High throughput profile-profile based fold recognition for the entire human proteome

BACKGROUND: In order to maintain the most comprehensive structural annotation databases we must carry out regular updates for each proteome using the latest profile-profile fold recognition methods. The ability to carry out these updates on demand is necessary to keep pace with the regular updates of sequence and structure databases. Providing the highest quality structural models requires the most intensive profile-profile fold recognition methods running with the very latest available sequence databases and fold libraries. However, running these methods on such a regular basis for every sequenced proteome requires large amounts of processing power.In this paper we describe and benchmark the JYDE (Job Yield Distribution Environment) system, which is a meta-scheduler designed to work above cluster schedulers, such as Sun Grid Engine (SGE) or Condor. We demonstrate the ability of JYDE to distribute the load of genomic-scale fold recognition across multiple independent Grid domains. We use the most recent profile-profile version of our mGenTHREADER software in order to annotate the latest version of the Human proteome against the latest sequence and structure databases in as short a time as possible. RESULTS: We show that our JYDE system is able to scale to large numbers of intensive fold recognition jobs running across several independent computer clusters. Using our JYDE system we have been able to annotate 99.9% of the protein sequences within the Human proteome in less than 24 hours, by harnessing over 500 CPUs from 3 independent Grid domains. CONCLUSION: This study clearly demonstrates the feasibility of carrying out on demand high quality structural annotations for the proteomes of major eukaryotic organisms. Specifically, we have shown that it is now possible to provide complete regular updates of profile-profile based fold recognition models for entire eukaryotic proteomes, through the use of Grid middleware such as JYDE.

Virulotyping and antimicrobial resistance typing of salmonella enterica serovars relevant to human health in Europe

The combination of virulence gene and antimicrobial resistance gene typing using DNA arrays is a recently developed genomics-based approach to bacterial molecular epidemiology. We have now applied this technology to 523 Salmonella enterica subsp. enterica strains collected from various host sources and public health and veterinary institutes across nine European countries. The strain set included the five predominant Salmonella serovars isolated in Europe (Enteritidis, Typhimurium, Infantis, Virchow, and Hadar). Initially, these strains were screened for 10 potential virulence factors (avrA, ssaQ, mgtC, siiD, sopB, gipA, sodC1, sopE1, spvC, and bcfC) by polymerase chain reaction. The results indicated that only 14 profiles comprising these genes (virulotypes) were observed throughout Europe. Moreover, most of these virulotypes were restricted to only one (n = 9) or two (n = 4) serovars. The data also indicated that the virulotype did not vary significantly with host source or geographical location. Subsequently, a representative subset of 77 strains was investigated using a microarray designed to detect 102 virulence and 49 resistance determinants. The results confirmed and extended the previous observations using the virulo-polymerase chain reaction screen. Strains belonging to the same serovar grouped together, indicating that the broader virulence-associated gene complement corresponded with the serovar. There were, however, some differences in the virulence gene profiles between strains belonging to an individual serovar. This variation occurred primarily within those virulence genes that were prophage encoded, in fimbrial clusters or in the virulence plasmid. It seems likely that such changes enable Salmonella to adapt to different environmental conditions, which might be reflected in serovar-specific ecology. In this strain subset a number of resistance genes were detected and were serovar restricted to a varying degree. Once again the profiles of those genes encoding resistance were similar or the same for each serovar in all hosts and countries investigated.

Construction of a Festuca pratensis BAC library for map-based cloning in Festulolium substitution lines

Introgression in Festulolium is a potentially powerful tool to isolate genes for a large number of traits which differ between Festuca pratensis Huds. and Lolium perenne L. Not only are hybrids between the two species fertile, but the two genomes can be distinguished by genomic in situ hybridisation and a high frequency of recombination occurs between homoeologous chromosomes and chromosome segments. By a programme of introgression and a series of backcrosses, L. perenne lines have been produced which contain small F. pratensis substitutions. This material is a rich source of polymorphic markers targeted towards any trait carried on the F. pratensis substitution not observed in the L. perenne background. We describe here the construction of an F. pratensis BAC library, which establishes the basis of a map-based cloning strategy in L. perenne. The library contains 49,152 clones, with an average insert size of 112 kbp, providing coverage of 2.5 haploid genome equivalents. We have screened the library for eight amplified fragment length polymorphism (AFLP) derived markers known to be linked to an F. pratensis gene introgressed into L. perenne and conferring a staygreen phenotype as a consequence of a mutation in primary chlorophyll catabolism. While for four of the markers it was possible to identify bacterial artificial chromosome (BAC) clones, the other four AFLPs were too repetitive to enable reliable identification of locus-specific BACs. Moreover, when the four BACs were partially sequenced, no obvious coding regions could be identified. This contrasted to BACs identified using cDNA sequences, when multiple genes were identified on the same BAC.

A SNP-based consensus genetic map for synteny-based trait targeting in faba bean (Vicia faba L.)

Faba bean (Vicia faba L.) is a globally important nitrogen-fixing legume, which is widely grown in a diverse range of environments. In this work, we mine and validate a set of 845 SNPs from the aligned transcriptomes of two contrasting inbred lines. Each V. faba SNP is assigned by BLAST analysis to a single Medicago orthologue. This set of syntenically anchored polymorphisms were then validated as individual KASP assays, classified according to their informativeness and performance on a panel of 37 inbred lines, and the best performing 757 markers used to genotype six mapping populations. The six resulting linkage maps were merged into a single consensus map on which 687 SNPs were placed on six linkage groups, each presumed to correspond to one of the six V. faba chromosomes. This sequence-based consensus map was used to explore synteny with the most closely-related crop species, lentil, and the most closely related fully sequenced genome, Medicago. Large tracts of uninterrupted colinearity were found between faba bean and Medicago, making it relatively straightforward to predict gene content and order in mapped genetic interval. As a demonstration of this, we mapped a flower colour gene to a 2 cM interval of Vf chromosome 2 which was highly collinear with Mt3. The obvious candidate gene from 77 gene models in the collinear Medicago chromosome segment was the previously characterized MtWD40-1 gene (Mt3g092830, Mt3g092840) controlling anthocyanin production in Medicago and re-sequencing of the Vf orthologue showed a putative causative deletion of the entire 5’ end of the gene.