Integrative analysis of C. elegans modENCODE ChIP-seq data sets to infer gene regulatory interactions

Artificial selection footprints in indigenous and commercial chicken genomes

BACKGROUND

Although many studies have been done to reveal artificial selection signatures in commercial and indigenous chickens, a limited number of genes have been linked to specific traits. To identify more trait-related artificial selection signatures and genes, we re-sequenced a total of 85 individuals of five indigenous chicken breeds with distinct traits from Yunnan Province, China.

RESULTS

We found 30 million non-redundant single nucleotide variants and small indels (< 50 bp) in the indigenous chickens, of which 10 million were not seen in 60 broilers, 56 layers and 35 red jungle fowls (RJFs) that we compared with. The variants in each breed are enriched in non-coding regions, while those in coding regions are largely tolerant, suggesting that most variants might affect cis-regulatory sequences. Based on 27 million bi-allelic single nucleotide polymorphisms identified in the chickens, we found numerous selective sweeps and affected genes in each indigenous chicken breed and substantially larger numbers of selective sweeps and affected genes in the broilers and layers than previously reported using a rigorous statistical model. Consistent with the locations of the variants, the vast majority (~ 98.3%) of the identified selective sweeps overlap known quantitative trait loci (QTLs). Meanwhile, 74.2% known QTLs overlap our identified selective sweeps. We confirmed most of previously identified trait-related genes and identified many novel ones, some of which might be related to body size and high egg production traits. Using RT-qPCR, we validated differential expression of eight genes (GHR, GHRHR, IGF2BP1, OVALX, ELF2, MGARP, NOCT, SLC25A15) that might be related to body size and high egg production traits in relevant tissues of relevant breeds.

CONCLUSION

We identify 30 million single nucleotide variants and small indels in the five indigenous chicken breeds, 10 million of which are novel. We predict substantially more selective sweeps and affected genes than previously reported in both indigenous and commercial breeds. These variants and affected genes are good candidates for further experimental investigations of genotype-phenotype relationships and practical applications in chicken breeding programs.

Identification of transcription factor high accumulation DNA zones

BACKGROUND

Transcription factors (TF) play a crucial role in the regulation of gene transcription; alterations of their activity and binding to DNA areas are strongly involved in cancer and other disease onset and development. For proper biomedical investigation, it is hence essential to correctly trace TF dense DNA areas, having multiple bindings of distinct factors, and select DNA high occupancy target (HOT) zones, showing the highest accumulation of such bindings. Indeed, systematic and replicable analysis of HOT zones in a large variety of cells and tissues would allow further understanding of their characteristics and could clarify their functional role.

RESULTS

Here, we propose, thoroughly explain and discuss a full computational procedure to study in-depth DNA dense areas of transcription factor accumulation and identify HOT zones. This methodology, developed as a computationally efficient parametric algorithm implemented in an R/Bioconductor package, uses a systematic approach with two alternative methods to examine transcription factor bindings and provide comparative and fully-reproducible assessments. It offers different resolutions by introducing three distinct types of accumulation, which can analyze DNA from single-base to region-oriented levels, and a moving window, which can estimate the influence of the neighborhood for each DNA base under exam.

CONCLUSIONS

We quantitatively assessed the full procedure by using our implemented software package, named TFHAZ, in two example applications of biological interest, proving its full reliability and relevance.

The regulatory landscape of neurite development in Caenorhabditis elegans

Neuronal communication requires precise connectivity of neurite projections (axons and dendrites). Developing neurites express cell-surface receptors that interpret extracellular cues to enable correct guidance toward, and connection with, target cells. Spatiotemporal regulation of neurite guidance molecule expression by transcription factors (TFs) is critical for nervous system development and function. Here, we review how neurite development is regulated by TFs in the Caenorhabditis elegans nervous system. By collecting publicly available transcriptome and ChIP-sequencing data, we reveal gene expression dynamics during neurite development, providing insight into transcriptional mechanisms governing construction of the nervous system architecture.

A metabolic regulatory network for the Caenorhabditis elegans intestine

Metabolic perturbations can affect gene expression, for instance to rewire metabolism. While numerous efforts have measured gene expression in response to individual metabolic perturbations, methods that determine all metabolic perturbations that affect the expression for a given gene or set of genes have not been available. Here, we use a gene-centered approach to derive a first-pass metabolic regulatory network for Caenorhabditis elegans by performing RNAi of more than 1,400 metabolic genes with a set of 19 promoter reporter strains that express a fluorescent protein in the animal's intestine. We find that metabolic perturbations generally increase promoter activity, which contrasts with transcription factor (TF) RNAi, which tends to repress promoter activity. We identify several TFs that modulate promoter activity in response to perturbations of the electron transport chain and explore complex genetic interactions among metabolic pathways. This work provides a blueprint for a systems-level understanding of how metabolism affects gene expression.

Nematode chromosomes

The nematode Caenorhabditis elegans has shed light on many aspects of eukaryotic biology, including genetics, development, cell biology, and genomics. A major factor in the success of C. elegans as a model organism has been the availability, since the late 1990s, of an essentially gap-free and well-annotated nuclear genome sequence, divided among 6 chromosomes. In this review, we discuss the structure, function, and biology of C. elegans chromosomes and then provide a general perspective on chromosome biology in other diverse nematode species. We highlight malleable chromosome features including centromeres, telomeres, and repetitive elements, as well as the remarkable process of programmed DNA elimination (historically described as chromatin diminution) that induces loss of portions of the genome in somatic cells of a handful of nematode species. An exciting future prospect is that nematode species may enable experimental approaches to study chromosome features and to test models of chromosome evolution. In the long term, fundamental insights regarding how speciation is integrated with chromosome biology may be revealed.

Refactoring transcription factors for metabolic engineering

Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.

Deficiency in RCAT-1 Function Causes Dopamine Metabolism Related Behavioral Disorders in Caenorhabditis elegans

When animals are faced with food depletion, food search-associated locomotion is crucial for their survival. Although food search-associated locomotion is known to be regulated by dopamine, it has yet to investigate the potential molecular mechanisms governing the regulation of genes involved in dopamine metabolism (e.g., cat-1, cat-2) and related behavioral disorders. During the studies of the pheromone ascaroside, a signal of starvation stress in C. elegans, we identified R02D3.7, renamed rcat-1 (regulator of cat genes-1), which had previously been shown to bind to regulatory sequences of both cat-1 and cat-2 genes. It was found that RCAT-1 (R02D3.7) is expressed in dopaminergic neurons and functions as a novel negative transcriptional regulator for cat-1 and cat-2 genes. When a food source becomes depleted, the null mutant, rcat-1(ok1745), exhibited an increased frequency of high-angled turns and intensified area restricted search behavior compared to the wild-type animals. Moreover, rcat-1(ok1745) also showed defects in state-dependent olfactory adaptation and basal slowing response, suggesting that the mutants are deficient in either sensing food or locomotion toward food. However, rcat-1(ok1745) has normal cuticular structures and locomotion genes. The discovery of rcat-1 not only identifies a new subtype of dopamine-related behaviors but also provides a potential therapeutic target in Parkinson’s disease.

A novel functional cross-interaction between opioid and pheromone signaling may be involved in stress avoidance in Caenorhabditis elegans

Upon sensing starvation stress, Caenorhabditis elegans larvae (L2d) elicit two seemingly opposing behaviors to escape from the stressful condition: food-seeking roaming mediated by the opioid peptide NLP-24 and dauer formation mediated by pheromones. Because opioid and pheromone signals both originate in ASI chemosensory neurons, we hypothesized that they might act sequentially or competitively to avoid starvation stress. Our data shows that NPR-17 opioid receptor signaling suppressed pheromone biosynthesis and the overexpression of opioid genes disturbed dauer formation. Likewise, DAF-37 pheromone receptor signaling negatively modulated nlp-24 expression in the ASI neurons. Under short-term starvation (STS, 3 h), both pheromone and opioid signaling were downregulated in gpa-3 mutants. Surprisingly, the gpa-3;nlp-24 double mutants exhibited much higher dauer formation than seen in either of the single mutants. Under long-term starvation (LTS, >24 h), the stress-activated SKN-1a downregulated opioid signaling and then enhanced dauer formation. Both insulin and serotonin stimulated opioid signaling, whereas NHR-69 suppressed opioid signaling. Thus, GPA-3 and SKN-1a are proposed to regulate cross-antagonistic interaction between opioids and pheromones in a cell-specific manner. These regulatory functions are suggested to be exerted via the selective interaction of GPA-3 with NPR-17 and site-specific SKN-1 binding to the promoter of nlp-24 to facilitate stress avoidance.

GLP-1 Notch-LAG-1 CSL control of the germline stem cell fate is mediated by transcriptional targets lst-1 and sygl-1

Stem cell systems are essential for the development and maintenance of polarized tissues. Intercellular signaling pathways control stem cell systems, where niche cells signal stem cells to maintain the stem cell fate/self-renewal and inhibit differentiation. In the C. elegans germline, GLP-1 Notch signaling specifies the stem cell fate, employing the sequence-specific DNA binding protein LAG-1 to implement the transcriptional response. We undertook a comprehensive genome-wide approach to identify transcriptional targets of GLP-1 signaling. We expected primary response target genes to be evident at the intersection of genes identified as directly bound by LAG-1, from ChIP-seq experiments, with genes identified as requiring GLP-1 signaling for RNA accumulation, from RNA-seq analysis. Furthermore, we performed a time-course transcriptomics analysis following auxin inducible degradation of LAG-1 to distinguish between genes whose RNA level was a primary or secondary response of GLP-1 signaling. Surprisingly, only lst-1 and sygl-1, the two known target genes of GLP-1 in the germline, fulfilled these criteria, indicating that these two genes are the primary response targets of GLP-1 Notch and may be the sole germline GLP-1 signaling protein-coding transcriptional targets for mediating the stem cell fate. In addition, three secondary response genes were identified based on their timing following loss of LAG-1, their lack of a LAG-1 ChIP-seq peak and that their glp-1 dependent mRNA accumulation could be explained by a requirement for lst-1 and sygl-1 activity. Moreover, our analysis also suggests that the function of the primary response genes lst-1 and sygl-1 can account for the glp-1 dependent peak protein accumulation of FBF-2, which promotes the stem cell fate and, in part, for the spatial restriction of elevated LAG-1 accumulation to the stem cell region.

Stem cell systems are central to tissue development, homeostasis and regeneration, where niche to stem cell signaling pathways promote the stem cell fate/self-renewal and inhibit differentiation. The evolutionarily conserved GLP-1 Notch signaling pathway in the C. elegans germline is an experimentally tractable system, allowing dissection of control of the stem cell fate and inhibition of meiotic development. However, as in many systems, the primary molecular targets of the signaling pathway in stem cells is incompletely known, as are secondary molecular targets, and this knowledge is essential for a deep understanding of stem cell systems. Here we focus on the identification of the primary transcriptional targets of the GLP-1 signaling pathway that promotes the stem cell fate, employing unbiased multilevel genomic approaches. We identify only lst-1 and sygl-1, two of a number of previously reported targets, as likely the sole primary mRNA transcriptional targets of GLP-1 signaling that promote the germline stem cell fate. We also identify secondary GLP-1 signaling RNA and protein targets, whose expression shows dependence on lst-1 and sygl-1, where the protein targets reinforce the importance of posttranscriptional regulation in control of the stem cell fate.

WormQTL2: an interactive platform for systems genetics in Caenorhabditis elegans

Quantitative genetics provides the tools for linking polymorphic loci to trait variation. Linkage analysis of gene expression is an established and widely applied method, leading to the identification of expression quantitative trait loci (eQTLs). (e)QTL detection facilitates the identification and understanding of the underlying molecular components and pathways, yet (e)QTL data access and mining often is a bottleneck. Here, we present WormQTL2, a database and platform for comparative investigations and meta-analyses of published (e)QTL data sets in the model nematode worm C. elegans. WormQTL2 integrates six eQTL studies spanning 11 conditions as well as over 1000 traits from 32 studies and allows experimental results to be compared, reused and extended upon to guide further experiments and conduct systems-genetic analyses. For example, one can easily screen a locus for specific cis-eQTLs that could be linked to variation in other traits, detect gene-by-environment interactions by comparing eQTLs under different conditions, or find correlations between QTL profiles of classical traits and gene expression. WormQTL2 makes data on natural variation in C. elegans and the identified QTLs interactively accessible, allowing studies beyond the original publications. Database URL: www.bioinformatics.nl/WormQTL2/.

NetProphet 2.0: mapping transcription factor networks by exploiting scalable data resources

Motivation

Cells process information, in part, through transcription factor (TF) networks, which control the rates at which individual genes produce their products. A TF network map is a graph that indicates which TFs bind and directly regulate each gene. Previous work has described network mapping algorithms that rely exclusively on gene expression data and ‘integrative’ algorithms that exploit a wide range of data sources including chromatin immunoprecipitation sequencing (ChIP-seq) of many TFs, genome-wide chromatin marks, and binding specificities for many TFs determined in vitro. However, such resources are available only for a few major model systems and cannot be easily replicated for new organisms or cell types.

Results

We present NetProphet 2.0, a ‘data light’ algorithm for TF network mapping, and show that it is more accurate at identifying direct targets of TFs than other, similarly data light algorithms. In particular, it improves on the accuracy of NetProphet 1.0, which used only gene expression data, by exploiting three principles. First, combining multiple approaches to network mapping from expression data can improve accuracy relative to the constituent approaches. Second, TFs with similar DNA binding domains bind similar sets of target genes. Third, even a noisy, preliminary network map can be used to infer DNA binding specificities from promoter sequences and these inferred specificities can be used to further improve the accuracy of the network map.

Availability and implementation

Source code and comprehensive documentation are freely available at https://github.com/yiming-kang/NetProphet_2.0.

Supplementary information

Supplementary data are available at Bioinformatics online.

Cooperation between a hierarchical set of recruitment sites targets the X chromosome for dosage compensation

In many organisms, it remains unclear how X chromosomes are specified for dosage compensation, since DNA sequence motifs shown to be important for dosage compensation complex (DCC) recruitment are themselves not X-specific. Here, we addressed this problem in C. elegans. We found that the DCC recruiter, SDC-2, is required to maintain open chromatin at a small number of primary DCC recruitment sites, whose sequence and genomic context are X-specific. Along the X, primary recruitment sites are interspersed with secondary sites, whose function is X-dependent. A secondary site can ectopically recruit the DCC when additional recruitment sites are inserted either in tandem or at a distance (>30 kb). Deletion of a recruitment site on the X results in reduced DCC binding across several megabases surrounded by topologically associating domain (TAD) boundaries. Our work elucidates that hierarchy and long-distance cooperativity between gene-regulatory elements target a single chromosome for regulation.

DOI:http://dx.doi.org/10.7554/eLife.23645.001

The DNA inside living cells is organized in structures called chromosomes. In many animals, females have two X chromosomes, whereas males have only one. To ensure that females do not end up with a double dose of the proteins encoded by the genes on the X chromosome, animals use a process called dosage compensation to correct this imbalance. The mechanisms underlying this process vary between species, but they typically involve a regulatory complex that binds to the X chromosomes of one sex to modify gene expression.

Caenorhabditis elegans, for example, is a species of nematode worm in which individuals with two X chromosomes are hermaphrodites and those with one X chromosome are males. In C. elegans, a regulatory complex, called the dosage compensation complex, attaches to both X chromosomes of a hermaphrodite, and reduces the expression of the genes on each by half to match the level seen in the males. Previous research has shown that short DNA sequences, known as motifs, recruit the dosage compensation complex to the X chromosomes. However, these sequences are also found on the other chromosomes and, until now, it was not known why the complex was only recruited to the X chromosomes.

Albritton et al. now show the X chromosomes have a ‘hierarchical’ recruitment system. A few sites on the X chromosomes contain clusters of a specific DNA motif, which initiate the process and attract the dosage compensation complex more strongly than other sites. These ‘strong’ recruitment sites are placed across the length of the X chromosomes and cooperate with several ‘weaker’ ones located in between. This way, multiple recruitment sites can cooperate over a long distance, while non-sex chromosomes, which have only one or two stronger recruitment sites, do not have thisadvantage.

Hierarchy and cooperativity may be general features of gene expression, in which proteins are targeted to chromosomes without the need for having specific motifs at every recruitment site. The way DNA sequences are distributed across the genome may give us clues about their role. Thus, knowing how genomes are structured will help us identify disrupted areas in diseases such as cancer.

DOI:http://dx.doi.org/10.7554/eLife.23645.002

Can We Predict Gene Expression by Understanding Proximal Promoter Architecture?

We review computational predictions of expression from the promoter architecture - the set of transcription factors that can bind the proximal promoter. We focus on spatial expression patterns in animals with complex body plans and many distinct tissue types. This field is ripe for change as functional genomics datasets accumulate for both expression and protein-DNA interactions. While there has been some success in predicting the breadth of expression (i.e., the fraction of tissue types a gene is expressed in), predicting tissue specificity remains challenging. We discuss how progress can be achieved through either machine learning or complementary combinatorial data mining. The likely impact of single-cell expression data is considered. Finally, we discuss the design of artificial promoters as a practical application.

A fast, efficient chromatin immunoprecipitation method for studying protein-DNA binding in Arabidopsis mesophyll protoplasts

BACKGROUND

Binding of transcription factors to their target sequences is a primary step in the regulation of gene expression and largely determines gene regulatory networks. Chromatin immunoprecipitation (ChIP) is an indispensable tool used to investigate the binding of DNA-binding proteins (e.g., transcription factors) to their target sequences in vivo. ChIP assays require specific antibodies that recognize endogenous target transcription factors; however, in most cases, such specific antibodies are unavailable. To overcome this problem, many ChIP assays use transgenic plants that express epitope-tagged transcription factors and immunoprecipitate the protein with a tag-specific antibody. However, generating transgenic plants that stably express epitope-tagged proteins is difficult and time-consuming.

RESULTS

Here, we present a rapid, efficient ChIP protocol using transient expression in Arabidopsis mesophyll protoplasts that can be completed in 4 days. We provide optimized experimental conditions, including the amount of transfected DNA and the number of protoplasts. We also show that the efficiency of our ChIP protocol using protoplasts is comparable to that obtained using transgenic Arabidopsis plants. We propose that our ChIP method can be used to analyze in vivo interactions between tissue-specific transcription factors and their target sequences, to test the effect of genotype on the binding of a transcription factor within a protein complex to its target sequences, and to measure temperature-dependent binding of a transcription factor to its target sequence.

CONCLUSIONS

The rapid and simple nature of our ChIP assay using Arabidopsis mesophyll protoplasts facilitates the investigation of in vivo interactions between transcription factors and their target genes.

ChIP-Seq: Library Preparation and Sequencing

Chromatin immunoprecipitation with massively parallel DNA sequencing (ChIP-Seq) has been used extensively to determine the genome-wide location of DNA-binding factors, such as transcription factors, posttranscriptionally modified histones, and members of the transcription complex, to assess regulatory input, epigenetic modifications, and transcriptional activity, respectively. Here we describe methods to isolate chromatin from tissues, immunoprecipitate DNA bound to a protein of interest, and perform next-generation sequencing to identify a genome-wide DNA-binding pattern.

E2F coregulates an essential HSF developmental program that is distinct from the heat-shock response

Heat-shock factor (HSF) is the master transcriptional regulator of the heat-shock response (HSR) and is essential for stress resilience. HSF is also required for metazoan development; however, its function and regulation in this process are poorly understood. Here, we characterize the genomic distribution and transcriptional activity of Caenorhabditis elegans HSF-1 during larval development and show that the developmental HSF-1 transcriptional program is distinct from the HSR. HSF-1 developmental activation requires binding of E2F/DP to a GC-rich motif that facilitates HSF-1 binding to a heat-shock element (HSE) that is degenerate from the consensus HSE sequence and adjacent to the E2F-binding site at promoters. In contrast, induction of the HSR is independent of these promoter elements or E2F/DP and instead requires a distinct set of tandem canonical HSEs. Together, E2F and HSF-1 directly regulate a gene network, including a specific subset of chaperones, to promote protein biogenesis and anabolic metabolism, which are essential in development.

Deactivation of the GATA Transcription Factor ELT-2 Is a Major Driver of Normal Aging in C. elegans

To understand the molecular processes underlying aging, we screened modENCODE ChIP-seq data to identify transcription factors that bind to age-regulated genes in C. elegans. The most significant hit was the GATA transcription factor encoded by elt-2, which is responsible for inducing expression of intestinal genes during embryogenesis. Expression of ELT-2 decreases during aging, beginning in middle age. We identified genes regulated by ELT-2 in the intestine during embryogenesis, and then showed that these developmental genes markedly decrease in expression as worms grow old. Overexpression of elt-2 extends lifespan and slows the rate of gene expression changes that occur during normal aging. Thus, our results identify the developmental regulator ELT-2 as a major driver of normal aging in C. elegans.

The Inflammatory Transcription Factors NFκB, STAT1 and STAT3 Drive Age-Associated Transcriptional Changes in the Human Kidney

Human kidney function declines with age, accompanied by stereotyped changes in gene expression and histopathology, but the mechanisms underlying these changes are largely unknown. To identify potential regulators of kidney aging, we compared age-associated transcriptional changes in the human kidney with genome-wide maps of transcription factor occupancy from ChIP-seq datasets in human cells. The strongest candidates were the inflammation-associated transcription factors NFκB, STAT1 and STAT3, the activities of which increase with age in epithelial compartments of the renal cortex. Stimulation of renal tubular epithelial cells with the inflammatory cytokines IL-6 (a STAT3 activator), IFNγ (a STAT1 activator), or TNFα (an NFκB activator) recapitulated age-associated gene expression changes. We show that common DNA variants in RELA and NFKB1, the two genes encoding subunits of the NFκB transcription factor, associate with kidney function and chronic kidney disease in gene association studies, providing the first evidence that genetic variation in NFκB contributes to renal aging phenotypes. Our results suggest that NFκB, STAT1 and STAT3 underlie transcriptional changes and chronic inflammation in the aging human kidney.

The structure and function of human kidneys deteriorate steadily with age, yet little is known about the underlying causes of kidney aging. In this work, we first used a genomics approach to identify candidate regulators of gene expression changes in the aging human kidney and identified inflammation-related transcription factors NFκB, STAT1 and STAT3 as the top candidate regulators. We found that kidney aging is associated with activation of NFκB, STAT1 and STAT3 in the renal parenchyma, and that the gene expression signatures evoked by activation of these transcription factors in human renal epithelial cells mimics age-associated gene expression changes in the kidney. Furthermore, we identified specific genetic variants in the NFκB transcription factor genes RELA and NFKB1 that associate with renal function and chronic kidney disease in humans, implicating NFκB as a potential contributor to the pathogenesis of chronic kidney disease and renal dysfunction in old age. Our findings suggest that activation of the inflammatory transcription factors STAT1, STAT3 and NFκB underlie transcriptional changes and reduced renal function in the elderly.

Reproductive Aging Drives Protein Accumulation in the Uterus and Limits Lifespan in C. elegans

Aging in Caenorhabditis elegans is characterized by widespread physiological and molecular changes, but the mechanisms that determine the rate at which these changes occur are not well understood. In this study, we identify a novel link between reproductive aging and somatic aging in C. elegans. By measuring global age-related changes in the proteome, we identify a previously uncharacterized group of secreted proteins in the adult uterus that dramatically increase in abundance with age. This accumulation is blunted in animals with an extended reproductive period and accelerated in sterile animals lacking a germline. Uterine proteins are not removed in old post-reproductive animals or in young vulvaless worms, indicating that egg-laying is necessary for their rapid removal in wild-type young animals. Together, these results suggest that age-induced infertility contributes to extracellular protein accumulation in the uterus with age. Finally, we show that knocking down multiple age-increased proteins simultaneously extends lifespan. These results provide a mechanistic example of how the cessation of reproduction contributes to detrimental changes in the soma, and demonstrate how the timing of reproductive decline can influence the rate of aging.

To understand the process of aging at the molecular level in C. elegans, we measured changes in protein abundance with age, determined whether these age-related protein changes lead to dysfunction in old animals, and have elucidated one of the upstream pathways responsible for these aging changes. We found that egg-laying in young worms permits removal of a novel class of proteins present in the uterus. When the reproductive period ends, the removal of uterine proteins stops, causing them to accumulate to toxic levels. This shows that the timing of reproductive decline influences the rate of somatic aging. The concept that the reproductive period has a direct role in specifying the rate of aging of the soma likely applies to other species as well.

Inhibition of elongin C promotes longevity and protein homeostasis via HIF-1 in C. elegans

The transcription factor hypoxia‐inducible factor 1 (HIF‐1) is crucial for responses to low oxygen and promotes longevity in Caenorhabditis elegans. We previously performed a genomewide RNA interference screen and identified many genes that act as potential negative regulators of HIF‐1. Here, we functionally characterized these genes and found several novel genes that affected lifespan. The worm ortholog of elongin C, elc‐1, encodes a subunit of E3 ligase and transcription elongation factor. We found that knockdown of elc‐1 prolonged lifespan and delayed paralysis caused by impaired protein homeostasis. We further showed that elc‐1 RNA interference increased lifespan and protein homeostasis by upregulating HIF‐1. The roles of elongin C and HIF‐1 are well conserved in eukaryotes. Thus, our study may provide insights into the aging regulatory pathway consisting of elongin C and HIF‐1 in complex metazoans.

Lessons from modENCODE

The modENCODE (Model Organism Encyclopedia of DNA Elements) Consortium aimed to map functional elements-including transcripts, chromatin marks, regulatory factor binding sites, and origins of DNA replication-in the model organisms Drosophila melanogaster and Caenorhabditis elegans. During its five-year span, the consortium conducted more than 2,000 genome-wide assays in developmentally staged animals, dissected tissues, and homogeneous cell lines. Analysis of these data sets provided foundational insights into genome, epigenome, and transcriptome structure and the evolutionary turnover of regulatory pathways. These studies facilitated a comparative analysis with similar data types produced by the ENCODE Consortium for human cells. Genome organization differs drastically in these distant species, and yet quantitative relationships among chromatin state, transcription, and cotranscriptional RNA processing are deeply conserved. Of the many biological discoveries of the modENCODE Consortium, we highlight insights that emerged from integrative studies. We focus on operational and scientific lessons that may aid future projects of similar scale or aims in other, emerging model systems.

Dynamic regulation of genetic pathways and targets during aging in Caenorhabditis elegans

Numerous genetic targets and some individual pathways associated with aging have been identified using the worm model. However, less is known about the genetic mechanisms of aging in genome wide, particularly at the level of multiple pathways as well as the regulatory networks during aging. Here, we employed the gene expression datasets of three time points during aging in Caenorhabditis elegans (C. elegans) and performed the approach of gene set enrichment analysis (GSEA) on each dataset between adjacent stages. As a result, multiple genetic pathways and targets were identified as significantly down- or up-regulated. Among them, 5 truly aging-dependent signaling pathways including MAPK signaling pathway, mTOR signaling pathway, Wnt signaling pathway, TGF-beta signaling pathway and ErbB signaling pathway as well as 12 significantly associated genes were identified with dynamic expression pattern during aging. On the other hand, the continued declines in the regulation of several metabolic pathways have been demonstrated to display age-related changes. Furthermore, the reconstructed regulatory networks based on three of aging related Chromatin immunoprecipitation experiments followed by sequencing (ChIP–seq) datasets and the expression matrices of 154 involved genes in above signaling pathways provide new insights into aging at the multiple pathways level. The combination of multiple genetic pathways and targets needs to be taken into consideration in future studies of aging, in which the dynamic regulation would be uncovered.

A functional and evolutionary perspective on transcription factor binding in Arabidopsis thaliana

Understanding the mechanisms underlying gene regulation is paramount to comprehend the translation from genotype to phenotype. The two are connected by gene expression, and it is generally thought that variation in transcription factor (TF) function is an important determinant of phenotypic evolution. We analyzed publicly available genome-wide chromatin immunoprecipitation experiments for 27 TFs in Arabidopsis thaliana and constructed an experimental network containing 46,619 regulatory interactions and 15,188 target genes. We identified hub targets and highly occupied target (HOT) regions, which are enriched for genes involved in development, stimulus responses, signaling, and gene regulatory processes in the currently profiled network. We provide several lines of evidence that TF binding at plant HOT regions is functional, in contrast to that in animals, and not merely the result of accessible chromatin. HOT regions harbor specific DNA motifs, are enriched for differentially expressed genes, and are often conserved across crucifers and dicots, even though they are not under higher levels of purifying selection than non-HOT regions. Distal bound regions are under purifying selection as well and are enriched for a chromatin state showing regulation by the Polycomb repressive complex. Gene expression complexity is positively correlated with the total number of bound TFs, revealing insights in the regulatory code for genes with different expression breadths. The integration of noncanonical and canonical DNA motif information yields new hypotheses on cobinding and tethering between specific TFs involved in flowering and light regulation.

Decoding ChIP-seq with a double-binding signal refines binding peaks to single-nucleotides and predicts cooperative interaction

The comprehension of protein and DNA binding in vivo is essential to understand gene regulation. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) provides a global map of the regulatory binding network. Most ChIP-seq analysis tools focus on identifying binding regions from coverage enrichment. However, less work has been performed to infer the physical and regulatory details inside the enriched regions. This research extends a previous blind-deconvolution approach to develop a post-peak-calling algorithm that improves binding site resolution and predicts cooperative interactions. At the core of our new method is a physically motivated model that characterizes the binding signal as an extreme value distribution. This model suggests a mathematical framework to study physical properties of DNA shearing from the ChIP-seq coverage. The model explains the ChIP-seq coverage with two signals: The first considers DNA fragments with only a single binding event, whereas the second considers fragments with two binding events (a double-binding signal). The model incorporates motif discovery and is able to detect multiple sites in an enriched region with single-nucleotide resolution, high sensitivity, and high specificity. Our method improves peak caller sensitivity, from less than 45% up to 94%, at a false positive rate < 11% for a set of 47 experimentally validated prokaryotic sites. It also improves resolution of highly enriched regions of large-scale eukaryotic data sets. The double-binding signal provides a novel application in ChIP-seq analysis: the identification of cooperative interaction. Predictions of known cooperative binding sites show a 0.85 area under an ROC curve.

Identification and characterization of alternative splicing in parasitic nematode transcriptomes

Background

Alternative splicing (AS) of mRNA is a vital mechanism for enhancing genomic complexity in eukaryotes. Spliced isoforms of the same gene can have diverse molecular and biological functions and are often differentially expressed across various tissues, times, and conditions. Thus, AS has important implications in the study of parasitic nematodes with complex life cycles. Transcriptomic datasets are available from many species, but data must be revisited with splice-aware assembly protocols to facilitate the study of AS in helminthes.

Methods

We sequenced cDNA from the model worm Caenorhabditis elegans using 454/Roche technology for use as an experimental dataset. Reads were assembled with Newbler software, invoking the cDNA option. Several combinations of parameters were tested and assembled transcripts were verified by comparison with previously reported C. elegans genes and transcript isoforms and with Illumina RNAseq data.

Results

Thoughtful adjustment of program parameters increased the percentage of assembled transcripts that matched known C. elegans sequences, decreased mis-assembly rates (i.e., cis- and trans-chimeras), and improved the coverage of the geneset. The optimized protocol was used to update de novo transcriptome assemblies from nine parasitic nematode species, including important pathogens of humans and domestic animals. Our assemblies indicated AS rates in the range of 20-30%, typically with 2-3 transcripts per AS locus, depending on the species. Transcript isoforms from the nine species were translated and searched for similarity to known proteins and functional domains. Some 21 InterPro domains, including several involved in nucleotide and chromatin binding, were statistically correlated with AS genetic loci. In most cases, the Roche/454 data explored in this study are the only sequences available from the species in question; however, the recently published genome of the human hookworm Necator americanus provided an additional opportunity to validate our results.

Conclusions

Our optimized assembly parameters facilitated the first survey of AS among parasitic nematodes. The nine transcriptome assemblies, their protein translations, and basic annotations are available from Nematode.net as a resource for the research community. These should be useful for studies of specific genes and gene families of interest as well as for curating draft genome assemblies as they become available.

MMDiff: quantitative testing for shape changes in ChIP-Seq data sets

Background

Cell-specific gene expression is controlled by epigenetic modifications and transcription factor binding. While genome-wide maps for these protein-DNA interactions have become widely available, quantitative comparison of the resulting ChIP-Seq data sets remains challenging. Current approaches to detect differentially bound or modified regions are mainly borrowed from RNA-Seq data analysis, thus focusing on total counts of fragments mapped to a region, ignoring any information encoded in the shape of the peaks.

Results

Here, we present MMDiff, a robust, broadly applicable method for detecting differences between sequence count data sets. Based on quantifying shape changes in signal profiles, it overcomes challenges imposed by the highly structured nature of the data and the paucity of replicates.

We first use a simulated data set to compare the performance of MMDiff with results obtained by four alternative methods. We demonstrate that MMDiff excels when peak profiles change between samples. We next use MMDiff to re-analyse a recent data set of the histone modification H3K4me3 elucidating the establishment of this prominent epigenomic marker. Our empirical analysis shows that the method yields reproducible results across experiments, and is able to detect functional important changes in histone modifications. To further explore the broader applicability of MMDiff, we apply it to two ENCODE data sets: one investigating the histone modification H3K27ac and one measuring the genome-wide binding of the transcription factor CTCF. In both cases, MMDiff proves to be complementary to count-based methods. In addition, we can show that MMDiff is capable of directly detecting changes of homotypic binding events at neighbouring binding sites. MMDiff is readily available as a Bioconductor package.

Conclusions

Our results demonstrate that higher order features of ChIP-Seq peaks carry relevant and often complementary information to total counts, and hence are important in assessing differential histone modifications and transcription factor binding. We have developed a new computational method, MMDiff, that is capable of exploring these features and therefore closes an existing gap in the analysis of ChIP-Seq data sets.