The polymorphic nature of HIV type 1 env V4 affects the patterns of potential N-glycosylation sites in proviral DNA at the intrahost level.

We have previously shown that env V4 from HIV-1 plasma RNA is highly heterogeneous within a single patient, due to indel-associated polymorphism. In this study, we have analyzed the variability of V4 in proviral DNA from unfractionated PBMC and sorted T and non-T cell populations within individual patients. Our data show that the degree of sequence variability and length polymorphism in V4 from HIV provirus is even higher than we previously reported in plasma. The data also show that the sequence of V4 depends largely on the experimental approach chosen. We could observe no clear trend for compartmentalization of V4 variants in specific cell types. Of interest is the fact that some variants that had been found to be predominant in plasma were not detected in any of the cell subsets analyzed. Consistently with our observations in plasma, V3 was found to be relatively conserved at both interpatient and intrapatient level. Our data show that V4 polymorphism involving insertions and deletions in addition to point mutations results in changes in the patterns of sequons in HIV-1 proviral DNA as well as in plasma RNA. These rearrangements may result in the coexistence, within the same individual, of a swarm of different V4 regions, each characterized by a different carbohydrate surface shield. Further studies are needed to investigate the mechanism responsible for the variability observed in V4 and its role in HIV pathogenesis.

Probabilistic base calling of Solexa sequencing data.

BACKGROUND: Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology. RESULTS: We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. CONCLUSION: We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.

An assessment of gene prediction accuracy in large DNA sequences

One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

The loss of GLUT2 expression in the pancreatic beta-cells of diabetic db/db mice is associated with an impaired DNA-binding activity of islet-specific trans-acting factors.

GLUT2 expression is reduced in the pancreatic beta-cells of several diabetic animals. The transcriptional control of the gene in beta-cells involves at least two islet-specific DNA-binding proteins, GTIIa and PDX-1, which also transactivates the insulin, somatostatin and glucokinase genes. In this report, we assessed the DNA-binding activities of GTIIa and PDX-1 to their respective cis-elements of the GLUT2 promoter using nuclear extracts prepared from pancreatic islets of 12 week old db/db diabetic mice. We show that the decreased GLUT2 mRNA expression correlates with a decrease of the GTIIa DNA-binding activity, whereas the PDX-1 binding activity is increased. In these diabetic animals, insulin mRNA expression remains normal. The adjunction of dexamethasone to isolated pancreatic islets, a treatment previously shown to decrease PDX-1 expression in the insulin-secreting HIT-T15 cells, has no effect on the GTIIa and PDX-1 DNA-binding activities. These data suggest that the decreased activity of GTIIa, in contrast to PDX-1, may be a major initial step in the development of the beta-cell dysfunction in this model of diabetes.

Nonshivering thermogenesis capacity associated to mitochondrial DNA haplotypes and gender in the greater white-toothed shrew, Crocidura russula.

A selection gradient was recently suggested as one possible cause for a clinal distribution of mitochondrial DNA (mtDNA) haplotypes along an altitudinal transect in the greater white-toothed shrew, Crocidura russula (Ehinger et al. 2002). One mtDNA haplotype (H1) rare in lowland, became widespread when approaching the altitudinal margin of the distribution. As H1 differs from the main lowland haplotype by several nonsynonymous mutations (including on ATP6), and as mitochondria play a crucial role in metabolism and thermogenesis, distribution patterns might stem from differences in the thermogenic capacity of different mtDNA haplotypes. In order to test this hypothesis, we measured the nonshivering thermogenesis (NST) associated with different mtDNA haplotypes. Sixty-two shrews, half of which had the H1 haplotype, were acclimated in November at semioutdoor conditions and measured for NST throughout winter. Our results showed the crucial role of NST for winter survival in C. russula. The individuals that survived winter displayed a higher significant increase in NST during acclimation, associated with a significant gain in body mass, presumably from brown fat accumulation. The NST capacity (ratio of NST to basal metabolic rate) was exceptionally high for such a small species. NST was significantly affected by a gender x haplotype interaction after winter-acclimation: females bearing the H1 haplotype displayed a better thermogenesis at the onset of the breeding season, while the reverse was true for males. Altogether, our results suggest a sexually antagonistic cyto-nuclear selection on thermogenesis.

Neutrophils activate plasmacytoid dendritic cells by releasing self-DNA-peptide complexes in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a severe and incurable autoimmune disease characterized by chronic activation of plasmacytoid dendritic cells (pDCs) and production of autoantibodies against nuclear self-antigens by hyperreactive B cells. Neutrophils are also implicated in disease pathogenesis; however, the mechanisms involved are unknown. Here, we identified in the sera of SLE patients immunogenic complexes composed of neutrophil-derived antimicrobial peptides and self-DNA. These complexes were produced by activated neutrophils in the form of web-like structures known as neutrophil extracellular traps (NETs) and efficiently triggered innate pDC activation via Toll-like receptor 9 (TLR9). SLE patients were found to develop autoantibodies to both the self-DNA and antimicrobial peptides in NETs, indicating that these complexes could also serve as autoantigens to trigger B cell activation. Circulating neutrophils from SLE patients released more NETs than those from healthy donors; this was further stimulated by the antimicrobial autoantibodies, suggesting a mechanism for the chronic release of immunogenic complexes in SLE. Our data establish a link between neutrophils, pDC activation, and autoimmunity in SLE, providing new potential targets for the treatment of this devastating disease.

Targeting of DNA polymerase to the adenovirus origin of DNA replication by interaction with nuclear factor I.

Efficient initiation by the DNA polymerase of adenovirus type 2 requires nuclear factor I (NFI), a cellular sequence-specific transcription factor. Three functions of NFI--dimerization, DNA binding, and activation of DNA replication--are colocalized within the N-terminal portion of the protein. To define more precisely the role of NFI in viral DNA replication, a series of site-directed mutations within the N-terminal domain have been generated, thus allowing the separation of all three functions contained within this region. Impairment of the dimerization function prevents sequence-specific DNA binding and in turn abolishes the NFI-mediated activation of DNA replication. NFI DNA-binding activity, although necessary, is not sufficient to activate the initiation of adenovirus replication. A distinct class of NFI mutations that abolish the recruitment of the viral DNA polymerase to the origin also prevent the activation of replication. Thus, a direct interaction of NFI with the viral DNA polymerase complex is required to form a stable and active preinitiation complex on the origin and is responsible for the activation of replication by NFI.

A user's guide to the encyclopedia of DNA elements (ENCODE).

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome.

Homologous DNA pairing domain peptides of RecA protein: intrinsic propensity to form beta-structures and filaments.

The 20 amino acid residue peptides derived from RecA loop L2 have been shown to be the pairing domain of RecA. The peptides bind to ss- and dsDNA, unstack ssDNA, and pair the ssDNA to its homologous target in a duplex DNA. As shown by circular dichroism, upon binding to DNA the disordered peptides adopt a beta-structure conformation. Here we show that the conformational change of the peptide from random coil to beta-structure is important in binding ss- and dsDNA. The beta-structure in the DNA pairing peptides can be induced by many environmental conditions such as high pH, high concentration, and non-micellar sodium dodecyl sulfate (6 mM). This behavior indicates an intrinsic property of these peptides to form a beta-structure. A beta-structure model for the loop L2 of RecA protein when bound to DNA is thus proposed. The fact that aromatic residues at the central position 203 strongly modulate the peptide binding to DNA and subsequent biochemical activities can be accounted for by the direct effect of the aromatic amino acids on the peptide conformational change. The DNA-pairing domain of RecA visualized by electron microscopy self-assembles into a filamentous structure like RecA. The relevance of such a peptide filamentous structure to the structure of RecA when bound to DNA is discussed.

Phenotypic switching in Pseudomonas brassicacearum involves GacS- and GacA-dependent Rsm small RNAs.

The plant-beneficial bacterium Pseudomonas brassicacearum forms phenotypic variants in vitro as well as in planta during root colonization under natural conditions. Transcriptome analysis of typical phenotypic variants using microarrays containing coding as well as noncoding DNA fragments showed differential expression of several genes relevant to secondary metabolism and of the small RNA (sRNA) genes rsmX, rsmY, and rsmZ. Naturally occurring mutations in the gacS-gacA system accounted for phenotypic switching, which was characterized by downregulation of antifungal secondary metabolites (2,4-diacetylphloroglucinol and cyanide), indoleacetate, exoenzymes (lipase and protease), and three different N-acyl-homoserine lactone molecules. Moreover, in addition to abrogating these biocontrol traits, gacS and gacA mutations resulted in reduced expression of the type VI secretion machinery, alginate biosynthesis, and biofilm formation. In a gacA mutant, the expression of rsmX was completely abolished, unlike that of rsmY and rsmZ. Overexpression of any of the three sRNAs in the gacA mutant overruled the pleiotropic changes and restored the wild-type phenotypes, suggesting functional redundancy of these sRNAs. In conclusion, our data show that phenotypic switching in P. brassicacearum results from mutations in the gacS-gacA system.

Transcript profiling suggests that differential metabolic adaptation of mice to a high fat diet is associated with changes in liver to muscle lipid fluxes.

Genetically homogenous C57Bl/6 mice display differential metabolic adaptation when fed a high fat diet for 9 months. Most become obese and diabetic, but a significant fraction remains lean and diabetic or lean and non-diabetic. Here, we performed microarray analysis of "metabolic" transcripts expressed in liver and hindlimb muscles to evaluate: (i) whether expressed transcript patterns could indicate changes in metabolic pathways associated with the different phenotypes, (ii) how these changes differed from the early metabolic adaptation to short term high fat feeding, and (iii) whether gene classifiers could be established that were characteristic of each metabolic phenotype. Our data indicate that obesity/diabetes was associated with preserved hepatic lipogenic gene expression and increased plasma levels of very low density lipoprotein and, in muscle, with an increase in lipoprotein lipase gene expression. This suggests increased muscle fatty acid uptake, which may favor insulin resistance. In contrast, the lean mice showed a strong reduction in the expression of hepatic lipogenic genes, in particular of Scd-1, a gene linked to sensitivity to diet-induced obesity; the lean and non-diabetic mice presented an additional increased expression of eNos in liver. After 1 week of high fat feeding the liver gene expression pattern was distinct from that seen at 9 months in any of the three mouse groups, thus indicating progressive establishment of the different phenotypes. Strikingly, development of the obese phenotype involved re-expression of Scd-1 and other lipogenic genes. Finally, gene classifiers could be established that were characteristic of each metabolic phenotype. Together, these data suggest that epigenetic mechanisms influence gene expression patterns and metabolic fates.

Identification and removal of low-complexity sites in allele-specific analysis of ChIP-seq data.

MOTIVATION: High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. Results: We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent-daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays.

A comparison of methods for differential expression analysis of RNA-seq data.

BACKGROUND: Finding genes that are differentially expressed between conditions is an integral part of understanding the molecular basis of phenotypic variation. In the past decades, DNA microarrays have been used extensively to quantify the abundance of mRNA corresponding to different genes, and more recently high-throughput sequencing of cDNA (RNA-seq) has emerged as a powerful competitor. As the cost of sequencing decreases, it is conceivable that the use of RNA-seq for differential expression analysis will increase rapidly. To exploit the possibilities and address the challenges posed by this relatively new type of data, a number of software packages have been developed especially for differential expression analysis of RNA-seq data. RESULTS: We conducted an extensive comparison of eleven methods for differential expression analysis of RNA-seq data. All methods are freely available within the R framework and take as input a matrix of counts, i.e. the number of reads mapping to each genomic feature of interest in each of a number of samples. We evaluate the methods based on both simulated data and real RNA-seq data. CONCLUSIONS: Very small sample sizes, which are still common in RNA-seq experiments, impose problems for all evaluated methods and any results obtained under such conditions should be interpreted with caution. For larger sample sizes, the methods combining a variance-stabilizing transformation with the 'limma' method for differential expression analysis perform well under many different conditions, as does the nonparametric SAMseq method.

Temporal and spatial origin of Gesneriaceae in the New World inferred from plastid DNA sequences

Gesneriaceae are represented in the New World (NW) by a major clade (c. 1000 species) currently recognized as subfamily Gesnerioideae. Radiation of this group occurred in all biomes of tropical America and was accompanied by extensive phenotypic and ecological diversification. Here we performed phylogenetic analyses using DNA sequences from three plastid loci to reconstruct the evolutionary history of Gesnerioideae and to investigate its relationship with other lineages of Gesneriaceae and Lamiales. Our molecular data confirm the inclusion of the South Pacific Coronanthereae and the Old World (OW) monotypic genus Titanotrichum in Gesnerioideae and the sister-group relationship of this subfamily to the rest of the OW Gesneriaceae. Calceolariaceae and the NW genera Peltanthera and Sanango appeared successively sister to Gesneriaceae, whereas Cubitanthus, which has been previously assigned to Gesneriaceae, is shown to be related to Linderniaceae. Based on molecular dating and biogeographical reconstruction analyses, we suggest that ancestors of Gesneriaceae originated in South America during the Late Cretaceous. Distribution of Gesneriaceae in the Palaeotropics and Australasia was inferred as resulting from two independent long-distance dispersals during the Eocene and Oligocene, respectively. In a short time span starting at 34 Mya, ancestors of Gesnerioideae colonized several Neotropical regions including the tropical Andes, Brazilian Atlantic forest, cerrado, Central America and the West Indies. Subsequent diversification within these areas occurred largely in situ and was particularly extensive in the mountainous systems of the Andes, Central America and the Brazilian Atlantic forest. Only two radiations account for 90% of the diversity of Gesneriaceae in the Brazilian Atlantic forest, whereas half of the species richness in the northern Andes and Central America originated during the last 10 Myr from a single radiation.

DNA-DNA interactions in bacteriophage capsids are responsible for the observed DNA knotting.

Recent experiments showed that the linear double-stranded DNA in bacteriophage capsids is both highly knotted and neatly structured. What is the physical basis of this organization? Here we show evidence from stochastic simulation techniques that suggests that a key element is the tendency of contacting DNA strands to order, as in cholesteric liquid crystals. This interaction favors their preferential juxtaposition at a small twist angle, thus promoting an approximately nematic (and apolar) local order. The ordering effect dramatically impacts the geometry and topology of DNA inside phages. Accounting for this local potential allows us to reproduce the main experimental data on DNA organization in phages, including the cryo-EM observations and detailed features of the spectrum of DNA knots formed inside viral capsids. The DNA knots we observe are strongly delocalized and, intriguingly, this is shown not to interfere with genome ejection out of the phage.