Building a dictionary for genomes: Identification of presumptive regulatory sites by statistical analysis

The availability of complete genome sequences and mRNA expression data for all genes creates new opportunities and challenges for identifying DNA sequence motifs that control gene expression. An algorithm, “MobyDick,” is presented that decomposes a set of DNA sequences into the most probable dictionary of motifs or words. This method is applicable to any set of DNA sequences: for example, all upstream regions in a genome or all genes expressed under certain conditions. Identification of words is based on a probabilistic segmentation model in which the significance of longer words is deduced from the frequency of shorter ones of various lengths, eliminating the need for a separate set of reference data to define probabilities. We have built a dictionary with 1,200 words for the 6,000 upstream regulatory regions in the yeast genome; the 500 most significant words (some with as few as 10 copies in all of the upstream regions) match 114 of 443 experimentally determined sites (a significance level of 18 standard deviations). When analyzing all of the genes up-regulated during sporulation as a group, we find many motifs in addition to the few previously identified by analyzing the subclusters individually to the expression subclusters. Applying MobyDick to the genes derepressed when the general repressor Tup1 is deleted, we find known as well as putative binding sites for its regulatory partners.

How Escherichia coli can bias the results of molecular cloning: Preferential selection of defective genomes of hepatitis C virus during the cloning procedure

Cloned PCR products containing hepatitis C virus (HCV) genomic fragments have been used for analyses of HCV genomic heterogeneity and protein expression. These studies assume that the clones derived are representative of the entire virus population and that subsets are not inadvertently selected. The aim of the present study was to express HCV structural proteins. However, we found that there was a strong cloning selection for defective genomes and that most clones generated initially were incapable of expressing the HCV proteins. The HCV structural region (C-E1-E2-p7) was directly amplified by long reverse transcription–PCR from the plasma of an HCV-infected patient or from a control plasmid containing a viable full-length cDNA of HCV derived from the same patient but cloned in a different vector. The PCR products were cloned into a mammalian expression vector, amplified in Escherichia coli, and tested for their ability to produce HCV structural proteins. Twenty randomly picked clones derived from the HCV-infected patient all contained nucleotide mutations leading to absence or truncation of the expected HCV products. Of 25 clones derived from the control plasmid, only 8% were fully functional for polyprotein synthesis. The insertion of extra nucleotides in the region just upstream of the start codon of the HCV insert led to a statistically significant increase in the number of fully functional clones derived from the patient (42%) and from the control plasmid (72–92%). Nonrandom selection of clones during the cloning procedure has enormous implications for the study of viral heterogeneity, because it can produce a false spectrum of genomic diversity. It can also be an impediment to the construction of infectious viral clones.

Arabidopsis genomes uncoupled 5 (GUN5) mutant reveals the involvement of Mg-chelatase H subunit in plastid-to-nucleus signal transduction

A plastid-derived signal plays an important role in the coordinated expression of both nuclear- and chloroplast-localized genes that encode photosynthesis-related proteins. Arabidopsis GUN (genomes uncoupled) loci have been identified as components of plastid-to-nucleus signal transduction. Unlike wild-type plants, gun mutants have nuclear Lhcb1 expression in the absence of chloroplast development. We observed a synergistic phenotype in some gun double-mutant combinations, suggesting there are at least two independent pathways in plastid-to-nucleus signal transduction. There is a reduction of chlorophyll accumulation in gun4 and gun5 mutant plants, and a gun4gun5 double mutant shows an albino phenotype. We cloned the GUN5 gene, which encodes the ChlH subunit of Mg-chelatase. We also show that gun2 and gun3 are alleles of the known photomorphogenic mutants, hy1 and hy2, which are required for phytochromobilin synthesis from heme. These findings suggest that certain perturbations of the tetrapyrrole biosynthetic pathway generate a signal from chloroplasts that causes transcriptional repression of nuclear genes encoding plastid-localized proteins. The comparison of mutant phenotypes of gun5 and another Mg-chelatase subunit (ChlI) mutant suggests a specific function for ChlH protein in the plastid-signaling pathway.

Prediction of operons in microbial genomes

Operon structure is an important organization feature of bacterial genomes. Many sets of genes occur in the same order on multiple genomes; these conserved gene groupings represent candidate operons. This study describes a computational method to estimate the likelihood that such conserved gene sets form operons. The method was used to analyze 34 bacterial and archaeal genomes, and yielded more than 7600 pairs of genes that are highly likely (P ≥ 0.98) to belong to the same operon. The sensitivity of our method is 30–50% for the Escherichia coli genome. The predicted gene pairs are available from our World Wide Web site http://www.tigr.org/tigr-scripts/operons/operons.cgi.

The COG database: new developments in phylogenetic classification of proteins from complete genomes

The database of Clusters of Orthologous Groups of proteins (COGs), which represents an attempt on a phylogenetic classification of the proteins encoded in complete genomes, currently consists of 2791 COGs including 45 350 proteins from 30 genomes of bacteria, archaea and the yeast Saccharomyces cerevisiae (http://www.ncbi.nlm.nih.gov/COG). In addition, a supplement to the COGs is available, in which proteins encoded in the genomes of two multicellular eukaryotes, the nematode Caenorhabditis elegans and the fruit fly Drosophila melanogaster, and shared with bacteria and/or archaea were included. The new features added to the COG database include information pages with structural and functional details on each COG and literature references, improvements of the COGNITOR program that is used to fit new proteins into the COGs, and classification of genomes and COGs constructed by using principal component analysis.

Proteome Analysis Database: online application of InterPro and CluSTr for the functional classification of proteins in whole genomes

The SWISS-PROT group at EBI has developed the Proteome Analysis Database utilising existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archaea and eukaryotes (http://www.ebi.ac.uk/proteome/). The two main projects used, InterPro and CluSTr, give a new perspective on families, domains and sites and cover 31–67% (InterPro statistics) of the proteins from each of the complete genomes. CluSTr covers the three complete eukaryotic genomes and the incomplete human genome data. The Proteome Analysis Database is accompanied by a program that has been designed to carry out InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

Genomes OnLine Database (GOLD): a monitor of genome projects world-wide

GOLD is a comprehensive resource for accessing information related to completed and ongoing genome projects world-wide. The database currently provides information on 350 genome projects, of which 48 have been completely sequenced and their analysis published. GOLD was created in 1997 and since April 2000 it has been licensed to Integrated Genomics. The database is freely available through the URL: http://igweb.integratedgenomics.com/GOLD/.

Phylogenetic footprinting of transcription factor binding sites in proteobacterial genomes

Toward the goal of identifying complete sets of transcription factor (TF)-binding sites in the genomes of several gamma proteobacteria, and hence describing their transcription regulatory networks, we present a phylogenetic footprinting method for identifying these sites. Probable transcription regulatory sites upstream of Escherichia coli genes were identified by cross-species comparison using an extended Gibbs sampling algorithm. Close examination of a study set of 184 genes with documented transcription regulatory sites revealed that when orthologous data were available from at least two other gamma proteobacterial species, 81% of our predictions corresponded with the documented sites, and 67% corresponded when data from only one other species were available. That the remaining predictions included bona fide TF-binding sites was proven by affinity purification of a putative transcription factor (YijC) bound to such a site upstream of the fabA gene. Predicted regulatory sites for 2097 E.coli genes are available at http://www.wadsworth.org/resnres/bioinfo/.

Identification of thermophilic species by the amino acid compositions deduced from their genomes

The global amino acid compositions as deduced from the complete genomic sequences of six thermophilic archaea, two thermophilic bacteria, 17 mesophilic bacteria and two eukaryotic species were analysed by hierarchical clustering and principal components analysis. Both methods showed an influence of several factors on amino acid composition. Although GC content has a dominant effect, thermophilic species can be identified by their global amino acid compositions alone. This study presents a careful statistical analysis of factors that affect amino acid composition and also yielded specific features of the average amino acid composition of thermophilic species. Moreover, we introduce the first example of a ‘compositional tree’ of species that takes into account not only homologous proteins, but also proteins unique to particular species. We expect this simple yet novel approach to be a useful additional tool for the study of phylogeny at the genome level.

Does recombination improve selection on codon usage? Lessons from nematode and fly complete genomes

Understanding the factors responsible for variations in mutation patterns and selection efficacy along chromosomes is a prerequisite for deciphering genome sequences. Population genetics models predict a positive correlation between the efficacy of selection at a given locus and the local rate of recombination because of Hill–Robertson effects. Codon usage is considered one of the most striking examples that support this prediction at the molecular level. In a wide range of species including Caenorhabditis elegans and Drosophila melanogaster, codon usage is essentially shaped by selection acting for translational efficiency. Codon usage bias correlates positively with recombination rate in Drosophila, apparently supporting the hypothesis that selection on codon usage is improved by recombination. Here we present an exhaustive analysis of codon usage in C. elegans and D. melanogaster complete genomes. We show that in both genomes there is a positive correlation between recombination rate and the frequency of optimal codons. However, we demonstrate that in both species, this effect is due to a mutational bias toward G and C bases in regions of high recombination rate, possibly as a direct consequence of the recombination process. The correlation between codon usage bias and recombination rate in these species appears to be essentially determined by recombination-dependent mutational patterns, rather than selective effects. This result highlights that it is necessary to take into account the mutagenic effect of recombination to understand the evolutionary role and impact of recombination.

Grass genomes

For the most part, studies of grass genome structure have been limited to the generation of whole-genome genetic maps or the fine structure and sequence analysis of single genes or gene clusters. We have investigated large contiguous segments of the genomes of maize, sorghum, and rice, primarily focusing on intergenic spaces. Our data indicate that much (>50%) of the maize genome is composed of interspersed repetitive DNAs, primarily nested retrotransposons that insert between genes. These retroelements are less abundant in smaller genome plants, including rice and sorghum. Although 5- to 200-kb blocks of methylated, presumably heterochromatic, retrotransposons flank most maize genes, rice and sorghum genes are often adjacent. Similar genes are commonly found in the same relative chromosomal locations and orientations in each of these three species, although there are numerous exceptions to this collinearity (i.e., rearrangements) that can be detected at the levels of both the recombinational map and cloned DNA. Evolutionarily conserved sequences are largely confined to genes and their regulatory elements. Our results indicate that a knowledge of grass genome structure will be a useful tool for gene discovery and isolation, but the general rules and biological significance of grass genome organization remain to be determined. Moreover, the nature and frequency of exceptions to the general patterns of grass genome structure and collinearity are still largely unknown and will require extensive further investigation.

Importance of anchor genomes for any plant genome project

Progress in agricultural and environmental technologies is hampered by a slower rate of gene discovery in plants than animals. The vast pool of genes in plants, however, will be an important resource for insertion of genes, via biotechnological procedures, into an array of plants, generating unique germ plasms not achievable by conventional breeding. It just became clear that genomes of grasses have evolved in a manner analogous to Lego blocks. Large chromosome segments have been reshuffled and stuffer pieces added between genes. Although some genomes have become very large, the genome with the fewest stuffer pieces, the rice genome, is the Rosetta Stone of all the bigger grass genomes. This means that sequencing the rice genome as anchor genome of the grasses will provide instantaneous access to the same genes in the same relative physical position in other grasses (e.g., corn and wheat), without the need to sequence each of these genomes independently. (i) The sequencing of the entire genome of rice as anchor genome for the grasses will accelerate plant gene discovery in many important crops (e.g., corn, wheat, and rice) by several orders of magnitudes and reduce research and development costs for government and industry at a faster pace. (ii) Costs for sequencing entire genomes have come down significantly. Because of its size, rice is only 12% of the human or the corn genome, and technology improvements by the human genome project are completely transferable, translating in another 50% reduction of the costs. (iii) The physical mapping of the rice genome by a group of Japanese researchers provides a jump start for sequencing the genome and forming an international consortium. Otherwise, other countries would do it alone and own proprietary positions.