The amphioxus (Branchiostoma floridae) genome contains a highly diversified set of G protein-coupled receptors

<p>Abstract</p> <p>Background</p> <p>G protein-coupled receptors (GPCRs) are one of the largest families of genes in mammals. <it>Branchiostoma floridae </it>(amphioxus) is one of the species most closely related species to vertebrates.</p> <p>Results</p> <p>Mining and phylogenetic analysis of the amphioxus genome showed the presence of at least 664 distinct GPCRs distributed among all the main families of GPCRs; <it>Glutamate (18)</it>, <it>Rhodopsin (570)</it>, <it>Adhesion (37)</it>, <it>Frizzled (6) </it>and <it>Secretin (16)</it>. Surprisingly, the <it>Adhesion </it>GPCR repertoire in amphioxus includes receptors with many new domains not previously observed in this family. We found many <it>Rhodopsin </it>GPCRs from all main groups including many amine and peptide binding receptors and several previously uncharacterized expansions were also identified. This genome has however no genes coding for bitter taste receptors (TAS2), the sweet and umami (TAS1), pheromone (VR1 or VR2) or mammalian olfactory receptors.</p> <p>Conclusion</p> <p>The amphioxus genome is remarkably rich in various GPCR subtypes while the main GPCR groups known to sense exogenous substances (such as Taste 2, mammalian olfactory, nematode chemosensory, gustatory, vomeronasal and odorant receptors) in other bilateral species are absent.</p

SPRIT: Identifying horizontal gene transfer in rooted phylogenetic trees

<p>Abstract</p> <p>Background</p> <p>Phylogenetic trees based on sequences from a set of taxa can be incongruent due to horizontal gene transfer (HGT). By identifying the HGT events, we can reconcile the gene trees and derive a taxon tree that adequately represents the species' evolutionary history. One HGT can be represented by a rooted Subtree Prune and Regraft (<smcaps>R</smcaps>SPR) operation and the number of <smcaps>R</smcaps>SPRs separating two trees corresponds to the minimum number of HGT events. Identifying the minimum number of <smcaps>R</smcaps>SPRs separating two trees is NP-hard, but the problem can be reduced to fixed parameter tractable. A number of heuristic and two exact approaches to identifying the minimum number of <smcaps>R</smcaps>SPRs have been proposed. This is the first implementation delivering an exact solution as well as the intermediate trees connecting the input trees.</p> <p>Results</p> <p>We present the SPR Identification Tool (SPRIT), a novel algorithm that solves the fixed parameter tractable minimum <smcaps>R</smcaps>SPR problem and its GPL licensed Java implementation. The algorithm can be used in two ways, exhaustive search that guarantees the minimum <smcaps>R</smcaps>SPR distance and a heuristic approach that guarantees finding a solution, but not necessarily the minimum one. We benchmarked SPRIT against other software in two different settings, small to medium sized trees i.e. five to one hundred taxa and large trees i.e. thousands of taxa. In the small to medium tree size setting with random artificial incongruence, SPRIT's heuristic mode outperforms the other software by always delivering a solution with a low overestimation of the <smcaps>R</smcaps>SPR distance. In the large tree setting SPRIT compares well to the alternatives when benchmarked on finding a minimum solution within a reasonable time. SPRIT presents both the minimum <smcaps>R</smcaps>SPR distance and the intermediate trees.</p> <p>Conclusions</p> <p>When used in exhaustive search mode, SPRIT identifies the minimum number of <smcaps>R</smcaps>SPRs needed to reconcile two incongruent rooted trees. SPRIT also performs quick approximations of the minimum <smcaps>R</smcaps>SPR distance, which are comparable to, and often better than, purely heuristic solutions. Put together, SPRIT is an excellent tool for identification of HGT events and pinpointing which taxa have been involved in HGT.</p

Mapping the human membrane proteome: a majority of the human membrane proteins can be classified according to function and evolutionary origin

Abstract Background Membrane proteins form key nodes in mediating the cell's interaction with the surroundings, which is one of the main reasons why the majority of drug targets are membrane proteins. Results Here we mined the human proteome and identified the membrane proteome subset using three prediction tools for alpha-helices: Phobius, TMHMM, and SOSUI. This dataset was reduced to a non-redundant set by aligning it to the human genome and then clustered with our own interactive implementation of the ISODATA algorithm. The genes were classified and each protein group was manually curated, virtually evaluating each sequence of the clusters, applying systematic comparisons with a range of databases and other resources. We identified 6,718 human membrane proteins and classified the majority of them into 234 families of which 151 belong to the three major functional groups: receptors (63 groups, 1,352 members), transporters (89 groups, 817 members) or enzymes (7 groups, 533 members). Also, 74 miscellaneous groups with 697 members were determined. Interestingly, we find that 41% of the membrane proteins are singlets with no apparent affiliation or identity to any human protein family. Our results identify major differences between the human membrane proteome and the ones in unicellular organisms and we also show a strong bias towards certain membrane topologies for different functional classes: 77% of all transporters have more than six helices while 60% of proteins with an enzymatic function and 88% receptors, that are not GPCRs, have only one single membrane spanning α-helix. Further, we have identified and characterized new gene families and novel members of existing families. Conclusion Here we present the most detailed roadmap of gene numbers and families to our knowledge, which is an important step towards an overall classification of the entire human proteome. We estimate that 27% of the total human proteome are alpha-helical transmembrane proteins and provide an extended classification together with in-depth investigations of the membrane proteome's functional, structural, and evolutionary features.</p