We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

MUSCLE: multiple sequence alignment with high accuracy and high throughput

The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

/pdf/initial-sequencing-and-analysis-of-the-human-genome-5dapk1rsx1.pdf

Initial sequencing and analysis of the human genome.

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is approximately 100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11,912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).

/pdf/the-pfam-protein-families-database-3t3lguk949.pdf

The Pfam protein families database

Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.

/pdf/blast-architecture-and-applications-2udguz40ns.pdf

BLAST+: architecture and applications.

Planktonic crenarchaeotes are present in high abundance in Antarctic winter surface waters, and they also make up a large proportion of total cell numbers throughout deep ocean waters. To better characterize these uncultivated marine crenarchaeotes, we analyzed large genome fragments from individuals recovered from a single Antarctic picoplankton population and compared them to those from a representative obtained from deeper waters of the temperate North Pacific. Sequencing and analysis of the entire DNA insert from one Antarctic marine archaeon (fosmid 74A4) revealed differences in genome structure and content between Antarctic surface water and temperate deepwater archaea. Analysis of the predicted gene products encoded by the 74A4 sequence and those derived from a temperate, deepwater planktonic crenarchaeote (fosmid 4B7) revealed many typical archaeal proteins but also several proteins that so far have not been detected in archaea. The unique fraction of marine archaeal genes included, among others, those for a predicted RNA-binding protein of the bacterial cold shock family and a eukaryote-type Zn finger protein. Comparison of closely related archaea originating from a single population revealed significant genomic divergence that was not evident from 16S rRNA sequence variation. The data suggest that considerable functional diversity may exist within single populations of coexisting microbial strains, even those with identical 16S rRNA sequences. Our results also demonstrate that genomic approaches can provide high-resolution information relevant to microbial population genetics, ecology, and evolution, even for microbes that have not yet been cultivated.

/pdf/comparative-genomic-analysis-of-archaeal-genotypic-variants-13ir8axwim.pdf

Comparative genomic analysis of archaeal genotypic variants in a single population and in two different oceanic provinces.

G-patch: a new conserved domain in eukaryotic RNA-processing proteins and type D retroviral polyproteins.

The use of nucleases as toxins for defense, offense or addiction of selfish elements is widely encountered across all life forms. Using sensitive sequence profile analysis methods, we characterize a novel superfamily (the SUKH superfamily) that unites a diverse group of proteins including Smi1/Knr4, PGs2, FBXO3, SKIP16, Syd, herpesviral US22, IRS1 and TRS1, and their bacterial homologs. Using contextual analysis we present evidence that the bacterial members of this superfamily are potential immunity proteins for a variety of toxin systems that also include the recently characterized contact-dependent inhibition (CDI) systems of proteobacteria. By analyzing the toxin proteins encoded in the neighborhood of the SUKH superfamily we predict that they possess domains belonging to diverse nuclease and nucleic acid deaminase families. These include at least eight distinct types of DNases belonging to HNH/EndoVII- and restriction endonuclease-fold, and RNases of the EndoU-like and colicin E3-like cytotoxic RNases-folds. The N-terminal domains of these toxins indicate that they are extruded by several distinct secretory mechanisms such as the two-partner system (shared with the CDI systems) in proteobacteria, ESAT-6/WXG-like ATP-dependent secretory systems in Gram-positive bacteria and the conventional Sec-dependent system in several bacterial lineages. The hedgehog-intein domain might also release a subset of toxic nuclease domains through auto-proteolytic action. Unlike classical colicin-like nuclease toxins, the overwhelming majority of toxin systems with the SUKH superfamily is chromosomally encoded and appears to have diversified through a recombination process combining different C-terminal nuclease domains to N-terminal secretion-related domains. Across the bacterial superkingdom these systems might participate in discriminating `self’ or kin from `non-self’ or non-kin strains. Using structural analysis we demonstrate that the SUKH domain possesses a versatile scaffold that can be used to bind a wide range of protein partners. In eukaryotes it appears to have been recruited as an adaptor to regulate modification of proteins by ubiquitination or polyglutamylation. Similarly, another widespread immunity protein from these toxin systems, namely the suppressor of fused (SuFu) superfamily has been recruited for comparable roles in eukaryotes. In animal DNA viruses, such as herpesviruses, poxviruses, iridoviruses and adenoviruses, the ability of the SUKH domain to bind diverse targets has been deployed to counter diverse anti-viral responses by interacting with specific host proteins.

/pdf/a-novel-immunity-system-for-bacterial-nucleic-acid-degrading-2xtogwmvgj.pdf

A novel immunity system for bacterial nucleic acid degrading toxins and its recruitment in various eukaryotic and DNA viral systems

The genome sequences churned out by the “genomic revolution” have challenged both computational and experimental biologists to come up with new methods to decipher the secrets of the encoded proteins. The experimental biologists have largely concentrated on a variety of large-scale methods to assay gene expression and protein–protein interactions (Brown and Botstein 1999; Uetz et al. 2000; Walhout et al. 2000). The computational biologists, however, have deeply mined the genomes for evolutionary information in the form of homology between genes (Tatusov et al. 1997; Koonin et al. 2000; Ponting et al. 2000,). Over the past few years there has been increasing interest in the kinds of information that exist in the context in which a protein or a domain thereof is encoded in the genome (Mushegian and Koonin 1996; Dandekar et al. 1998). Recently, contextual information has been offered as a strong handle on the problem of in silico inference of protein function (Enright et al. 1999; Marcotte et al. 1999a,b; Overbeek et al. 1999; Pellegrini et al. 1999; Huynen et al. 2000). Understanding the scope and limitations of the use of these methods may be critical for the experimental biologists seeking to use computational guidelines for large-scale investigations of protein function. Here, we outline the recent advances in this direction and briefly illustrate the new leads they provide in understanding protein function. Contextual information comes in several overlapping grades, each with a different degree of specificity with regards to a particular protein’s role (Fig. 1). The most general form of contextual information is a phyletic profile, that is, the pattern of occurrence of orthologs of a particular gene in a set of genomes under comparison (Pellegrini et al. 1999; Tatusov et al. 2000). In this setup, the null hypothesis would be that genes that functionally interact in a particular pathway or complex would share a similar phyletic profile. This hypothesis is supported by the phyletic distribution of components of the core cellular machinery—the translation, transcription, and replication complexes, which interact very tightly—as well as those of metabolic pathways. For example, most of the proteins with a shared phyletic pattern between the archaea and the eukaryotes are components of one of the many protein complexes that have a role in the above-stated three-core cellular processes. Thus, the detection of uncharacterized proteins, such as the family typified by MJ0586 from Methanococcus jannaschii, with a similar phyletic profile would implicate them in one of the core functions (Fig. 1). When the information from sequence homology is applied to these proteins, one can often arrive at rather precise functions for these proteins. In the case of the MJ0586-like proteins, sequence comparisons reveal that they have a DNA binding helix-turn-helix domain (Aravind and Koonin 1999), suggesting that it is a component of the basal transcription machinery similar to TFIIB or TBP, which share the same phyletic profile (Fig. 1). This inference is compatible with the recent implication of the eukaryotic representative of this family MBF1 in transcriptional regulation (Kabe et al. 1999). When a rare shared phyletic pattern is seen for certain proteins whose sequence affinities suggest a related function, a strong case can be made for their interaction. One example of this is the typically eukaryotic chromatin protein methyltransferase—the SET domain that is seen in the bacteria Chlamydiae and Bordatella pertussis, along with another eukaryotic chromatin protein domain, SWIB (Stephens et al. 1998). The rare phyletic profile of these proteins in bacteria suggests that the SET and SWIB domains probably interact not only in these bacteria but possibly also in other organisms. Since the pioneering works of Jacob and Monod, scientists have realized that functionally linked genes are coregulated and occur in proximity to each other on the chromosome. Genome comparisons have supported this and show that, in prokaryotes, functionally interacting genes are in clusters that range from the giant ribosomal operons to gene pairs that survive over large phylogenetic distances (Dandekar et al. 1998; Overbeek et al. 1999). Thus, the occurrence of an uncharacterized gene in the neighborhood (the same operon) of genes with known functions could potentially betray its function. However, the variability of operons and the inability to predict them with a high level of certainty causes a loss of specificity of this form of contextual information. On this issue, Huynen et al. argue that greater stringency in the criteria for gene neighborhood reduces false positives in these inferences, with physical interactions between gene products strongly predicted by conservation of gene order in an operon. Furthermore, as the number of gene neighborhood combinations are far from exhausted with the currently available genomes, this method is likely to improve in its scope and confidence with the availability of more genomes in the future. E-MAIL aravind@ncbi.nlm.nih.gov; FAX (301) 480-9241. Insight/Outlook

Guilt by association: contextual information in genome analysis.

Although several studies have provided important insights into the general principles of biological networks, the link between network organization and the genome-scale dynamics of the underlying entities (genes, mRNAs, and proteins) and its role in systems behavior remain unclear. Here we show that transcription factor (TF) dynamics and regulatory network organization are tightly linked. By classifying TFs in the yeast regulatory network into three hierarchical layers (top, core, and bottom) and integrating diverse genome-scale datasets, we find that the TFs have static and dynamic properties that are similar within a layer and different across layers. At the protein level, the top-layer TFs are relatively abundant, long-lived, and noisy compared with the core- and bottom-layer TFs. Although variability in expression of top-layer TFs might confer a selective advantage, as this permits at least some members in a clonal cell population to initiate a response to changing conditions, tight regulation of the core- and bottom-layer TFs may minimize noise propagation and ensure fidelity in regulation. We propose that the interplay between network organization and TF dynamics could permit differential utilization of the same underlying network by distinct members of a clonal cell population.

/pdf/genomic-analysis-reveals-a-tight-link-between-transcription-4f315qqsgw.pdf

L. Aravind

Papers

Comparative genomic analysis of archaeal genotypic variants in a single population and in two different oceanic provinces.

G-patch: a new conserved domain in eukaryotic RNA-processing proteins and type D retroviral polyproteins.

A novel immunity system for bacterial nucleic acid degrading toxins and its recruitment in various eukaryotic and DNA viral systems

Guilt by association: contextual information in genome analysis.

Genomic analysis reveals a tight link between transcription factor dynamics and regulatory network architecture