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Microarray expression analysis of meiosis and microsporogenesis in hexaploid bread wheat.

BACKGROUND: Our understanding of the mechanisms that govern the cellular process of meiosis is limited in higher plants with polyploid genomes. Bread wheat is an allohexaploid that behaves as a diploid during meiosis. Chromosome pairing is restricted to homologous chromosomes despite the presence of homoeologues in the nucleus. The importance of wheat as a crop and the extensive use of wild wheat relatives in breeding programs has prompted many years of cytogenetic and genetic research to develop an understanding of the control of chromosome pairing and recombination. The rapid advance of biochemical and molecular information on meiosis in model organisms such as yeast provides new opportunities to investigate the molecular basis of chromosome pairing control in wheat. However, building the link between the model and wheat requires points of data contact. RESULTS: We report here a large-scale transcriptomics study using the Affymetrix wheat GeneChip(R) aimed at providing this link between wheat and model systems and at identifying early meiotic genes. Analysis of the microarray data identified 1,350 transcripts temporally-regulated during the early stages of meiosis. Expression profiles with annotated transcript functions including chromatin condensation, synaptonemal complex formation, recombination and fertility were identified. From the 1,350 transcripts, 30 displayed at least an eight-fold expression change between and including pre-meiosis and telophase II, with more than 50% of these having no similarities to known sequences in NCBI and TIGR databases. CONCLUSION: This resource is now available to support research into the molecular basis of pairing and recombination control in the complex polyploid, wheat.

Chromosome Pairing↗

Comprehensive gene expression analysis by transcript profiling.

After the completion of the genomic sequence of Arabidopsis thaliana, it is now a priority to identify all the genes, their patterns of expression and functions. Transcript profiling is playing a substantial role in annotating and determining gene functions, having advanced from one-gene-at-a-time methods to technologies that provide a holistic view of the genome. In this review, comprehensive transcript profiling methodologies are described, including two that are used extensively by the authors, cDNA-AFLP and cDNA microarraying. Both these technologies illustrate the requirement to integrate molecular biology, automation, LIMS and data analysis. With so much uncharted territory in the Arabidopsis genome, and the desire to tackle complex biological traits, such integrated systems will provide a rich source of data for the correlative, functional annotation of genes.

Gene Expression Profiling↗

Rice bioinformatics. analysis of rice sequence data and leveraging the data to other plant species.

Rice (Oryza sativa) is a model species for monocotyledonous plants, especially for members in the grass family. Several attributes such as small genome size, diploid nature, transformability, and establishment of genetic and molecular resources make it a tractable organism for plant biologists. With an estimated genome size of 430 Mb (Arumuganathan and Earle, 1991), it is feasible to obtain the complete genome sequence of rice using current technologies. An international effort has been established and is in the process of sequencing O. sativa spp. japonica var "Nipponbare" using a bacterial artificial chromosome/P1 artificial chromosome shotgun sequencing strategy. Annotation of the rice genome is performed using prediction-based and homology-based searches to identify genes. Annotation tools such as optimized gene prediction programs are being developed for rice to improve the quality of annotation. Resources are also being developed to leverage the rice genome sequence to partial genome projects such as expressed sequence tag projects, thereby maximizing the output from the rice genome project. To provide a low level of annotation for rice genomic sequences, we have aligned all rice bacterial artificial chromosome/P1 artificial chromosome sequences with The Institute of Genomic Research Gene Indices that are a set of nonredundant transcripts that are generated from nine public plant expressed sequence tag projects (rice, wheat, sorghum, maize, barley, Arabidopsis, tomato, potato, and barrel medic). In addition, we have used data from The Institute of Genomic Research Gene Indices and the Arabidopsis and Rice Genome Projects to identify putative orthologues and paralogues among these nine genomes.

Base Sequence↗

De novo Genes in Plants: Origins, Mechanisms, and Functional Implications.

De novo genes originate from previously non-coding genomic regions. They provide an important source of lineage-specific innovation. In plants, these genes may contribute to adaptation, trait diversity and crop evolution. This review summarizes recent progress in plant de novo gene research. It first discusses major routes of gene birth, including transcription-first, open reading frame (ORF)-first and concurrent models. It also examines how nascent loci acquire regulatory control and enter existing biological networks. The review then summarizes their evolutionary features, including weak early constraint, rapid molecular change, restricted expression and structural refinement. It further discusses plant de novo genes involved in stress responses, seed germination, kernel dehydration, subspecies divergence, reproductive isolation and floral scent diversification. Current methods for identifying de novo genes remain limited by rapid sequence evolution, genome annotation quality, polyploidy and transposable elements. Whole-genome synteny alignment, multi-omics evidence and machine-learning approaches can improve candidate discovery. However, each method has important limitations. Finally, this review highlights key future questions in functional validation, latent coding potential in long non-coding RNAs, epigenetic activation, regulatory-network integration and crop improvement. These perspectives clarify how de novo genes shape plant adaptation and how they may be used in precision breeding and synthetic biology.

adaptive evolution↗

PineappleDB: an online pineapple bioinformatics resource.

BACKGROUND: A world first pineapple EST sequencing program has been undertaken to investigate genes expressed during non-climacteric fruit ripening and the nematode-plant interaction during root infection. Very little is known of how non-climacteric fruit ripening is controlled or of the molecular basis of the nematode-plant interaction. PineappleDB was developed to provide the research community with access to a curated bioinformatics resource housing the fruit, root and nematode infected gall expressed sequences. DESCRIPTION: PineappleDB is an online, curated database providing integrated access to annotated expressed sequence tag (EST) data for cDNA clones isolated from pineapple fruit, root, and nematode infected root gall vascular cylinder tissues. The database currently houses over 5600 EST sequences, 3383 contig consensus sequences, and associated bioinformatic data including splice variants, Arabidopsis homologues, both MIPS based and Gene Ontology functional classifications, and clone distributions. The online resource can be searched by text or by BLAST sequence homology. The data outputs provide comprehensive sequence, bioinformatic and functional classification information. CONCLUSION: The online pineapple bioinformatic resource provides the research community with access to pineapple fruit and root/gall sequence and bioinformatic data in a user-friendly format. The search tools enable efficient data mining and present a wide spectrum of bioinformatic and functional classification information. PineappleDB will be of broad appeal to researchers investigating pineapple genetics, non-climacteric fruit ripening, root-knot nematode infection, crassulacean acid metabolism and alternative RNA splicing in plants.

Alternative Splicing↗

Annotating sequence data using Genotator.

In this postgenomic era, it is no longer necessary to argue the need for automated methods for sequence annotation. Many researchers have designed tools for analyzing DNA sequences, but running multiple tools and interpreting the results can be tedious and confusing. In the last few years, many analysis workbenches have been developed to help streamline the process of sequence annotation. Genotator, developed in 1996, is still a popular choice owing to its ease of use and its configurability. This article will review annotating sequence data using the Genotator.

Amino Acid Sequence↗

Large-scale analysis of pseudogenes in the human genome.

Pseudogenes are considered as genomic fossils: disabled copies of functional genes that were once active in the ancient genome. Recently, whole-genome computational approaches have revealed thousands of pseudogenes in the genomes of the human and other eukaryotes. Identification of these pseudogenes can improve the accuracy of gene annotation. It also offers new insight on the evolutionary history and the stability of the genome as a whole.

Amino Acid Sequence↗

Tropinone reductases, enzymes at the branch point of tropane alkaloid metabolism.

Two stereospecific oxidoreductases constitute a branch point in tropane alkaloid metabolism. Products of tropane metabolism are the alkaloids hyoscyamine, scopolamine, cocaine, and polyhydroxylated nortropane alkaloids, the calystegines. Both tropinone reductases reduce the precursor tropinone to yield either tropine or pseudotropine. In Solanaceae, tropine is incorporated into hyoscyamine and scopolamine; pseudotropine is the first specific metabolite on the way to the calystegines. Isolation, cloning and heterologous expression of both tropinone reductases enabled kinetic characterisation, protein crystallisation, and structure elucidation. Stereospecificity of reduction is achieved by binding tropinone in the respective enzyme active centre in opposite orientation. Immunolocalisation of both enzyme proteins in cultured roots revealed a tissue-specific protein accumulation. Metabolite flux through both arms of the tropane alkaloid pathway appears to be regulated by the activity of both enzymes and by their access to the precursor tropinone. Both tropinone reductases are NADPH-dependent short-chain dehydrogenases with amino acid sequence similarity of more than 50% suggesting their descent from a common ancestor. Putative tropinone reductase sequences annotated in plant genomes other that Solanaceae await functional characterisation.

Alcohol Oxidoreductases↗

Phylogeny of related functions: the case of polyamine biosynthetic enzymes.

Genome annotation requires explicit identification of gene function. This task frequently uses protein sequence alignments with examples having a known function. Genetic drift, co-evolution of subunits in protein complexes and a variety of other constraints interfere with the relevance of alignments. Using a specific class of proteins, it is shown that a simple data analysis approach can help solve some of the problems posed. The origin of ureohydrolases has been explored by comparing sequence similarity trees, maximizing amino acid alignment conservation. The trees separate agmatinases from arginases but suggest the presence of unknown biases responsible for unexpected positions of some enzymes. Using factorial correspondence analysis, a distance tree between sequences was established, comparing regions with gaps in the alignments. The gap tree gives a consistent picture of functional kinship, perhaps reflecting some aspects of phylogeny, with a clear domain of enzymes encoding two types of ureohydrolases (agmatinases and arginases) and activities related to, but different from ureohydrolases. Several annotated genes appeared to correspond to a wrong assignment if the trees were significant. They were cloned and their products expressed and identified biochemically. This substantiated the validity of the gap tree. Its organization suggests a very ancient origin of ureohydrolases. Some enzymes of eukaryotic origin are spread throughout the arginase part of the trees: they might have been derived from the genes found in the early symbiotic bacteria that became the organelles. They were transferred to the nucleus when symbiotic genes had to escape Muller's ratchet. This work also shows that arginases and agmatinases share the same two manganese-ion-binding sites and exhibit only subtle differences that can be accounted for knowing the three-dimensional structure of arginases. In the absence of explicit biochemical data, extreme caution is needed when annotating genes having similarities to ureohydrolases.

Amino Acid Sequence↗

Genotator: a workbench for sequence annotation.

Sequencing centers such as the Human Genome Center at LBNL are producing an ever-increasing flood of genetic data. Annotation can greatly enhance the biological value of these sequences. Useful annotations include possible gene locations, homologies to known genes, and gene signal such as promoters and splice sites. Genotator is a workbench for automated sequence annotation and annotation browsing. The back end runs a series of sequence analysis tools on a DNA sequence, handling the various input and output formats required by the tools. Genotator currently runs five different gene-finding programs, three homology searches, and searches for promoters, splice sites, and ORFs. The results of the analyses run by Genotator can be viewed with the interactive graphical browser. The browser displays color-coded sequence annotations on a canvas that can be scrolled and zoomed, allowing the annotated sequence to be explored at multiple levels of detail. The user can view the actual DNA sequence in a separate window; when a region is selected in the map display, it is highlighted automatically in the sequence display, and vice versa. By displaying the output of all of the sequence analyses, Genotator provides an intuitive way to identify the significant regions (for example, probable exons) in a sequence. Users can interactively add personal annotations to label regions of interest. Additional capabilities of Genotator include primer design and pattern searching.

Base Sequence↗

Automatic generation and evaluation of sparse protein signatures for families of protein structural domains.

We identified key residues from the structural alignment of families of protein domains from SCOP which we represented in the form of sparse protein signatures. A signature-generating algorithm (SigGen) was developed and used to automatically identify key residues based on several structural and sequence-based criteria. The capacity of the signatures to detect related sequences from the SWISSPROT database was assessed by receiver operator characteristic (ROC) analysis and jack-knife testing. Test signatures for families from each of the main SCOP classes are described in relation to the quality of the structural alignments, the SigGen parameters used, and their diagnostic performance. We show that automatically generated signatures are potently diagnostic for their family (ROC50 scores typically >0.8), consistently outperform random signatures, and can identify sequence relationships in the "twilight zone" of protein sequence similarity (<40%). Signatures based on 15%-30% of alignment positions occurred most frequently among the best-performing signatures. When alignment quality is poor, sparser signatures perform better, whereas signatures generated from higher-quality alignments of fewer structures require more positions to be diagnostic. Our validation of signatures from the Globin family shows that when sequences from the structural alignment are removed and new signatures generated, the omitted sequences are still detected. The positions highlighted by the signature often correspond (alignment specificity >0.7) to the key positions in the original (non-jack-knifed) alignment. We discuss potential applications of sparse signatures in sequence annotation and homology modeling.

Algorithms↗

Phylogenetic detection of conserved gene clusters in microbial genomes.

BACKGROUND: Microbial genomes contain an abundance of genes with conserved proximity forming clusters on the chromosome. However, the conservation can be a result of many factors such as vertical inheritance, or functional selection. Thus, identification of conserved gene clusters that are under functional selection provides an effective channel for gene annotation, microarray screening, and pathway reconstruction. The problem of devising a robust method to identify these conserved gene clusters and to evaluate the significance of the conservation in multiple genomes has a number of implications for comparative, evolutionary and functional genomics as well as synthetic biology. RESULTS: In this paper we describe a new method for detecting conserved gene clusters that incorporates the information captured by a genome phylogenetic tree. We show that our method can overcome the common problem of overestimation of significance due to the bias in the genome database and thereby achieve better accuracy when detecting functionally connected gene clusters. Our results can be accessed at database GeneChords http://genomics10.bu.edu/GeneChords. CONCLUSION: The methodology described in this paper gives a scalable framework for discovering conserved gene clusters in microbial genomes. It serves as a platform for many other functional genomic analyses in microorganisms, such as operon prediction, regulatory site prediction, functional annotation of genes, evolutionary origin and development of gene clusters.

Algorithms↗

Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs.

BACKGROUND: Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins. RESULTS: "Mixed COGs" of ORFs (clusters in which some sequences correspond to annotated genes and some do not) are attractive targets when seeking errors of gene prediction. Examination of mixed COGs reveals some situations in which genes appear to have been missed in current annotations and a smaller number of regions that appear to have been annotated as gene loci erroneously. This technique can also be used to detect potential pseudogenes or sequencing errors. Our method uses an adjustable parameter for degree of conservation among the studied genomes (stringency). We detail results for one level of stringency at which we found 83 potential genes which had not previously been identified, 60 potential pseudogenes, and 7 sequences with existing gene annotations that are probably incorrect. CONCLUSION: Systematic study of sequence conservation offers a way to improve existing annotations by identifying potentially homologous regions where the annotation of the presence or absence of a gene is inconsistent among genomes.

Algorithms↗

Pilot Anopheles gambiae full-length cDNA study: sequencing and initial characterization of 35,575 clones.

We describe the preliminary analysis of over 35,000 clones from a full-length enriched cDNA library from the malaria mosquito vector Anopheles gambiae. The clones define nearly 3,700 genes, of which around 2,600 significantly improve current gene definitions. An additional 17% of the genes were not previously annotated, suggesting that an equal percentage may be missing from the current Anopheles genome annotation.

Animals↗

Proteome research: complementarity and limitations with respect to the RNA and DNA worlds.

A methodological overview of proteome analysis is provided along with details of efforts to achieve high-throughput screening (HTS) of protein samples derived from two-dimensional electrophoresis gels. For both previously sequenced organisms and those lacking significant DNA sequence information, mass spectrometry has a key role to play in achieving HTS. Prototype robotics designed to conduct appropriate chemistries and deliver 700-1000 protein (genes) per day to batteries of mass spectrometers or liquid chromatography (LC)-based analyses are well advanced, as are efforts to produce high density gridded arrays containing > 1000 proteins on a single matrix assisted laser desorption ionisation/time-of-flight (MALDI-TOF) sample stage. High sensitivity HTS of proteins is proposed by employing principally mass spectrometry in an hierarchical manner: (i) MALDI-TOF-mass spectrometry (MS) on at least 1000 proteins per day; (ii) electrospray ionisation (ESI)/MS/MS for analysis of peptides with respect to predicted fragmentation patterns or by sequence tagging; and (iii) ESI/MS/MS for peptide sequencing. Genomic sequences when complemented with information derived from hybridisation assays and proteome analysis may herald in a new era of holistic cellular biology. The current preoccupation with the absolute quantity of gene-product (RNA and/or protein) should move backstage with respect to more molecularly relevant parameters, such as: molecular half-life; synthesis rate; functional competence (presence or absence of mutations); reaction kinetics; the influence of individual gene-products on biochemical flux; the influence of the environment, cell-cycle, stress and disease on gene-products; and the collective roles of multigenic and epigenetic phenomena governing cellular processes. Proteome analysis is demonstrated as being capable of proceeding independently of DNA sequence information and aiding in genomic annotation. Its ability to confirm the existence of gene-products predicted from DNA sequence is a major contribution to genomic science. The workings of software engines necessary to achieve large-scale proteome analysis are outlined, along with trends towards miniaturisation, analyte concentration and protein detection independent of staining technologies. A challenge for proteome analysis into the future will be to reduce its dependence on two-dimensional (2-D) gel electrophoresis as the preferred method of separating complex mixtures of cellular proteins. Nonetheless, proteome analysis already represents a means of efficiently complementing differential display, high density expression arrays, expressed sequence tags, direct or subtractive hybridisation, chromosomal linkage studies and nucleic acid sequencing as a problem solving tool in molecular biology.

Animals↗

Comprehensive de novo structure prediction in a systems-biology context for the archaea Halobacterium sp. NRC-1.

BACKGROUND: Large fractions of all fully sequenced genomes code for proteins of unknown function. Annotating these proteins of unknown function remains a critical bottleneck for systems biology and is crucial to understanding the biological relevance of genome-wide changes in mRNA and protein expression, protein-protein and protein-DNA interactions. The work reported here demonstrates that de novo structure prediction is now a viable option for providing general function information for many proteins of unknown function. RESULTS: We have used Rosetta de novo structure prediction to predict three-dimensional structures for 1,185 proteins and protein domains (<150 residues in length) found in Halobacterium NRC-1, a widely studied halophilic archaeon. Predicted structures were searched against the Protein Data Bank to identify fold similarities and extrapolate putative functions. They were analyzed in the context of a predicted association network composed of several sources of functional associations such as: predicted protein interactions, predicted operons, phylogenetic profile similarity and domain fusion. To illustrate this approach, we highlight three cases where our combined procedure has provided novel insights into our understanding of chemotaxis, possible prophage remnants in Halobacterium NRC-1 and archaeal transcriptional regulators. CONCLUSIONS: Simultaneous analysis of the association network, coordinated mRNA level changes in microarray experiments and genome-wide structure prediction has allowed us to glean significant biological insights into the roles of several Halobacterium NRC-1 proteins of previously unknown function, and significantly reduce the number of proteins encoded in the genome of this haloarchaeon for which no annotation is available.

Archaeal Proteins↗

Selection system for genes encoding nuclear-targeted proteins.

Nuclear proteins have essential roles in cell proliferation and differentiation. We have developed a yeast selection system-the nuclear transportation trap (NTT)-to identify genes encoding nuclear transport signals. Both unknown and previously identified nuclear localization signals were identified from a human fetal brain cDNA library. The majority (75%) of the unknown proteins examined were exclusively localized to the nucleus in COS-7 cells. We propose that NTT is an efficient method for isolating cDNAs that encode nuclear targeted proteins that can be applied to the retrieval of novel nuclear proteins and to annotate gene function.

Amino Acid Sequence↗

Complex SNP-related sequence variation in segmental genome duplications.

There is uncertainty about the true nature of predicted single-nucleotide polymorphisms (SNPs) in segmental duplications (duplicons) and whether these markers genuinely exist at increased density as indicated in public databases. We explored these issues by genotyping 157 predicted SNPs in duplicons and control regions in normal diploid genomes and fully homozygous complete hydatidiform moles. Our data identified many true SNPs in duplicon regions and few paralogous sequence variants. Twenty-eight percent of the polymorphic duplicon sequences we tested involved multisite variation, a new type of polymorphism representing the sum of the signals from many individual duplicon copies that vary in sequence content due to duplication, deletion or gene conversion. Multisite variations can masquerade as normal SNPs when genotyped. Given that duplicons comprise at least 5% of the genome and many are yet to be annotated in the genome draft, effective strategies to identify multisite variation must be established and deployed.

Evolution, Molecular↗