Field Of Functional Genomics Research Articles

Unraveling of Central Nervous System Disease Mechanisms Using CRISPR Genome Manipulation.

The complex structure and highly variable gene expression profile of the brain makes it among the most challenging fields to study in both basic and translational biological research. Most of the brain diseases are multifactorial and despite the rapidly increasing genomic data, molecular pathways and causal links between genes and central nervous system (CNS) diseases are largely unknown. The advent of an easy and flexible CRISPR-Cas genome editing technology has rapidly revolutionized the field of functional genomics and opened unprecedented possibilities to dissect the mechanisms of CNS disease. CRISPR-Cas allows a plenitude of applications for both gene-focused and genome-wide approaches, ranging from original “gene scissors” making permanent modifications in the genome to the regulation of gene expression and epigenetics. CRISPR technology provides a unique opportunity to establish new cellular and animal models of CNS diseases and holds potential for breakthroughs in the CNS research and drug development.

Activity-Based Protein Profiling for the Study of Parasite Biology.

Parasites exist within most ecological niches, often transitioning through biologically and chemically complex host environments over the course of their parasitic life cycles. While the development of technologies for genetic engineering has revolutionised the field of functional genomics, parasites have historically been less amenable to such modification. In light of this, parasitologists have often been at the forefront of adopting new small-molecule technologies, repurposing drugs into biological tools and probes. Over the last decade, activity-based protein profiling (ABPP) has evolved into a powerful and versatile chemical proteomic platform for characterising the function of enzymes. Central to ABPP is the use of activity-based probes (ABPs), which covalently modify the active sites of enzyme classes ranging from serine hydrolases to glycosidases. The application of ABPP to cellular systems has contributed vastly to our knowledge on the fundamental biology of a diverse range of organisms and has facilitated the identification of potential drug targets in many pathogens. In this chapter, we provide a comprehensive review on the different forms of ABPP that have been successfully applied to parasite systems, and highlight key biological insights that have been enabled through their application.

Gene Editing and Crop Improvement Using CRISPR-Cas9 System.

Advancements in Genome editing technologies have revolutionized the fields of functional genomics and crop improvement. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeat)-Cas9 is a multipurpose technology for genetic engineering that relies on the complementarity of the guideRNA (gRNA) to a specific sequence and the Cas9 endonuclease activity. It has broadened the agricultural research area, bringing in new opportunities to develop novel plant varieties with deletion of detrimental traits or addition of significant characters. This RNA guided genome editing technology is turning out to be a groundbreaking innovation in distinct branches of plant biology. CRISPR technology is constantly advancing including options for various genetic manipulations like generating knockouts; making precise modifications, multiplex genome engineering, and activation and repression of target genes. The review highlights the progression throughout the CRISPR legacy. We have studied the rapid evolution of CRISPR/Cas9 tools with myriad functionalities, capabilities, and specialized applications. Among varied diligences, plant nutritional improvement, enhancement of plant disease resistance and production of drought tolerant plants are reviewed. The review also includes some information on traditional delivery methods of Cas9-gRNA complexes into plant cells and incorporates the advent of CRISPR ribonucleoproteins (RNPs) that came up as a solution to various limitations that prevailed with plasmid-based CRISPR system.

RNA interference- a novel approach for plant disease management

RNA interference (RNAi) is an incredible revolution in the field of functional genomics, a breakthrough in plant molecular genetics. This technology will generate enormous potential for engineering control of gene expres-sion. The success of managing biotic stress using RNAi technology will prove to be biologically and environmentally safe. It is therapeutic in approach as the resistance induced by RNAi is triggered by ds RNA that results in silencing of specific genes before being translated in a homology dependent manner. Over the time, RNAi is significantly proving it as one of the most promiscent management strategy which eliminates certain risks associated with the development of transgenic plants. This review gives an insight into the probability of management of plant diseases caused by various biotic agents viz. fungi, bacteria and viruses using RNA interference technique and host-pathogen related targeted sites.

Fusion of expression values and protein interaction information using multi-objective optimization for improving gene clustering

One of the crucial problems in the field of functional genomics is to identify a set of genes which are responsible for a particular cellular mechanism. The current work explores the usage of a multi-objective optimization based genetic clustering technique to classify genes into groups with respect to their functional similarities and biological relevance. Our contribution is two-fold: firstly a new quality measure to compute the goodness of gene-clusters namely protein-protein interaction confidence score is developed. This utilizes the confidence scores of the protein-protein interaction networks to measure the similarity between genes of a particular cluster with respect to their biochemical protein products. Secondly, a multi-objective based clustering approach is developed which intelligently uses integrated information of expression values of microarray dataset and protein-protein interaction confidence scores to select both statistically and biologically relevant genes. For that very purpose, some biological cluster validity indices, viz. biological homogeneity index and protein-protein interaction confidence score, along with two traditional internal cluster validity indices, viz. fuzzy partition coefficient and Pakhira-Bandyopadhyay-Maulik-index, are simultaneously optimized during the clustering process. Experimental results on three real-life gene expression datasets show that the addition of new objective capturing protein-protein interaction information aids in clustering the genes as compared to the existing techniques. The observations are further supported by biological and statistical significance tests.

Associating cellular epigenetic models with human phenotypes.

Epigenetic association studies have been carried out to test the hypothesis that environmental perturbations trigger cellular reprogramming, with downstream effects on cellular function and phenotypes. There have now been numerous studies of the potential molecular mediators of epigenetic changes by epigenome-wide association studies (EWAS). However, a challenge for the field is the interpretation of the results obtained. We describe a second-generation EWAS approach, which focuses on the possible cellular models of epigenetic perturbations, studied by rigorous analysis and interpretation of genomic data. Thus refocused, epigenetics research aligns with the field of functional genomics to provide insights into environmental and genetic influences on phenotypic variation in humans.

Use of functional genomics to assess the climate change impact onAspergillus flavus and aflatoxin production

Aspergillus flavus is an opportunistic and pathogenic fungus that infects several crops of agricultural importance and under certain conditions may produce carcinogenic mycotoxins. Rising global temperatures, disrupted precipitation patterns and increased CO2 levels that are associated with future climate conditions are expected to impact the growth and toxigenic potential ofA. flavus. Both laboratory and real world observations have demonstrated this potential, especially when examining the effects of water availability and temperature. Recent experiments have also established that CO2 may also be affecting toxin production. The application of current technologies in the field of functional genomics, including genomic sequencing, RNA-seq, microarray technologies and proteomics have revealed climate change-related, abiotic regulation of the aflatoxin cluster and influence on the plant-fungus interaction. Furthermore, elevated CO2 levels have been shown to impact expression of the aflatoxin biosynthetic regulatory geneaflR. The use of functional genomics will allow researchers to better understand the underlying transcriptomic response within the fungus to climate change, with a view towards predicting changes in fungal infection and toxin production associated with climate change.

Comparative Transcriptome Reconstruction of Four Hypericum Species Focused on Hypericin Biosynthesis.

Next generation sequencing technology rapidly developed research applications in the field of plant functional genomics. Several Hypericum spp. with an aim to generate and enhance gene annotations especially for genes coding the enzymes supposedly included in biosynthesis of valuable bioactive compounds were analyzed. The first de novo transcriptome profiling of Hypericum annulatum Moris, H. tomentosum L., H. kalmianum L., and H. androsaemum L. leaves cultivated in vitro was accomplished. All four species with only limited genomic information were selected on the basis of differences in ability to synthesize hypericins and presence of dark nodules accumulating these metabolites with purpose to enrich genomic background of Hypericum spp. H. annulatum was chosen because of high number of the dark nodules and high content of hypericin. H. tomentosum leaves are typical for the presence of only 1–2 dark nodules localized in the apical part. Both H. kalmianum and H. androsaemum lack hypericin and have no dark nodules. Four separated datasets of the pair-end reads were gathered and used for de novo assembly by Trinity program. Assembled transcriptomes were annotated to the public databases Swiss-Prot and non-redundant protein database (NCBI-nr). Gene ontology analysis was performed. Differences of expression levels in the marginal tissues with dark nodules and inner part of leaves lacking these nodules indicate a potential genetic background for hypericin formation as the presumed site of hypericin biosynthesis is in the cells adjacent to these structures. Altogether 165 contigs in H. annulatum and 100 contigs in H. tomentosum were detected as significantly differentially expressed (P < 0.05) and upregulated in the leaf rim tissues containing the dark nodules. The new sequences homologous to octaketide synthase and enzymes catalyzing phenolic oxidative coupling reactions indispensable for hypericin biosynthesis were discovered. The presented transcriptomic sequence data will improve current knowledge about the selected Hypericum spp. with proposed relation to hypericin biosynthesis and will provide a useful resource of genomic information for consequential studies in the field of functional genomics, proteomics and metabolomics.

Gene discovery by chemical mutagenesis and whole-genome sequencing in Dictyostelium.

Whole-genome sequencing is a useful approach for identification of chemical-induced lesions, but previous applications involved tedious genetic mapping to pinpoint the causative mutations. We propose that saturation mutagenesis under low mutagenic loads, followed by whole-genome sequencing, should allow direct implication of genes by identifying multiple independent alleles of each relevant gene. We tested the hypothesis by performing three genetic screens with chemical mutagenesis in the social soil amoeba Dictyostelium discoideum. Through genome sequencing, we successfully identified mutant genes with multiple alleles in near-saturation screens, including resistance to intense illumination and strong suppressors of defects in an allorecognition pathway. We tested the causality of the mutations by comparison to published data and by direct complementation tests, finding both dominant and recessive causative mutations. Therefore, our strategy provides a cost- and time-efficient approach to gene discovery by integrating chemical mutagenesis and whole-genome sequencing. The method should be applicable to many microbial systems, and it is expected to revolutionize the field of functional genomics in Dictyostelium by greatly expanding the mutation spectrum relative to other common mutagenesis methods.

Common variation in atrial fibrillation: navigating the path from genetic association to mechanism.

Atrial fibrillation (AF) is the most common cardiac arrhythmia with well-established clinical and genetic risk components. Genome-wide association studies (GWAS) have identified 17 independent susceptibility signals for AF at 14 genomic regions, but the mechanisms through which these loci confer risk to AF remain largely undefined. This problem is not unique to AF, as the field of functional genomics, which attempts to bridge this gap from genotype to phenotype, has only uncovered the mechanisms for a handful of GWAS loci. Recent functional genomic studies have made great strides towards translating genetic discoveries to an underlying mechanism, but the large-scale application of these techniques to AF has remain limited. These advances, as well as the continued unresolved challenges for both common variation in AF and the functional genomics field in general, will be the subject of the following review.

Strategies to avoid drowning in the deep sequencing data flood

The enormous technological progress in the field of functional genomics during the last 15 years had a significant impact on animal sciences. With the development of Next Generation Sequencing it became feasible to analyze genomes and transcriptomes within short time frames and affordable costs. One major challenge of this rapid development is to manage the data flood and to perform data analysis and integration in an optimal manner. This review provides some information about a typical analysis pipeline for RNASequencing (RNA-Seq) data and a strategy for the analysis of small RNA-Seq data derived from species with poor annotation for non-coding RNA genes. Furthermore, problems regarding gene annotation in livestock species and their possible implications for data analysis and interpretation are discussed. Despite of not yet solved problems and challenges with respect to data analysis and integration the approaches in the field of functional genome analysis opened up new ways to try to understand the complex trait fertility.

Morgan’s Legacy: Fruit Flies and the Functional Annotation of Conserved Genes

In 1915, "The Mechanism of Mendelian Heredity" was published by four prominent Drosophila geneticists. They discovered that genes form linkage groups on chromosomes inherited in a Mendelian fashion and laid the genetic foundation that promoted Drosophila as a model organism. Flies continue to offer great opportunities, including studies in the field of functional genomics.

Targeted gene knockout in chickens mediated by TALENs.

Genetically modified animals are used for industrial applications as well as scientific research, and studies on these animals contribute to a better understanding of biological mechanisms. Gene targeting techniques have been developed to edit specific gene loci in the genome, but the conventional strategy of homologous recombination with a gene-targeted vector has low efficiency and many technical complications. Here, we generated specific gene knockout chickens through the use of transcription activator-like effector nuclease (TALEN)-mediated gene targeting. In this study, we accomplished targeted knockout of the ovalbumin (OV) gene in the chicken primordial germ cells, and OV gene mutant offspring were generated through test-cross analysis. TALENs successfully induced nucleotide deletion mutations of ORF shifts, resulting in loss of chicken OV gene function. Our results demonstrate that the TALEN technique used in the chicken primordial germ cell line is a powerful strategy to create specific genome-edited chickens safely for practical applications.

Resources for systems biology in rice

Systems biology is an upcoming trend in the field of functional genomics. Recently, there has been a significant improvement in the resources for systems biology in Oryza sativa (rice), a model crop. These resources include whole-genome sequencing/re-sequencing data, transcriptomes, protein-protein interactomes, reactomes, functional gene network tools, and gene indexed mutant populations. The integration of diverse omics data can lead to greater understanding of the functional genomics of rice. In this review, we address the development and current progress of the resources available for systems biology in rice: Genome browsers and databases for the orthology identification, transcriptome analysis, protein-protein interaction network and functional gene network analyses, a co-expression network, metabolic pathway analysis for promoter analysis, and gene indexed mutants.

A Pre- and Co-Knockdown of RNAseT Enzyme, Eri-1, Enhances the Efficiency of RNAi Induced Gene Silencing in Caenorhabditis elegans

BackgroundThe approach of RNAi mediated gene knockdown, employing exogenous dsRNA, is being beneficially exploited in various fields of functional genomics. The immense utility of the approach came to fore from studies with model system C. elegans, but quickly became applicable with varied research models ranging from in vitro to various in vivo systems. Previously, there have been reports on the refractoriness of the neuronal cells to RNAi mediated gene silencing following which several modulators like eri-1 and lin-15 were described in C. elegans which, when present, would negatively impact the gene knockdown.Methodology/Principal FindingsTaking a clue from these findings, we went on to screen hypothesis-driven- methodologies towards exploring the efficiency in the process of RNAi under various experimental conditions, wherein these genes would be knocked down preceding to, or concurrently with, the knocking down of a gene of interest. For determining the efficiency of gene knockdown, we chose to study visually stark phenotypes of uncoordinated movement, dumpy body morphology and blistered cuticle obtained by knocking down of genes unc-73, dpy-9 and bli-3 respectively, employing the RNAi-by-feeding protocol in model system C. elegans.Conclusions/SignificanceOur studies led to a very interesting outcome as the results reveal that amongst various methods tested, pre-incubation with eri-1 dsRNA synthesizing bacteria followed by co-incubation with eri-1 and gene-of-interest dsRNA synthesizing bacteria leads to the most efficient gene silencing as observed by the analysis of marker phenotypes. This provides an approach for effectively employing RNAi induced gene silencing while working with different genetic backgrounds including transgenic and mutant strains.

A siRNA screen identifies RAD21 , EIF3H , CHRAC1 and TANC2 as driver genes within the 8q23, 8q24.3 and 17q23 amplicons in breast cancer with effects on cell growth, survival and transformation

RNA interference has boosted the field of functional genomics, by making it possible to carry out 'loss-of-function' screens in cultured cells. Here, we performed a small interfering RNA screening, in three breast cancer cell lines, for 101 candidate driver genes overexpressed in amplified breast tumors and belonging to eight amplicons on chromosomes 8q and 17q, investigating their role in cell survival/proliferation. This screening identified eight driver genes that were amplified, overexpressed and critical for breast tumor cell proliferation or survival. They included the well-described oncogenic driver genes for the 17q12 amplicon, ERBB2 and GRB7. Four of six other candidate driver genes-RAD21 and EIF3H, both on chromosome 8q23, CHRAC1 on chromosome 8q24.3 and TANC2 on chromosome 17q23-were confirmed to be driver genes regulating the proliferation/survival of clonogenic breast cancer cells presenting an amplification of the corresponding region. Indeed, knockdown of the expression of these genes decreased cell viability, through both cell cycle arrest and apoptosis induction, and inhibited the formation of colonies in anchorage-independent conditions, in soft agar. Strategies for inhibiting the expression of these genes or the function of the proteins they encode are therefore of potential value for the treatment of breast cancers presenting amplifications of the corresponding genomic region.

The challenges of delivering bioinformatics training in the analysis of high-throughput data

High-throughput technologies are widely used in the field of functional genomics and used in an increasing number of applications. For many ‘wet lab’ scientists, the analysis of the large amount of data generated by such technologies is a major bottleneck that can only be overcome through very specialized training in advanced data analysis methodologies and the use of dedicated bioinformatics software tools. In this article, we wish to discuss the challenges related to delivering training in the analysis of high-throughput sequencing data and how we addressed these challenges in the hands-on training courses that we have developed at the European Bioinformatics Institute.

Black Swans and Bell Curves

Two hundred terabytes of data from the Thousand Genomes project is now publicly available through an Amazon Web Services cloud. But the data describing human genetic variation will only be useful when we know how to translate it to improve human health. This partly depends on a comprehensive understanding of the relationship between our genomes and a vast range of phenotypes, be they rare mendelian or common quantitative traits. Moyra Smith helps us in this endeavour; she begins her book on phenotypic variation with cautious words from Lewis Thomas ‘Now that we have begun exploring in earnest, doing serious science, we are getting glimpses of how huge the questions are and how far from being answered'. This is an apt quotation for Smith's book, which painstakingly curates an impressive swath of very serious science published in her field of functional genomics up until 2009, and is modest in its claims about how we can currently apply the findings to medicine. The early chapters provide a detailed context for issues that are subsequently explored with increasing complexity. Genome architecture and structural DNA changes are described that have a functional influence on protein expression and in some cases may mark evolutionarily important stages for humans. For example, comparative genomic studies in humans and primates have identified loci that influence brain function (FOXP2, ASPM) and that have undergone rapid evolution. The influence of alleles under positive natural selection on the human genome is also considered with the concomitant reduction in genetic diversity for specific haplotypes. Chapter 4, Linkage, Association, and Linkage Disequilibrium, presents data from GWAS (genome-wide association studies) and explores both the rapid progress made and factors that can impede our understanding of associations between genotype and complex phenotypes. Some of the factors are technical; the limitations of data generated from microarrays that were constructed before large-scale mRNA sequencing had revealed the complexity of the transcriptome. Other confounding factors are biological; functional studies reveal a good deal of redundancy because evolutionary processes result in chaotic complex systems, and the co-segregation of some SNPs with disease phenotypes is because of linkage disequilibrium with the causal structural variants within the genome. Further complexity that necessitates the functional plasticity of the human genome is elaborated on in chapters 5–7, which consider transcriptional control; the spliceosome; protein turnover; and the heteroplasmy and mutations that affect the expression of the mitochondrial genome. Aberrant protein folding and impaired autophagy are phenotypic changes associated with ageing and neurodegenerative disease, as are somatic mutations in the mitochondrial genome. The later chapters consider complex disease phenotypes, including neurobehavioural disorders, malformation syndromes, and late-onset conditions such as Parkinson's disease. Some overarching themes emerge from Smith's detailed review of the results of familial, population genetic, and experimental studies. For psychiatric diseases, the diagnostic categorisation may need to change in the light of genetic findings and an understanding of molecular pathophysiology; a paradigm shift that is already underway in other fields such as oncology. In considering the molecular basis of schizophrenia Matt Ridley's maxim of nature via nurture came to mind because of the putative role of infectious agents in the disease aetiology (schizophrenia-associated markers identified in the MHC region) and the effects of cannabis in its associated cognitive impairment (cannabis sensitivity associated COMT genotypes). By reviewing the common clinical features of Noonan, Costello, and cardio-facial cutaneous syndromes, caused by perturbation of the RAS MAP kinase signalling pathway, we are reminded that we can't understand complex phenotypes without considering how individual proteins function in (networks of) biochemical pathways. This book provided a deeply satisfying read for the human genetics geek who does not get out of her own narrow research niche nearly often enough. But it is quite dry in places and would be a challenge for the novice. The book has a narrative within and between chapters but the story is far from explicit and may have benefited from more signposting and figures with detailed legends; for example, a diagram of the RAS MAP kinase pathway would have been helpful in chapter 10. Perhaps the paucity of emphatic conclusions in this book was deliberate, to illustrate the fact that functional genomics has not yet come of age? The new generation of GWAS, the rapid pace of eQTL (expression quantitative trait loci) mapping and metabolomics, together with the launch of the Human Proteome Project all suggest that a detailed understanding of the relationships between our genomes, intermediate phenotypes, and disease aetiology is finally within sight▪

Simple and precise targeted editing of the human genome using rAAV-mediated homologous recombination

The rate limiting step in translating normal and pathological human genetic variations into a deeper understanding of which are functionally relevant, and the development of genetically defined disease models that can speed up and rationalize the discovery of novel targeted therapies, now lies firmly with our ability to quickly and precisely alter any sequence in the human genome, just as we have been able to do in mice and other lower organisms for many years. However, routinely altering any user-defined endogenous DNA sequence in somatic human cells has been historically challenging due to their uniformly low levels of homologous recombination. Horizon's GENESIS™ gene-editing platform [http://www.horizondiscovery.com] uses the unique ability of targeted recombinant adeno-associated viral (rAAV) vectors to naturally stimulate and piggyback on the high-fidelity homologous recombination DNA-repair pathway in human cells, without the requirement for eliciting double-stranded DNA breaks using exogenous nucleases, to precisely engineer any DNA variation of choice into any human cell line, including the introduction of subtle point mutations and single nucleotide polymorphisms (SNPs), just as they occur in real patients. The ability to rapidly, accurately and stably engineer human genomes without introducing confounding off-target effects has the potential to transform the field of functional genomics and the design of future targeted, or personalized, therapies. Data will be presented highlighting the use of GENESIS to create genetically defined 'X-MAN' (gene X, mutant and normal) human isogenic cell-line pairs, which accurately model specific genetic variations present in a defined cancer patient population, and provide a matched normal genetic background for reference, in key application areas. First, defining the core phenotype driven by specific cancer genes; second, profiling the activity and therapeutic window of novel cancer therapies on specific target patient genotypes; third, systematically de-orphaning the cancer genome with next-generation'synthetically lethal'drug targets by combining with RNA interference and chemical genomics tools; and fourth, their use as gold-standard genomic reference materials for benchmarking molecular diagnostic assays and platforms.

Transcriptional Network Structure Assessment Via the Data Processing Inequality

Whole genome transcriptional regulation involves an enormous number of physicochemical processes re- sponsible for phenotypic variability and organismal function. The actual mechanisms of regulation are only partially under- stood. In this sense, an extremely important conundrum is related with the probabilistic inference of gene regulatory net- works. A plethora of different methods and algorithms exists. Many of these algorithms are inspired in statistical mechanics and rely on information theoretical grounds. However, an important shortcoming of most of these methods, when it comes to deconvolute the actual, functional structure of gene regulatory networks lies in the presence of indirect interactions. We present a proposal to discover and assess for such indirect interactions within the framework of information theory by means of the data processing inequality. We also present some actual examples of the applicability of the method in several instances in the field of functional genomics.