Showing papers on "Functional genomics published in 2006"

Global landscape of protein complexes in the yeast Saccharomyces cerevisiae

Abstract: Identification of protein-protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization-time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein-protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein-protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.

Proteome survey reveals modularity of the yeast cell machinery

Abstract: Protein complexes are key molecular entities that integrate multiple gene products to perform cellular functions. Here we report the first genome-wide screen for complexes in an organism, budding yeast, using affinity purification and mass spectrometry. Through systematic tagging of open reading frames (ORFs), the majority of complexes were purified several times, suggesting screen saturation. The richness of the data set enabled a de novo characterization of the composition and organization of the cellular machinery. The ensemble of cellular proteins partitions into 491 complexes, of which 257 are novel, that differentially combine with additional attachment proteins or protein modules to enable a diversification of potential functions. Support for this modular organization of the proteome comes from integration with available data on expression, localization, function, evolutionary conservation, protein structure and binary interactions. This study provides the largest collection of physically determined eukaryotic cellular machines so far and a platform for biological data integration and modelling.

Gateway-compatible vectors for plant functional genomics and proteomics.

Abstract: *Summary Gateway cloning technology facilitates high-throughput cloning of target sequences by making use of the bacteriophage lambda site-specific recombination system. Target sequences are first captured in a commercially available ‘entry vector’ and are then recombined into various ‘destination vectors’ for expression in different experimental organisms. Gateway technology has been embraced by a number of plant laboratories that have engineered destination vectors for promoter specificity analyses, protein localization studies, protein/protein interaction studies, constitutive or inducible protein expression studies, gene knockdown by RNA interference, or affinity purification experiments. We review the various types of Gateway destination vectors that are currently available to the plant research community and provide links and references to enable additional information to be obtained concerning these vectors. We also describe a set of ‘pEarleyGate’ plasmid vectors for Agrobacterium-mediated plant transformation that translationally fuse FLAG, HA, cMyc, AcV5 or tandem affinity purification epitope tags onto target proteins, with or without an adjacent fluorescent protein. The oligopeptide epitope tags allow the affinity purification, immunolocalization or immunoprecipitation of recombinant proteins expressed in vivo. We demonstrate the utility of pEarleyGate destination vectors for the expression of epitope-tagged proteins that can be affinity captured or localized by immunofluorescence microscopy. Antibodies detecting the FLAG, HA, cMyc and AcV5 tags show relatively little cross-reaction with endogenous proteins in a variety of monocotyledonous and dicotyledonous plants, suggesting broad utility for the tags and vectors.

Met-regulated expression signature defines a subset of human hepatocellular carcinomas with poor prognosis and aggressive phenotype

Abstract: Identification of specific gene expression signatures characteristic of oncogenic pathways is an important step toward molecular classification of human malignancies. Aberrant activation of the Met signaling pathway is frequently associated with tumor progression and metastasis. In this study, we defined the Met-dependent gene expression signature using global gene expression profiling of WT and Met-deficient primary mouse hepatocytes. Newly identified transcriptional targets of the Met pathway included genes involved in the regulation of oxidative stress responses as well as cell motility, cytoskeletal organization, and angiogenesis. To assess the importance of a Met-regulated gene expression signature, a comparative functional genomic approach was applied to 242 human hepatocellular carcinomas (HCCs) and 7 metastatic liver lesions. Cluster analysis revealed that a subset of human HCCs and all liver metastases shared the Met-induced expression signature. Furthermore, the presence of the Met signature showed significant correlation with increased vascular invasion rate and microvessel density as well as with decreased mean survival time of HCC patients. We conclude that the genetically defined gene expression signatures in combination with comparative functional genomics constitute an attractive paradigm for defining both the function of oncogenic pathways and the clinically relevant subgroups of human cancers.

Functional genomics reveals genes involved in protein secretion and Golgi organization

Abstract: Yeast genetics and in vitro biochemical analysis have identified numerous genes involved in protein secretion1,2. As compared with yeast, however, the metazoan secretory pathway is more complex and many mechanisms that regulate organization of the Golgi apparatus remain poorly characterized. We performed a genome-wide RNA-mediated interference screen in a Drosophila cell line to identify genes required for constitutive protein secretion. We then classified the genes on the basis of the effect of their depletion on organization of the Golgi membranes. Here we show that depletion of class A genes redistributes Golgi membranes into the endoplasmic reticulum, depletion of class B genes leads to Golgi fragmentation, depletion of class C genes leads to aggregation of Golgi membranes, and depletion of class D genes causes no obvious change. Of the 20 new gene products characterized so far, several localize to the Golgi membranes and the endoplasmic reticulum.

Short hairpin RNA–expressing bacteria elicit RNA interference in mammals

Abstract: RNA-interference (RNAi) is a potent mechanism, conserved from plants to humans for specific silencing of genes, which holds promise for functional genomics and gene-targeted therapies. Here we show that bacteria engineered to produce a short hairpin RNA (shRNA) targeting a mammalian gene induce trans-kingdom RNAi in vitro and in vivo. Nonpathogenic Escherichia coli were engineered to transcribe shRNAs from a plasmid containing the invasin gene Inv and the listeriolysin O gene HlyA, which encode two bacterial factors needed for successful transfer of the shRNAs into mammalian cells. Upon oral or intravenous administration, E. coli encoding shRNA against CTNNB1 (catenin beta-1) induce significant gene silencing in the intestinal epithelium and in human colon cancer xenografts in mice. These results provide an example of trans-kingdom RNAi in higher organisms and suggest the potential of bacteria-mediated RNAi for functional genomics, therapeutic target validation and development of clinically compatible RNAi-based therapies.

AgBase: a functional genomics resource for agriculture

Abstract: Background: Many agricultural species and their pathogens have sequenced genomes and more are in progress. Agricultural species provide food, fiber, xenotransplant tissues, biopharmaceuticals and biomedical models. Moreover, many agricultural microorganisms are human zoonoses. However, systems biology from functional genomics data is hindered in agricultural species because agricultural genome sequences have relatively poor structural and functional annotation and agricultural research communities are smaller with limited funding compared to many model organism communities. Description: To facilitate systems biology in these traditionally agricultural species we have established "AgBase", a curated, web-accessible, public resource http://www.agbase.msstate.edu for structural and functional annotation of agricultural genomes. The AgBase database includes a suite of computational tools to use GO annotations. We use standardized nomenclature following the Human Genome Organization Gene Nomenclature guidelines and are currently functionally annotating chicken, cow and sheep gene products using the Gene Ontology (GO). The computational tools we have developed accept and batch process data derived from different public databases (with different accession codes), return all existing GO annotations, provide a list of products without GO annotation, identify potential orthologs, model functional genomics data using GO and assist proteomics analysis of ESTs and EST assemblies. Our journal database helps prevent redundant manual GO curation. We encourage and publicly acknowledge GO annotations from researchers and provide a service for researchers interested in GO and analysis of functional genomics data. Conclusion: The AgBase database is the first database dedicated to functional genomics and systems biology analysis for agriculturally important species and their pathogens. We use experimental data to improve structural annotation of genomes and to functionally characterize gene products. AgBase is also directly relevant for researchers in fields as diverse as agricultural production, cancer biology, biopharmaceuticals, human health and evolutionary biology. Moreover, the experimental methods and bioinformatics tools we provide are widely applicable to many other species including model organisms.

Genome-wide prediction of C. elegans genetic interactions.

Abstract: To obtain a global view of functional interactions among genes in a metazoan genome, we computationally integrated interactome data, gene expression data, phenotype data, and functional annotation data from three model organisms—Saccharomyces cerevisiae, Caenorhabditis elegans, and Drosophila melanogaster—and predicted genome-wide genetic interactions in C. elegans. The resulting genetic interaction network (consisting of 18,183 interactions) provides a framework for system-level understanding of gene functions. We experimentally tested the predicted interactions for two human disease-related genes and identified 14 new modifiers.

Genomic and functional evolution of the Drosophila melanogaster sperm proteome

Abstract: In addition to delivering a haploid genome to the egg, sperm have additional critical functions, including egg activation, origination of the zygote centrosome and delivery of paternal factors. Despite this, existing knowledge of the molecular basis of sperm form and function is limited. We used whole-sperm mass spectrometry to identify 381 proteins of the Drosophila melanogaster sperm proteome (DmSP). This approach identified mitochondrial, metabolic and cytoskeletal proteins, in addition to several new functional categories. We also observed nonrandom genomic clustering of sperm genes and underrepresentation on the X chromosome. Identification of widespread functional constraint on the proteome indicates that sexual selection has had a limited role in the overall evolution of D. melanogaster sperm. The relevance of the DmSP to the study of mammalian sperm function and fertilization mechanisms is demonstrated by the identification of substantial homology between the DmSP and proteins of the mouse axoneme accessory structure.

Analyses of Expressed Sequence Tags from Apple

Abstract: The domestic apple (Malus domestica; also known as Malus pumila Mill.) has become a model fruit crop in which to study commercial traits such as disease and pest resistance, grafting, and flavor and health compound biosynthesis. To speed the discovery of genes involved in these traits, develop markers to map genes, and breed new cultivars, we have produced a substantial expressed sequence tag collection from various tissues of apple, focusing on fruit tissues of the cultivar Royal Gala. Over 150,000 expressed sequence tags have been collected from 43 different cDNA libraries representing 34 different tissues and treatments. Clustering of these sequences results in a set of 42,938 nonredundant sequences comprising 17,460 tentative contigs and 25,478 singletons, together representing what we predict are approximately one-half the expressed genes from apple. Many potential molecular markers are abundant in the apple transcripts. Dinucleotide repeats are found in 4,018 nonredundant sequences, mainly in the 5'-untranslated region of the gene, with a bias toward one repeat type (containing AG, 88%) and against another (repeats containing CG, 0.1%). Trinucleotide repeats are most common in the predicted coding regions and do not show a similar degree of sequence bias in their representation. Bi-allelic single-nucleotide polymorphisms are highly abundant with one found, on average, every 706 bp of transcribed DNA. Predictions of the numbers of representatives from protein families indicate the presence of many genes involved in disease resistance and the biosynthesis of flavor and health-associated compounds. Comparisons of some of these gene families with Arabidopsis (Arabidopsis thaliana) suggest instances where there have been duplications in the lineages leading to apple of biosynthetic and regulatory genes that are expressed in fruit. This resource paves the way for a concerted functional genomics effort in this important temperate fruit crop.

Chance and necessity in the evolution of minimal metabolic networks

Abstract: It is common enough to read a paper that uses genome-sequence data to make conclusions about how an organism lives. Less common is the approach used by Pal et al. who have generated gene networks for a group of related organisms with similar lifestyles, and used those to infer gene content of another member of the group. With the genome of E. coli as starting point, they predicted the metabolism of Buchnera, an intracellular symbiont with a heavily reduced genome, that was derived from an ancestor of E. coli. This work has implications for the search for a ‘minimal genome’, and already indicates that the concept of a ‘non-essential gene’ can be spurious, as a gene can easily become essential in changing genomic contexts. Rather than using genome sequence data to make conclusions about how an organism lives, the reverse approach can be adopted — using gene networks generated for a group of related organisms with similar lifestyles to infer the gene content of another member of the group. It is possible to infer aspects of an organism's lifestyle from its gene content1. Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.

The e3 ubiquitin ligase gene family in plants: regulation by degradation.

Abstract: The regulation of protein expression and activity has been for long time considered only in terms of transcription/translation efficiency. In the last years, the discovery of post-transcriptional and post-translational regulation mechanisms pointed out that the key factor in determining transcript/protein amount is the synthesis/degradation ratio, together with post-translational modifications of proteins. Polyubiquitinaytion marks target proteins directed to degradation mediated by 26S-proteasome. Recent functional genomics studies pointed out that about 5% of Arabidopsis genome codes for proteins of ubiquitination pathway. The most of them (more than one thousand genes) correspond to E3 ubiquitin ligases that specifically recognise target proteins. The huge size of this gene family, whose members are involved in regulation of a number of biological processes including hormonal control of vegetative growth, plant reproduction, light response, biotic and abiotic stress tolerance and DNA repair, indicates a major role for protein degradation in control of plant life.

Plant cell wall biosynthesis: genetic, biochemical and functional genomics approaches to the identification of key genes.

Abstract: Cell walls are dynamic structures that represent key determinants of overall plant form, plant growth and development, and the responses of plants to environmental and pathogen-induced stresses. Walls play centrally important roles in the quality and processing of plant-based foods for both human and animal consumption, and in the production of fibres during pulp and paper manufacture. In the future, wall material that constitutes the major proportion of cereal straws and other crop residues will find increasing application as a source of renewable fuel and composite manufacture. Although the chemical structures of most wall constituents have been defined in detail, the enzymes involved in their synthesis and remodelling remain largely undefined, particularly those involved in polysaccharide biosynthesis. There have been real recent advances in our understanding of cellulose biosynthesis in plants, but, with few exceptions, the identities and modes of action of polysaccharide synthases and other glycosyltransferases that mediate the biosynthesis of the major non-cellulosic wall polysaccharides are not known. Nevertheless, emerging functional genomics and molecular genetics technologies are now allowing us to re-examine the central questions related to wall biosynthesis. The availability of the rice, Populus trichocarpa and Arabidopsis genome sequences, a variety of mutant populations, high-density genetic maps for cereals and other industrially important plants, high-throughput genome and transcript analysis systems, extensive publicly available genomics resources and an increasing armoury of analysis systems for the definition of candidate gene function will together allow us to take a systems approach to the description of wall biosynthesis in plants.

Forest-tree population genomics and adaptive evolution.

Abstract: Forest trees have gained much attention in recent years as nonclassical model eukaryotes for population, evolutionary and ecological genomic studies. Because of low domestication, large open-pollinated native populations, and high levels of both genetic and phenotypic variation, they are ideal organisms to unveil the molecular basis of population adaptive divergence in nature. Population genomics, in its broad-sense definition, is an emerging discipline that combines genome-wide sampling with traditional population genetic approaches to understanding evolution. Here we briefly review traditional methods of studying adaptive genetic variation in forest trees, and describe a new, integrated population genomics approach. First, alleles (haplotypes) at candidate genes for adaptive traits and their effects on phenotypes need to be characterized via sequencing and association mapping. At this stage, functional genomics can assist in understanding gene action and regulation by providing detailed transcriptional profiles. Second, frequencies of alleles in native populations for causative single-nucleotide polymorphisms are estimated to identify patterns of adaptive variation across heterogeneous environments. Population genomics, through deciphering allelic effects on phenotypes and identifying patterns of adaptive variation at the landscape level, will in the future constitute a useful tool, if cost-effective, to design conservation strategies for forest trees.

A recombineering pipeline for functional genomics applied to Caenorhabditis elegans

Abstract: We present a new concept in DNA engineering based on a pipeline of serial recombineering steps in liquid culture. This approach is fast, straightforward and facilitates simultaneous processing of multiple samples in parallel. We validated the approach by generating green fluorescent protein (GFP)-tagged transgenes from Caenorhabditis briggsae genomic clones in a multistep pipeline that takes only 4 d. The transgenes were engineered with minimal disturbance to the natural genomic context so that the correct level and pattern of expression will be secured after transgenesis. An example transgene for the C. briggsae ortholog of lin-59 was used for ballistic transformation in Caenorhabditis elegans. We show that the cross-species transgene is correctly expressed and rescues RNA interference (RNAi)-mediated knockdown of the endogenous C. elegans gene. The strategy that we describe adapts the power of recombineering in Escherichia coli for fluent DNA engineering to a format that can be directly scaled up for genomic projects.

Reverse Engineering the Gap Gene Network of Drosophila melanogaster

Abstract: A fundamental problem in functional genomics is to determine the structure and dynamics of genetic networks based on expression data. We describe a new strategy for solving this problem and apply it to recently published data on early Drosophila melanogaster development. Our method is orders of magnitude faster than current fitting methods and allows us to fit different types of rules for expressing regulatory relationships. Specifically, we use our approach to fit models using a smooth nonlinear formalism for modeling gene regulation (gene circuits) as well as models using logical rules based on activation and repression thresholds for transcription factors. Our technique also allows us to infer regulatory relationships de novo or to test network structures suggested by the literature. We fit a series of models to test several outstanding questions about gap gene regulation, including regulation of and by hunchback and the role of autoactivation. Based on our modeling results and validation against the experimental literature, we propose a revised network structure for the gap gene system. Interestingly, some relationships in standard textbook models of gap gene regulation appear to be unnecessary for or even inconsistent with the details of gap gene expression during wild-type development.

Genomics of hybrid poplar (Populus trichocarpa× deltoides) interacting with forest tent caterpillars (Malacosoma disstria): normalized and full‐length cDNA libraries, expressed sequence tags, and a cDNA microarray for the study of insect‐induced defences in poplar

Abstract: As part of a genomics strategy to characterize inducible defences against insect herbivory in poplar, we developed a comprehensive suite of functional genomics resources including cDNA libraries, expressed sequence tags (ESTs) and a cDNA microarray platform. These resources are designed to complement the existing poplar genome sequence and poplar (Populus spp.) ESTs by focusing on herbivore- and elicitor-treated tissues and incorporating normalization methods to capture rare transcripts. From a set of 15 standard, normalized or full-length cDNA libraries, we generated 139,007 3'- or 5'-end sequenced ESTs, representing more than one-third of the c. 385,000 publicly available Populus ESTs. Clustering and assembly of 107,519 3'-end ESTs resulted in 14,451 contigs and 20,560 singletons, altogether representing 35,011 putative unique transcripts, or potentially more than three-quarters of the predicted c. 45,000 genes in the poplar genome. Using this EST resource, we developed a cDNA microarray containing 15,496 unique genes, which was utilized to monitor gene expression in poplar leaves in response to herbivory by forest tent caterpillars (Malacosoma disstria). After 24 h of feeding, 1191 genes were classified as up-regulated, compared to only 537 down-regulated. Functional classification of this induced gene set revealed genes with roles in plant defence (e.g. endochitinases, Kunitz protease inhibitors), octadecanoid and ethylene signalling (e.g. lipoxygenase, allene oxide synthase, 1-aminocyclopropane-1-carboxylate oxidase), transport (e.g. ABC proteins, calreticulin), secondary metabolism [e.g. polyphenol oxidase, isoflavone reductase, (-)-germacrene D synthase] and transcriptional regulation [e.g. leucine-rich repeat transmembrane kinase, several transcription factor classes (zinc finger C3H type, AP2/EREBP, WRKY, bHLH)]. This study provides the first genome-scale approach to characterize insect-induced defences in a woody perennial providing a solid platform for functional investigation of plant-insect interactions in poplar.

RNA interference-based gene silencing as an efficient tool for functional genomics in hexaploid bread wheat.

Abstract: Insertional mutagenesis and gene silencing are efficient tools for the determination of gene function. In contrast to gain- or loss-of-function approaches, RNA interference (RNAi)-induced gene silencing can possibly silence multigene families and homoeologous genes in polyploids. This is of great importance for functional studies in hexaploid wheat (Triticum aestivum), where most of the genes are present in at least three homoeologous copies and conventional insertional mutagenesis is not effective. We have introduced into bread wheat double-stranded RNA-expressing constructs containing fragments of genes encoding Phytoene Desaturase (PDS) or the signal transducer of ethylene, Ethylene Insensitive 2 (EIN2). Transformed plants showed phenotypic changes that were stably inherited over at least two generations. These changes were very similar to mutant phenotypes of the two genes in diploid model plants. Quantitative real-time polymerase chain reaction revealed a good correlation between decreasing mRNA levels and increasingly severe phenotypes. RNAi silencing had the same quantitative effect on all three homoeologous genes. The most severe phenotypes were observed in homozygous plants that showed the strongest mRNA reduction and, interestingly, produced around 2-fold the amount of small RNAs compared to heterozygous plants. This suggests that the effect of RNAi in hexaploid wheat is gene-dosage dependent. Wheat seedlings with low mRNA levels for EIN2 were ethylene insensitive. Thus, EIN2 is a positive regulator of the ethylene-signaling pathway in wheat, very similar to its homologs in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa). Our data show that RNAi results in stably inherited phenotypes and therefore represents an efficient tool for functional genomic studies in polyploid wheat.

Approaches to functional genomics in filamentous fungi.

Abstract: The study of gene function in filamentous fungi is a field of research that has made great advances in very recent years. A number of transformation and gene manipulation strategies have been developed and applied to a diverse and rapidly expanding list of economically important filamentous fungi and oomycetes. With the significant number of fungal genomes now sequenced or being sequenced, functional genomics promises to uncover a great deal of new information in coming years. This review discusses recent advances that have been made in examining gene function in filamentous fungi and describes the advantages and limitations of the different approaches.

Comparative genomics reveals what makes an enterobacterial plant pathogen.

Abstract: The bacterial family Enterobacteriaceae contains some of the most devastating human and animal pathogens, including Escherichia coli, Salmonella enterica and species of Yersinia and Shigella. These are among the best-studied of any organisms, yet there is much to be learned about the nature and evolution of interactions with their hosts and with the wider environment. Comparative and functional genomics have fundamentally improved our understanding of their modes of adaptation to different ecological niches and the genes that determine their pathogenicity. In addition to animal pathogens, Enterobacteriaceae include important plant pathogens, such as Erwinia carotovora subsp. atroseptica (Eca), the first plant-pathogenic enterobacterium to be sequenced. This review focuses on genomic comparisons between Eca and other enterobacteria, with particular emphasis on the differences that exemplify or explain the plant-associated lifestyle(s) of Eca. Horizontal gene transfer in Eca may directly have led to the acquisition of a number of determinants that mediate its interactions, pathogenic or otherwise, with plants, offering a glimpse into its evolutionary divergence from animal-pathogenic enterobacteria.

Benchmarking ortholog identification methods using functional genomics data

Abstract: The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.

Functional conservation of MADS-box factors controlling floral organ identity in rice and Arabidopsis

Abstract: Studies on MADS-box genes in Arabidopsis and other higher eudicotyledonous flowering plants have shown that they are key regulators of flower development. Since Arabidopsis and monocotyledonous rice are distantly related plant species it is interesting to investigate whether the floral organ identity factors have been conserved in their functions, and if not, to understand the differences. Arabidopsis and rice are very suitable for these studies since they are both regarded as models for plant functional genomics. Both their genomes are sequenced and tools are available for the analysis of gene function. These developments have accelerated experiments and increased our knowledge on rice gene function. Therefore it is the right moment to perform a comparative analysis on MADS-box factors controlling floral organ identity as reported in this review.

Benchmarking ortholog identification methods using functional genomics data.

Abstract: The transfer of functional annotations from model organism proteins to human proteins is one of the main applications of comparative genomics. Various methods are used to analyze cross-species orthologous relationships according to an operational definition of orthology. Often the definition of orthology is incorrectly interpreted as a prediction of proteins that are functionally equivalent across species, while in fact it only defines the existence of a common ancestor for a gene in different species. However, it has been demonstrated that orthologs often reveal significant functional similarity. Therefore, the quality of the orthology prediction is an important factor in the transfer of functional annotations (and other related information). To identify protein pairs with the highest possible functional similarity, it is important to qualify ortholog identification methods. To measure the similarity in function of proteins from different species we used functional genomics data, such as expression data and protein interaction data. We tested several of the most popular ortholog identification methods. In general, we observed a sensitivity/selectivity trade-off: the functional similarity scores per orthologous pair of sequences become higher when the number of proteins included in the ortholog groups decreases. By combining the sensitivity and the selectivity into an overall score, we show that the InParanoid program is the best ortholog identification method in terms of identifying functionally equivalent proteins.

Global analysis of gene function in yeast by quantitative phenotypic profiling

Abstract: We present a method for the global analysis of the function of genes in budding yeast based on hierarchical clustering of the quantitative sensitivity profiles of the 4756 strains with individual homozygous deletion of nonessential genes to a broad range of cytotoxic or cytostatic agents. This method is superior to other global methods of identifying the function of genes involved in the various DNA repair and damage checkpoint pathways as well as other interrogated functions. Analysis of the phenotypic profiles of the 51 diverse treatments places a total of 860 genes of unknown function in clusters with genes of known function. We demonstrate that this can not only identify the function of unknown genes but can also suggest the mechanism of action of the agents used. This method will be useful when used alone and in conjunction with other global approaches to identify gene function in yeast.

A functional genomics approach to the mode of action of apratoxin A

Abstract: The cyanobacterial metabolite apratoxin A (1) demonstrates potent cytotoxicity against tumor cell lines by a hitherto unknown mechanism. We have used functional genomics to elucidate the molecular basis for this activity. Gene expression profiling and DNA content analysis showed that apratoxin A induces G1-phase cell cycle arrest and apoptosis. Cell-based functional assays with a genome-wide collection of expression cDNAs showed that ectopic induction of fibroblast growth factor receptor (FGFR) signaling attenuates the apoptotic activity of apratoxin A. This natural product inhibited phosphorylation and activation of STAT3, a downstream effector of FGFR signaling. It also caused defects in FGF-dependent processes during zebrafish development, with concomitant reductions in expression levels of the FGF target gene mkp3. We conclude that apratoxin A mediates its antiproliferative activity through the induction of G1 cell cycle arrest and an apoptotic cascade, which is at least partially initiated through antagonism of FGF signaling via STAT3.