Comparative genomics of archaea: how much have we learned in six years,and what's next?

Archaea comprise one of the three distinct domains of life (with bacteria and eukaryotes). With 16 complete archaeal genomes sequenced to date, comparative genomics has revealed a conserved core of 313 genes that are represented in all sequenced archaeal genomes, plus a variable 'shell' that is prone to lineage-specific gene loss and horizontal gene exchange. The majority of archaeal genes have not been experimentally characterized, but novel functional pathways have been predicted.     

Genomics and early cellular evolution. The origin of the DNA world.

The sequencing of several genomes from each of the three domains of life (Archaea, Bacteria and Eukarya) has provided a huge amount of data that can be used to gain insight about early cellular evolution. Some features of the universal tree of life based on rRNA polygenies have been confirmed, such as the division of the cellular living world into three domains. The monophyly of each domain is supported by comparative genomics. However, the hyperthermophilic nature of the 'last universal common ancestor' (LUCA) is not confirmed. Comparative genomics has revealed that gene transfers have been (and still are) very frequent in genome evolution. Nevertheless, a core of informational genes appears more resistant to transfer, testifying for a close relationship between archaeal and eukaryal informational processes. This observation can be explained either by a common unique history between Archaea and Eukarya or by an atypical evolution of these systems in Bacteria. At the moment, comparative genomics still does not allow to choose between a simple LUCA, possibly with an RNA genome, or a complex LUCA, with a DNA genome and informational mechanisms similar to those of Archaea and Eukarya. Further comparative studies on informational mechanisms in the three domains should help to resolve this critical question. The role of viruses in the origin and evolution of DNA genomes also appears an area worth of active investigations. I suggest here that DNA and DNA replication mechanisms appeared first in the virus world before being transferred into cellular organisms.     

Phylogenomics of prokaryotic ribosomal proteins

Archaeal and bacterial ribosomes contain more than 50 proteins, including 34 that are universally conserved in the three domains of cellular life (bacteria, archaea, and eukaryotes). Despite the high sequence conservation, annotation of ribosomal (r-) protein genes is often difficult because of their short lengths and biased sequence composition. We developed an automated computational pipeline for identification of r-protein genes and applied it to 995 completely sequenced bacterial and 87 archaeal genomes available in the RefSeq database. The pipeline employs curated seed alignments of r-proteins to run position-specific scoring matrix (PSSM)-based BLAST searches against six-frame genome translations, mitigating possible gene annotation errors. As a result of this analysis, we performed a census of prokaryotic r-protein complements, enumerated missing and paralogous r-proteins, and analyzed the distributions of ribosomal protein genes among chromosomal partitions. Phyletic patterns of bacterial and archaeal r-protein genes were mapped to phylogenetic trees reconstructed from concatenated alignments of r-proteins to reveal the history of likely multiple independent gains and losses. These alignments, available for download, can be used as search profiles to improve genome annotation of r-proteins and for further comparative genomics studies.     

The convergence of haemodynamics,genomics, and endothelial structure in studies of the focal origin of atherosclerosis

The completion of the Human Genome Project and ongoing sequencing of mouse, rat and other genomes has led to an explosion of genetics-related technologies that are finding their way into all areas of biological research; the field of biorheology is no exception. Here we outline how two disparate modern molecular techniques, microarray analyses of gene expression and real-time spatial imaging of living cell structures, are being utilized in studies of endothelial mechanotransduction associated with controlled shear stress in vitro and haemodynamics in vivo. We emphasize the value of such techniques as components of an integrated understanding of vascular rheology. In mechanotransduction, a systems approach is recommended that encompasses fluid dynamics, cell biomechanics, live cell imaging, and the biochemical, cell biology and molecular biology methods that now encompass genomics. Microarrays are a useful and powerful tool for such integration by identifying simultaneous changes in the expression of many genes associated with interconnecting mechanoresponsive cellular pathways.     

三维基因组学研究进展

三维基因组学是一门研究基因组三维空间结构与功能的新兴学科,主要研究基因组序列在细胞核内的三维空间构象,及其对DNA复制、DNA重组、基因表达调控等生物过程的生物学效应。自染色质构象捕获技术(3C)出现后,三维基因组学相关研究领域飞速发展。借助于3C及其衍生技术、Hi-C和ChIA-PET等技术,科学家能对各类物种的三维基因组进行更为深入的研究,从而揭示微生物、植物和动物基因组的空间构象、染色质的相互作用模式、转录调控以及不同生物学性状的形成机制;挖掘与生命活动和疾病相关的关键基因和信号通路;推动农业科学、生命科学和医学等领域的快速发展。文中就三维基因组学研究进展作一综述,主要阐述三维基因组学的概念和研究技术的发展及其在农业科学、生命科学和医学等领域的应用,尤其是肿瘤领域所取得的阶段性研究成果。     

Progress of structural genomics initiatives: an analysis of solved target structures

The explosion in gene sequence data and technological breakthroughs in protein structure determination inspired the launch of structural genomics (SG) initiatives. An often stated goal of structural genomics is the high-throughput structural characterisation of all protein sequence families, with the long-term hope of significantly impacting on the life sciences, biotechnology and drug discovery. Here, we present a comprehensive analysis of solved SG targets to assess progress of these initiatives. Eleven consortia have contributed 316 non-redundant entries and 323 protein chains to the Protein Data Bank (PDB), and 459 and 393 domains to the CATH and SCOP structure classifications, respectively. The quality and size of these proteins are comparable to those solved in traditional structural biology and, despite huge scope for duplicated efforts, only 14% of targets have a close homologue (>/=30% sequence identity) solved by another consortium. Analysis of CATH and SCOP revealed the significant contribution that structural genomics is making to the coverage of superfamilies and folds. A total of 67% of SG domains in CATH are unique, lacking an already characterised close homologue in the PDB, whereas only 21% of non-SG domains are unique. For 29% of domains, structure determination revealed a remote evolutionary relationship not apparent from sequence, and 19% and 11% contributed new superfamilies and folds. The secondary structure class, fold and superfamily distributions of this dataset reflect those of the genomes. The domains fall into 172 different folds and 259 superfamilies in CATH but the distribution is highly skewed. The most populous of these are those that recur most frequently in the genomes. Whilst 11% of superfamilies are bacteria-specific, most are common to all three superkingdoms of life and together the 316 PDB entries have provided new and reliable homology models for 9287 non-redundant gene sequences in 206 completely sequenced genomes. From the perspective of this analysis, it appears that structural genomics is on track to be a success, and it is hoped that this work will inform future directions of the field.     

Global strategies to integrate the proteome and metabolome

A fundamental goal of proteomics is to assign physiological functions to all proteins encoded by eukaryotic and prokaryotic genomes. Of the many activities performed by proteins, the chemical transformations catalyzed by enzymes form the basis for most, if not all, metabolic and signaling pathways. Elucidation of these pathways and their integration into larger cellular networks require new strategies to rapidly and systematically identify physiological substrates of enzymes. Here, we review emerging technologies that aim to assign endogenous biochemical functions to enzymes by profiling the metabolome.     

Genetical genomics: the added value from segregation.

The recent successes of genome-wide expression profiling in biology tend to overlook the power of genetics. We here propose a merger of genomics and genetics into 'genetical genomics'. This involves expression profiling and marker-based fingerprinting of each individual of a segregating population, and exploits all the statistical tools used in the analysis of quantitative trait loci. Genetical genomics will combine the power of two different worlds in a way that is likely to become instrumental in the further unravelling of metabolic, regulatory and developmental pathways.     

Bacterial genomics: the use of DNA microarrays and bacterial artificial chromosomes

Immense amounts of genetic information are contained within microbial genomes. As the number of completely sequenced microbial genomes is increasing, functional and comparative genomic techniques will be employed for sequence analysis and gene characterization. Sequence comparison and expression profiling by DNA microarrays can determine phylogenetic relationships and identify genes while bacterial artificial chromosomes (BACs) allow the study of entire biochemical pathways and permit the expression of bacterial genes in a foreign host.     

Optimal design of genetic studies of gene expression with two-color microarrays in outbred crosses

Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the “distant pair design” maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the “optimal pair design,” for use with F₂ crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance.     

Data merging for integrated microarray and proteomic analysis.

The functioning of even a simple biological system is much more complicated than the sum of its genes, proteins and metabolites. A premise of systems biology is that molecular profiling will facilitate the discovery and characterization of important disease pathways. However, as multiple levels of effector pathway regulation appear to be the norm rather than the exception, a significant challenge presented by high-throughput genomics and proteomics technologies is the extraction of the biological implications of complex data. Thus, integration of heterogeneous types of data generated from diverse global technology platforms represents the first challenge in developing the necessary foundational databases needed for predictive modelling of cell and tissue responses. Given the apparent difficulty in defining the correspondence between gene expression and protein abundance measured in several systems to date, how do we make sense of these data and design the next experiment? In this review, we highlight current approaches and challenges associated with integration and analysis of heterogeneous data sets, focusing on global analysis obtained from high-throughput technologies.     

Dissecting plant genomes with the PLAZA comparative genomics platform

With the arrival of low-cost, next-generation sequencing, a multitude of new plant genomes are being publicly released, providing unseen opportunities and challenges for comparative genomics studies. Here, we present PLAZA 2.5, a user-friendly online research environment to explore genomic information from different plants. This new release features updates to previous genome annotations and a substantial number of newly available plant genomes as well as various new interactive tools and visualizations. Currently, PLAZA hosts 25 organisms covering a broad taxonomic range, including 13 eudicots, five monocots, one lycopod, one moss, and five algae. The available data consist of structural and functional gene annotations, homologous gene families, multiple sequence alignments, phylogenetic trees, and colinear regions within and between species. A new Integrative Orthology Viewer, combining information from different orthology prediction methodologies, was developed to efficiently investigate complex orthology relationships. Cross-species expression analysis revealed that the integration of complementary data types extended the scope of complex orthology relationships, especially between more distantly related species. Finally, based on phylogenetic profiling, we propose a set of core gene families within the green plant lineage that will be instrumental to assess the gene space of draft or newly sequenced plant genomes during the assembly or annotation phase.     

Expression and genomic profiling of colorectal cancer

Colorectal cancer still represents a paradigm for the elucidation of the cellular, genetic and molecular mechanisms that underly solid tumor initiation, progression to malignancy, and metastasis to distal organ sites. The relative ease with which pathological specimens can be obtained by either surgery or endoscopy from different stages of tumor progression has facilitated the application of omics technologies to allow the genome-wide analysis both at the RNA (gene expression) and DNA (aneuploidy) levels. Here, we have reviewed the multiplicity of studies appeared to date in the scientific literature on the expression and genomic analysis of colorectal cancer, and attempted an integration of the profiling data generated and made available in the public domain. This approach is likely to pinpoint specific chromosomal loci and the corresponding genes which (i) play rate-limiting roles in colorectal cancer, (ii) represent putative diagnostic and prognostic markers for the accurate prediction of clinical outcome and response to treatment, and (iii) encompass potential therapeutic targets. Moreover, cross-species data mining and integration of the human colorectal cancer profiles with those obtained from mouse models of intestinal tumorigenesis will even more contribute to the elucidation of highly conserved pathways and cellular functions underlying malignancy in the GI tract. Notwithstanding the above promises, tumor heterogeneity, limited cohort sizes, and methodological differences among experimental and bioinformatic approaches still poses main obstacles towards the optimal utilization and integration of omics profiles.     

Bioinformatics in microbial biotechnology – a mini review

The revolutionary growth in the computation speed and memory storage capability has fueled a new era in the analysis of biological data. Hundreds of microbial genomes and many eukaryotic genomes including a cleaner draft of human genome have been sequenced raising the expectation of better control of microorganisms. The goals are as lofty as the development of rational drugs and antimicrobial agents, development of new enhanced bacterial strains for bioremediation and pollution control, development of better and easy to administer vaccines, the development of protein biomarkers for various bacterial diseases, and better understanding of host-bacteria interaction to prevent bacterial infections. In the last decade the development of many new bioinformatics techniques and integrated databases has facilitated the realization of these goals. Current research in bioinformatics can be classified into: (i) genomics – sequencing and comparative study of genomes to identify gene and genome functionality, (ii) proteomics – identification and characterization of protein related properties and reconstruction of metabolic and regulatory pathways, (iii) cell visualization and simulation to study and model cell behavior, and (iv) application to the development of drugs and anti-microbial agents. In this article, we will focus on the techniques and their limitations in genomics and proteomics. Bioinformatics research can be classified under three major approaches: (1) analysis based upon the available experimental wet-lab data, (2) the use of mathematical modeling to derive new information, and (3) an integrated approach that integrates search techniques with mathematical modeling. The major impact of bioinformatics research has been to automate the genome sequencing, automated development of integrated genomics and proteomics databases, automated genome comparisons to identify the genome function, automated derivation of metabolic pathways, gene expression analysis to derive regulatory pathways, the development of statistical techniques, clustering techniques and data mining techniques to derive protein-protein and protein-DNA interactions, and modeling of 3D structure of proteins and 3D docking between proteins and biochemicals for rational drug design, difference analysis between pathogenic and non-pathogenic strains to identify candidate genes for vaccines and anti-microbial agents, and the whole genome comparison to understand the microbial evolution. The development of bioinformatics techniques has enhanced the pace of biological discovery by automated analysis of large number of microbial genomes. We are on the verge of using all this knowledge to understand cellular mechanisms at the systemic level. The developed bioinformatics techniques have potential to facilitate (i) the discovery of causes of diseases, (ii) vaccine and rational drug design, and (iii) improved cost effective agents for bioremediation by pruning out the dead ends. Despite the fast paced global effort, the current analysis is limited by the lack of available gene-functionality from the wet-lab data, the lack of computer algorithms to explore vast amount of data with unknown functionality, limited availability of protein-protein and protein-DNA interactions, and the lack of knowledge of temporal and transient behavior of genes and pathways.