Circall: fast and accurate methodology for discovery of circular RNAs from paired-end RNA-sequencing data

Background Circular RNA (circRNA) is an emerging class of RNA molecules attracting researchers due to its potential for serving as markers for diagnosis, prognosis, or therapeutic targets of cancer, cardiovascular, and autoimmune diseases. Current methods for detection of circRNA from RNA sequencing (RNA-seq) focus mostly on improving mapping quality of reads supporting the back-splicing junction (BSJ) of a circRNA to eliminate false positives (FPs). We show that mapping information alone often cannot predict if a BSJ-supporting read is derived from a true circRNA or not, thus increasing the rate of FP circRNAs. Results We have developed Circall, a novel circRNA detection method from RNA-seq. Circall controls the FPs using a robust multidimensional local false discovery rate method based on the length and expression of circRNAs. It is computationally highly efficient by using a quasi-mapping algorithm for fast and accurate RNA read alignments. We applied Circall on two simulated datasets and three experimental datasets of human cell-lines. The results show that Circall achieves high sensitivity and precision in the simulated data. In the experimental datasets it performs well against current leading methods. Circall is also substantially faster than the other methods, particularly for large datasets. Conclusions With those better performances in the detection of circRNAs and in computational time, Circall facilitates the analyses of circRNAs in large numbers of samples. Circall is implemented in C++ and R, and available for use at https://www.meb.ki.se/sites/biostatwiki/circall and https://github.com/datngu/Circall.

A community-supported metaproteomic pipeline for improving peptide identifications in hydrothermal vent microbiota

Microorganisms in deep-sea hydrothermal vents provide valuable insights into life under extreme conditions. Mass spectrometry-based proteomics has been widely used to identify protein expression and function. However, the metaproteomic studies in deep-sea microbiota have been constrained largely by the low identification rates of protein or peptide. To improve the efficiency of metaproteomics for hydrothermal vent microbiota, we firstly constructed a microbial gene database (HVentDB) based on 117 public metagenomic samples from hydrothermal vents and proposed a metaproteomic analysis strategy, which takes the advantages of not only the sample-matched metagenome, but also the metagenomic information released publicly in the community of hydrothermal vents. A two-stage false discovery rate method was followed up to control the risk of false positive. By applying our community-supported strategy to a hydrothermal vent sediment sample, about twice as many peptides were identified when compared with the ways against the sample-matched metagenome or the public reference database. In addition, more enriched and explainable taxonomic and functional profiles were detected by the HVentDB-based approach exclusively, as well as many important proteins involved in methane, amino acid, sugar, glycan metabolism and DNA repair, etc. The new metaproteomic analysis strategy will enhance our understanding of microbiota, including their lifestyles and metabolic capabilities in extreme environments. The database HVentDB is freely accessible from http://lilab.life.sjtu.edu.cn:8080/HventDB/main.html.

LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications

Summary We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate method, utilizing a target–decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder’s online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools. Availability and implementation LipidFinder 2.0 is freely available at https://github.com/ODonnell-Lipidomics/LipidFinder and http://lipidmaps.org/resources/tools/lipidfinder. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

1201. Sarcoidosis Candidate Microbes Identified by Next Generation Sequencing

Background Sarcoidosis is an autoimmune disease characterized by granulomatous lung disease with very prominent mediastinal adenopathy. Acid-fast bacteria, fungi, and viruses have been considered as possible causes of sarcoidosis. We used next-generation or deep sequencing to characterize the microbial content of diseased mediastinal lymph nodes from 10 sarcoidosis patients compared to a set of 10 negative-controls. Methods RNA was extracted from fixed paraffinized mediastinal lymph nodes (MLN) from 12 diseased specimens taken from 10 sarcoidosis patients and 2 positive control subjects (TB, MAI), and normal appearing MLN from 10 negative-control subjects (mostly cancer patients). The extracted RNA was sequenced on the Illumina 2500, yielding 125-bp paired-end reads. These reads were aligned to the human genome, human transcriptome, and a nonredundant panmicrobial database. Each experimental sample were compared against the set of 10 negative-controls using the false discovery rate method (q-value). Directed qPCR was performed on all the samples. Results 100-153 million read-pairs were obtained from the 24 sequenced samples (12 sarcoidosis, 10 negative-control, 2 positive-control). Among these, 0.01-1.32% of the reads were microbial, with a trend towards fewer microbial reads in the sarcoidosis group compared to controls (means 66K vs. 457K, p=0.09). Mycobacterial sequence was significantly enriched (q< 0.05) in the MAI but not the TB sample compared to the negative-controls. Among the 12 sarcoidosis samples, sequence mappings were significantly enriched (q< 0.05) for the following genera: fungal, Magnaporthe (N=4 samples) and Debaromyces (1); bacteria, Odoribacter (1) and Granulicella (1); and viral, Roseolovirus (6) and Mardivirus (6). Further metagenomic analysis eliminated Magnaporthe as a candidate. qPCR confirmed the presence of Odoribacter in 2 specimens and Debaromyces in 1. Roseolovirus (HHV6) could not be detected by qPCR in any of the samples. Conclusion We conclude that sequencing is a feasible method for identifying candidate microbes that might trigger sarcoidosis in human subjects. Further research is required to establish or refute the pathogenicity of these organisms in patients with sarcoidosis. Disclosures All Authors: No reported disclosures

Genetically distinct clinical subsets, and associations with asthma and eosinophil abundance, within Eosinophilic Granulomatosis with Polyangiitis

Eosinophilic granulomatosis with polyangiitis (EGPA: formerly Churg-Strauss syndrome) is a rare inflammatory disease of unknown cause. 30% of patients have anti-neutrophil cytoplasm antibodies (ANCA) specific for myeloperoxidase (MPO). We performed a genome-wide association study (GWAS) of EGPA, testing 7.5 million genetic variants in 684 cases and 6,838 controls. Case-control analyses were performed for EGPA as a whole, and stratified by ANCA. To increase power, we used a conditional false discovery rate method to leverage findings from GWASs of related phenotypes. In total, 11 variants were associated with EGPA, two specifically with ANCA-negative EGPA, and one (HLA-DQ) with MPO+ANCA EGPA. Many variants were associated with asthma, eosinophilic and immune-mediated diseases and, strikingly, nine were associated with eosinophil count in the general population. Through Mendelian randomisation, we show that a primary tendency to eosinophilia underlies EGPA susceptibility. We demonstrate that EGPA comprises two genetically and clinically distinct syndromes, with ANCA-negative EGPA genetically more similar to asthma. MPO+ ANCA EGPA is an eosinophilic autoimmune disease sharing certain clinical features and an MHC association with MPO+ ANCA-associated vasculitis, while ANCA-negative EGPA may instead have a mucosal/barrier dysfunction origin. Five identified candidate genes are targets of therapies in development, supporting their exploration in EGPA.

The Completeness and Reliability of Threshold and False-discovery Rate Source Extraction Algorithms for Compact Continuum Sources

The process of determining the number and characteristics of sources in astronomical images is so fundamental to a large range of astronomical problems that it is perhaps surprising that no standard procedure has ever been defined that has well-understood properties with a high degree of statistical rigour on completeness and reliability. The Evolutionary Map of the Universe (EMU) survey with the Australian Square Kilometre Array Pathfinder (ASKAP), a continuum survey of the Southern Hemisphere up to declination +30°, aims to utilise an automated source identification and measurement approach that is demonstrably optimal, to maximise the reliability, utility and robustness of the resulting radio source catalogues. A key stage in source extraction methods is the background estimation (background level and noise level) and the choice of a threshold high enough to reject false sources, yet not so high that the catalogues are significantly incomplete. In this analysis, we present results from testing the SExtractor, Selavy (Duchamp), and SFIND source extraction tools on simulated data. In particular, the effects of background estimation, threshold and false-discovery rate settings are explored. For parameters that give similar completeness, we find the false-discovery rate method employed by SFIND results in a more reliable catalogue compared to the peak threshold methods of SExtractor and Selavy.

Tagging SNPs in REN, AGTR1 and AGTR2 genes and response of renin activity, angiotensin II and aldosterone concentrations to antihypertensive treatment in Kazakans

Hypothesis: Polymorphisms of REN, AGTR1 and AGTR2 may be associated with responses of renin–angiotensin–aldosterone system (RAAS) activity phenotypes to angiotensin-converting enzyme inhibitor (ACEI) antihypertensive treatment. Materials and methods: A total of 400 first diagnosed Kazak hypertensives were randomly allocated to two groups and received a 3-week course of either captopril and atenolol as monotherapy under double blinding. Genotype–phenotype association analyses were performed by covariance analyses between baseline level and responses of blood pressure, renin, angiotensin II and aldosterone concentrations with tagging single nucleotide polymorphisms (SNPs) in REN, AGTR1 and AGTR2 genes. A false discovery rate method was used to adjust multiple testing. Results: After adjustment for multiple testing, we found that the G allele of rs6676670 (T/G) in intron 1 of REN was significantly associated with higher baseline aldosterone concentrations ( p < 0.0001, explained variance (EV) = 2.3%). Significant associations after adjustments were also found between the A allele of rs2887284, with higher baseline renin activity ( p = 0.022, EV = 1.0%), higher responses of renin ( p = 0.018 EV = 5.4%), and higher responses of angiotensin II ( p = 0.0255, EV = 3.13%) to the treatment of ACEI. The carriers of the A allele of rs2887284 appeared to be more sensitive to the ACEI treatment. Conclusion: rs2887284 in intron 9 of REN is associated with the response of renin and angiotensin II levels to ACEI treatment.

Association of Interleukin 23 Receptor Polymorphisms with Anti-Topoisomerase-I Positivity and Pulmonary Hypertension in Systemic Sclerosis

Objective.IL23R has been identified as a susceptibility gene for development of multiple autoimmune diseases. We investigated the possible association of IL23R with systemic sclerosis (SSc), an autoimmune disease that leads to the development of cutaneous and visceral fibrosis.Methods.We tested 9 single-nucleotide polymorphisms (SNP) in IL23R for association with SSc in a cohort of 1402 SSc cases and 1038 controls. IL23R SNP tested were previously identified as SNP showing associations with inflammatory bowel disease.Results.Case-control comparisons revealed no statistically significant differences between patients and healthy controls with any of the IL23R polymorphisms. Analyses of subsets of SSc patients showed that rs11209026 (Arg381Gln variant) was associated with anti-topoisomerase I antibody (ATA)-positive SSc (p = 0.001)) and rs11465804 SNP was associated with diffuse and ATA-positive SSc (p = 0.0001, p = 0.0026, respectively). These associations remained significant after accounting for multiple comparisons using the false discovery rate method. Wild-type genotype at both rs11209026 and rs11465804 showed significant protection against the presence of pulmonary hypertension (PHT). (p = 3×10−5, p = 1×10−5, respectively).Conclusion.Polymorphisms in IL23R are associated with susceptibility to ATA-positive SSc and protective against development of PHT in patients with SSc.