Complete genome sequence of the Clostridium difficile laboratory strain 630Δerm reveals differences from strain 630, including translocation of the mobile element CTn5

Background

Clostridium difficile strain 630Δerm is a spontaneous erythromycin sensitive derivative of the reference strain 630 obtained by serial passaging in antibiotic-free media. It is widely used as a defined and tractable C. difficile strain. Though largely similar to the ancestral strain, it demonstrates phenotypic differences that might be the result of underlying genetic changes. Here, we performed a de novo assembly based on single-molecule real-time sequencing and an analysis of major methylation patterns.

Results

In addition to single nucleotide polymorphisms and various indels, we found that the mobile element CTn5 is present in the gene encoding the methyltransferase rumA rather than adhesin CD1844 where it is located in the reference strain.

Conclusions

Together, the genetic features identified in this study may help to explain at least part of the phenotypic differences. The annotated genome sequence of this lab strain, including the first analysis of major methylation patterns, will be a valuable resource for genetic research on C. difficile.

Electronic supplementary material

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Multiple antibiotic susceptibility of polyphosphate kinase mutants (ppk1 and ppk2) from Pseudomonas aeruginosa PAO1 as revealed by global phenotypic analysis

Background

Pseudomonas aeruginosa is known to be a multidrug resistant opportunistic pathogen. Particularly, P. aeruginosa PAO1 polyphosphate kinase mutant (ppk1) is deficient in motility, quorum sensing, biofilm formation and virulence.

Findings

By using Phenotypic Microarrays (PM) we analyzed near 2000 phenotypes of P. aeruginosa PAO1 polyP kinase mutants (ppk1 and ppk2). We found that both ppk mutants shared most of the phenotypic changes and interestingly many of them related to susceptibility toward numerous and different type of antibiotics such as Ciprofloxacin, Chloramphenicol and Rifampicin.

Conclusions

Combining the fact that ppk1 mutants have reduced virulence and are more susceptible to antibiotics, polyP synthesis and particularly PPK1, is a good target for the design of molecules with anti-virulence and anti-persistence properties.

Electronic supplementary material

The online version of this article (doi:10.1186/s40659-015-0012-0) contains supplementary material, which is available to authorized users.     

seqCNA: an R package for DNA copy number analysis in cancer using high-throughput sequencing

Background

Deviations in the amount of genomic content that arise during tumorigenesis, called copy number alterations, are structural rearrangements that can critically affect gene expression patterns. Additionally, copy number alteration profiles allow insight into cancer discrimination, progression and complexity. On data obtained from high-throughput sequencing, improving quality through GC bias correction and keeping false positives to a minimum help build reliable copy number alteration profiles.

Results

We introduce seqCNA, a parallelized R package for an integral copy number analysis of high-throughput sequencing cancer data. The package includes novel methodology on (i) filtering, reducing false positives, and (ii) GC content correction, improving copy number profile quality, especially under great read coverage and high correlation between GC content and copy number. Adequate analysis steps are automatically chosen based on availability of paired-end mapping, matched normal samples and genome annotation.

Conclusions

seqCNA, available through Bioconductor, provides accurate copy number predictions in tumoural data, thanks to the extensive filtering and better GC bias correction, while providing an integrated and parallelized workflow.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-178) contains supplementary material, which is available to authorized users.     

Characterization of the MLO gene family in Rosaceae and gene expression analysis in Malus domestica

Background

Powdery mildew (PM) is a major fungal disease of thousands of plant species, including many cultivated Rosaceae. PM pathogenesis is associated with up-regulation of MLO genes during early stages of infection, causing down-regulation of plant defense pathways. Specific members of the MLO gene family act as PM-susceptibility genes, as their loss-of-function mutations grant durable and broad-spectrum resistance.

Results

We carried out a genome-wide characterization of the MLO gene family in apple, peach and strawberry, and we isolated apricot MLO homologs through a PCR-approach. Evolutionary relationships between MLO homologs were studied and syntenic blocks constructed. Homologs that are candidates for being PM susceptibility genes were inferred by phylogenetic relationships with functionally characterized MLO genes and, in apple, by monitoring their expression following inoculation with the PM causal pathogen Podosphaera leucotricha.

Conclusions

Genomic tools available for Rosaceae were exploited in order to characterize the MLO gene family. Candidate MLO susceptibility genes were identified. In follow-up studies it can be investigated whether silencing or a loss-of-function mutations in one or more of these candidate genes leads to PM resistance.

Electronic supplementary material

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Comparative sequencing analysis reveals high genomic concordance between matched primary and metastatic colorectal cancer lesions

Background

Colorectal cancer is the second leading cause of cancer death in the United States, with over 50,000 deaths estimated in 2014. Molecular profiling for somatic mutations that predict absence of response to anti-EGFR therapy has become standard practice in the treatment of metastatic colorectal cancer; however, the quantity and type of tissue available for testing is frequently limited. Further, the degree to which the primary tumor is a faithful representation of metastatic disease has been questioned. As next-generation sequencing technology becomes more widely available for clinical use and additional molecularly targeted agents are considered as treatment options in colorectal cancer, it is important to characterize the extent of tumor heterogeneity between primary and metastatic tumors.

Results

We performed deep coverage, targeted next-generation sequencing of 230 key cancer-associated genes for 69 matched primary and metastatic tumors and normal tissue. Mutation profiles were 100% concordant for KRAS, NRAS, and BRAF, and were highly concordant for recurrent alterations in colorectal cancer. Additionally, whole genome sequencing of four patient trios did not reveal any additional site-specific targetable alterations.

Conclusions

Colorectal cancer primary tumors and metastases exhibit high genomic concordance. As current clinical practices in colorectal cancer revolve around KRAS, NRAS, and BRAF mutation status, diagnostic sequencing of either primary or metastatic tissue as available is acceptable for most patients. Additionally, consistency between targeted sequencing and whole genome sequencing results suggests that targeted sequencing may be a suitable strategy for clinical diagnostic applications.

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RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets

Background

Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck.

Results

To overcome the bottleneck of data analysis, we developed an automated computational workflow called RIEMS – Reliable Information Extraction from Metagenomic Sequence datasets. RIEMS assigns every individual read sequence within a dataset taxonomically by cascading different sequence analyses with decreasing stringency of the assignments using various software applications. After completion of the analyses, the results are summarised in a clearly structured result protocol organised taxonomically. The high accuracy and performance of RIEMS analyses were proven in comparison with other tools for metagenomics data analysis using simulated sequencing read datasets.

Conclusions

RIEMS has the potential to fill the gap that still exists with regard to data analysis for metagenomics studies. The usefulness and power of RIEMS for the analysis of genuine sequencing datasets was demonstrated with an early version of RIEMS in 2011 when it was used to detect the orthobunyavirus sequences leading to the discovery of Schmallenberg virus.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0503-6) contains supplementary material, which is available to authorized users.     

Anthocyanin biosynthetic genes in Brassica rapa

Background

Anthocyanins are a group of flavonoid compounds. As a group of important secondary metabolites, they perform several key biological functions in plants. Anthocyanins also play beneficial health roles as potentially protective factors against cancer and heart disease. To elucidate the anthocyanin biosynthetic pathway in Brassica rapa, we conducted comparative genomic analyses between Arabidopsis thaliana and B. rapa on a genome-wide level.

Results

In total, we identified 73 genes in B. rapa as orthologs of 41 anthocyanin biosynthetic genes in A. thaliana. In B. rapa, the anthocyanin biosynthetic genes (ABGs) have expanded and most genes exist in more than one copy. The anthocyanin biosynthetic structural genes have expanded through whole genome and tandem duplication in B. rapa. More structural genes located upstream of the anthocyanin biosynthetic pathway have been retained than downstream. More negative regulatory genes are retained in the anthocyanin biosynthesis regulatory system of B. rapa.

Conclusions

These results will promote an understanding of the genetic mechanism of anthocyanin biosynthesis, as well as help the improvement of the nutritional quality of B. rapa through the breeding of high anthocyanin content varieties.

Electronic supplementary material

The online version of this article (doi: 10.1186/1471-2164-15-426) contains supplementary material, which is available to authorized users.     

The genome of the Tiger Milk mushroom,Lignosus rhinocerotis,provides insights into the genetic basis of its medicinal properties

Background

The sclerotium of Lignosus rhinocerotis (Cooke) Ryvarden or Tiger milk mushroom (Polyporales, Basidiomycota) is a valuable folk medicine for indigenous peoples in Southeast Asia. Despite the increasing interest in this ethnobotanical mushroom, very little is known about the molecular and genetic basis of its medicinal and nutraceutical properties.

Results

The de novo assembled 34.3 Mb L. rhinocerotis genome encodes 10,742 putative genes with 84.30% of them having detectable sequence similarities to others available in public databases. Phylogenetic analysis revealed a close evolutionary relationship of L. rhinocerotis to Ganoderma lucidum, Dichomitus squalens, and Trametes versicolor in the core polyporoid clade. The L. rhinocerotis genome encodes a repertoire of enzymes engaged in carbohydrate and glycoconjugate metabolism, along with cytochrome P450s, putative bioactive proteins (lectins and fungal immunomodulatory proteins) and laccases. Other genes annotated include those encoding key enzymes for secondary metabolite biosynthesis, including those from polyketide, nonribosomal peptide, and triterpenoid pathways. Among them, the L. rhinocerotis genome is particularly enriched with sesquiterpenoid biosynthesis genes.

Conclusions

The genome content of L. rhinocerotis provides insights into the genetic basis of its reported medicinal properties as well as serving as a platform to further characterize putative bioactive proteins and secondary metabolite pathway enzymes and as a reference for comparative genomics of polyporoid fungi.

Electronic supplementary material

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Exploiting single-molecule transcript sequencing for eukaryotic gene prediction

We develop a method to predict and validate gene models using PacBio single-molecule, real-time (SMRT) cDNA reads. Ninety-eight percent of full-insert SMRT reads span complete open reading frames. Gene model validation using SMRT reads is developed as automated process. Optimized training and prediction settings and mRNA-seq noise reduction of assisting Illumina reads results in increased gene prediction sensitivity and precision. Additionally, we present an improved gene set for sugar beet (Beta vulgaris) and the first genome-wide gene set for spinach (Spinacia oleracea). The workflow and guidelines are a valuable resource to obtain comprehensive gene sets for newly sequenced genomes of non-model eukaryotes.

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Genomic and transcriptomic analysis of the endophytic fungus Pestalotiopsis fici reveals its lifestyle and high potential for synthesis of natural products

Background

In recent years, the genus Pestalotiopsis is receiving increasing attention, not only because of its economic impact as a plant pathogen but also as a commonly isolated endophyte which is an important source of bioactive natural products. Pestalotiopsis fici Steyaert W106-1/CGMCC3.15140 as an endophyte of tea produces numerous novel secondary metabolites, including chloropupukeananin, a derivative of chlorinated pupukeanane that is first discovered in fungi. Some of them might be important as the drug leads for future pharmaceutics.

Results

Here, we report the genome sequence of the endophytic fungus of tea Pestalotiopsis fici W106-1/CGMCC3.15140. The abundant carbohydrate-active enzymes especially significantly expanding pectinases allow the fungus to utilize the limited intercellular nutrients within the host plants, suggesting adaptation of the fungus to endophytic lifestyle. The P. fici genome encodes a rich set of secondary metabolite synthesis genes, including 27 polyketide synthases (PKSs), 12 non-ribosomal peptide synthases (NRPSs), five dimethylallyl tryptophan synthases, four putative PKS-like enzymes, 15 putative NRPS-like enzymes, 15 terpenoid synthases, seven terpenoid cyclases, seven fatty-acid synthases, and five hybrids of PKS-NRPS. The majority of these core enzymes distributed into 74 secondary metabolite clusters. The putative Diels-Alderase genes have undergone expansion.

Conclusion

The significant expansion of pectinase encoding genes provides essential insight in the life strategy of endophytes, and richness of gene clusters for secondary metabolites reveals high potential of natural products of endophytic fungi.

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An efficient algorithm to explore liquid association on a genome-wide scale

Background

The growing wealth of public available gene expression data has made the systemic studies of how genes interact in a cell become more feasible. Liquid association (LA) describes the extent to which coexpression of two genes may vary based on the expression level of a third gene (the controller gene). However, genome-wide application has been difficult and resource-intensive. We propose a new screening algorithm for more efficient processing of LA estimation on a genome-wide scale and apply its use to a Saccharomyces cerevisiae data set.

Results

On a test subset of the data, the fast screening algorithm achieved >99.8% agreement with the exhaustive search of LA values, while reduced run time by 81–93 %. Using a well-known yeast cell-cycle data set with 6,178 genes, we identified triplet combinations with significantly large LA values. In an exploratory gene set enrichment analysis, the top terms for the controller genes in these triplets with large LA values are involved in some of the most fundamental processes in yeast such as energy regulation, transportation, and sporulation.

Conclusion

In summary, in this paper we propose a novel, efficient algorithm to explore LA on a genome-wide scale and identified triplets of interest in cell cycle pathways using the proposed method in a yeast data set. A software package named fastLiquidAssociation for implementing the algorithm is available through http://www.bioconductor.org.

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Construction of a virtual Mycobacterium tuberculosis consensus genome and its application to data from a next generation sequencer

Background

Although Mycobacterium tuberculosis isolates are consisted of several different lineages and the epidemiology analyses are usually assessed relative to a particular reference genome, M. tuberculosis H37Rv, which might introduce some biased results. Those analyses are essentially based genome sequence information of M. tuberculosis and could be performed in sillico in theory, with whole genome sequence (WGS) data available in the databases and obtained by next generation sequencers (NGSs). As an approach to establish higher resolution methods for such analyses, whole genome sequences of the M. tuberculosis complexes (MTBCs) strains available on databases were aligned to construct virtual reference genome sequences called the consensus sequence (CS), and evaluated its feasibility in in sillico epidemiological analyses.

Results

The consensus sequence (CS) was successfully constructed and utilized to perform phylogenetic analysis, evaluation of read mapping efficacy, which is crucial for detecting single nucleotide polymorphisms (SNPs), and various MTBC typing methods virtually including spoligotyping, VNTR, Long sequence polymorphism and Beijing typing. SNPs detected based on CS, in comparison with H37Rv, were utilized in concatemer-based phylogenetic analysis to determine their reliability relative to a phylogenetic tree based on whole genome alignment as the gold standard. Statistical comparison of phylogenic trees based on CS with that of H37Rv indicated the former showed always better results that that of later. SNP detection and concatenation with CS was advantageous because the frequency of crucial SNPs distinguishing among strain lineages was higher than those of H37Rv. The number of SNPs detected was lower with the consensus than with the H37Rv sequence, resulting in a significant reduction in computational time. Performance of each virtual typing was satisfactory and accorded with those published when those are available.

Conclusions

These results indicated that virtual CS constructed from genome sequence data is an ideal approach as a reference for MTBC studies.

Electronic supplementary material

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