Aerobic methanotrophic bacteria consume methane as it diffuses away from methanogenic zones of soil and sediment. They act as a biofilter to reduce methane emissions to the atmosphere, and they are therefore targets in strategies to combat global climate change. No cultured methanotroph grows optimally below pH 5, but some environments with active methane cycles are very acidic. Here we describe an extremely acidophilic methanotroph that grows optimally at pH 2.0-2.5. Unlike the known methanotrophs, it does not belong to the phylum Proteobacteria but rather to the Verrucomicrobia, a widespread and diverse bacterial phylum that primarily comprises uncultivated species with unknown genotypes. Analysis of its draft genome detected genes encoding particulate methane monooxygenase that were homologous to genes found in methanotrophic proteobacteria. However, known genetic modules for methanol and formaldehyde oxidation were incomplete or missing, suggesting that the bacterium uses some novel methylotrophic pathways. Phylogenetic analysis of its three pmoA genes (encoding a subunit of particulate methane monooxygenase) placed them into a distinct cluster from proteobacterial homologues. This indicates an ancient divergence of Verrucomicrobia and Proteobacteria methanotrophs rather than a recent horizontal gene transfer of methanotrophic ability. The findings show that methanotrophy in the Bacteria is more taxonomically, ecologically and genetically diverse than previously thought, and that previous studies have failed to assess the full diversity of methanotrophs in acidic environments.

Although transcription and pre-mRNA processing are colocalized in eukaryotic nuclei, molecules linking these processes have not previously been described. We have identified four novel rat proteins by their ability to interact with the repetitive C-terminal domain (CTD) of RNA polymerase II in a yeast two-hybrid assay. A yeast homolog of one of the rat proteins has also been shown to interact with the CTD. These CTD-binding proteins are all similar to the SR (serine/arginine-rich) family of proteins that have been shown to be involved in constitutive and regulated splicing. In addition to alternating Ser-Arg domains, these proteins each contain discrete N-terminal or C-terminal CTD-binding domains. We have identified SR-related proteins in a complex that can be immunoprecipitated from nuclear extracts with antibodies directed against RNA polymerase II. In addition, in vitro splicing is inhibited either by an antibody directed against the CTD or by wild-type but not mutant CTD peptides. Thus, these results suggest that the CTD and a set of CTDbinding proteins may act to physically and functionally link transcription and pre-mRNA processing.The C-terminal domain of the largest subunit of RNA polymerase II (CTD) consists of tandem repeats of the consensus sequence Tyr-Ser-Pro-Thr-Ser-Pro-Ser (1, 2). Deletion studies demonstrated that the ClD is essential for cell growth (3-6), but the nature of this essential function is not known. The CID is only found on RNA polymerase II (pol II), suggesting that it plays a unique role in mRNA biogenesis (7 Despite identification of interaction partners, the role of the CTD in transcription remains unclear. The CTD is not required for either basalV(14, 15) or activated (16, 17) transcription of some genes in vitro. Furthermore, inhibition of CTD kinase does not block in vitro transcription from the adenovirus major late promoter or from a GAL4 VP16-activated promoter (18,19). Thus, these results indicate that the CTD is not essential for specific initiation at some promoters.CTD function may be required for postinitiation steps in the biogenesis of mRNA. O'Brien et al. (20) have demonstrated that several genes contain paused pol IIA complexes that can reenter the elongation mode coincident with CTD phosphorylation. In yeast, CTD-truncated pol II synthesizes an excess of GAL4-induced promoter proximal transcripts (D. L. Bentley, personal communication). Thus, these results argue that the CTD plays an important role subsequent to initiation. While the CTD has previously been proposed to function in premRNA processing (refs. 7 and 21 and H. Rienhoff and J. Boeke, personal communication), no experimental data have yet supported these models.We used the yeast two-hybrid system (22) to identify proteins that interact with the CTD. This unbiased approach did not yield proteins that are expected to be involved in transcription initiation, like TBP or the SRBs, but rather a set of proteins similar to RNA processing factors. In this paper we report the identification and characte...

BackgroundHevea brasiliensis, a member of the Euphorbiaceae family, is the major commercial source of natural rubber (NR). NR is a latex polymer with high elasticity, flexibility, and resilience that has played a critical role in the world economy since 1876.ResultsHere, we report the draft genome sequence of H. brasiliensis. The assembly spans ~1.1 Gb of the estimated 2.15 Gb haploid genome. Overall, ~78% of the genome was identified as repetitive DNA. Gene prediction shows 68,955 gene models, of which 12.7% are unique to Hevea. Most of the key genes associated with rubber biosynthesis, rubberwood formation, disease resistance, and allergenicity have been identified.ConclusionsThe knowledge gained from this genome sequence will aid in the future development of high-yielding clones to keep up with the ever increasing need for natural rubber.

We investigate a very simple model describing the evolution of protein-protein interaction networks via duplication and divergence. The model exhibits a remarkably rich behavior depending on a single parameter, the probability to retain a duplicated link during divergence. When this parameter is large, the network growth is not self-averaging and an average node degree increases algebraically. The lack of self-averaging results in a great diversity of networks grown out of the same initial condition. When less than a half of links are (on average) preserved after divergence, the growth is selfaveraging, the average degree increases very slowly or tends to a constant, and a degree distribution has a power-law tail. The predicted degree distributions are in a very good agreement with the distributions observed in real protein networks.