TFCONES: a database of vertebrate transcription factor-encoding genes and their associated conserved noncoding elements

Impact of Genetic Variation in Gene Regulatory Sequences: A Population Genomics Perspective

The unprecedented rise of high-throughput sequencing and assay technologies has provided a detailed insight into the non-coding sequences and their potential role as gene expression regulators. These regulatory non-coding sequences are also referred to as cis-regulatory elements (CREs). Genetic variants occurring within CREs have been shown to be associated with altered gene expression and phenotypic changes. Such variants are known to occur spontaneously and ultimately get fixed, due to selection and genetic drift, in natural populations and, in some cases, pave the way for speciation. Hence, the study of genetic variation at CREs has improved our overall understanding of the processes of local adaptation and evolution. Recent advances in high-throughput sequencing and better annotations of CREs have enabled the evaluation of the impact of such variation on gene expression, phenotypic alteration and fitness. Here, we review recent research on the evolution of CREs and concentrate on studies that have investigated genetic variation occurring in these regulatory sequences within the context of population genetics.

Multiple Isolated Transcription Factors Act as Switches and Contribute to Species Uniqueness

Mammals have variable numbers (1300-2000) of transcription factors (TFs), but the reasons for this large variation are unclear. To investigate general TF patterns, we de novo identified 156,906 TFs from 96 mammalian species. We identified more than 500 human isolated TFs that are rarely reported in human TF-to-TF networks. Mutations in the genes of these TFs were less lethal than those of connected TFs. Consequently, these isolated TFs are more tolerant of changes and have become unique during speciation. They may also serve as a source of variation for TF evolution. Reconciliation of TF-family phylogenetic trees with a mammalian species tree revealed an average of 37.8% TF gains and 15.0% TF losses over 177 million years, which implies that isolated TFs are pervasive in mammals. Compared with non-TF interacting genes, TF-interacting genes have unique TF profiles and have higher expression levels in mice than in humans. Different expression levels of the same TF-interacting gene contribute to species-specific phenotypes. Formation and loss of isolated TFs enabling unique TF profiles may provide variable switches that adjust divergent expression profiles of target genes to generate species-specific phenotypes, thereby making species unique.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

ChIP-Seq analysis identifies p27(Kip1)-target genes involved in cell adhesion and cell signalling in mouse embryonic fibroblasts

The protein p27^Kip1 (p27), a member of the Cip-Kip family of cyclin-dependent kinase inhibitors, is involved in tumorigenesis and a correlation between reduced levels of this protein in human tumours and a worse prognosis has been established. Recent reports revealed that p27 also behaves as a transcriptional regulator. Thus, it has been postulated that the development of tumours with low amounts of p27 could be propitiated by deregulation of transcriptional programs under the control of p27. However, these programs still remain mostly unknown. The aim of this study has been to define the transcriptional programs regulated by p27 by first identifying the p27-binding sites (p27-BSs) on the whole chromatin of quiescent mouse embryonic fibroblasts. The chromatin regions associated to p27 have been annotated to the most proximal genes and it has been considered that the expression of these genes could by regulated by p27. The identification of the chromatin p27-BSs has been performed by Chromatin Immunoprecipitation Sequencing (ChIP-seq). Results revealed that p27 associated with 1839 sites that were annotated to 1417 different genes being 852 of them protein coding genes. Interestingly, most of the p27-BSs were in distal intergenic regions and introns whereas, in contrast, its association with promoter regions was very low. Gene ontology analysis of the protein coding genes revealed a number of relevant transcriptional programs regulated by p27 as cell adhesion, intracellular signalling and neuron differentiation among others. We validated the interaction of p27 with different chromatin regions by ChIP followed by qPCR and demonstrated that the expressions of several genes belonging to these programs are actually regulated by p27. Finally, cell adhesion assays revealed that the adhesion of p27^-/- cells to the plates was much higher that controls, revealing a role of p27 in the regulation of a transcriptional program involved in cell adhesion.

Transcription Factor Repertoire of Necrotrophic Fungal Phytopathogen Ascochyta rabiei: Predominance of MYB Transcription Factors As Potential Regulators of Secretome

Transcription factors (TFs) are the key players in gene expression and their study is highly significant for shedding light on the molecular mechanisms and evolutionary history of organisms. During host-pathogen interaction, extensive reprogramming of gene expression facilitated by TFs is likely to occur in both host and pathogen. To date, the knowledge about TF repertoire in filamentous fungi is in infancy. The necrotrophic fungus Ascochyta rabiei, that causes destructive Ascochyta blight (AB) disease of chickpea (Cicer arietinum), demands more comprehensive study for better understanding of Ascochyta-legume pathosystem. In the present study, we performed the genome-wide identification and analysis of TFs in A. rabiei. Taking advantage of A. rabiei genome sequence, we used a bioinformatic approach to predict the TF repertoire of A. rabiei. For identification and classification of A. rabiei TFs, we designed a comprehensive pipeline using a combination of BLAST and InterProScan software. A total of 381 A. rabiei TFs were predicted and divided into 32 fungal specific families of TFs. The gene structure, domain organization and phylogenetic analysis of abundant families of A. rabiei TFs were also carried out. Comparative study of A. rabiei TFs with that of other necrotrophic, biotrophic, hemibiotrophic, symbiotic, and saprotrophic fungi was performed. It suggested presence of both conserved as well as unique features among them. Moreover, cis-acting elements on promoter sequences of earlier predicted A. rabiei secretome were also identified. With the help of published A. rabiei transcriptome data, the differential expression of TF and secretory protein coding genes was analyzed. Furthermore, comprehensive expression analysis of few selected A. rabiei TFs using quantitative real-time polymerase chain reaction revealed variety of expression patterns during host colonization. These genes were expressed in at least one of the time points tested post infection. Overall, this study illustrates the first genome-wide identification and analysis of TF repertoire of A. rabiei. This work would provide the basis for further studies to dissect role of TFs in the molecular mechanisms during A. rabiei-chickpea interactions.

BicPAMS: software for biological data analysis with pattern-based biclustering

BACKGROUND

Biclustering has been largely applied for the unsupervised analysis of biological data, being recognised today as a key technique to discover putative modules in both expression data (subsets of genes correlated in subsets of conditions) and network data (groups of coherently interconnected biological entities). However, given its computational complexity, only recent breakthroughs on pattern-based biclustering enabled efficient searches without the restrictions that state-of-the-art biclustering algorithms place on the structure and homogeneity of biclusters. As a result, pattern-based biclustering provides the unprecedented opportunity to discover non-trivial yet meaningful biological modules with putative functions, whose coherency and tolerance to noise can be tuned and made problem-specific.

METHODS

To enable the effective use of pattern-based biclustering by the scientific community, we developed BicPAMS (Biclustering based on PAttern Mining Software), a software that: 1) makes available state-of-the-art pattern-based biclustering algorithms (BicPAM (Henriques and Madeira, Alg Mol Biol 9:27, 2014), BicNET (Henriques and Madeira, Alg Mol Biol 11:23, 2016), BicSPAM (Henriques and Madeira, BMC Bioinforma 15:130, 2014), BiC2PAM (Henriques and Madeira, Alg Mol Biol 11:1-30, 2016), BiP (Henriques and Madeira, IEEE/ACM Trans Comput Biol Bioinforma, 2015), DeBi (Serin and Vingron, AMB 6:1-12, 2011) and BiModule (Okada et al., IPSJ Trans Bioinf 48(SIG5):39-48, 2007)); 2) consistently integrates their dispersed contributions; 3) further explores additional accuracy and efficiency gains; and 4) makes available graphical and application programming interfaces.

RESULTS

Results on both synthetic and real data confirm the relevance of BicPAMS for biological data analysis, highlighting its essential role for the discovery of putative modules with non-trivial yet biologically significant functions from expression and network data.

CONCLUSIONS

BicPAMS is the first biclustering tool offering the possibility to: 1) parametrically customize the structure, coherency and quality of biclusters; 2) analyze large-scale biological networks; and 3) tackle the restrictive assumptions placed by state-of-the-art biclustering algorithms. These contributions are shown to be key for an adequate, complete and user-assisted unsupervised analysis of biological data.

SOFTWARE

BicPAMS and its tutorial available in http://www.bicpams.com .

TcoF-DB v2: update of the database of human and mouse transcription co-factors and transcription factor interactions

Transcription factors (TFs) play a pivotal role in transcriptional regulation, making them crucial for cell survival and important biological functions. For the regulation of transcription, interactions of different regulatory proteins known as transcription co-factors (TcoFs) and TFs are essential in forming necessary protein complexes. Although TcoFs themselves do not bind DNA directly, their influence on transcriptional regulation and initiation, although indirect, has been shown to be significant, with the functionality of TFs strongly influenced by the presence of TcoFs. In the TcoF-DB v2 database, we collect information on TcoFs. In this article, we describe updates and improvements implemented in TcoF-DB v2. TcoF-DB v2 provides several new features that enables exploration of the roles of TcoFs. The content of the database has significantly expanded, and is enriched with information from Gene Ontology, biological pathways, diseases and molecular signatures. TcoF-DB v2 now includes many more TFs; has substantially increased the number of human TcoFs to 958, and now includes information on mouse (418 new TcoFs). TcoF-DB v2 enables the exploration of information on TcoFs and allows investigations into their influence on transcriptional regulation in humans and mice. TcoF-DB v2 can be accessed at http://tcofdb.org/.

BicPAM: Pattern-based biclustering for biomedical data analysis

BACKGROUND

Biclustering, the discovery of sets of objects with a coherent pattern across a subset of conditions, is a critical task to study a wide-set of biomedical problems, where molecular units or patients are meaningfully related with a set of properties. The challenging combinatorial nature of this task led to the development of approaches with restrictions on the allowed type, number and quality of biclusters. Contrasting, recent biclustering approaches relying on pattern mining methods can exhaustively discover flexible structures of robust biclusters. However, these approaches are only prepared to discover constant biclusters and their underlying contributions remain dispersed.

METHODS

The proposed BicPAM biclustering approach integrates existing principles made available by state-of-the-art pattern-based approaches with two new contributions. First, BicPAM is the first efficient attempt to exhaustively mine non-constant types of biclusters, including additive and multiplicative coherencies in the presence or absence of symmetries. Second, BicPAM provides strategies to effectively compose different biclustering structures and to handle arbitrary levels of noise inherent to data and with discretization procedures.

RESULTS

Results show BicPAM's superiority against its peers and its ability to retrieve unique types of biclusters of interest, to efficiently deliver exhaustive solutions and to successfully recover planted biclusters in datasets with varying levels of missing values and noise. Its application over gene expression data leads to unique solutions with heightened biological relevance.

CONCLUSIONS

BicPAM approaches integrate existing disperse efforts towards pattern-based biclustering and provides the first critical strategies to efficiently discover exhaustive solutions of biclusters with shifting, scaling and symmetric assumptions with varying quality and underlying structures. Additionally, BicPAM dynamically adapts its behavior to mine data with different levels of missing values and noise.

AnimalTFDB 2.0: a resource for expression, prediction and functional study of animal transcription factors

Transcription factors (TFs) are key regulators for gene expression. Here we updated the animal TF database AnimalTFDB to version 2.0 (http://bioinfo.life.hust.edu.cn/AnimalTFDB/). Using the improved prediction pipeline, we identified 72 336 TF genes, 21 053 transcription co-factor genes and 6502 chromatin remodeling factor genes from 65 species covering main animal lineages. Besides the abundant annotations (basic information, gene model, protein functional domain, gene ontology, pathway, protein interaction, ortholog and paralog, etc.) in the previous version, we made several new features and functions in the updated version. These new features are: (i) gene expression from RNA-Seq for nine model species, (ii) gene phenotype information, (iii) multiple sequence alignment of TF DNA-binding domains, and the weblogo and phylogenetic tree based on the alignment, (iv) a TF prediction server to identify new TFs from input sequences and (v) a BLAST server to search against TFs in AnimalTFDB. A new nice web interface was designed for AnimalTFDB 2.0 allowing users to browse and search all data in the database. We aim to maintain the AnimalTFDB as a solid resource for TF identification and studies of transcription regulation and comparative genomics.

UCbase 2.0: ultraconserved sequences database (2014 update)

UCbase 2.0 (http://ucbase.unimore.it) is an update, extension and evolution of UCbase, a Web tool dedicated to the analysis of ultraconserved sequences (UCRs). UCRs are 481 sequences >200 bases sharing 100% identity among human, mouse and rat genomes. They are frequently located in genomic regions known to be involved in cancer or differentially expressed in human leukemias and carcinomas. UCbase 2.0 is a platform-independent Web resource that includes the updated version of the human genome annotation (hg19), information linking disorders to chromosomal coordinates based on the Systematized Nomenclature of Medicine classification, a query tool to search for Single Nucleotide Polymorphisms (SNPs) and a new text box to directly interrogate the database using a MySQL interface. To facilitate the interactive visual interpretation of UCR chromosomal positioning, UCbase 2.0 now includes a graph visualization interface directly linked to UCSC genome browser.

Database URL:http://ucbase.unimore.it

The most deeply conserved noncoding sequences in plants serve similar functions to those in vertebrates despite large differences in evolutionary rates

In vertebrates, conserved noncoding elements (CNEs) are functionally constrained sequences that can show striking conservation over >400 million years of evolutionary distance and frequently are located megabases away from target developmental genes. Conserved noncoding sequences (CNSs) in plants are much shorter, and it has been difficult to detect conservation among distantly related genomes. In this article, we show not only that CNS sequences can be detected throughout the eudicot clade of flowering plants, but also that a subset of 37 CNSs can be found in all flowering plants (diverging ∼170 million years ago). These CNSs are functionally similar to vertebrate CNEs, being highly associated with transcription factor and development genes and enriched in transcription factor binding sites. Some of the most highly conserved sequences occur in genes encoding RNA binding proteins, particularly the RNA splicing-associated SR genes. Differences in sequence conservation between plants and animals are likely to reflect differences in the biology of the organisms, with plants being much more able to tolerate genomic deletions and whole-genome duplication events due, in part, to their far greater fecundity compared with vertebrates.

An improved SELEX-Seq strategy for characterizing DNA-binding specificity of transcription factor: NF-κB as an example

SELEX-Seq is now the optimal high-throughput technique for characterizing DNA-binding specificities of transcription factors. In this study, we introduced an improved EMSA-based SELEX-Seq strategy with several advantages. The improvements of this strategy included: (1) using a FAM-labeled probe to track protein-DNA complex in polyacrylamide gel for rapidly recovering the protein-bound dsDNA without relying on traditional radioactive labeling or ethidium bromide staining; (2) monitoring the specificity of SELEX selection by detecting a positive and negative sequence doped into the input DNAs used in each round with PCR amplification; (3) using nested PCR to ensure the specificity of PCR amplification of the selected DNAs after each round; (4) using the nucleotides added at the 5′ end of the nested PCR primers as the split barcode to code DNAs from various rounds for multiplexing sequencing samples. The split barcode minimized selection times and thus greatly simplified the current SELEX-Seq procedure. The reliability of the strategy was demonstrated by performing a successful SELEX-Seq of a well-known transcription factor, NF-κB. Therefore, this study provided a useful SELEX-Seq strategy for characterizing DNA-binding specificities of transcription factors.

The Loci of repeated evolution: a catalog of genetic hotspots of phenotypic variation

What is the nature of the genetic changes underlying phenotypic evolution? We have catalogued 1008 alleles described in the literature that cause phenotypic differences among animals, plants, and yeasts. Surprisingly, evolution of similar traits in distinct lineages often involves mutations in the same gene ("gene reuse"). This compilation yields three important qualitative implications about repeated evolution. First, the apparent evolution of similar traits by gene reuse can be traced back to two alternatives, either several independent causative mutations or a single original mutational event followed by sorting processes. Second, hotspots of evolution-defined as the repeated occurrence of de novo mutations at orthologous loci and causing similar phenotypic variation-are omnipresent in the literature with more than 100 examples covering various levels of analysis, including numerous gain-of-function events. Finally, several alleles of large effect have been shown to result from the aggregation of multiple small-effect mutations at the same hotspot locus, thus reconciling micromutationist theories of adaptation with the empirical observation of large-effect variants. Although data heterogeneity and experimental biases prevented us from extracting quantitative trends, our synthesis highlights the existence of genetic paths of least resistance leading to viable evolutionary change.

UCNEbase--a database of ultraconserved non-coding elements and genomic regulatory blocks

UCNEbase (http://ccg.vital-it.ch/UCNEbase) is a free, web-accessible information resource on the evolution and genomic organization of ultra-conserved non-coding elements (UCNEs). It currently covers 4351 such elements in 18 different species. The majority of UCNEs are supposed to be transcriptional regulators of key developmental genes. As most of them occur as clusters near potential target genes, the database is organized along two hierarchical levels: individual UCNEs and ultra-conserved genomic regulatory blocks (UGRBs). UCNEbase introduces a coherent nomenclature for UCNEs reflecting their respective associations with likely target genes. Orthologous and paralogous UCNEs share components of their names and are systematically cross-linked. Detailed synteny maps between the human and other genomes are provided for all UGRBs. UCNEbase is managed by a relational database system and can be accessed by a variety of web-based query pages. As it relies on the UCSC genome browser as visualization platform, a large part of its data content is also available as browser viewable custom track files. UCNEbase is potentially useful to any computational, experimental or evolutionary biologist interested in conserved non-coding DNA elements in vertebrates.

Transcription factors expressed in embryonic and adult olfactory bulb neural stem cells reveal distinct proliferation, differentiation and epigenetic control

TF genomic markers associated with neurogenesis, proliferation, differentiation, and epigenetic control in human embryonic neural stem cells (hENSC(, and adult human olfactory bulb neural stem cells (OBNSC) were studied by immunohistochemistry (IHC) and DNA microarray. The biological impact of TF gene changes in the examined cell types was estimated using DAVID to specify a different GO class and signaling pathway based on KEGG database. Eleven, and twenty eight TF genes were up-regulated (fold change≤2-39) in OBNSC, and hENSC respectively. KEGG pathway analysis for the up-regulated TF genes revealed significant enrichments for the basal transcription factor pathway, and Notch signaling pathway in OBNSCs, and hENSCs, respectively. Immunofluorescence analysis revealed a significantly greater number of β-tubulin III (TUBB3), MAP, glial fibrillary acidic protein (GFAP), and O4 in hENSC when compared to those in OBNSC. Furthermore, the expression of epigenetic-related TF-genes SMARCC1, TAF12, and UHRF1 increased significantly in OBNSC when compared with hENSC.

A genome-wide screen to identify transcription factors expressed in pelvic Ganglia of the lower urinary tract

Relative positions of neurons within mature murine pelvic ganglia based on expression of neurotransmitters have been described. However the spatial organization of developing innervation in the murine urogenital tract (UGT) and the gene networks that regulate specification and maturation of neurons within the pelvic ganglia of the lower urinary tract (LUT) are unknown. We used whole-mount immunohistochemistry and histochemical stains to localize neural elements in 15.5 days post coitus (dpc) fetal mice. To identify potential regulatory factors expressed in pelvic ganglia, we surveyed expression patterns for known or probable transcription factors (TF) annotated in the mouse genome by screening a whole-mount in situ hybridization library of fetal UGTs. Of the 155 genes detected in pelvic ganglia, 88 encode TFs based on the presence of predicted DNA-binding domains. Neural crest (NC)-derived progenitors within the LUT were labeled by Sox10, a well-known regulator of NC development. Genes identified were categorized based on patterns of restricted expression in pelvic ganglia, pelvic ganglia and urethral epithelium, or pelvic ganglia and urethral mesenchyme. Gene expression patterns and the distribution of Sox10+, Phox2b+, Hu+, and PGP9.5+ cells within developing ganglia suggest previously unrecognized regional segregation of Sox10+ progenitors and differentiating neurons in early development of pelvic ganglia. Reverse transcription-PCR of pelvic ganglia RNA from fetal and post-natal stages demonstrated that multiple TFs maintain post-natal expression, although Pax3 is extinguished before weaning. Our analysis identifies multiple potential regulatory genes including TFs that may participate in segregation of discrete lineages within pelvic ganglia. The genes identified here are attractive candidate disease genes that may now be further investigated for their roles in malformation syndromes or in LUT dysfunction.

Identification of molecular compartments and genetic circuitry in the developing mammalian kidney

Lengthy developmental programs generate cell diversity within an organotypic framework, enabling the later physiological actions of each organ system. Cell identity, cell diversity and cell function are determined by cell type-specific transcriptional programs; consequently, transcriptional regulatory factors are useful markers of emerging cellular complexity, and their expression patterns provide insights into the regulatory mechanisms at play. We performed a comprehensive genome-scale in situ expression screen of 921 transcriptional regulators in the developing mammalian urogenital system. Focusing on the kidney, analysis of regional-specific expression patterns identified novel markers and cell types associated with development and patterning of the urinary system. Furthermore, promoter analysis of synexpressed genes predicts transcriptional control mechanisms that regulate cell differentiation. The annotated informational resource (www.gudmap.org) will facilitate functional analysis of the mammalian kidney and provides useful information for the generation of novel genetic tools to manipulate emerging cell populations.

How do you find transcription factors? Computational approaches to compile and annotate repertoires of regulators for any genome

Transcription factors (TFs) play an important role in regulating gene expression. The availability of complete genome sequences and associated functional genomic data offer excellent opportunities to understand the transcriptional regulatory system of an entire organism. To do so, however, it is essential to compile a reliable dataset of regulatory components. Here, we review computational methods and publicly accessible resources that help identify TF-coding genes in prokaryotic and eukaryotic genomes. Since the regulatory functions of most TFs remain unknown, we also discuss approaches for combining diverse genomic datasets that will help elucidate their chromosomal organisation, expression, and evolutionary conservation. These analysis methods provide a solid foundation for further investigations of the transcriptional regulatory system.

AnimalTFDB: a comprehensive animal transcription factor database

Transcription factors (TFs) are proteins that bind to specific DNA sequences, thereby playing crucial roles in gene-expression regulation through controlling the transcription of genetic information from DNA to RNA. Transcription cofactors and chromatin remodeling factors are also essential in the gene transcriptional regulation. Identifying and annotating all the TFs are primary and crucial steps for illustrating their functions and understanding the transcriptional regulation. In this study, based on manual literature reviews, we collected and curated 72 TF families for animals, which is currently the most complete list of TF families in animals. Then, we systematically characterized all the TFs in 50 animal species and constructed a comprehensive animal TF database, AnimalTFDB. To better serve the community, we provided detailed annotations for each TF, including basic information, gene structure, functional domain, 3D structure hit, Gene Ontology, pathway, protein–protein interaction, paralogs, orthologs, potential TF-binding sites and targets. In addition, we collected and annotated transcription cofactors and chromatin remodeling factors. AnimalTFDB has a user-friendly web interface with multiple browse and search functions, as well as data downloading. It is freely available at http://www.bioguo.org/AnimalTFDB/.

Mouse transgenesis identifies conserved functional enhancers and cis-regulatory motif in the vertebrate LIM homeobox gene Lhx2 locus

The vertebrate Lhx2 is a member of the LIM homeobox family of transcription factors. It is essential for the normal development of the forebrain, eye, olfactory system and liver as well for the differentiation of lymphoid cells. However, despite the highly restricted spatio-temporal expression pattern of Lhx2, nothing is known about its transcriptional regulation. In mammals and chicken, Crb2, Dennd1a and Lhx2 constitute a conserved linkage block, while the intervening Dennd1a is lost in the fugu Lhx2 locus. To identify functional enhancers of Lhx2, we predicted conserved noncoding elements (CNEs) in the human, mouse and fugu Crb2-Lhx2 loci and assayed their function in transgenic mouse at E11.5. Four of the eight CNE constructs tested functioned as tissue-specific enhancers in specific regions of the central nervous system and the dorsal root ganglia (DRG), recapitulating partial and overlapping expression patterns of Lhx2 and Crb2 genes. There was considerable overlap in the expression domains of the CNEs, which suggests that the CNEs are either redundant enhancers or regulating different genes in the locus. Using a large set of CNEs (810 CNEs) associated with transcription factor-encoding genes that express predominantly in the central nervous system, we predicted four over-represented 8-mer motifs that are likely to be associated with expression in the central nervous system. Mutation of one of them in a CNE that drove reporter expression in the neural tube and DRG abolished expression in both domains indicating that this motif is essential for expression in these domains. The failure of the four functional enhancers to recapitulate the complete expression pattern of Lhx2 at E11.5 indicates that there must be other Lhx2 enhancers that are either located outside the region investigated or divergent in mammals and fishes. Other approaches such as sequence comparison between multiple mammals are required to identify and characterize such enhancers.

Components and mechanisms of regulation of gene expression

The control of gene expression is a biological process essential to all organisms. This is accomplished through the interaction of regulatory proteins with specific DNA motifs in the control regions of the genes that they regulate. Upon binding to DNA, and through specific protein-protein interactions, these regulatory proteins convey signals to the basal transcriptional machinery, containing the respective RNA polymerases, resulting in particular rates of gene expression. In eukaryotes, in addition and complementary to the binding of regulatory proteins to DNA, chromatin structure plays a role in modulating gene expression. Small RNAs are emerging as key components in this process. This chapter provides an introduction to some of the basic players participating in these processes, the transcription factors and co-regulators, the cis-regulatory elements that often function as transcription factor docking sites, and the emerging role of small RNAs in the regulation of gene expression.

Experimental advances in the characterization of metazoan gene regulatory networks

Gene regulatory networks (GRNs) play a vital role in metazoan development and function, and deregulation of these networks is often implicated in disease. GRNs depict the dynamic interactions between genomic and regulatory state components. The genomic components comprise genes and their associated cis-regulatory elements. The regulatory state components consist primarily of transcriptional complexes that bind the latter elements. With the availability of complete genome sequences, several approaches have recently been developed which promise to significantly enhance our ability to identify either the genomic or regulatory state components, or the interactions between these two. In this review, I provide an in-depth overview of these approaches and detail how each contributes to a more comprehensive understanding of GRN composition and function.

TFCat: the curated catalog of mouse and human transcription factors

TFCat is a catalog of mouse and human transcription factors based on a reliable core collection of annotations obtained by expert review of the scientific literature

Unravelling regulatory programs governed by transcription factors (TFs) is fundamental to understanding biological systems. TFCat is a catalog of mouse and human TFs based on a reliable core collection of annotations obtained by expert review of the scientific literature. The collection, including proven and homology-based candidate TFs, is annotated within a function-based taxonomy and DNA-binding proteins are organized within a classification system. All data and user-feedback mechanisms are available at the TFCat portal .

Evolution of conserved secondary structures and their function in transcriptional regulation networks

Background

Many conserved secondary structures have been identified within conserved elements in the human genome, but only a small fraction of them are known to be functional RNAs. The evolutionary variations of these conserved secondary structures in human populations and their biological functions have not been fully studied.

Results

We searched for polymorphisms within conserved secondary structures and identified a number of SNPs within these elements even though they are highly conserved among species. The density of SNPs in conserved secondary structures is about 65% of that of their flanking, non-conserved, sequences. Classification of sites as stems or as loops/bulges revealed that the density of SNPs in stems is about 62% of that found in loops/bulges. Analysis of derived allele frequency data indicates that sites in stems are under stronger evolutionary constraint than sites in loops/bulges. Intergenic conserved secondary structures tend to associate with transcription factor-encoding genes with genetic distance being the measure of regulator-gene associations. A substantial fraction of intergenic conserved secondary structures overlap characterized binding sites for multiple transcription factors.

Conclusion

Strong purifying selection implies that secondary structures are probably important carriers of biological functions for conserved sequences. The overlap between intergenic conserved secondary structures and transcription factor binding sites further suggests that intergenic conserved secondary structures have essential roles in directing gene expression in transcriptional regulation networks.