Genomic characterisation of the effector complement of the potato cyst nematode Globodera pallida

Background

The potato cyst nematode Globodera pallida has biotrophic interactions with its host. The nematode induces a feeding structure – the syncytium – which it keeps alive for the duration of the life cycle and on which it depends for all nutrients required to develop to the adult stage. Interactions of G. pallida with the host are mediated by effectors, which are produced in two sets of gland cells. These effectors suppress host defences, facilitate migration and induce the formation of the syncytium.

Results

The recent completion of the G. pallida genome sequence has allowed us to identify the effector complement from this species. We identify 128 orthologues of effectors from other nematodes as well as 117 novel effector candidates. We have used in situ hybridisation to confirm gland cell expression of a subset of these effectors, demonstrating the validity of our effector identification approach. We have examined the expression profiles of all effector candidates using RNAseq; this analysis shows that the majority of effectors fall into one of three clusters of sequences showing conserved expression characteristics (invasive stage nematode only, parasitic stage only or invasive stage and adult male only). We demonstrate that further diversity in the effector pool is generated by alternative splicing. In addition, we show that effectors target a diverse range of structures in plant cells, including the peroxisome. This is the first identification of effectors from any plant pathogen that target this structure.

Conclusion

This is the first genome scale search for effectors, combined to a life-cycle expression analysis, for any plant-parasitic nematode. We show that, like other phylogenetically unrelated plant pathogens, plant parasitic nematodes deploy hundreds of effectors in order to parasitise plants, with different effectors required for different phases of the infection process.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

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Genome Wide Analysis for Searching Novel Markers to Rapidly Identify Clostridium Strains

Microbial classification is based largely on the 16S rRNA (rrs) gene sequence, which is conserved throughout the prokaryotic domain. The Ribosomal Database Project (RDP) has become a reference point for almost all practical purposes. The use of this gene is limited by the fact that it can be used to identify only to the extent to what has been known and is available in the RDP. In order to identify an organism whose rrs is not present in the RDP database, we need to generate novel markers to place the unknown on the evolutionary map. Here, sequenced genomes of 27 Clostridium strains belonging to 9 species have been used to identify two sets of genes: (1) common to most of the species, and (2) unique to a species. Combinations of genes (recN, dnaJ, secA, mutS, and/or grpE) and their unique restriction endonuclease digestion (AluI, BfaI and/or Tru9I) patterns have been established to rapidly identify Clostridium species. This strategy for identifying novel markers can be extended to all other organisms and diagnostic applications.

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Local synthesis of interferon-alpha in lupus nephritis is associated with type I interferons signature and LMP7 induction in renal tubular epithelial cells

IntroductionType I interferons are pivotal in the activation of autoimmune response in systemic lupus erythematous. However, the pathogenic role of interferon-alpha in patients affected by lupus nephritis remains uncertain. The aim of our study was to investigate the presence of a specific interferon signature in lupus nephritis and the effects of interferon-alpha at renal level.MethodsWe performed immunohistochemical analysis for MXA-protein and in situ hybridization to detect interferon-alpha signature and production in human lupus nephritis. Through microarray studies, we analyzed the gene expression profile of renal tubular epithelial cells, stimulated with interferon-alpha. We validated microarray results through real-time polymerase chain reaction, flow cytometry on renal tubular epithelial cells, and through immunohistochemical analysis and confocal microscopy on renal biopsies.ResultsType I interferons signature was characterized by MXA-specific staining in renal tubular epithelial cells; in addition, in situ hybridization showed that renal tubular epithelial cells were the major producers of interferon-alpha, indicating a potential autocrine effect. Whole-genome expression profile showed interferon-alpha induced up-regulation of genes involved in innate immunity, protein ubiquitination and switching to immunoproteasome. In accordance with the in vitro data, class IV lupus nephritis showed up-regulation of the immunoproteasome subunit LMP7 in tubular epithelial cells associated with type I interferon signature.ConclusionsOur data indicate that type I interferons might have a pathogenic role in lupus nephritis characterized by an autocrine effect of interferon-alpha on renal tubular epithelial cells. Therefore we hypothesize that inhibition of type I interferons might represent a therapeutic target to prevent tubulo-interstitial damage in patients with lupus nephritis.

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Sequence-based ultra-dense genetic and physical maps reveal structural variations of allopolyploid cotton genomes

BackgroundSNPs are the most abundant polymorphism type, and have been explored in many crop genomic studies, including rice and maize. SNP discovery in allotetraploid cotton genomes has lagged behind that of other crops due to their complexity and polyploidy. In this study, genome-wide SNPs are detected systematically using next-generation sequencing and efficient SNP genotyping methods, and used to construct a linkage map and characterize the structural variations in polyploid cotton genomes.ResultsWe construct an ultra-dense inter-specific genetic map comprising 4,999,048 SNP loci distributed unevenly in 26 allotetraploid cotton linkage groups and covering 4,042 cM. The map is used to order tetraploid cotton genome scaffolds for accurate assembly of G. hirsutum acc. TM-1. Recombination rates and hotspots are identified across the cotton genome by comparing the assembled draft sequence and the genetic map. Using this map, genome rearrangements and centromeric regions are identified in tetraploid cotton by combining information from the publicly-available G. raimondii genome with fluorescent in situ hybridization analysis.ConclusionsWe report the genotype-by-sequencing method used to identify millions of SNPs between G. hirsutum and G. barbadense. We construct and use an ultra-dense SNP map to correct sequence mis-assemblies, merge scaffolds into pseudomolecules corresponding to chromosomes, detect genome rearrangements, and identify centromeric regions in allotetraploid cottons. We find that the centromeric retro-element sequence of tetraploid cotton derived from the D subgenome progenitor might have invaded the A subgenome centromeres after allotetrapolyploid formation. This study serves as a valuable genomic resource for genetic research and breeding of cotton.

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Comparative population genomics reveals the domestication history of the peach,Prunus persica,and human influences on perennial fruit crops

Background

Recently, many studies utilizing next generation sequencing have investigated plant evolution and domestication in annual crops. Peach, Prunus persica, is a typical perennial fruit crop that has ornamental and edible varieties. Unlike other fruit crops, cultivated peach includes a large number of phenotypes but few polymorphisms. In this study, we explore the genetic basis of domestication in peach and the influence of humans on its evolution.

Results

We perform large-scale resequencing of 10 wild and 74 cultivated peach varieties, including 9 ornamental, 23 breeding, and 42 landrace lines. We identify 4.6 million SNPs, a large number of which could explain the phenotypic variation in cultivated peach. Population analysis shows a single domestication event, the speciation of P. persica from wild peach. Ornamental and edible peach both belong to P. persica, along with another geographically separated subgroup, Prunus ferganensis.We identify 147 and 262 genes under edible and ornamental selection, respectively. Some of these genes are associated with important biological features. We perform a population heterozygosity analysis in different plants that indicates that free recombination effects could affect domestication history. By applying artificial selection during the domestication of the peach and facilitating its asexual propagation, humans have caused a sharp decline of the heterozygote ratio of SNPs.

Conclusions

Our analyses enhance our knowledge of the domestication history of perennial fruit crops, and the dataset we generated could be useful for future research on comparative population genomics.

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Comparative genomics reveals molecular features unique to the songbird lineage

Background

Songbirds (oscine Passeriformes) are among the most diverse and successful vertebrate groups, comprising almost half of all known bird species. Identifying the genomic innovations that might be associated with this success, as well as with characteristic songbird traits such as vocal learning and the brain circuits that underlie this behavior, has proven difficult, in part due to the small number of avian genomes available until recently. Here we performed a comparative analysis of 48 avian genomes to identify genomic features that are unique to songbirds, as well as an initial assessment of function by investigating their tissue distribution and predicted protein domain structure.

Results

Using BLAT alignments and gene synteny analysis, we curated a large set of Ensembl gene models that were annotated as novel or duplicated in the most commonly studied songbird, the Zebra finch (Taeniopygia guttata), and then extended this analysis to 47 additional avian and 4 non-avian genomes. We identified 10 novel genes uniquely present in songbird genomes. A refined map of chromosomal synteny disruptions in the Zebra finch genome revealed that the majority of these novel genes localized to regions of genomic instability associated with apparent chromosomal breakpoints. Analyses of in situ hybridization and RNA-seq data revealed that a subset of songbird-unique genes is expressed in the brain and/or other tissues, and that 2 of these (YTHDC2L1 and TMRA) are highly differentially expressed in vocal learning-associated nuclei relative to the rest of the brain.

Conclusions

Our study reveals novel genes unique to songbirds, including some that may subserve their unique vocal control system, substantially improves the quality of Zebra finch genome annotations, and contributes to a better understanding of how genomic features may have evolved in conjunction with the emergence of the songbird lineage.

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Combined image and genomic analysis of high-grade serous ovarian cancer reveals PTEN loss as a common driver event and prognostic classifier

Background

TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events.

Results

Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort.

Conclusion

PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.

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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.

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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.

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De novo ChIP-seq analysis

Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical tests enabling motif discovery without the use of a reference genome. We validate the performance of our method using human and mouse data. Analysis of fly data indicates that our method outperforms alignment based methods that utilize closely related species.

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Genome-wide next-generation DNA and RNA sequencing reveals a mutation that perturbs splicing of the phosphatidylinositol glycan anchor biosynthesis class H gene (PIGH) and causes arthrogryposis in Belgian Blue cattle

Background

Cattle populations are characterized by regular outburst of genetic defects as a result of the extensive use of elite sires. The causative genes and mutations can nowadays be rapidly identified by means of genome-wide association studies combined with next generation DNA sequencing, provided that the causative mutations are conventional loss-of-function variants. We show in this work how the combined use of next generation DNA and RNA sequencing allows for the rapid identification of otherwise difficult to identify splice-site variants.

Results

We report the use of haplotype-based association mapping to identify a locus on bovine chromosome 10 that underlies autosomal recessive arthrogryposis in Belgian Blue Cattle. We identify 31 candidate mutations by resequencing the genome of four cases and 15 controls at ~10-fold depth. By analyzing RNA-Seq data from a carrier fetus, we observe skipping of the second exon of the PIGH gene, which we confirm by RT-PCR to be fully penetrant in tissues from affected calves. We identify - amongst the 31 candidate variants - a C-to-G transversion in the first intron of the PIGH gene (c211-10C > G) that is predicted to affect its acceptor splice-site. The resulting PIGH protein is likely to be non-functional as it lacks essential domains, and hence to cause arthrogryposis.

Conclusions

This work illustrates how the growing arsenal of genome exploration tools continues to accelerate the identification of an even broader range of disease causing mutations, therefore improving the management and control of genetic defects in livestock.

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