Showing papers on "Functional genomics published in 2014"

High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells

Abstract: Targeted genome editing technologies are powerful tools for studying biology and disease, and have a broad range of research applications. In contrast to the rapid development of toolkits to manipulate individual genes, large-scale screening methods based on the complete loss of gene expression are only now beginning to be developed. Here we report the development of a focused CRISPR/Cas-based (clustered regularly interspaced short palindromic repeats/CRISPR-associated) lentiviral library in human cells and a method of gene identification based on functional screening and high-throughput sequencing analysis. Using knockout library screens, we successfully identified the host genes essential for the intoxication of cells by anthrax and diphtheria toxins, which were confirmed by functional validation. The broad application of this powerful genetic screening strategy will not only facilitate the rapid identification of genes important for bacterial toxicity but will also enable the discovery of genes that participate in other biological processes.

Joint Analysis of Functional Genomic Data and Genome-wide Association Studies of 18 Human Traits

Abstract: Annotations of gene structures and regulatory elements can inform genome-wide association studies (GWASs). However, choosing the relevant annotations for interpreting an association study of a given trait remains challenging. I describe a statistical model that uses association statistics computed across the genome to identify classes of genomic elements that are enriched with or depleted of loci influencing a trait. The model naturally incorporates multiple types of annotations. I applied the model to GWASs of 18 human traits, including red blood cell traits, platelet traits, glucose levels, lipid levels, height, body mass index, and Crohn disease. For each trait, I used the model to evaluate the relevance of 450 different genomic annotations, including protein-coding genes, enhancers, and DNase-I hypersensitive sites in over 100 tissues and cell lines. The fraction of phenotype-associated SNPs influencing protein sequence ranged from around 2% (for platelet volume) up to around 20% (for low-density lipoprotein cholesterol), repressed chromatin was significantly depleted for SNPs associated with several traits, and cell-type-specific DNase-I hypersensitive sites were enriched with SNPs associated with several traits (for example, the spleen in platelet volume). Finally, reweighting each GWAS by using information from functional genomics increased the number of loci with high-confidence associations by around 5%.

Microhomology-based choice of Cas9 nuclease target sites

Abstract: To the Editor: Programmable nucleases such as Cas9 RNA-guided engineered nucleases (RGENs)1 enable gene knockout in cultured cells and organisms by producing site-specific DNA double-strand breaks, whose repair via error-prone nonhomologous end joining gives rise to small insertions and deletions (indels) at target sites, often causing frameshift mutations in a protein-coding sequence2. The efficiency of this method can be reduced by in-frame mutations via microhomology-mediated end joining3,4 (Fig. 1a). Here we present a computer program that assists in the choice of Cas9 nuclease, zinc-finger nuclease and transcription activator–like effector nuclease (TALEN) target sites, using microhomology prediction to achieve efficient gene disruption in cell lines and whole organisms. First we examined the mutations induced by ten TALENs and ten RGENs in human cells via deep sequencing (Supplementary Table 1 and Supplementary Methods). We focused our analysis on deletions because they are much more prevalent than insertions (98.7% vs. 1.3%, respectively, for TALENs; 75.1% vs. 24.9% for RGENs) and because microhomology is irrelevant for insertions. In aggregate, microhomologies of 2–8 bases were found in 44.3% and 52.7% of all deletions induced by TALENs and RGENs, respectively (Supplementary Fig. 1 and Supplementary Table 2). Thus, 43.7% (0.987 × 0.443) and 39.6% (0.751 × 0.527) of all the mutations induced by TALENs and RGENs, respectively, were associated with microhomology. At a given nuclease target site, the effect of these microhomologyassociated deletions can be predicted. In the extreme cases, (i) all deletions cause frameshifts in a protein-coding gene or (ii) no deletions cause frameshifts. In contrast, one-third of microhomologyindependent deletions result in in-frame mutations. Assuming that ~60% of indels are microhomology independent on average, the fraction of in-frame mutations at a given site can range from 20% (60%/3 + 0%) to 60% (60%/3 + 40%), a threefold difference between the two extreme cases. Because most eukaryotic cells are diploid rather than haploid, the fraction of null cells carrying two outof-frame mutations can range from 16% (0.40 × 0.40) to 64% (0.80 × 0.80), depending on the choice of target site. A careful analysis of indel sequences also revealed that the frequency of microhomology-associated deletions depends on both the size of the microhomology and the length of the deletion (Supplementary Fig. 2). On the basis of these observations, we developed a simple formula and a computer program (Supplementary Fig. 3) to predict the deletion patterns at a given nuclease target site that are associated with microhomology of at least two bases (Fig. 1b and Supplementary Note). We assigned a pattern score to each deletion pattern and a microhomology score (equaling the sum of pattern scores) to each target site. We then obtained an out-of-frame score at a given site by dividing the sum of pattern scores assigned to frameshifting deletions by the microhomology score. To evaluate the utility of our scoring system, we arbitrarily chose two target sites in exons, one with a high score (top 20%) and the other with a low score (bottom 20%) in each of nine human genes. We targeted a total of 6 and 12 sites in human cells with RGENs and TALENs, respectively (Supplementary Table 3), and then analyzed the mutant patterns by deep sequencing (Supplementary Table 4). High-score sites produced out-of-frame indels much more frequently than did low-score sites in all nine pairs (Fig. 1c), even at two adjacent target sites separated by 29 bases in the MCM6 gene (Supplementary Fig. 4). On average, the high-score sites and low-score sites produced frameshifting indels at frequencies of 79.3% and 42.5%, respectively (Student’s t-test, P < 0.01). We then tested in HeLa cells 68 new RGENs that target different genes (Supplementary Table 5). Again, out-of-frame scores correlated well with the frequencies of frameshifting indels or deletions (Pearson coefficient = 0.717 and 0.732, respectively) (Fig. 1d and Supplementary Fig. 5). The frequencies of out-of-frame indels ranged from 38.7% to 94.0%. In a diploid human cell, the probability of obtaining null clones would thus range from 15.0% (0.387 × 0.387) to 88.4%. Most cancer cell lines including HeLa are multi-ploid (>3n), making it even more important to choose high-score sites. We expect that the scoring system would work even better for TALENs because TALENs induce microhomology-independent insertions much less frequently than do RGENs (Supplementary Fig. 1b). We also analyzed the genotypes of 81 mice carrying mutations produced via TALENs5 or RGENs6, from our previous studies. The frequencies of out-of-frame deletions correlated well with predicted scores (Pearson coefficient = 0.996; Supplementary Fig. 6). In summary, we developed a scoring system to estimate the frequency of microhomology-associated deletions at nuclease

Expression Atlas update—a database of gene and transcript expression from microarray- and sequencing-based functional genomics experiments

Abstract: Expression Atlas (http://www.ebi.ac.uk/gxa) is a value-added database providing information about gene, protein and splice variant expression in different cell types, organism parts, developmental stages, diseases and other biological and experimental conditions. The database consists of selected high-quality microarray and RNA-sequencing experiments from ArrayExpress that have been manually curated, annotated with Experimental Factor Ontology terms and processed using standardized microarray and RNA-sequencing analysis methods. The new version of Expression Atlas introduces the concept of 'baseline' expression, i.e. gene and splice variant abundance levels in healthy or untreated conditions, such as tissues or cell types. Differential gene expression data benefit from an in-depth curation of experimental intent, resulting in biologically meaningful 'contrasts', i.e. instances of differential pairwise comparisons between two sets of biological replicates. Other novel aspects of Expression Atlas are its strict quality control of raw experimental data, up-to-date RNA-sequencing analysis methods, expression data at the level of gene sets, as well as genes and a more powerful search interface designed to maximize the biological value provided to the user.

Long non-coding RNA UCA1 promotes breast tumor growth by suppression of p27 (Kip1).

Abstract: Functional genomics studies have led to the discovery of a large amount of non-coding RNAs from the human genome; among them are long non-coding RNAs (lncRNAs). Emerging evidence indicates that lncRNAs could have a critical role in the regulation of cellular processes such as cell growth and apoptosis as well as cancer progression and metastasis. As master gene regulators, lncRNAs are capable of forming lncRNA–protein (ribonucleoprotein) complexes to regulate a large number of genes. For example, lincRNA-RoR suppresses p53 in response to DNA damage through interaction with heterogeneous nuclear ribonucleoprotein I (hnRNP I). The present study demonstrates that hnRNP I can also form a functional ribonucleoprotein complex with lncRNA urothelial carcinoma-associated 1 (UCA1) and increase the UCA1 stability. Of interest, the phosphorylated form of hnRNP I, predominantly in the cytoplasm, is responsible for the interaction with UCA1. Moreover, although hnRNP I enhances the translation of p27 (Kip1) through interaction with the 5′-untranslated region (5′-UTR) of p27 mRNAs, the interaction of UCA1 with hnRNP I suppresses the p27 protein level by competitive inhibition. In support of this finding, UCA1 has an oncogenic role in breast cancer both in vitro and in vivo. Finally, we show a negative correlation between p27 and UCA in the breast tumor cancer tissue microarray. Together, our results suggest an important role of UCA1 in breast cancer.

Human Social Genomics

Abstract: A growing literature in human social genomics has begun to analyze how everyday life circumstances influence human gene expression. Social-environmental conditions such as urbanity, low socioeconomic status, social isolation, social threat, and low or unstable social status have been found to associate with differential expression of hundreds of gene transcripts in leukocytes and diseased tissues such as metastatic cancers. In leukocytes, diverse types of social adversity evoke a common conserved transcriptional response to adversity (CTRA) characterized by increased expression of proinflammatory genes and decreased expression of genes involved in innate antiviral responses and antibody synthesis. Mechanistic analyses have mapped the neural “social signal transduction” pathways that stimulate CTRA gene expression in response to social threat and may contribute to social gradients in health. Research has also begun to analyze the functional genomics of optimal health and thriving. Two emerging opportunities now stand to revolutionize our understanding of the everyday life of the human genome: network genomics analyses examining how systems-level capabilities emerge from groups of individual socially sensitive genomes and near-real-time transcriptional biofeedback to empirically optimize individual well-being in the context of the unique genetic, geographic, historical, developmental, and social contexts that jointly shape the transcriptional realization of our innate human genomic potential for thriving.

RNA-seq analyses of multiple meristems of soybean: novel and alternative transcripts, evolutionary and functional implications

Abstract: Soybean is one of the most important crops, providing large amounts of dietary proteins and edible oil, and is also an excellent model for studying evolution of duplicated genes. However, relative to the model plants Arabidopsis and rice, the present knowledge about soybean transcriptome is quite limited. In this study, we employed RNA-seq to investigate transcriptomes of 11 soybean tissues, for genome-wide discovery of truly expressed genes, and novel and alternative transcripts, as well as analyses of conservation and divergence of duplicated genes and their functional implications. We detected a total of 54,132 high-confidence expressed genes, and identified 6,718 novel transcriptional regions with a mean length of 372 bp. We also provided strong evidence for alternative splicing (AS) events for ~15.9% of the genes with two or more exons. Among them, 1,834 genes exhibited stage-dependent AS, and 202 genes had tissue-biased exon-skipping events. We further defined the conservation and divergence in expression patterns between duplicated gene pairs from recent whole genome duplications (WGDs); differentially expressed genes, tissue preferentially expressed genes, transcription factors and specific gene family members were identified for shoot apical meristem and flower development. Our results significantly improved soybean gene annotation, and also provide valuable resources for functional genomics and studies of the evolution of duplicated genes from WGDs in soybean.

Expanding the computational toolbox for mining cancer genomes

Abstract: High-throughput DNA sequencing has revolutionized the study of cancer genomics with numerous discoveries that are relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations, including single-nucleotide variants, insertions and deletions, copy-number aberrations, structural variants and gene fusions. Additional computational techniques have proved useful for defining the mutations, genes and molecular networks that drive diverse cancer phenotypes and that determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic and epigenomic alterations in cancer, and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.

Gramene 2013: comparative plant genomics resources

Abstract: Gramene (http://www.gramene.org) is a curated online resource for comparative functional genomics in crops and model plant species, currently hosting 27 fully and 10 partially sequenced reference genomes in its build number 38. Its strength derives from the application of a phylogenetic framework for genome comparison and the use of ontologies to integrate structural and functional annotation data. Whole-genome alignments complemented by phylogenetic gene family trees help infer syntenic and orthologous relationships. Genetic variation data, sequences and genome mappings available for 10 species, including Arabidopsis, rice and maize, help infer putative variant effects on genes and transcripts. The pathways section also hosts 10 species-specific metabolic pathways databases developed in-house or by our collaborators using Pathway Tools software, which facilitates searches for pathway, reaction and metabolite annotations, and allows analyses of user-defined expression datasets. Recently, we released a Plant Reactome portal featuring 133 curated rice pathways. This portal will be expanded for Arabidopsis, maize and other plant species. We continue to provide genetic and QTL maps and marker datasets developed by crop researchers. The project provides a unique community platform to support scientific research in plant genomics including studies in evolution, genetics, plant breeding, molecular biology, biochemistry and systems biology.

Functional genomics of lactic acid bacteria: from food to health

Abstract: Genome analysis using next generation sequencing technologies has revolutionized the characterization of lactic acid bacteria and complete genomes of all major groups are now available. Comparative genomics has provided new insights into the natural and laboratory evolution of lactic acid bacteria and their environmental interactions. Moreover, functional genomics approaches have been used to understand the response of lactic acid bacteria to their environment. The results have been instrumental in understanding the adaptation of lactic acid bacteria in artisanal and industrial food fermentations as well as their interactions with the human host. Collectively, this has led to a detailed analysis of genes involved in colonization, persistence, interaction and signaling towards to the human host and its health. Finally, massive parallel genome re-sequencing has provided new opportunities in applied genomics, specifically in the characterization of novel non-GMO strains that have potential to be used in the food industry. Here, we provide an overview of the state of the art of these functional genomics approaches and their impact in understanding, applying and designing lactic acid bacteria for food and health.

Quantitative genome-wide enhancer activity maps for five Drosophila species show functional enhancer conservation and turnover during cis-regulatory evolution

Abstract: Phenotypic differences between closely related species are thought to arise primarily from changes in gene expression due to mutations in cis-regulatory sequences (enhancers). However, it has remained unclear how frequently mutations alter enhancer activity or create functional enhancers de novo. Here we use STARR-seq, a recently developed quantitative enhancer assay, to determine genome-wide enhancer activity profiles for five Drosophila species in the constant trans-regulatory environment of Drosophila melanogaster S2 cells. We find that the functions of a large fraction of D. melanogaster enhancers are conserved for their orthologous sequences owing to selection and stabilizing turnover of transcription factor motifs. Moreover, hundreds of enhancers have been gained since the D. melanogaster–Drosophila yakuba split about 11 million years ago without apparent adaptive selection and can contribute to changes in gene expression in vivo. Our finding that enhancer activity is often deeply conserved and frequently gained provides functional insights into regulatory evolution.

Non-coding RNA: a new frontier in regulatory biology

Abstract: A striking finding in the past decade is the production of numerous non-coding RNAs (ncRNAs) from mammalian genomes. While it is entirely possible that many of those ncRNAs are transcription noises or by-products of RNA processing, increasing evidence suggests that a large fraction of them are functional and provide various regulatory activities in the cell. Thus, functional genomics and proteomics are incomplete without understanding functional ribonomics. As has been long suggested by the 'RNA world' hypothesis, many ncRNAs have the capacity to act like proteins in diverse biochemical processes. The enormous amount of information residing in the primary sequences and secondary structures of ncRNAs makes them particularly suited to function as scaffolds for molecular interactions. In addition, their functions appear to be stringently controlled by default via abundant nucleases when not engaged in specific interactions. This review focuses on the functional properties of regulatory ncRNAs in comparison with proteins and emphasizes both the opportunities and challenges in future ncRNA research.

Integrating diverse datasets improves developmental enhancer prediction.

Abstract: Gene-regulatory enhancers have been identified using various approaches, including evolutionary conservation, regulatory protein binding, chromatin modifications, and DNA sequence motifs. To integrate these different approaches, we developed EnhancerFinder, a two-step method for distinguishing developmental enhancers from the genomic background and then predicting their tissue specificity. EnhancerFinder uses a multiple kernel learning approach to integrate DNA sequence motifs, evolutionary patterns, and diverse functional genomics datasets from a variety of cell types. In contrast with prediction approaches that define enhancers based on histone marks or p300 sites from a single cell line, we trained EnhancerFinder on hundreds of experimentally verified human developmental enhancers from the VISTA Enhancer Browser. We comprehensively evaluated EnhancerFinder using cross validation and found that our integrative method improves the identification of enhancers over approaches that consider a single type of data, such as sequence motifs, evolutionary conservation, or the binding of enhancer-associated proteins. We find that VISTA enhancers active in embryonic heart are easier to identify than enhancers active in several other embryonic tissues, likely due to their uniquely high GC content. We applied EnhancerFinder to the entire human genome and predicted 84,301 developmental enhancers and their tissue specificity. These predictions provide specific functional annotations for large amounts of human non-coding DNA, and are significantly enriched near genes with annotated roles in their predicted tissues and lead SNPs from genome-wide association studies. We demonstrate the utility of EnhancerFinder predictions through in vivo validation of novel embryonic gene regulatory enhancers from three developmental transcription factor loci. Our genome-wide developmental enhancer predictions are freely available as a UCSC Genome Browser track, which we hope will enable researchers to further investigate questions in developmental biology.

RNA Interference (RNAi) Induced Gene Silencing: A Promising Approach of Hi-Tech Plant Breeding.

Abstract: RNA interference (RNAi) is a promising gene regulatory approach in functional genomics that has significant impact on crop improvement which permits down-regulation in gene expression with greater precise manner without affecting the expression of other genes. RNAi mechanism is expedited by small molecules of interfering RNA to suppress a gene of interest effectively. RNAi has also been exploited in plants for resistance against pathogens, insect/pest, nematodes, and virus that cause significant economic losses. Keeping beside the significance in the genome integrity maintenance as well as growth and development, RNAi induced gene syntheses are vital in plant stress management. Modifying the genes by the interference of small RNAs is one of the ways through which plants react to the environmental stresses. Hence, investigating the role of small RNAs in regulating gene expression assists the researchers to explore the potentiality of small RNAs in abiotic and biotic stress management. This novel approach opens new avenues for crop improvement by developing disease resistant, abiotic or biotic stress tolerant, and high yielding elite varieties.

Functional genomics using crispr-cas systems, compositions methods, screens and applications thereof

Abstract: The present invention generally relates to libraries, compositions, methods, applications, kits and screens used in functional genomics that focus on gene function in a cell and that may use vector systems and other aspects related to Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas systems and components thereof. Provided are vectors and vector systems, some of which encode one or more components of a CRISPR complex, as well as methods for the design and use of such vectors. Also provided are methods of directing CRISPR complex formation in eukaryotic cells and methods for utilizing the CRISPR-Cas system.

Protein–protein interactions: switch from classical methods to proteomics and bioinformatics-based approaches

Abstract: Following the sequencing of the human genome and many other organisms, research on protein-coding genes and their functions (functional genomics) has intensified. Subsequently, with the observation that proteins are indeed the molecular effectors of most cellular processes, the discipline of proteomics was born. Clearly, proteins do not function as single entities but rather as a dynamic network of team players that have to communicate. Though genetic (yeast two-hybrid Y2H) and biochemical methods (co-immunoprecipitation Co-IP, affinity purification AP) were the methods of choice at the beginning of the study of protein-protein interactions (PPI), in more recent years there has been a shift towards proteomics-based methods and bioinformatics-based approaches. In this review, we first describe in depth PPIs and we make a strong case as to why unraveling the interactome is the next challenge in the field of proteomics. Furthermore, classical methods of investigation of PPIs and structure-based bioinformatics approaches are presented. The greatest emphasis is placed on proteomic methods, especially native techniques that were recently developed and that have been shown to be reliable. Finally, we point out the limitations of these methods and the need to set up a standard for the validation of PPI experiments.

Functional genomics reveals that Clostridium difficile Spo0A coordinates sporulation, virulence and metabolism

Abstract: Background: Clostridium difficile is an anaerobic, Gram-positive bacterium that can reside as a commensal within the intestinal microbiota of healthy individuals or cause life-threatening antibiotic-associated diarrhea in immunocompromised hosts. C. difficile can also form highly resistant spores that are excreted facilitating host-to-host transmission. The C. difficile spo0A gene encodes a highly conserved transcriptional regulator of sporulation that is required for relapsing disease and transmission in mice. Results: Here we describe a genome-wide approach using a combined transcriptomic and proteomic analysis to identify Spo0A regulated genes. Our results validate Spo0A as a positive regulator of putative and novel sporulation genes as well as components of the mature spore proteome. We also show that Spo0A regulates a number of virulence-associated factors such as flagella and metabolic pathways including glucose fermentation leading to butyrate production. Conclusions: The C. difficile spo0A gene is a global transcriptional regulator that controls diverse sporulation, virulence and metabolic phenotypes coordinating pathogen adaptation to a wide range of host interactions. Additionally, the rich breadth of functional data allowed us to significantly update the annotation of the C. difficile 630 reference genome which will facilitate basic and applied research on this emerging pathogen.

Artificial microRNA mediated gene silencing in plants: progress and perspectives

Abstract: Homology based gene silencing has emerged as a convenient approach for repressing expression of genes in order to study their functions. For this purpose, several antisense or small interfering RNA based gene silencing techniques have been frequently employed in plant research. Artificial microRNAs (amiRNAs) mediated gene silencing represents one of such techniques which can utilize as a potential tool in functional genomics. Similar to microRNAs, amiRNAs are single-stranded, approximately 21 nt long, and designed by replacing the mature miRNA sequences of duplex within pre-miRNAs. These amiRNAs are processed via small RNA biogenesis and silencing machinery and deregulate target expression. Holding to various refinements, amiRNA technology offers several advantages over other gene silencing methods. This is a powerful and robust tool, and could be applied to unravel new insight of metabolic pathways and gene functions across the various disciplines as well as in translating observations for improving favourable traits in plants. This review highlights general background of small RNAs, improvements made in RNAi based gene silencing, implications of amiRNA in gene silencing, and describes future themes for improving value of this technology in plant science.

Virus-induced gene silencing is a versatile tool for unraveling the functional relevance of multiple abiotic-stress-responsive genes in crop plants.

Abstract: Virus-induced gene silencing (VIGS) is an effective tool for gene function analysis in plants. Over the last decade, VIGS has been successfully used as both a forward and reverse genetics technique for gene function analysis in various model plants, as well as crop plants. With the increased identification of differentially expressed genes under various abiotic stresses through high-throughput transcript profiling, the application of VIGS is expected to be important in the future for functional characterization of a large number of genes. In the recent past, VIGS was proven to be an elegant tool for functional characterization of genes associated with abiotic stress responses. In this review, we provide an overview of how VIGS is used in different crop species to characterize genes associated with drought-, salt-, oxidative- and nutrient-deficiency-stresses. We describe the examples from studies where abiotic stress related genes are characterized using VIGS. In addition, we describe the major advantages of VIGS over other currently available functional genomics tools. We also summarize the recent improvements, limitations and future prospects of using VIGS as a tool for studying plant responses to abiotic stresses.

A Drosophila RNAi collection is subject to dominant phenotypic effects.

Abstract: tion site for pKC26 in the KK library is the non-annotated pKC43 target (occupied in all 39 lines tested), whereas only the nine lines displaying the elav-GAL4c155–dependent non-inflating wing phenotype were found to have a pKC26 integration into the annotated pKC43 insertion (Supplementary Table 1). After separating the two occupied pKC43 targets by recombination (Supplementary Methods and Supplementary Fig. 2), we found that occupancy of the non-annotated site resulted in saturating expression of the split mini-white (w+mC) transgenesis marker, making it impossible to phenotypically distinguish lines with single or double pKC26 integrations (compare Fig. 1b,c). We observed some variability in mini-white expression from pKC26 integrations at the annotated site (Supplementary Fig. 3). Molecular analyses revealed that this site could be occupied by at least three different pKC26 derived sequences: (i) a pKC26 vector containing a normal hairpin sequence, (ii) an empty pKC26 vector containing no hairpin and (iii) a truncated pKC26 in which sequence-specific recombination between the hsp70 elements used to drive expression of both the shRNA and the mini-white marker had deleted an ~1.1-kilobase vector fragment. Each of the three types of annotated site insertions was sufficient to cause the non-inflating wing phenotype when crossed to elav-GALc155 in the absence of any integration at the non-annotated pKC43 target. A Drosophila RNAi collection is subject to dominant phenotypic effects

An efficient reverse genetics platform in the model legume Medicago truncatula.

Abstract: Summary Medicago truncatula is one of the model species for legume studies. In an effort to develop legume genetics resources, > 21 700 Tnt1 retrotransposon insertion lines have been generated. To facilitate fast-growing needs in functional genomics, two reverse genetics approaches have been established: web-based database searching and PCR-based reverse screening. More than 840 genes have been reverse screened using the PCR-based approach over the past 6 yr to identify mutants in these genes. Overall, c. 84% (705 genes) success rate was achieved in identifying mutants with at least one Tnt1 insertion, of which c. 50% (358 genes) had three or more alleles. To demonstrate the utility of the two reverse genetics platforms, two mutant alleles were isolated for each of the two floral homeotic MADS-box genes, MtPISTILATA and MtAGAMOUS. Molecular and genetic analyses indicate that Tnt1 insertions in exons of both genes are responsible for the defects in floral organ development. In summary, we have developed two efficient reverse genetics platforms to facilitate functional characterization of M. truncatula genes.

Transcriptomics and functional genomics of ROS-induced cell death regulation by RADICAL-INDUCED CELL DEATH1.

Abstract: Plant responses to changes in environmental conditions are mediated by a network of signaling events leading to downstream responses, including changes in gene expression and activation of cell death programs. Arabidopsis thaliana RADICAL-INDUCED CELL DEATH1 (RCD1) has been proposed to regulate plant stress responses by protein-protein interactions with transcription factors. Furthermore, the rcd1 mutant has defective control of cell death in response to apoplastic reactive oxygen species (ROS). Combining transcriptomic and functional genomics approaches we first used microarray analysis in a time series to study changes in gene expression after apoplastic ROS treatment in rcd1. To identify a core set of cell death regulated genes, RCD1-regulated genes were clustered together with other array experiments from plants undergoing cell death or treated with various pathogens, plant hormones or other chemicals. Subsequently, selected rcd1 double mutants were constructed to further define the genetic requirements for the execution of apoplastic ROS induced cell death. Through the genetic analysis we identified WRKY70 and SGT1b as cell death regulators functioning downstream of RCD1 and show that quantitative rather than qualitative differences in gene expression related to cell death appeared to better explain the outcome. Allocation of plant energy to defenses diverts resources from growth. Recently, a plant response termed stress-induced morphogenic response (SIMR) was proposed to regulate the balance between defense and growth. Using a rcd1 double mutant collection we show that SIMR is mostly independent of the classical plant defense signaling pathways and that the redox balance is involved in development of SIMR.

Integrative functional genomics of hepatitis C virus infection identifies host dependencies in complete viral replication cycle.

Abstract: Recent functional genomics studies including genome-wide small interfering RNA (siRNA) screens demonstrated that hepatitis C virus (HCV) exploits an extensive network of host factors for productive infection and propagation. How these co-opted host functions interact with various steps of HCV replication cycle and exert pro- or antiviral effects on HCV infection remains largely undefined. Here we present an unbiased and systematic strategy to functionally interrogate HCV host dependencies uncovered from our previous infectious HCV (HCVcc) siRNA screen. Applying functional genomics approaches and various in vitro HCV model systems, including HCV pseudoparticles (HCVpp), single-cycle infectious particles (HCVsc), subgenomic replicons, and HCV cell culture systems (HCVcc), we identified and characterized novel host factors or pathways required for each individual step of the HCV replication cycle. Particularly, we uncovered multiple HCV entry factors, including E-cadherin, choline kinase α, NADPH oxidase CYBA, Rho GTPase RAC1 and SMAD family member 6. We also demonstrated that guanine nucleotide binding protein GNB2L1, E2 ubiquitin-conjugating enzyme UBE2J1, and 39 other host factors are required for HCV RNA replication, while the deubiquitinating enzyme USP11 and multiple other cellular genes are specifically involved in HCV IRES-mediated translation. Families of antiviral factors that target HCV replication or translation were also identified. In addition, various virologic assays validated that 66 host factors are involved in HCV assembly or secretion. These genes included insulin-degrading enzyme (IDE), a proviral factor, and N-Myc down regulated Gene 1 (NDRG1), an antiviral factor. Bioinformatics meta-analyses of our results integrated with literature mining of previously published HCV host factors allows the construction of an extensive roadmap of cellular networks and pathways involved in the complete HCV replication cycle. This comprehensive study of HCV host dependencies yields novel insights into viral infection, pathogenesis and potential therapeutic targets.

A Sorghum bicolor expression atlas reveals dynamic genotype-specific expression profiles for vegetative tissues of grain, sweet and bioenergy sorghums

Abstract: Effective improvement in sorghum crop development necessitates a genomics-based approach to identify functional genes and QTLs. Sequenced in 2009, a comprehensive annotation of the sorghum genome and the development of functional genomics resources is key to enable the discovery and deployment of regulatory and metabolic genes and gene networks for crop improvement. This study utilizes the first commercially available whole-transcriptome sorghum microarray (Sorgh-WTa520972F) to identify tissue and genotype-specific expression patterns for all identified Sorghum bicolor exons and UTRs. The genechip contains 1,026,373 probes covering 149,182 exons (27,577 genes) across the Sorghum bicolor nuclear, chloroplast, and mitochondrial genomes. Specific probesets were also included for putative non-coding RNAs that may play a role in gene regulation (e.g., microRNAs), and confirmed functional small RNAs in related species (maize and sugarcane) were also included in our array design. We generated expression data for 78 samples with a combination of four different tissue types (shoot, root, leaf and stem), two dissected stem tissues (pith and rind) and six diverse genotypes, which included 6 public sorghum lines (R159, Atlas, Fremont, PI152611, AR2400 and PI455230) representing grain, sweet, forage, and high biomass ideotypes. Here we present a summary of the microarray dataset, including analysis of tissue-specific gene expression profiles and associated expression profiles of relevant metabolic pathways. With an aim to enable identification and functional characterization of genes in sorghum, this expression atlas presents a new and valuable resource to the research community.

Function-based identification of mammalian enhancers using site-specific integration.

Abstract: The accurate and comprehensive identification of functional regulatory sequences in mammalian genomes remains a major challenge. Here we describe site-specific integration fluorescence-activated cell sorting followed by sequencing (SIF-seq), an unbiased, medium-throughput functional assay for the discovery of distant-acting enhancers. Targeted single-copy genomic integration into pluripotent cells, reporter assays and flow cytometry are coupled with high-throughput DNA sequencing to enable parallel screening of large numbers of DNA sequences. By functionally interrogating >500 kilobases (kb) of mouse and human sequence in mouse embryonic stem cells for enhancer activity we identified enhancers at pluripotency loci including NANOG. In in vitro-differentiated cardiomyocytes and neural progenitor cells, we identified cardiac enhancers and neuronal enhancers, respectively. SIF-seq is a powerful and flexible method for de novo functional identification of mammalian enhancers in a potentially wide variety of cell types.

Functional genomics of acclimation and adaptation in response to thermal stress in Daphnia

Abstract: Gene expression regulation is one of the fundamental mechanisms of phenotypic plasticity and is expected to respond to selection in conditions favoring phenotypic response. The observation that many organisms increase their stress tolerance after acclimation to moderate levels of stress is an example of plasticity which has been long hypothesized to be based on adaptive changes in gene expression. We report genome-wide patterns of gene expression in two heat-tolerant and two heat-sensitive parthenogenetic clones of the zooplankton crustacean Daphnia pulex exposed for three generations to either optimal (18°C) or substressful (28°C) temperature. A large number of genes responded to temperature and many demonstrated a significant genotype-by-environment (GxE) interaction. Among genes with a significant GxE there were approximately equally frequent instances of canalization, i.e. stronger plasticity in heat-sensitive than in heat-tolerant clones, and of enhancement of plasticity along the evolutionary vector toward heat tolerance. The strongest response observed is the across-the-board down-regulation of a variety of genes occurring in heat-tolerant, but not in heat-sensitive clones. This response is particularly obvious among genes involved in core metabolic pathways and those responsible for transcription, translation and DNA repair. The observed down-regulation of metabolism, consistent with previous findings in yeast and Drosophila, may reflect a general compensatory stress response. The associated down-regulation of DNA repair pathways potentially creates a trade-off between short-term benefits of survival at high temperature and long-term costs of accelerated mutation accumulation.

A DNA-binding-site landscape and regulatory network analysis for NAC transcription factors in Arabidopsis thaliana

Abstract: Target gene identification for transcription factors is a prerequisite for the systems wide understanding of organismal behaviour. NAM-ATAF1/2-CUC2 (NAC) transcription factors are amongst the largest transcription factor families in plants, yet limited data exist from unbiased approaches to resolve the DNA-binding preferences of individual members. Here, we present a TF-target gene identification workflow based on the integration of novel protein binding microarray data with gene expression and multi-species promoter sequence conservation to identify the DNA-binding specificities and the gene regulatory networks of 12 NAC transcription factors. Our data offer specific single-base resolution fingerprints for most TFs studied and indicate that NAC DNA-binding specificities might be predicted from their DNA-binding domain's sequence. The developed methodology, including the application of complementary functional genomics filters, makes it possible to translate, for each TF, protein binding microarray data into a set of high-quality target genes. With this approach, we confirm NAC target genes reported from independent in vivo analyses. We emphasize that candidate target gene sets together with the workflow associated with functional modules offer a strong resource to unravel the regulatory potential of NAC genes and that this workflow could be used to study other families of transcription factors.