cis-Regulatory control circuits in development

Targeted mutagenesis of specific genomic DNA sequences in animals for the in vivo generation of variant libraries

Understanding how the number, placement and affinity of transcription factor binding sites dictates gene regulatory programs remains a major unsolved challenge in biology, particularly in the context of multicellular organisms. To uncover these rules, it is first necessary to find the binding sites within a regulatory region with high precision, and then to systematically modulate this binding site arrangement while simultaneously measuring the effect of this modulation on output gene expression. Massively parallel reporter assays (MPRAs), where the gene expression stemming from 10,000s of in vitro-generated regulatory sequences is measured, have made this feat possible in high-throughput in single cells in culture. However, because of lack of technologies to incorporate DNA libraries, MPRAs are limited in whole organisms. To enable MPRAs in multicellular organisms, we generated tools to create a high degree of mutagenesis in specific genomic loci in vivo using base editing. Targeting GFP integrated in genome of Drosophila cell culture and whole animals as a case study, we show that the base editor AID evoCDA1 stemming from sea lamprey fused to nCas9 is highly mutagenic. Surprisingly, longer gRNAs increase mutation efficiency and expand the mutating window, which can allow the introduction of mutations in previously untargetable sequences. Finally, we demonstrate arrays of >20 gRNAs that can efficiently introduce mutations along a 200bp sequence, making it a promising tool to test enhancer function in vivo in a high throughput manner.

Cellular computation and cognition

Contemporary neural network models often overlook a central biological fact about neural processing: that single neurons are themselves complex, semi-autonomous computing systems. Both the information processing and information storage abilities of actual biological neurons vastly exceed the simple weighted sum of synaptic inputs computed by the "units" in standard neural network models. Neurons are eukaryotic cells that store information not only in synapses, but also in their dendritic structure and connectivity, as well as genetic "marking" in the epigenome of each individual cell. Each neuron computes a complex nonlinear function of its inputs, roughly equivalent in processing capacity to an entire 1990s-era neural network model. Furthermore, individual cells provide the biological interface between gene expression, ongoing neural processing, and stored long-term memory traces. Neurons in all organisms have these properties, which are thus relevant to all of neuroscience and cognitive biology. Single-cell computation may also play a particular role in explaining some unusual features of human cognition. The recognition of the centrality of cellular computation to "natural computation" in brains, and of the constraints it imposes upon brain evolution, thus has important implications for the evolution of cognition, and how we study it.

Exploring the genetic landscape of nitrogen uptake in durum wheat: genome-wide characterization and expression profiling of NPF and NRT2 gene families

Nitrate uptake by plants primarily relies on two gene families: Nitrate transporter 1/peptide transporter (NPF) and Nitrate transporter 2 (NRT2). Here, we extensively characterized the NPF and NRT2 families in the durum wheat genome, revealing 211 NPF and 20 NRT2 genes. The two families share many Cis Regulatory Elements (CREs) and Transcription Factor binding sites, highlighting a partially overlapping regulatory system and suggesting a coordinated response for nitrate transport and utilization. Analyzing RNA-seq data from 9 tissues and 20 cultivars, we explored expression profiles and co-expression relationships of both gene families. We observed a strong correlation between nucleotide variation and gene expression within the NRT2 gene family, implicating a shared selection mechanism operating on both coding and regulatory regions. Furthermore, NPF genes showed highly tissue-specific expression profiles, while NRT2s were mainly divided in two co-expression modules, one expressed in roots (NAR2/NRT3 dependent) and the other induced in anthers and/ovaries during maturation. Our evidences confirmed that the majority of these genes were retained after small-scale duplication events, suggesting a neo- or sub-functionalization of many NPFs and NRT2s. Altogether, these findings indicate that the expansion of these gene families in durum wheat could provide valuable genetic variability useful to identify NUE-related and candidate genes for future breeding programs in the context of low-impact and sustainable agriculture.

In-silico identification and comparison of transcription factor binding sites cluster in anterior-posterior patterning genes in Drosophila melanogaster and Tribolium castaneum

The cis-regulatory data that help in transcriptional regulation is arranged into modular pieces of a few hundred base pairs called CRMs (cis-regulatory modules) and numerous binding sites for multiple transcription factors are prominent characteristics of these cis-regulatory modules. The present study was designed to localize transcription factor binding site (TFBS) clusters on twelve Anterior-posterior (A-P) genes in Tribolium castaneum and compare them to their orthologous gene enhancers in Drosophila melanogaster. Out of the twelve A-P patterning genes, six were gap genes (Kruppel, Knirps, Tailless, Hunchback, Giant, and Caudal) and six were pair rule genes (Hairy, Runt, Even-skipped, Fushi-tarazu, Paired, and Odd-skipped). The genes along with 20 kb upstream and downstream regions were scanned for TFBS clusters using the Motif Cluster Alignment Search Tool (MCAST), a bioinformatics tool that looks for set of nucleotide sequences for statistically significant clusters of non-overlapping occurrence of a given set of motifs. The motifs used in the current study were Hunchback, Caudal, Giant, Kruppel, Knirps, and Even-skipped. The results of the MCAST analysis revealed the maximum number of TFBS for Hunchback, Knirps, Caudal, and Kruppel in both D. melanogaster and T. castaneum, while Bicoid TFBS clusters were found only in D. melanogaster. The size of all the predicted TFBS clusters was less than 1kb in both insect species. These sequences revealed more transversional sites (Tv) than transitional sites (Ti) and the average Ti/Tv ratio was 0.75.

Changes in locus wide repression underlie the evolution of Drosophila abdominal pigmentation

Changes in gene regulation represent an important path to generate developmental differences affecting anatomical traits. Interspecific divergence in gene expression often results from changes in transcription-stimulating enhancer elements. While gene repression is crucial for precise spatiotemporal expression patterns, the relative contribution of repressive transcriptional silencers to regulatory evolution remains to be addressed. Here, we show that the Drosophila pigmentation gene ebony has mainly evolved through changes in the spatial domains of silencers patterning its abdominal expression. By precisely editing the endogenous ebony locus of D. melanogaster, we demonstrate the requirement of two redundant abdominal enhancers and three silencers that repress the redundant enhancers in a patterned manner. We observe a role for changes in these silencers in every case of ebony evolution observed to date. Our findings suggest that negative regulation by silencers likely has an under-appreciated role in gene regulatory evolution.

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements

Purpose

Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learning approach, trained on epigenomic data from the adult human retina, to systematically quantify the predicted impact of cis-regulatory variants.

Methods

We used human retinal DNA accessibility data (ATAC-seq) to determine a set of 18.9k high-confidence, putative cis-regulatory elements. Eighty percent of these elements were used to train a machine learning model utilizing a gapped k-mer support vector machine-based approach. In silico saturation mutagenesis and variant scoring was applied to predict the functional impact of all potential single nucleotide variants within cis-regulatory elements. Impact scores were tested in a 20% hold-out dataset and compared to allele population frequency, phylogenetic conservation, transcription factor (TF) binding motifs, and existing massively parallel reporter assay data.

Results

We generated a model that distinguishes between human retinal regulatory elements and negative test sequences with 95% accuracy. Among a hold-out test set of 3.7k human retinal CREs, all possible single nucleotide variants were scored. Variants with negative impact scores correlated with higher phylogenetic conservation of the reference allele, disruption of predicted TF binding motifs, and massively parallel reporter expression.

Conclusions

We demonstrated the utility of human retinal epigenomic data to train a machine learning model for the purpose of predicting the impact of non-coding regulatory sequence variants. Our model accurately scored sequences and predicted putative transcription factor binding motifs. This approach has the potential to expedite the characterization of pathogenic non-coding sequence variants in the context of unexplained retinal disease.

Translational Relevance

This workflow and resulting dataset serve as a promising genomic tool to facilitate the clinical prioritization of functionally disruptive non-coding mutations in the retina.

Interpretation of deep learning in genomics and epigenomics

Machine learning methods have been widely applied to big data analysis in genomics and epigenomics research. Although accuracy and efficiency are common goals in many modeling tasks, model interpretability is especially important to these studies towards understanding the underlying molecular and cellular mechanisms. Deep neural networks (DNNs) have recently gained popularity in various types of genomic and epigenomic studies due to their capabilities in utilizing large-scale high-throughput bioinformatics data and achieving high accuracy in predictions and classifications. However, DNNs are often challenged by their potential to explain the predictions due to their black-box nature. In this review, we present current development in the model interpretation of DNNs, focusing on their applications in genomics and epigenomics. We first describe state-of-the-art DNN interpretation methods in representative machine learning fields. We then summarize the DNN interpretation methods in recent studies on genomics and epigenomics, focusing on current data- and computing-intensive topics such as sequence motif identification, genetic variations, gene expression, chromatin interactions and non-coding RNAs. We also present the biological discoveries that resulted from these interpretation methods. We finally discuss the advantages and limitations of current interpretation approaches in the context of genomic and epigenomic studies. Contact:xiaoman@mail.ucf.edu, haihu@cs.ucf.edu.

Ciona Brachyury proximal and distal enhancers have different FGF dose-response relationships

Many genes are regulated by two or more enhancers that drive similar expression patterns. Evolutionary theory suggests that these seemingly redundant enhancers must have functionally important differences. In the simple ascidian chordate Ciona, the transcription factor Brachyury is induced exclusively in the presumptive notochord downstream of lineage specific regulators and FGF-responsive Ets family transcription factors. Here we exploit the ability to finely titrate FGF signaling activity via the MAPK pathway using the MEK inhibitor U0126 to quantify the dependence of transcription driven by different Brachyury reporter constructs on this direct upstream regulator. We find that the more powerful promoter-adjacent proximal enhancer and a weaker distal enhancer have fundamentally different dose-response relationships to MAPK inhibition. The Distal enhancer is more sensitive to MAPK inhibition but shows a less cooperative response, whereas the Proximal enhancer is less sensitive and more cooperative. A longer construct containing both enhancers has a complex dose-response curve that supports the idea that the proximal and distal enhancers are moderately super-additive. We show that the overall expression loss from intermediate doses of U0126 is not only a function of the fraction of cells expressing these reporters, but also involves graded decreases in expression at the single-cell level. Expression of the endogenous gene shows a comparable dose-response relationship to the full length reporter, and we find that different notochord founder cells are differentially sensitive to MAPK inhibition. Together, these results indicate that although the two Brachyury enhancers have qualitatively similar expression patterns, they respond to FGF in quantitatively different ways and act together to drive high levels of Brachyury expression with a characteristic input/output relationship. This indicates that they are fundamentally not equivalent genetic elements.

When and where genes are expressed is controlled by regulatory DNA regions known as enhancers. Genes often have multiple enhancers that control expression in different cell types or embryonic regions, but there are also genes that have multiple enhancers that control near-identical expression patterns. These ‘shadow’ enhancers are common features of many animal genomes, but it is unclear to what extent they are truly identical in function. Here we studied a pair of shadow enhancers for the notochord-specific gene Brachyury in the simple model chordate Ciona that are both directly activated by the same signaling pathway. We titrated the activity of this pathway with graded doses of a pharmacological inhibitor and measured the effects in quantitative enhancer assays. We found that the two enhancers had significant differences in sensitivity and cooperativity to the same shared regulator and are thus not identical in function when assessed quantitatively. We also identified subtle differences in sensitivity to this upstream signal between different notochord precursor cells.

Lymphedema distichiasis syndrome may be caused by FOXC2 promoter-enhancer dissociation and disruption of a topological associated domain

Lymphedema distichiasis syndrome (LDS) is a rare autosomal dominant condition characterized by lower limb lymphedema, distichiasis, and variable additional features. LDS is usually caused by heterozygous sequence variants in the FOXC2 gene located at 16q24, but in one previous instance LDS has resulted from a balanced reciprocal translocation with a breakpoint at 16q24, 120 kb distal to the FOXC2 gene suggesting a position effect. Here, we describe a second family with LDS caused by a translocation involving 16q24. The family were ascertained after detection of a paternally inherited balanced reciprocal translocation t(16;22)(q24;q13.1) in a pregnancy complicated by severe fetal hydrops. There was a past history of multiple miscarriages in the father's family, and a personal and family history of lymphedema and distichiasis, consistent with the diagnosis of LDS. Using whole genome amplified DNA from single sperm of the male proband, bead array analysis demonstrated that the FOXC2 gene was intact and the chromosome 16 breakpoint mapped to the same region 120Kb distal to the FOXC2 gene. This case highlights the clinical consequences that can arise from a translocation of genomic material without dosage imbalance, and that it is increasingly feasible to predict and characterize possible effects with improved access to molecular techniques.

Retrograde BMP signaling activates neuronal gene expression through widespread deployment of a conserved BMP-responsive cis-regulatory activation element

Retrograde Bone Morphogenetic Protein (BMP) signaling in neurons is essential for the differentiation and synaptic function of many neuronal subtypes. BMP signaling regulates these processes via Smad transcription factor activity, yet the scope and nature of Smad-dependent gene regulation in neurons are mostly unknown. Here, we applied a computational approach to predict Smad-binding cis-regulatory BMP-Activating Elements (BMP-AEs) in Drosophila, followed by transgenic in vivo reporter analysis to test their neuronal subtype enhancer activity in the larval central nervous system (CNS). We identified 34 BMP-AE-containing genomic fragments that are responsive to BMP signaling in neurons, and showed that the embedded BMP-AEs are required for this activity. RNA-seq analysis identified BMP-responsive genes in the CNS and revealed that BMP-AEs selectively enrich near BMP-activated genes. These data suggest that functional BMP-AEs control nearby BMP-activated genes, which we validated experimentally. Finally, we demonstrated that the BMP-AE motif mediates a conserved Smad-responsive function in the Drosophila and vertebrate CNS. Our results provide evidence that BMP signaling controls neuronal function by directly coordinating the expression of a battery of genes through widespread deployment of a conserved Smad-responsive cis-regulatory motif.

Gfi1aa and Gfi1b set the pace for primitive erythroblast differentiation from hemangioblasts in the zebrafish embryo

The transcriptional repressors Gfi1(a) and Gfi1b are epigenetic regulators with unique and overlapping roles in hematopoiesis. In different contexts, Gfi1 and Gfi1b restrict or promote cell proliferation, prevent apoptosis, influence cell fate decisions, and are essential for terminal differentiation. Here, we show in primitive red blood cells (prRBCs) that they can also set the pace for cellular differentiation. In zebrafish, prRBCs express 2 of 3 zebrafish Gfi1/1b paralogs, Gfi1aa and Gfi1b. The recently identified zebrafish gfi1aa gene trap allele qmc551 drives erythroid green fluorescent protein (GFP) instead of Gfi1aa expression, yet homozygous carriers have normal prRBCs. prRBCs display a maturation defect only after splice morpholino-mediated knockdown of Gfi1b in gfi1aa qmc551 homozygous embryos. To study the transcriptome of the Gfi1aa/1b double-depleted cells, we performed an RNA-Seq experiment on GFP-positive prRBCs sorted from 20-hour-old embryos that were heterozygous or homozygous for gfi1aa qmc551 , as well as wt or morphant for gfi1b We subsequently confirmed and extended these data in whole-mount in situ hybridization experiments on newly generated single- and double-mutant embryos. Combined, the data showed that in the absence of Gfi1aa, the synchronously developing prRBCs were delayed in activating late erythroid differentiation, as they struggled to suppress early erythroid and endothelial transcription programs. The latter highlighted the bipotent nature of the progenitors from which prRBCs arise. In the absence of Gfi1aa, Gfi1b promoted erythroid differentiation as stepwise loss of wt gfi1b copies progressively delayed Gfi1aa-depleted prRBCs even further, showing that Gfi1aa and Gfi1b together set the pace for prRBC differentiation from hemangioblasts.

Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs

Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, "Exploration of Distinctive CREs and CRMs" (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, "CRM Network Generator" (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression.

A CD47-associated super-enhancer links pro-inflammatory signalling to CD47 upregulation in breast cancer

CD47 is a cell surface molecule that inhibits phagocytosis of cells that express it by binding to its receptor, SIRPα, on macrophages and other immune cells. CD47 is expressed at different levels by neoplastic and normal cells. Here, to reveal mechanisms by which different neoplastic cells generate this dominant 'don't eat me' signal, we analyse the CD47 regulatory genomic landscape. We identify two distinct super-enhancers (SEs) associated with CD47 in certain cancer cell types. We show that a set of active constituent enhancers, located within the two CD47 SEs, regulate CD47 expression in different cancer cell types and that disruption of CD47 SEs reduces CD47 gene expression. Finally we report that the TNF-NFKB1 signalling pathway directly regulates CD47 by interacting with a constituent enhancer located within a CD47-associated SE specific to breast cancer. These results suggest that cancers can evolve SE to drive CD47 overexpression to escape immune surveillance.

NF-E2, FLI1 and RUNX1 collaborate at areas of dynamic chromatin to activate transcription in mature mouse megakaryocytes

Mutations in mouse and human Nfe2, Fli1 and Runx1 cause thrombocytopenia. We applied genome-wide chromatin dynamics and ChIP-seq to determine these transcription factors’ (TFs) activities in terminal megakaryocyte (MK) maturation. Enhancers with H3K4me2-marked nucleosome pairs were most enriched for NF-E2, FLI and RUNX sequence motifs, suggesting that this TF triad controls much of the late MK program. ChIP-seq revealed NF-E2 occupancy near previously implicated target genes, whose expression is compromised in Nfe2-null cells, and many other genes that become active late in MK differentiation. FLI and RUNX were also the motifs most enriched near NF-E2 binding sites and ChIP-seq implicated FLI1 and RUNX1 in activation of late MK, including NF-E2-dependent, genes. Histones showed limited activation in regions of single TF binding, while enhancers that bind NF-E2 and either RUNX1, FLI1 or both TFs gave the highest signals for TF occupancy and H3K4me2; these enhancers associated best with genes activated late in MK maturation. Thus, three essential TFs co-occupy late-acting cis-elements and show evidence for additive activity at genes responsible for platelet assembly and release. These findings provide a rich dataset of TF and chromatin dynamics in primary MK and explain why individual TF losses cause thrombopocytopenia.

Spatial distribution of predicted transcription factor binding sites in Drosophila ChIP peaks

In the development of the Drosophila embryo, gene expression is directed by the sequence-specific interactions of a large network of protein transcription factors (TFs) and DNA cis-regulatory binding sites. Once the identity of the typically 8-10bp binding sites for any given TF has been determined by one of several experimental procedures, the sequences can be represented in a position weight matrix (PWM) and used to predict the location of additional TF binding sites elsewhere in the genome. Often, alignments of large (>200bp) genomic fragments that have been experimentally determined to bind the TF of interest in Chromatin Immunoprecipitation (ChIP) studies are trimmed under the assumption that the majority of the binding sites are located near the center of all the aligned fragments. In this study, ChIP/chip datasets are analyzed using the corresponding PWMs for the well-studied TFs; CAUDAL, HUNCHBACK, KNIRPS and KRUPPEL, to determine the distribution of predicted binding sites. All four TFs are critical regulators of gene expression along the anterio-posterior axis in early Drosophila development. For all four TFs, the ChIP peaks contain multiple binding sites that are broadly distributed across the genomic region represented by the peak, regardless of the prediction stringency criteria used. This result suggests that ChIP peak trimming may exclude functional binding sites from subsequent analyses.

Brachyury, Foxa2 and the cis-Regulatory Origins of the Notochord

A main challenge of modern biology is to understand how specific constellations of genes are activated to differentiate cells and give rise to distinct tissues. This study focuses on elucidating how gene expression is initiated in the notochord, an axial structure that provides support and patterning signals to embryos of humans and all other chordates. Although numerous notochord genes have been identified, the regulatory DNAs that orchestrate development and propel evolution of this structure by eliciting notochord gene expression remain mostly uncharted, and the information on their configuration and recurrence is still quite fragmentary. Here we used the simple chordate Ciona for a systematic analysis of notochord cis-regulatory modules (CRMs), and investigated their composition, architectural constraints, predictive ability and evolutionary conservation. We found that most Ciona notochord CRMs relied upon variable combinations of binding sites for the transcription factors Brachyury and/or Foxa2, which can act either synergistically or independently from one another. Notably, one of these CRMs contains a Brachyury binding site juxtaposed to an (AC) microsatellite, an unusual arrangement also found in Brachyury-bound regulatory regions in mouse. In contrast, different subsets of CRMs relied upon binding sites for transcription factors of widely diverse families. Surprisingly, we found that neither intra-genomic nor interspecific conservation of binding sites were reliably predictive hallmarks of notochord CRMs. We propose that rather than obeying a rigid sequence-based cis-regulatory code, most notochord CRMs are rather unique. Yet, this study uncovered essential elements recurrently used by divergent chordates as basic building blocks for notochord CRMs.

Handling Permutation in Sequence Comparison: Genome-Wide Enhancer Prediction in Vertebrates by a Novel Non-Linear Alignment Scoring Principle

Enhancers have been described to evolve by permutation without changing function. This has posed the problem of how to predict enhancer elements that are hidden from alignment-based approaches due to the loss of co-linearity. Alignment-free algorithms have been proposed as one possible solution. However, this approach is hampered by several problems inherent to its underlying working principle. Here we present a new approach, which combines the power of alignment and alignment-free techniques into one algorithm. It allows the prediction of enhancers based on the query and target sequence only, no matter whether the regulatory logic is co-linear or reshuffled. To test our novel approach, we employ it for the prediction of enhancers across the evolutionary distance of ~450Myr between human and medaka. We demonstrate its efficacy by subsequent in vivo validation resulting in 82% (9/11) of the predicted medaka regions showing reporter activity. These include five candidates with partially co-linear and four with reshuffled motif patterns. Orthology in flanking genes and conservation of the detected co-linear motifs indicates that those candidates are likely functionally equivalent enhancers. In sum, our results demonstrate that the proposed principle successfully predicts mutated as well as permuted enhancer regions at an encouragingly high rate.

Proteogenomics of the human hippocampus: The road ahead

The hippocampus is one of the most essential components of the human brain and plays an important role in learning and memory. The hippocampus has drawn great attention from scientists and clinicians due to its clinical importance in diseases such as Alzheimer's disease (AD), non-AD dementia, and epilepsy. Understanding the function of the hippocampus and related disease mechanisms requires comprehensive knowledge of the orchestration of the genome, epigenome, transcriptome, proteome, and post-translational modifications (PTMs) of proteins. The past decade has seen remarkable advances in the high-throughput sequencing techniques that are collectively called next generation sequencing (NGS). NGS enables the precise analysis of gene expression profiles in cells and tissues, allowing powerful and more feasible integration of expression data from the gene level to the protein level, even allowing "-omic" level assessment of PTMs. In addition, improved bioinformatics algorithms coupled with NGS technology are finally opening a new era for scientists to discover previously unidentified and elusive proteins. In the present review, we will focus mainly on the proteomics of the human hippocampus with an emphasis on the integrated analysis of genomics, epigenomics, transcriptomics, and proteomics. Finally, we will discuss our perspectives on the potential and future of proteomics in the field of hippocampal biology. This article is part of a Special Issue entitled: Neuroproteomics: Applications in Neuroscience and Neurology.

Gene network exploration of crosstalk between apoptosis and autophagy in chronic myelogenous leukemia

BACKGROUND

Gene expression levels change to adapt the stress, such as starvation, toxin, and radiation. The changes are signals transmitted through molecular interactions, eventually leading to two cellular fates, apoptosis and autophagy. Due to genetic variations, the signals may not be effectively transmitted to modulate apoptotic and autophagic responses. Such aberrant modulation may lead to carcinogenesis and drug resistance. The balance between apoptosis and autophagy becomes very crucial in coping with the stress. Though there have been evidences illustrating the apoptosis-autophagy interplay, the underlying mechanism and the participation of the regulators including transcription factors (TFs) and microRNAs (miRNAs) remain unclear.

RESULTS

Gene network is a graphical illustration for exploring the functional linkages and the potential coordinate regulations of genes. Microarray dataset for the study of chronic myeloid leukemia was obtained from Gene Expression Omnibus. The expression profiles of those genes related to apoptosis and autophagy, including MCL1, BCL2, ATG, beclin-1, BAX, BAK, E2F, cMYC, PI3K, AKT, BAD, and LC3, were extracted from the dataset to construct the gene networks.

CONCLUSION

The network analysis of these genes explored the underlying mechanisms and the roles of TFs and miRNAs for the crosstalk between apoptosis and autophagy.

The gene regulatory networks underlying formation of the auditory hindbrain

Development and evolution of auditory hindbrain nuclei are two major unsolved issues in hearing research. Recent characterization of transgenic mice identified the rhombomeric origins of mammalian auditory nuclei and unraveled genes involved in their formation. Here, we provide an overview on these data by assembling them into rhombomere-specific gene regulatory networks (GRNs), as they underlie developmental and evolutionary processes. To explore evolutionary mechanisms, we compare the GRNs operating in the mammalian auditory hindbrain with data available from the inner ear and other vertebrate groups. Finally, we propose that the availability of genomic sequences from all major vertebrate taxa and novel genetic techniques for non-model organisms provide an unprecedented opportunity to investigate development and evolution of the auditory hindbrain by comparative molecular approaches. The dissection of the molecular mechanisms leading to auditory structures will also provide an important framework for auditory processing disorders, a clinical problem difficult to tackle so far. These data will, therefore, foster basic and clinical hearing research alike.

A method for using direct injection of plasmid DNA to study cis-regulatory element activity in F0 Xenopus embryos and tadpoles

The ability to express exogenous reporter genes in intact, externally developing embryos, such as Xenopus, is a powerful tool for characterizing the activity of cis-regulatory gene elements during development. Although methods exist for generating transgenic Xenopus lines, more simplified methods for use with F0 animals would significantly speed the characterization of these elements. We discovered that injecting 2-cell stage embryos with a plasmid bearing a ϕC31 integrase-targeted attB element and two dual β-globin HS4 insulators flanking a reporter transgene in opposite orientations relative to each other yielded persistent expression with sufficiently high penetrance for characterizing the activity of the promoter without having to coinject integrase RNA. Expression began appropriately during development and persisted into swimming tadpole stages without perturbing the expression of the cognate endogenous gene. Coinjected plasmids having the same elements but expressing different reporter proteins were reliably coexpressed within the same cells, providing a useful control for variations in injections between animals. To overcome the high propensity of these plasmids to undergo recombination, we developed a method for generating them using conventional cloning methods and DH5α cells for propagation. We conclude that this method offers a convenient and reliable way to evaluate the activity of cis-regulatory gene elements in the intact F0 embryo.

The rise of regulatory RNA

Discoveries over the past decade portend a paradigm shift in molecular biology. Evidence suggests that RNA is not only functional as a messenger between DNA and protein but also involved in the regulation of genome organization and gene expression, which is increasingly elaborate in complex organisms. Regulatory RNA seems to operate at many levels; in particular, it plays an important part in the epigenetic processes that control differentiation and development. These discoveries suggest a central role for RNA in human evolution and ontogeny. Here, we review the emergence of the previously unsuspected world of regulatory RNA from a historical perspective.

Genetic evidence for conserved non-coding element function across species-the ears have it

Comparison of genomic sequences from diverse vertebrate species has revealed numerous highly conserved regions that do not appear to encode proteins or functional RNAs. Often these “conserved non-coding elements,” or CNEs, can direct gene expression to specific tissues in transgenic models, demonstrating they have regulatory function. CNEs are frequently found near “developmental” genes, particularly transcription factors, implying that these elements have essential regulatory roles in development. However, actual examples demonstrating CNE regulatory functions across species have been few, and recent loss-of-function studies of several CNEs in mice have shown relatively minor effects. In this Perspectives article, we discuss new findings in “fancy” rats and Highland cattle demonstrating that function of a CNE near the Hmx1 gene is crucial for normal external ear development and when disrupted can mimic loss-of function Hmx1 coding mutations in mice and humans. These findings provide important support for conserved developmental roles of CNEs in divergent species, and reinforce the concept that CNEs should be examined systematically in the ongoing search for genetic causes of human developmental disorders in the era of genome-scale sequencing.

Cross talk and interference enhance information capacity of a signaling pathway

A recurring motif in gene regulatory networks is transcription factors (TFs) that regulate each other and then bind to overlapping sites on DNA, where they interact and synergistically control transcription of a target gene. Here, we suggest that this motif maximizes information flow in a noisy network. Gene expression is an inherently noisy process due to thermal fluctuations and the small number of molecules involved. A consequence of multiple TFs interacting at overlapping binding sites is that their binding noise becomes correlated. Using concepts from information theory, we show that in general a signaling pathway transmits more information if 1), noise of one input is correlated with that of the other; and 2), input signals are not chosen independently. In the case of TFs, the latter criterion hints at upstream cross-regulation. We demonstrate these ideas for competing TFs and feed-forward gene-regulatory modules, and discuss generalizations to other signaling pathways. Our results challenge the conventional approach of treating biological noise as uncorrelated fluctuations, and present a systematic method for understanding TF cross-regulation networks either from direct measurements of binding noise or from bioinformatic analysis of overlapping binding sites.

Life's timekeeper

Life's timekeeper is a 'free-running' intracellular oscillator synchronised across all cells. It runs throughout life splitting lifespan into equal length phases. During the maturational period it controls the overall rate of progression whereas in the post-maturational period it controls the overall rate of ageing. This includes the rate of senescence and hence time to death. As such life's timekeeper equates maturational and post-maturational time, hence explains the tight correlation between these time periods that has existed throughout mammalian evolution. Life's timekeeper is proposed to have played an important role in vertebrate evolution. A slower oscillatory frequency results in proportional life phase prolongation. This leads to increased body and brain size, together with extended lifespan. Higher brain centres, neocortex in mammals, are disproportionately enlarged. Hence behavioural capacity is increased. The extended post-maturational period ensures that there is enough time in order that the behavioural advantages can be fully manifest in the environment. A faster oscillatory frequency would result in proportional life phase reduction. This process however would lead to reduced behavioural capacity, and is hence unlikely to be positively selected. Therefore throughout evolution life's timekeeper has operated to extend lifespan. It has hence functioned to promote longevity as opposed to ageing.

Enhancer activity sensitive to the orientation of the gene it regulates in the chordate genome

Enhancers are flexible in terms of their location and orientation relative to the genes they regulate. However, little is known about whether the flexibility can be applied in every combination of enhancers and genes. Enhancer detection with transposable elements is a powerful method to identify enhancers in the genome and to create marker lines expressing fluorescent proteins in a tissue-specific manner. In the chordate Ciona intestinalis, this method has been established with a Tc1/mariner superfamily transposon Minos. Previously, we created the enhancer detection line E[MiTSAdTPOG]15 (E15) that specifically expresses green fluorescent protein (GFP) in the central nervous system (CNS) after metamorphosis. In this study, we identified the causal insertion site of the transgenic line. There are two genes flanking the causal insertion of the E15 line, and the genomic region around the insertion site contains the enhancers responsible for the expression in the endostyle and gut in addition to the CNS. We found that the endostyle and gut enhancers show sensitivity to the orientation of the GFP gene for their enhancer activity. Namely, the enhancers cannot enhance the expression of GFP which is inserted at the same orientation as the E15 line, while the enhancers can enhance GFP expression inserted at the opposite orientation. The CNS enhancer can enhance GFP expression in both orientations. The DNA element adjacent to the endostyle enhancer is responsible for the orientation sensitivity of the enhancer. The different sensitivity of the enhancers to the orientation of the transgene is a cause of CNS-specific GFP expression in the E15 line.

Uncovering transcription factor modules using one- and three-dimensional analyses

Transcriptional regulation is a critical mediator of many normal cellular processes, as well as disease progression. Transcription factors (TFs) often co-localize at cis-regulatory elements on the DNA, form protein complexes, and collaboratively regulate gene expression. Machine learning and Bayesian approaches have been used to identify TF modules in a one-dimensional context. However, recent studies using high throughput technologies have shown that TF interactions should also be considered in three-dimensional nuclear space. Here, we describe methods for identifying TF modules and discuss how moving from a one-dimensional to a three-dimensional paradigm, along with integrated experimental and computational approaches, can lead to a better understanding of TF association networks.

Gene regulatory networks in cardiac conduction system development

The cardiac conduction system is a specialized tract of myocardial cells responsible for maintaining normal cardiac rhythm. Given its critical role in coordinating cardiac performance, a detailed analysis of the molecular mechanisms underlying conduction system formation should inform our understanding of arrhythmia pathophysiology and affect the development of novel therapeutic strategies. Historically, the ability to distinguish cells of the conduction system from neighboring working myocytes presented a major technical challenge for performing comprehensive mechanistic studies. Early lineage tracing experiments suggested that conduction cells derive from cardiomyocyte precursors, and these claims have been substantiated by using more contemporary approaches. However, regional specialization of conduction cells adds an additional layer of complexity to this system, and it appears that different components of the conduction system utilize unique modes of developmental formation. The identification of numerous transcription factors and their downstream target genes involved in regional differentiation of the conduction system has provided insight into how lineage commitment is achieved. Furthermore, by adopting cutting-edge genetic techniques in combination with sophisticated phenotyping capabilities, investigators have made substantial progress in delineating the regulatory networks that orchestrate conduction system formation and their role in cardiac rhythm and physiology. This review describes the connectivity of these gene regulatory networks in cardiac conduction system development and discusses how they provide a foundation for understanding normal and pathological human cardiac rhythms.

Cis-regulatory properties of medaka synexpression groups

During embryogenesis, tissue specification is triggered by the expression of a unique combination of developmental genes and their expression in time and space is crucial for successful development. Synexpression groups are batteries of spatiotemporally co-expressed genes that act in shared biological processes through their coordinated expression. Although several synexpression groups have been described in numerous vertebrate species, the regulatory mechanisms that orchestrate their common complex expression pattern remain to be elucidated. Here we performed a pilot screen on 560 genes of the vertebrate model system medaka (Oryzias latipes) to systematically identify synexpression groups and investigate their regulatory properties by searching for common regulatory cues. We find that synexpression groups share DNA motifs that are arranged in various combinations into cis-regulatory modules that drive co-expression. In contrast to previous assumptions that these genes are located randomly in the genome, we discovered that genes belonging to the same synexpression group frequently occur in synexpression clusters in the genome. This work presents a first repertoire of synexpression group common signatures, a resource that will contribute to deciphering developmental gene regulatory networks.

Lens development depends on a pair of highly conserved Sox21 regulatory elements

Highly conserved non-coding elements (CNEs) linked to genes involved in embryonic development have been hypothesised to correspond to cis-regulatory modules due to their ability to induce tissue-specific expression patterns. However, attempts to prove their requirement for normal development or for the correct expression of the genes they are associated with have yielded conflicting results. Here, we show that CNEs at the vertebrate Sox21 locus are crucial for Sox21 expression in the embryonic lens and that loss of Sox21 function interferes with normal lens development. Using different expression assays in zebrafish we find that two CNEs linked to Sox21 in all vertebrates contain lens enhancers and that their removal from a reporter BAC abolishes lens expression. Furthermore inhibition of Sox21 function after the injection of a sox21b morpholino into zebrafish leads to defects in lens development. These findings identify a direct link between sequence conservation and genomic function of regulatory sequences. In addition to this we provide evidence that putative Sox binding sites in one of the CNEs are essential for induction of lens expression as well as enhancer function in the CNS. Our results show that CNEs identified in pufferfish-mammal whole-genome comparisons are crucial developmental enhancers and hence essential components of gene regulatory networks underlying vertebrate embryogenesis.

Mapping association between long-range cis-regulatory regions and their target genes using synteny

In chordates, long-range cis-regulatory regions are involved in the control of transcription initiation (either as repressors or enhancers). Their main characteristics are that (i) they can be located as far as 1 Mb away from the transcription start site of the target gene, (ii) they can regulate more than one gene, and (iii) they are usually orientation-independent. Therefore, proper characterization of functional interactions between long-range cis-regulatory regions and their target genes remains problematic. We present a novel method to predict such interactions based on the analysis of rearrangements between the human and 16 other vertebrate genomes. Our method is based on the assumption that genome rearrangements that would disrupt the functional interaction between a cis-regulatory region and its target gene are likely to be deleterious. Therefore, conservation of synteny through evolution would be an indication of a functional interaction. We use our algorithm to predict the association between a set of 123,905 human candidate regulatory regions to their target gene(s). This genome-wide map of interactions has many potential applications, including the selection of candidate regions prior to in vivo experimental characterization, a better characterization of regulatory regions involved in position effect diseases, and an improved understanding of the mechanisms and importance of long-range regulation.

Thousands of cis-regulatory sequence combinations are shared by Arabidopsis and poplar

The identification of cis-regulatory modules (CRMs) can greatly advance our understanding of gene regulatory mechanisms. Despite the existence of binding sites of more than three transcription factors (TFs) in a CRM, studies in plants often consider only the cooccurrence of binding sites of one or two TFs. In addition, CRM studies in plants are limited to combinations of only a few families of TFs. It is thus not clear how widespread plant TFs work together, which TFs work together to regulate plant genes, and how the combinations of these TFs are shared by different plants. To fill these gaps, we applied a frequent pattern-mining-based approach to identify frequently used cis-regulatory sequence combinations in the promoter sequences of two plant species, Arabidopsis (Arabidopsis thaliana) and poplar (Populus trichocarpa). A cis-regulatory sequence here corresponds to a DNA motif bound by a TF. We identified 18,638 combinations composed of two to six cis-regulatory sequences that are shared by the two plant species. In addition, with known cis-regulatory sequence combinations, gene function annotation, gene expression data, and known functional gene sets, we showed that the functionality of at least 96.8% and 65.2% of these shared combinations in Arabidopsis are partially supported, under a false discovery rate of 0.1 and 0.05, respectively. Finally, we discovered that 796 of the 18,638 combinations might relate to functions that are important in bioenergy research. Our work will facilitate the study of gene transcriptional regulation in plants.

Enhancers regulate progression of development in mammalian cells

During development and differentiation of an organism, accurate gene regulation is central for cells to maintain and balance their differentiation processes. Transcriptional interactions between cis-acting DNA elements such as promoters and enhancers are the basis for precise and balanced transcriptional regulation. We identified modules of combinations of binding sites in proximal and distal regulatory regions upstream of all transcription start sites (TSSs) in silico and applied these modules to gene expression time-series of mouse embryonic development and differentiation of human stem cells. In addition to tissue-specific regulation controlled by combinations of transcription factors (TFs) binding at promoters, we observed that in particular the combination of TFs binding at promoters together with TFs binding at the respective enhancers regulate highly specifically temporal progression during development: whereas 40% of TFs were specific for time intervals, 79% of TF pairs and even 97% of promoter-enhancer modules showed specificity for single time intervals of the human stem cells. Predominantly SP1 and E2F contributed to temporal specificity at promoters and the forkhead (FOX) family of TFs at enhancer regions. Altogether, we characterized three classes of TFs: with binding sites being enriched at the TSS (like SP1), depleted at the TSS (like FOX), and rather uniformly distributed.

Combining computational prediction of cis-regulatory elements with a new enhancer assay to efficiently label neuronal structures in the medaka fish

The developing vertebrate nervous system contains a remarkable array of neural cells organized into complex, evolutionarily conserved structures. The labeling of living cells in these structures is key for the understanding of brain development and function, yet the generation of stable lines expressing reporter genes in specific spatio-temporal patterns remains a limiting step. In this study we present a fast and reliable pipeline to efficiently generate a set of stable lines expressing a reporter gene in multiple neuronal structures in the developing nervous system in medaka. The pipeline combines both the accurate computational genome-wide prediction of neuronal specific cis-regulatory modules (CRMs) and a newly developed experimental setup to rapidly obtain transgenic lines in a cost-effective and highly reproducible manner. 95% of the CRMs tested in our experimental setup show enhancer activity in various and numerous neuronal structures belonging to all major brain subdivisions. This pipeline represents a significant step towards the dissection of embryonic neuronal development in vertebrates.

Segment-specific regulation of the Drosophila AP-2 gene during leg and antennal development

Segmentation involves subdivision of a developing body part into multiple repetitive units during embryogenesis. In Drosophila and other insects, embryonic segmentation is regulated by genes expressed in the same domain of every segment. Less is known about the molecular basis for segmentation of individual body parts occurring at later developmental stages. The Drosophila transcription factor AP-2 gene, dAP-2, is required for outgrowth of leg and antennal segments and is expressed in every segment boundary within the larval imaginal discs. To investigate the molecular mechanisms generating the segmentally repetitive pattern of dAP-2 expression, we performed transgenic reporter analyses and isolated multiple cis-regulatory elements that can individually or cooperatively recapitulate endogenous dAP-2 expression in different segments of the appendages. We further analyzed an enhancer specific for the proximal femur region which corresponds to the distal-most expression domain of homothorax (hth) in the leg imaginal discs. Hth is known to be responsible for the nuclear localization and, hence, function of the Hox cofactor, Extradenticle (Exd). We show that both Hth and Exd are required for dAP-2 expression in the femur and that a conserved Exd/Hox binding site is essential for enhancer activity. Our loss- and gain-of-function studies further support direct regulation of dAP-2 by Hox proteins and suggest that Hox proteins function redundantly in dAP-2 regulation. Our study reveals that discrete segment-specific enhancers underlie the seemingly simple repetitive expression of dAP-2 and provides evidence for direct regulation of leg segmentation by regional combinations of the proximodistal patterning genes.

The NFI-Regulome Database: A tool for annotation and analysis of control regions of genes regulated by Nuclear Factor I transcription factors

BACKGROUND

Genome annotation plays an essential role in the interpretation and use of genome sequence information. While great strides have been made in the annotation of coding regions of genes, less success has been achieved in the annotation of the regulatory regions of genes, including promoters, enhancers/silencers, and other regulatory elements. One reason for this disparity in annotated information is that coding regions can be assessed using high-throughput techniques such as EST sequencing, while annotation of regulatory regions often requires a gene-by-gene approach.

RESULTS

The NFI-Regulome database http://nfiregulome.ccr.buffalo.edu was designed to promote easy annotation of the regulatory regions of genes that contain binding sites for the NFI (Nuclear Factor I) family of transcription factors, using data from the published literature. Binding sites are annotated together with the sequence of the gene, obtained from the UCSC Genome site, and the locations of all binding sites for multiple genes can be displayed in a number of formats designed to facilitate inter-gene comparisons. Classes of genes based on expression pattern, disease involvement, or types of binding sites present can be readily compared in order to assess common "architectural" structures in the regulatory regions.

CONCLUSIONS

The NFI-Regulome database allows rapid display of the relative locations and number of transcription factor binding sites of individual or defined sets of genes that contain binding sites for NFI transcription factors. This database may in the future be expanded into a distributed database structure including other families of transcription factors. Such databases may be useful for identifying common regulatory structures in genes essential for organ development, tissue-specific gene expression or those genes related to specific diseases.

A proposal in relation to a genetic control of lifespan in mammals

This article proposes that behavioural advancement during mammalian evolution had been in part mediated through extension of total developmental time. Such time extensions would have resulted in increased numbers of neuronal precursor cells, hence larger brains and a disproportionate increase in the neocortex. Larger neocortical areas enabled new connections to be formed during development and hence expansion of existing behavioural circuits. To have been positively selected such behavioural advances would have required enough postdevelopmental time to enable the behaviour to be fully manifest. It is therefore proposed that the success of mammalian evolution depended on initiating a genetic control of total postdevelopmental time. This could have been mediated through the redeployment of gene regulatory networks controlling total developmental time to additionally control total postdevelopmental time. The result would be that any extension of developmental time, leading to a behavioural advancement, would be accompanied by a proportional extension to postdevelopmental time. In effect it is proposed that mammalian lifespan as a whole is genetically controlled.

Genomics and proteomics in stem cell research: the road ahead

Stem cell research has been widely studied over the last few years and has attracted increasing attention from researchers in all fields of medicine due to its potential to treat many previously incurable diseases by replacing damaged cells or tissues. As illustrated by hematopoietic stem research, understanding stem cell differentiation at molecular levels is essential for both basic research and for clinical applications of stem cells. Although multiple integrative analyses, such as genomics, epigenomics, transcriptomics and proteomics, are required to understand stem cell biology, proteomics has a unique position in stem cell research. For example, several major breakthroughs in HSC research were due to the identification of proteins such as colony-stimulating factors (CSFs) and cell-surface CD molecules. In 2007, the Human Proteome Organization (HUPO) and the International Society for Stem Cell Research (ISSCR) launched the joint Proteome Biology of Stem Cells Initiative. A systematic proteomics approach to understanding stem cell differentiation will shed new light on stem cell biology and accelerate clinical applications of stem cells.

Cis-regulatory mechanisms of gene expression in an olfactory neuron type in Caenorhabditis elegans

The generation of cellular diversity is dependent on the precise spatiotemporal regulation of gene expression by both cis- and trans-acting mechanisms. The developmental principles regulating expression of specific gene subsets in individual cell types are not fully understood. Here we define the cis-regulatory mechanisms driving expression of cell-selective and broadly expressed genes in vivo in the AWB olfactory neuron subtype in C. elegans. We identify an element that is necessary to drive expression of neuron-selective chemoreceptor genes in the AWB neurons, and show that this element functions in a context-dependent manner. We find that the expression of broadly expressed sensory neuronal genes in the AWB neurons is regulated by diverse cis- and trans-regulatory mechanisms that act partly in parallel to the pathways governing expression of AWB-selective genes. We further demonstrate that cis-acting mechanisms driving gene expression in the AWB neurons appear to have diverged in related nematode species. Our results provide insights into the cis-regulatory logic driving cell-specific gene expression, and suggest that variations in this logic contribute to the generation of functional diversity.

Kernel-based identification of regulatory modules

The challenge of identifying cis-regulatory modules (CRMs) is an important milestone for the ultimate goal of understanding transcriptional regulation in eukaryotic cells. It has been approached, among others, by motif-finding algorithms that identify overrepresented motifs in regulatory sequences. These methods succeed in finding single, well-conserved motifs, but fail to identify combinations of degenerate binding sites, like the ones often found in CRMs. We have developed a method that combines the abilities of existing motif finding with the discriminative power of a machine learning technique to model the regulation of genes (Schultheiss et al. (2009) Bioinformatics 25, 2126-2133). Our software is called KIRMES: , which stands for kernel-based identification of regulatory modules in eukaryotic sequences. Starting from a set of genes thought to be co-regulated, KIRMES: can identify the key CRMs responsible for this behavior and can be used to determine for any other gene not included on that list if it is also regulated by the same mechanism. Such gene sets can be derived from microarrays, chromatin immunoprecipitation experiments combined with next-generation sequencing or promoter/whole genome microarrays. The use of an established machine learning method makes the approach fast to use and robust with respect to noise. By providing easily understood visualizations for the results returned, they become interpretable and serve as a starting point for further analysis. Even for complex regulatory relationships, KIRMES: can be a helpful tool in directing the design of biological experiments.

Evolution of cis-regulatory sequences in Drosophila

Cross-species comparison is an emerging paradigm for identifying cis-regulatory sequences and understanding their function and evolution. In this chapter, we review probabilistic models of evolution of transcription factor binding sites, which provide the theoretical basis for a number of new bioinformatics tools for comparative sequence analysis. We illustrate how important functional and evolutionary insights on binding site gain and loss can be acquired through sequence comparison. This includes the observation that binding site turnover follows a molecular clock and that its rate correlates with the strength of binding sites and the presence of other sites in the neighborhood. We also comment on emerging trends that go beyond individual binding sites to a more holistic study of regulatory evolution. We point out common technical challenges, such as reliable sequence alignment and binding site prediction, when doing comparative regulatory sequence analysis and note some potential solutions thereof.

Statistical tests for natural selection on regulatory regions based on the strength of transcription factor binding sites

Background

Although cis-regulatory changes play an important role in evolution, it remains difficult to establish the contribution of natural selection to regulatory differences between species. For protein coding regions, powerful tests of natural selection have been developed based on comparisons of synonymous and non-synonymous substitutions, and analogous tests for regulatory regions would be of great utility.

Results

Here, tests for natural selection on regulatory regions are proposed based on nucleotide substitutions that occur in characterized transcription factor binding sites (an important type functional element within regulatory regions). In the absence of selection, these substitutions will tend to reduce the strength of existing binding sites. On the other hand, purifying selection will act to preserve the binding sites in regulatory regions, while positive selection can act to create or destroy binding sites, as well as change their strength. Using standard models of binding site strength and molecular evolution in the absence of selection, this intuition can be used to develop statistical tests for natural selection. Application of these tests to two well-characterized regulatory regions in Drosophila provides evidence for purifying selection.

Conclusion

This demonstrates that it is possible to develop tests for selection on regulatory regions based on the specific functional constrains on these sequences.

A biophysical model for analysis of transcription factor interaction and binding site arrangement from genome-wide binding data

Background

How transcription factors (TFs) interact with cis-regulatory sequences and interact with each other is a fundamental, but not well understood, aspect of gene regulation.

Methodology/Principal Findings

We present a computational method to address this question, relying on the established biophysical principles. This method, STAP (sequence to affinity prediction), takes into account all combinations and configurations of strong and weak binding sites to analyze large scale transcription factor (TF)-DNA binding data to discover cooperative interactions among TFs, infer sequence rules of interaction and predict TF target genes in new conditions with no TF-DNA binding data. The distinctions between STAP and other statistical approaches for analyzing cis-regulatory sequences include the utility of physical principles and the treatment of the DNA binding data as quantitative representation of binding strengths. Applying this method to the ChIP-seq data of 12 TFs in mouse embryonic stem (ES) cells, we found that the strength of TF-DNA binding could be significantly modulated by cooperative interactions among TFs with adjacent binding sites. However, further analysis on five putatively interacting TF pairs suggests that such interactions may be relatively insensitive to the distance and orientation of binding sites. Testing a set of putative Nanog motifs, STAP showed that a novel Nanog motif could better explain the ChIP-seq data than previously published ones. We then experimentally tested and verified the new Nanog motif. A series of comparisons showed that STAP has more predictive power than several state-of-the-art methods for cis-regulatory sequence analysis. We took advantage of this power to study the evolution of TF-target relationship in Drosophila. By learning the TF-DNA interaction models from the ChIP-chip data of D. melanogaster (Mel) and applying them to the genome of D. pseudoobscura (Pse), we found that only about half of the sequences strongly bound by TFs in Mel have high binding affinities in Pse. We show that prediction of functional TF targets from ChIP-chip data can be improved by using the conservation of STAP predicted affinities as an additional filter.

Conclusions/Significance

STAP is an effective method to analyze binding site arrangements, TF cooperativity, and TF target genes from genome-wide TF-DNA binding data.

High resolution transcriptome maps for wild-type and nonsense-mediated decay-defective Caenorhabditis elegans

The high-resolution transcriptome of wild-type and nonsense-mediated decay (NMD) defective C. elegans during development reveals insights into the NMD pathway and it’s role in development.

Background

While many genome sequences are complete, transcriptomes are less well characterized. We used both genome-scale tiling arrays and massively parallel sequencing to map the Caenorhabditis elegans transcriptome across development. We utilized this framework to identify transcriptome changes in animals lacking the nonsense-mediated decay (NMD) pathway.

Results

We find that while the majority of detectable transcripts map to known gene structures, >5% of transcribed regions fall outside current gene annotations. We show that >40% of these are novel exons. Using both technologies to assess isoform complexity, we estimate that >17% of genes change isoform across development. Next we examined how the transcriptome is perturbed in animals lacking NMD. NMD prevents expression of truncated proteins by degrading transcripts containing premature termination codons. We find that approximately 20% of genes produce transcripts that appear to be NMD targets. While most of these arise from splicing errors, NMD targets are enriched for transcripts containing open reading frames upstream of the predicted translational start (uORFs). We identify a relationship between the Kozak consensus surrounding the true start codon and the degree to which uORF-containing transcripts are targeted by NMD and speculate that translational efficiency may be coupled to transcript turnover via the NMD pathway for some transcripts.

Conclusions

We generated a high-resolution transcriptome map for C. elegans and used it to identify endogenous targets of NMD. We find that these transcripts arise principally through splicing errors, strengthening the prevailing view that splicing and NMD are highly interlinked processes.