introns of naturally occurring spliced genes, supporting their biological relevance. In vivo characterization, including an RNAi silencing study, demonstrate that ISRE sequences can exhibit combinatorial regulatory activity and that multiple trans-acting factors are involved in the regulatory effect of a single ISRE. Our work provides an initial examination into the sequence characteristics and function of ISREs, providing an important contribution to the splicing code

Systematic identification of functional plant modules through the integration of complementary data sources

A major challenge is to unravel how genes interact and are regulated to exert specific biological functions. The integration of genome-wide functional genomics data, followed by the construction of gene networks, provides a powerful approach to identify functional gene modules. Large-scale expression data, functional gene annotations, experimental protein-protein interactions, and transcription factor-target interactions were integrated to delineate modules in Arabidopsis (Arabidopsis thaliana). The different experimental input data sets showed little overlap, demonstrating the advantage of combining multiple data types to study gene function and regulation. In the set of 1,563 modules covering 13,142 genes, most modules displayed strong coexpression, but functional and cis-regulatory coherence was less prevalent. Highly connected hub genes showed a significant enrichment toward embryo lethality and evidence for cross talk between different biological processes. Comparative analysis revealed that 58% of the modules showed conserved coexpression across multiple plants. Using module-based functional predictions, 5,562 genes were annotated, and an evaluation experiment disclosed that, based on 197 recently experimentally characterized genes, 38.1% of these functions could be inferred through the module context. Examples of confirmed genes of unknown function related to cell wall biogenesis, xylem and phloem pattern formation, cell cycle, hormone stimulus, and circadian rhythm highlight the potential to identify new gene functions. The module-based predictions offer new biological hypotheses for functionally unknown genes in Arabidopsis (1,701 genes) and six other plant species (43,621 genes). Furthermore, the inferred modules provide new insights into the conservation of coexpression and coregulation as well as a starting point for comparative functional annotation

Application of regulatory sequence analysis and metabolic network analysis to the interpretation of gene expression data

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked: 1. Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements. 2. What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways. We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/)

Loss of YABBY2-Like Gene Expression May Underlie the Evolution of the Laminar Style in Canna and Contribute to Floral Morphological Diversity in the Zingiberales.

The Zingiberales is an order of tropical monocots that exhibits diverse floral morphologies. The evolution of petaloid, laminar stamens, staminodes, and styles contributes to this diversity. The laminar style is a derived trait in the family Cannaceae and plays an important role in pollination as its surface is used for secondary pollen presentation. Previous work in the Zingiberales has implicated YABBY2-like genes, which function in promoting laminar outgrowth, in the evolution of stamen morphology. Here, we investigate the evolution and expression of Zingiberales YABBY2-like genes in order to understand the evolution of the laminar style in Canna. Phylogenetic analyses show that multiple duplication events have occurred in this gene lineage prior to the diversification of the Zingiberales. Reverse transcription-PCR in Canna, Costus, and Musa reveals differential expression across floral organs, taxa, and gene copies, and a role for YABBY2-like genes in the evolution of the laminar style is proposed. Selection tests indicate that almost all sites in conserved domains are under purifying selection, consistent with their functional relevance, and a motif unique to monocot YABBY2-like genes is identified. These results contribute to our understanding of the molecular mechanisms underlying the evolution of floral morphologies

The fate of Arabidopsis thaliana homeologous CNSs and their motifs in the Paleohexaploid Brassica rapa.

Following polyploidy, duplicate genes are often deleted, and if they are not, then duplicate regulatory regions are sometimes lost. By what mechanism is this loss and what is the chance that such a loss removes function? To explore these questions, we followed individual Arabidopsis thaliana-A. thaliana conserved noncoding sequences (CNSs) into the Brassica ancestor, through a paleohexaploidy and into Brassica rapa. Thus, a single Brassicaceae CNS has six potential orthologous positions in B. rapa; a single Arabidopsis CNS has three potential homeologous positions. We reasoned that a CNS, if present on a singlet Brassica gene, would be unlikely to lose function compared with a more redundant CNS, and this is the case. Redundant CNSs go nondetectable often. Using this logic, each mechanism of CNS loss was assigned a metric of functionality. By definition, proved deletions do not function as sequence. Our results indicated that CNSs that go nondetectable by base substitution or large insertion are almost certainly still functional (redundancy does not matter much to their detectability frequency), whereas those lost by inferred deletion or indels are approximately 75% likely to be nonfunctional. Overall, an average nondetectable, once-redundant CNS more than 30 bp in length has a 72% chance of being nonfunctional, and that makes sense because 97% of them sort to a molecular mechanism with deletion in its description, but base substitutions do cause loss. Similarly, proved-functional G-boxes go undetectable by deletion 82% of the time. Fractionation mutagenesis is a procedure that uses polyploidy as a mutagenic agent to genetically alter RNA expression profiles, and then to construct testable hypotheses as to the function of the lost regulatory site. We show fractionation mutagenesis to be a deletion machine in the Brassica lineage

Intracompartmental and Intercompartmental Transcriptional Networks Coordinate the Expression of Genes for Organellar Functions

Genes for mitochondrial and chloroplast proteins are distributed between the nuclear and organellar genomes. Organelle biogenesis and metabolism, therefore, require appropriate coordination of gene expression in the different compartments to ensure efficient synthesis of essential multiprotein complexes of mixed genetic origin. Whereas organelle-to-nucleus signaling influences nuclear gene expression at the transcriptional level, organellar gene expression (OGE) is thought to be primarily regulated posttranscriptionally. Here, we show that intracompartmental and intercompartmental transcriptional networks coordinate the expression of genes for organellar functions. Nearly 1,300 ATH1 microarray-based transcriptional profiles of nuclear and organellar genes for mitochondrial and chloroplast proteins in the model plant Arabidopsis (Arabidopsis thaliana) were analyzed. The activity of genes involved in organellar energy production (OEP) or OGE in each of the organelles and in the nucleus is highly coordinated. Intracompartmental networks that link the OEP and OGE gene sets serve to synchronize the expression of nucleus- and organelle-encoded proteins. At a higher regulatory level, coexpression of organellar and nuclear OEP/OGE genes typically modulates chloroplast functions but affects mitochondria only when chloroplast functions are perturbed. Under conditions that induce energy shortage, the intercompartmental coregulation of photosynthesis genes can even override intracompartmental networks. We conclude that dynamic intracompartmental and intercompartmental transcriptional networks for OEP and OGE genes adjust the activity of organelles in response to the cellular energy state and environmental stresses, and we identify candidate cis-elements involved in the transcriptional coregulation of nuclear genes. Regarding the transcriptional regulation of chloroplast genes, novel tentative target genes of σ factors are identified

Propagation-Based Biclustering Algorithm for Extracting Inclusion-Maximal Motifs

Biclustering, which is simultaneous clustering of columns and rows in data matrix, became an issue when classical clustering algorithms proved not to be good enough to detect similar expressions of genes under subset of conditions. Biclustering algorithms may be also applied to different datasets, such as medical, economical, social networks etc. In this article we explain the concept beneath hybrid biclustering algorithms and present details of propagation-based biclustering, a novel approach for extracting inclusion-maximal gene expression motifs conserved in gene microarray data. We prove that this approach may successfully compete with other well-recognized biclustering algorithms

Genome-Wide Survey of MicroRNA - Transcription Factor Feed-Forward Regulatory Circuits in Human

In this work, we describe a computational framework for the genome-wide identification and characterization of mixed transcriptional/post-transcriptional regulatory circuits in humans. We concentrated in particular on feed-forward loops (FFL), in which a master transcription factor regulates a microRNA, and together with it, a set of joint target protein coding genes. The circuits were assembled with a two step procedure. We first constructed separately the transcriptional and post-transcriptional components of the human regulatory network by looking for conserved over-represented motifs in human and mouse promoters, and 3'-UTRs. Then, we combined the two subnetworks looking for mixed feed-forward regulatory interactions, finding a total of 638 putative (merged) FFLs. In order to investigate their biological relevance, we filtered these circuits using three selection criteria: (I) GeneOntology enrichment among the joint targets of the FFL, (II) independent computational evidence for the regulatory interactions of the FFL, extracted from external databases, and (III) relevance of the FFL in cancer. Most of the selected FFLs seem to be involved in various aspects of organism development and differentiation. We finally discuss a few of the most interesting cases in detail.Comment: 51 pages, 5 figures, 4 tables. Supporting information included. Accepted for publication in Molecular BioSystem