Genomic Reads Research Articles

Pandemic analysis of infection and death correlated with genomic open reading frame 10 mutation in severe acute respiratory syndrome coronavirus 2 victims.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues the pandemic spread of the coronavirus disease 2019 (COVID-19), over 60 million people confirmed infected and at least 1.8 million dead. One of the most known features of this RNA virus is its easiness to be mutated. In late 2020, almost no region of this SARS-CoV-2 genome can be found completely conserved within the original Wuhan coronavirus. Any information of the SARS-CoV-2 variants emerged through as time being will be evaluated for diagnosis, treatment, and prevention of COVID-19. We extracted more than two million data of SARS-CoV-2 infected patients from the open COVID-19 dashboard. The sequences of the 38-amino acid putative open reading frame 10 (Orf10) protein within infected patients were gathered output through from National Center for Biotechnology Information and the mutation rates in each position were analyzed and presented in each month of 2020. The mutation rates of A8 and V30 within Orf10 are displayed in selected counties: United States, India, German, and Japan. The numbers of COVID-19 patients are correlated to the death numbers, but not with the death rates (stable and <3%). The amino acid positions locating at A8(F/G/L), I13, and V30(L) within the Orf10 sequence stay the highest mutation rate; N5, N25, and N36 rank at the lowest one. A8F expressed highly dominant in Japan (over 80%) and German (around 40%) coming to the end of 2020, but no significant finding in other countries. The results demonstrate via mutation analysis of Orf10 can be further combined with advanced tools such as molecular simulation, artificial intelligence, and biosensors that can practically revealed for protein interactions and thus to imply the authentic Orf10 function of SARS-CoV-2 in the future.

Genome sequence, transcriptome, and annotation of rodent malaria parasite Plasmodium yoelii nigeriensis N67

BackgroundRodent malaria parasites are important models for studying host-malaria parasite interactions such as host immune response, mechanisms of parasite evasion of host killing, and vaccine development. One of the rodent malaria parasites is Plasmodium yoelii, and multiple P. yoelii strains or subspecies that cause different disease phenotypes have been widely employed in various studies. The genomes and transcriptomes of several P. yoelii strains have been analyzed and annotated, including the lethal strains of P. y. yoelii YM (or 17XL) and non-lethal strains of P. y. yoelii 17XNL/17X. Genomic DNA sequences and cDNA reads from another subspecies P. y. nigeriensis N67 have been reported for studies of genetic polymorphisms and parasite response to drugs, but its genome has not been assembled and annotated.ResultsWe performed genome sequencing of the N67 parasite using the PacBio long-read sequencing technology, de novo assembled its genome and transcriptome, and predicted 5383 genes with high overall annotation quality. Comparison of the annotated genome of the N67 parasite with those of YM and 17X parasites revealed a set of genes with N67-specific orthology, expansion of gene families, particularly the homologs of the Plasmodium chabaudi erythrocyte membrane antigen, large numbers of SNPs and indels, and proteins predicted to interact with host immune responses based on their functional domains.ConclusionsThe genomes of N67 and 17X parasites are highly diverse, having approximately one polymorphic site per 50 base pairs of DNA. The annotated N67 genome and transcriptome provide searchable databases for fast retrieval of genes and proteins, which will greatly facilitate our efforts in studying the parasite biology and gene function and in developing effective control measures against malaria.

SneakerNet: A modular quality assurance and quality check workflow for primary genomic and metagenomic read data.

SummaryLaboratories that run Whole Genome Sequencing (WGS) produce a tremendous amount of data, up to 10 gigabytes for some common instruments. There is a need to standardize the quality assurance and quality control process (QA/QC). Therefore we have created SneakerNet to automate the QA/QC for WGS.

Genomic characteristics and clinical effect of the emergent SARS-CoV-2 B.1.1.7 lineage in London, UK: a whole-genome sequencing and hospital-based cohort study

BackgroundEmergence of variants with specific mutations in key epitopes in the spike protein of SARS-CoV-2 raises concerns pertinent to mass vaccination campaigns and use of monoclonal antibodies. We aimed to describe the emergence of the B.1.1.7 variant of concern (VOC), including virological characteristics and clinical severity in contemporaneous patients with and without the variant.MethodsIn this cohort study, samples positive for SARS-CoV-2 on PCR that were collected from Nov 9, 2020, for patients acutely admitted to one of two hospitals on or before Dec 20, 2020, in London, UK, were sequenced and analysed for the presence of VOC-defining mutations. We fitted Poisson regression models to investigate the association between B.1.1.7 infection and severe disease (defined as point 6 or higher on the WHO ordinal scale within 14 days of symptoms or positive test) and death within 28 days of a positive test and did supplementary genomic analyses in a cohort of chronically shedding patients and in a cohort of remdesivir-treated patients. Viral load was compared by proxy, using PCR cycle threshold values and sequencing read depths.FindingsOf 496 patients with samples positive for SARS-CoV-2 on PCR and who met inclusion criteria, 341 had samples that could be sequenced. 198 (58%) of 341 had B.1.1.7 infection and 143 (42%) had non-B.1.1.7 infection. We found no evidence of an association between severe disease and death and lineage (B.1.1.7 vs non-B.1.1.7) in unadjusted analyses (prevalence ratio [PR] 0·97 [95% CI 0·72–1·31]), or in analyses adjusted for hospital, sex, age, comorbidities, and ethnicity (adjusted PR 1·02 [0·76–1·38]). We detected no B.1.1.7 VOC-defining mutations in 123 chronically shedding immunocompromised patients or in 32 remdesivir-treated patients. Viral load by proxy was higher in B.1.1.7 samples than in non-B.1.1.7 samples, as measured by cycle threshold value (mean 28·8 [SD 4·7] vs 32·0 [4·8]; p=0·0085) and genomic read depth (1280 [1004] vs 831 [682]; p=0·0011).InterpretationEmerging evidence exists of increased transmissibility of B.1.1.7, and we found increased virus load by proxy for B.1.1.7 in our data. We did not identify an association of the variant with severe disease in this hospitalised cohort.FundingUniversity College London Hospitals NHS Trust, University College London/University College London Hospitals NIHR Biomedical Research Centre, Engineering and Physical Sciences Research Council.

A simple PCR-based genetic sex identification method in the blotched snakehead (Channa maculata) developed by high-throughput sequencing

Sex dimorphism is a common phenomenon in animals. Blotched snakehead (Channa maculata) is an economically important freshwater fish with a faster growth rate in males. However, existing sex-specific markers were too few and difficult to use in production practice, which hindered the development of all-male breeding. Here, we generated 15.64, 20.77 and 29.03 Gb paired-end genomic sequence reads for three male libraries, 12.82, 19.36 and 28.33 Gb for three female libraries and 30.93 Gb for a female mixed pool libraries to screen male-specific sequences. After assembly, we obtained a male reference genome with 541,932 assembled sequences and a female reference genome containing 853,706 assembled sequences. After mapping, 23 male-specific sequences were identified. Six candidate male-specific markers were successfully validated using PCR reaction. Moreover, based on homology analysis and coverage information, we found a candidate X chromosome sequence that was partially similar to the corresponding Y chromosome sequence, and two resulting primers were successfully used in the identification of female (XX), male (XY) and supermale (YY) individuals. In general, a deep genome sequencing method was first provided to effectively enrich large sex-specific segments of Blotched snakehead, which would greatly contribute to elucidation of its sex determination mechanisms and development of all-male breeding.

Multiple Cross Displacement Amplification Linked with Nanoparticles-Based Lateral Flow Biosensor in Screening of Hepatitis B Virus in Clinical Application.

BackgroundHepatitis B virus (HBV) is a common pathogen that predominantly causes severe liver disease, and remains one of a huge challenge worldwide, especially in many resource-constrained areas. Developing a low-cost, sensitive, specific, and rapid approach for screening HBV is critical for its treatment and prevention. In the current study, a novel molecular detection approach, multiple cross displacement amplification (MCDA) coupled with polymer nanoparticle-based lateral flow biosensor (MCDA-LFB), was applied for detection of HBV in blood samples.MethodsHBV standard substance and clinical donor serum samples were collected and used for the establishment and confirmation of the HBV-MCDA-LFB assay. A set of 10 MCDA primers was designed according to HBV-specific gene S. The HBV-MCDA-LFB assay conditions, including genomic template concentration, MCDA reaction temperature and time were optimized. The sensitivity and specificity of the HBV-MCDA -LFB assay were evaluated in this report. The HBV-MCDA-LFB assay was applied to detect the HBV agent from clinical samples.ResultsThe HBV-MCDA primers based on the S gene were valid for establishment of MCDA assay. The HBV-MCDA reaction with optimized conditions could be carried out at a constant temperature 64°C for 35 min. The whole process, including sample preparation (5 min), genomic template extraction (~30 min), MCDA amplification (35 min), and LFB reading (~2 min), could be completed within 80 min. The sensitivity of this assay was 5 IU per reaction. The specificity was 100% for HBV-MCDA-LFB assay.ConclusionThese results confirmed that the HBV-MCDA-LFB is a low-cost, sensitive, specific, simple, and rapid method for detecting HBV agents. This technique has great potential to develop a point-of-care testing (POCT) method in clinical practice, especially in endemic and resource-constrained regions.

Nudivirus Sequences Identified from the Southern and Western Corn Rootworms (Coleoptera: Chrysomelidae).

Analysis of pooled genomic short read sequence data revealed the presence of nudivirus-derived sequences from U.S. populations of both southern corn rootworm (SCR, Diabrotica undecimpunctata howardi Barber) and western corn rootworm (WCR, Diabrotica virgifera virgifera LeConte). A near complete nudivirus genome sequence was assembled from sequence data for an SCR population with relatively high viral titers. A total of 147,179 bp was assembled from five contigs that collectively encode 109 putative open reading frames (ORFs) including 20 nudivirus core genes. In contrast, genome sequence recovery was incomplete for a second nudivirus from WCR, although sequences derived from this virus were present in three geographically dispersed populations. Only 48,989 bp were assembled with 48 putative ORFs including 13 core genes, representing about 20% of a typical nudivirus genome. Phylogenetic analysis indicated that both corn rootworm nudiviruses grouped with the third known nudivirus of beetles, Oryctes rhinoceros nudivirus in the genus Alphanudivirus. On the basis of phylogenetic and additional analyses, we propose further taxonomic separation of nudiviruses within Alphanudivirus and Betanudivirus into two subfamilies and five genera. Identification of nudivirus-derived sequences from two species of corn rootworm highlights the diversity of viruses associated with these agricultural insect pests.

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding.

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

Burrows Wheeler Transform and Wavelet Tree Based Retrieval of Genome Sequence in an Indexed Genome Database

Background: New generation sequencing machinery such as Illumina and Solexa can generate millions of reads from given genome sequence on a single run. There is a need for suitable data structure, efficient with respect to memory as well as time to align these enormous reads into reference genome. There are a number of existing techniques of indexing and reads alignment, such as MAQ, Bowtie, BWA, BWBBLE and Kart. Memory efficient versions of these techniques are 10- 20% slower than their respective normal versions. Objective: A new approach for efficient indexing and retrieval of large genomic data. Methods: In this paper, we propose an efficient method based on Burrows Wheeler Transform and Wavelet Tree (BWIT) for genome sequence indexing and reads alignment. Both types of alignments (exact and approximate) are possible by the proposed approach (BWIT). Results: The performance of BWIT is experimentally found to be better than existing ones with respect to both memory and speed. Experimental work shows that proposed approach performs best in case of protein sequence indexing. All the existing read alignment approaches depend upon the size of index used. In general, time required increases with reduction in index size used. Experiments have been done with Bowtie, BWA &amp; Kart by taking index size as 1.25N, 1.05N, .98N, where N is the size of the text (reference genome). In our approach BWIT index size is .6N which is lesser than index size used in all other approaches. It is observed that even using smallest index size alignment time in our approach is least. Conclusion: An innovative indexing technique is presented to address the problem of storage, transmission and retrieval of large DNA/Protein Sequence data.

Improving CLIP-seq data analysis by incorporating transcript information

BackgroundCurrent peak callers for identifying RNA-binding protein (RBP) binding sites from CLIP-seq data take into account genomic read profiles, but they ignore the underlying transcript information, that is information regarding splicing events. So far, there are no studies available that closer observe this issue.ResultsHere we show that current peak callers are susceptible to false peak calling near exon borders. We quantify its extent in publicly available datasets, which turns out to be substantial. By providing a tool called CLIPcontext for automatic transcript and genomic context sequence extraction, we further demonstrate that context choice affects the performances of RBP binding site prediction tools. Moreover, we show that known motifs of exon-binding RBPs are often enriched in transcript context sites, which should enable the recovery of more authentic binding sites. Finally, we discuss possible strategies on how to integrate transcript information into future workflows.ConclusionsOur results demonstrate the importance of incorporating transcript information in CLIP-seq data analysis. Taking advantage of the underlying transcript information should therefore become an integral part of future peak calling and downstream analysis tools.

Alterations of circulating bacterial DNA in colorectal cancer and adenoma: A proof-of-concept study.

The gut microbiota is closely associated with colorectal neoplasia. While most metagenomics studies utilized fecal samples, circulating bacterial DNA in colorectal neoplasia patients remained unexplored. This proof-of-concept study aims to characterize alterations of circulating bacterial DNA in colorectal neoplasia patients. We performed WGS of plasma samples from 25 colorectal cancer (CRC) patients, 10 colorectal adenoma (CRA) patients and 22 healthy controls (HC). Bacterial relative abundance was measured by removing the host genome and mapping reads into bacterial genomes. By diversity analysis, we found plasma samples required less sample size to approach saturation than fecal samples, and species diversity in HC was slightly higher compared with CRC/CRA patients. The majority of circulating bacterial DNA came from bacterial genera which commonly associated with gastrointestine and oral tract. By differential analysis, a total of 127 significant species between CRC patients and HC were identified, on which basis 28 species with top predictive ability were selected and showed promise in preliminary discrimination between CRC/CRA and HC. In CRA patients, relative abundance of the selected 28 species more closely resembled those in CRC patients than HC. By comparing with fecal metagenomics studies, we found there was moderate positive correlation between fold changes of the overlapped fecal and circulating bacterial DNA. Finally, species correlation analysis revealed that CRC and HC displayed distinct patterns of species association. In conclusion, this study demonstrated alterations of circulating bacterial DNA in colorectal neoplasia patients, which had the potential to become non-invasive biomarkers for colorectal neoplasia screening and early diagnosis.

ARBitR: an overlap-aware genome assembly scaffolder for linked reads.

SummaryLinked genomic sequencing reads contain information that can be used to join sequences together into scaffolds in draft genome assemblies. Existing software for this purpose performs the scaffolding by joining sequences with a gap between them, not considering potential overlaps of contigs. We developed ARBitR to create scaffolds where overlaps are taken into account and show that it can accurately recreate regions where draft assemblies are broken.Availability and implementationARBitR is written and implemented in Python3 for Unix-based operative systems. All source code is available at https://github.com/markhilt/ARBitR under the GNU General Public License v3.Supplementary informationSupplementary data are available at Bioinformatics online.

Data Sanitization to Reduce Private Information Leakage from Functional Genomics

The generation of functional genomics datasets is surging, because they provide insight into gene regulation and organismal phenotypes (e.g., genes upregulated in cancer). The intent behind functional genomics experiments is not necessarily to study genetic variants, yet they pose privacy concerns due to their use of next-generation sequencing. Moreover, there is a great incentive to broadly share raw reads for better statistical power and general research reproducibility. Thus, we need new modes of sharing beyond traditional controlled-access models. Here, we develop a data-sanitization procedure allowing raw functional genomics reads to be shared while minimizing privacy leakage, enabling principled privacy-utility trade-offs. Our protocol works with traditional Illumina-based assays and newer technologies such as 10x single-cell RNA sequencing. It involves quantifying the privacy leakage in reads by statistically linking study participants to known individuals. We carried out these linkages using data from highly accurate reference genomes and more realistic environmental samples.

Comparing rates of introgression in parasitic feather lice with differing dispersal capabilities

Organisms vary in their dispersal abilities, and these differences can have important biological consequences, such as impacting the likelihood of hybridization events. However, there is still much to learn about the factors influencing hybridization, and specifically how dispersal ability affects the opportunities for hybridization. Here, using the ecological replicate system of dove wing and body lice (Insecta: Phthiraptera), we show that species with higher dispersal abilities exhibited increased genomic signatures of introgression. Specifically, we found a higher proportion of introgressed genomic reads and more reticulated phylogenetic networks in wing lice, the louse group with higher dispersal abilities. Our results are consistent with the hypothesis that differences in dispersal ability might drive the extent of introgression through hybridization.

NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy.

BackgroundLong-read sequencing can be applied to generate very long contigs and even completely assembled genomes at relatively low cost and with minimal sample preparation. As a result, long-read sequencing platforms are becoming more popular. In this respect, the Oxford Nanopore Technologies–based long-read sequencing “nanopore" platform is becoming a widely used tool with a broad range of applications and end-users. However, the need to explore and manipulate the complex data generated by long-read sequencing platforms necessitates accompanying specialized bioinformatics platforms and tools to process the long-read data correctly. Importantly, such tools should additionally help democratize bioinformatics analysis by enabling easy access and ease-of-use solutions for researchers.ResultsThe Galaxy platform provides a user-friendly interface to computational command line–based tools, handles the software dependencies, and provides refined workflows. The users do not have to possess programming experience or extended computer skills. The interface enables researchers to perform powerful bioinformatics analysis, including the assembly and analysis of short- or long-read sequence data. The newly developed “NanoGalaxy" is a Galaxy-based toolkit for analysing long-read sequencing data, which is suitable for diverse applications, including de novo genome assembly from genomic, metagenomic, and plasmid sequence reads.ConclusionsA range of best-practice tools and workflows for long-read sequence genome assembly has been integrated into a NanoGalaxy platform to facilitate easy access and use of bioinformatics tools for researchers. NanoGalaxy is freely available at the European Galaxy server https://nanopore.usegalaxy.eu with supporting self-learning training material available at https://training.galaxyproject.org.

Vulvar squamous cell carcinoma: Comprehensive genomic profiling of HPV(+) versus HPV(–) forms reveals a different set of potentially actionable biomarkers

Objective: Vulvar squamous cell carcinoma (vSCC) is often associated with either detectable high-risk strains of human papillomavirus (HPV) or chronic dystrophic/inflammatory lesions of postmenopausal women. We sought to assess the genomics of a large cohort of aggressive vSCCs, with an aim to identify distinct mutational signatures based on the presence or absence of HPV genome reads.

Identification of Y chromosome markers in the eastern three-lined skink (Bassiana duperreyi) using in silico whole genome subtraction

BackgroundHomologous sex chromosomes can differentiate over time because recombination is suppressed in the region of the sex determining locus, leading to the accumulation of repeats, progressive loss of genes that lack differential influence on the sexes and sequence divergence on the hemizygous homolog. Divergence in the non-recombining regions leads to the accumulation of Y or W specific sequence useful for developing sex-linked markers. Here we use in silico whole-genome subtraction to identify putative sex-linked sequences in the scincid lizard Bassiana duperreyi which has heteromorphic XY sex chromosomes.ResultsWe generated 96.7 × 109 150 bp paired-end genomic sequence reads from a XY male and 81.4 × 109 paired-end reads from an XX female for in silico whole genome subtraction to yield Y enriched contigs. We identified 7 reliable markers which were validated as Y chromosome specific by polymerase chain reaction (PCR) against a panel of 20 males and 20 females.ConclusionsThe sex of B. duperreyi can be reversed by low temperatures (XX genotype reversed to a male phenotype). We have developed sex-specific markers to identify the underlying genotypic sex and its concordance or discordance with phenotypic sex in wild populations of B. duperreyi. Our pipeline can be applied to isolate Y or W chromosome-specific sequences of any organism and is not restricted to sequence residing within single-copy genes. This study greatly improves our knowledge of the Y chromosome in B. duperreyi and will enhance future studies of reptile sex determination and sex chromosome evolution.

Abstract 1163: Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study

Abstract Background: Little is known about the microbiomes of the lung and oral cavity with electronic cigarette (e-cig) use and how they compare to those of smokers and never-smokers. E-cigs have been promoted as a safe alternative to smoking cigarettes. Given the recent outbreak of E-cigarette or Vaping product use Associated Lung Injury (EVALI) there is an urgent need for understanding the biological effects of e-cig use on the lung and oral cavity, including effects on the microbiome. Previous studies have been limited to 16S-rRNA sequencing which were used to detect bacteria genera. In this study, we used metatranscriptome profiling to study differentially abundant bacteria species in the oral and lung microbiome of never-smokers, smokers, and e-cig users. Methods: A cross-sectional study of 10 never-smokers, 8 cigarette smokers, and 10 e-cig users was conducted, with saliva and bronchoalveolar lavage (BAL) collected for each study participant. RNA was extracted from saliva and BAL samples for total transcriptome RNA-seq analysis. Sequences were aligned with bowtie2 v.2.2.8 to the human genome (hg19) and non-aligned reads were aligned and annotated using NCBI metagenomes database and Kraken v.1. Differences in the microbiome by smoking status were determined by pairwise comparisons using limma-voom with FDR q-value cutoffs &amp;lt;0.2. Results: The distribution of richness and evenness of bacterial communities measured by Shannon diversity in our metatranscriptome data did not significantly differ between the three smoking status groups. When comparing levels of bacteria species between groups in the saliva, 234 were differentially abundant between smokers and never-smokers, and 39 were differentially abundant between smokers and e-cig users. In the lung, 87 bacterial species were differentially abundant between smokers and never-smokers and 36 were differentially abundant between smokers and e-cig users. Notably, no bacteria species were differentially abundant when comparing e-cig users and never-smokers in both the saliva and lung samples. There are 50 bacterial species found to be differentially abundant in both the lung and saliva samples, 47 of which are decreased in smokers. These 47 bacteria species included common commensal oral microbiome species such as Haemophilus parainfluenzae, Capnocytophaga gingivalis and Neisseria species. The 3 species that were increased in smokers were Lactobacillus species. Conclusion: Our findings suggests that smoking cigarettes may alter populations of common commensal species in both the oral and lung microbiome. The lack of differentially abundant bacterial species between electronic cigarette users and never-smokers indicates that e-cigs may alter bacterial species to a lesser extent than smoking. Citation Format: Kevin L. Ying, Min-Ae Song, Daniel Y. Weng, Quentin A. Nickerson, Joseph P. McElory, Theodore M. Brasky, Noah B. Whiteman, Mark D. Wewers, Jo L. Freudenheim, Ewy A. Mathé, Peter G. Shields. Lung and salivary microbiome in electronic cigarette users, never-smokers, and smokers: A pilot cross-sectional study [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1163.

Evaluation of computational methods for human microbiome analysis using simulated data.

BackgroundOur understanding of the composition, function, and health implications of human microbiota has been advanced by high-throughput sequencing and the development of new genomic analyses. However, trade-offs among alternative strategies for the acquisition and analysis of sequence data remain understudied.MethodsWe assessed eight popular taxonomic profiling pipelines; MetaPhlAn2, metaMix, PathoScope 2.0, Sigma, Kraken, ConStrains, Centrifuge and Taxator-tk, against a battery of metagenomic datasets simulated from real data. The metagenomic datasets were modeled on 426 complete or permanent draft genomes stored in the Human Oral Microbiome Database and were designed to simulate various experimental conditions, both in the design of a putative experiment; read length (75–1,000 bp reads), sequence depth (100K–10M), and in metagenomic composition; number of species present (10, 100, 426), species distribution. The sensitivity and specificity of each of the pipelines under various scenarios were measured. We also estimated the relative root mean square error and average relative error to assess the abundance estimates produced by different methods. Additional datasets were generated for five of the pipelines to simulate the presence within a metagenome of an unreferenced species, closely related to other referenced species. Additional datasets were also generated in order to measure computational time on datasets of ever-increasing sequencing depth (up to 6 × 107).ResultsTesting of eight pipelines against 144 simulated metagenomic datasets initially produced 1,104 discrete results. Pipelines using a marker gene strategy; MetaPhlAn2 and ConStrains, were overall less sensitive, than other pipelines; with the notable exception of Taxator-tk. This difference in sensitivity was largely made up in terms of runtime, significantly lower than more sensitive pipelines that rely on whole-genome alignments such as PathoScope2.0. However, pipelines that used strategies to speed-up alignment between genomic references and metagenomic reads, such as kmerization, were able to combine both high sensitivity and low run time, as is the case with Kraken and Centrifuge. Absent species genomes in the database mostly led to assignment of reads to the most closely related species available in all pipelines. Our results therefore suggest that taxonomic profilers that use kmerization have largely superseded those that use gene markers, coupling low run times with high sensitivity and specificity. Taxonomic profilers using more time-consuming read reassignment, such as PathoScope 2.0, provided the most sensitive profiles under common metagenomic sequencing scenarios. All the results described and discussed in this paper can be visualized using the dedicated R Shiny application (https://github.com/microgenomics/HumanMicrobiomeAnalysis). All of our datasets, pipelines and results are made available through the GitHub repository for future benchmarking.

Oncogenic Features in Histologically Normal Mucosa: Novel Insights Into Field Effect From a Mega-Analysis of Colorectal Transcriptomes.

INTRODUCTION:Colorectal cancer is a common malignancy that can be cured when detected early, but recurrence among survivors is a persistent risk. A field effect of cancer in the colon has been reported and could have implications for surveillance, but studies to date have been limited. A joint analysis of pooled transcriptomic data from all available bulk RNA-sequencing data sets of healthy, histologically normal tumor-adjacent, and tumor tissues was performed to provide an unbiased assessment of field effect.METHODS:A novel bulk RNA-sequencing data set from biopsies of nondiseased colon from screening colonoscopy along with published data sets from the Genomic Data Commons and Sequence Read Archive were considered for inclusion. Analyses were limited to samples with a quantified read depth of at least 10 million reads. Transcript abundance was estimated with Salmon, and downstream analysis was performed in R.RESULTS:A total of 1,139 samples were analyzed in 3 cohorts. The primary cohort consisted of 834 independent samples from 8 independent data sets, including 462 healthy, 61 tumor-adjacent, and 311 tumor samples. Tumor-adjacent gene expression was found to represent an intermediate state between healthy and tumor expression. Among differentially expressed genes in tumor-adjacent samples, 1,143 were expressed in patterns similar to tumor samples, and these genes were enriched for cancer-associated pathways.DISCUSSION:Novel insights into the field effect in colorectal cancer were generated in this mega-analysis of the colorectal transcriptome. Oncogenic features that might help explain metachronous lesions in cancer survivors and could be used for surveillance and risk stratification were identified.