Raw Sequencing Reads Research Articles

Single-Cell Proteogenomic Sequencing Allows Early Detection of Relapse Clone with CN-LOH at FLT3-ITD Locus from Initial Diagnosis in AML

IntroductionFLT3-ITD is one of the most common and clinically relevant mutations in acute myeloid leukemia (AML). A high FLT3-ITD allelic ratio (AR) (>0.5) is strongly associated with poor prognosis. FLT3-ITDs are heterogeneous mutations, varying in sizes and locations with some patients having multiple FLT3-ITDs. Unfortunately, conventional clinical techniques are often not adequate in measuring these characteristics at sufficient resolution. The current study aimed to characterize an AML case with 2 FLT3-ITDs at diagnosis, map the multi-omic evolution of AML clones, and understand genetic patterns underlying AML relapse using single-cell proteogenomic sequencing (ScPGseq).MethodsLeukemic samples from a 46-year old female patient diagnosed with de novo AML obtained at initial diagnosis and relapse were archived and used in this study. Based on the 2017 ELN risk stratification, the patient was classified into a low-risk group due to normal karyotype/low FLT3-ITD AR/NPM1+. The patient achieved complete remission (CR) after induction chemotherapy in combination with midostaurin. The patient relapsed 2 months after 4 cycles of consolidation, with a CR duration of 6 months. After relapse, the disease was refractory despite reinduction and salvage therapies, even with gilteritinib (Fig A). ScPGseq was performed using the Mission Bio's AML panel and antibody oligoconjugates for 16 cell surface proteins. Raw sequencing reads were processed using Mission Bio's Tapestri pipeline and results were exported from Tapestri Insights (v3.0.2). All downstream computational and statistical analyses were performed using R and Python.ResultsConsistent with clinical sequencing (R 2 = 0.997) and PCR, ScPGseq identified 5 mutations in FLT3 (21bp and 39bp ITDs and D835Y), NPM1, and WT1 at diagnosis (2367 cells). At relapse, 1 FLT3-ITD (21bp) and mutations in NPM1 and WT1 were detected while the other FLT3-ITD (39bp) and FLT3 D835Y were absent (2611 cells). Clonal analyses of mutation patterns identified 4 AML clones at diagnosis (C1-4) and 1 at relapse (C3R; Fig B). Two closely related clones, C3 and C3R (WT1+/NPM1+/21bp FLT3-ITD+) differed in zygosity of 21bp FLT3-ITD, where nearly all cells in C3R carries homozygous FLT3-ITD. SNP array confirmed the presence of copy neutral loss of heterozygosity (CN-LOH) in chr13q.Analysis of 16 cell surface proteins along with clonal information identified 3 clusters including one devoted to non-leukemic fractions (i.e., no mutations) (top) and another nearly exclusively consisting of mutant cells from diagnosis, which we termed “monocyte-like signature” (right bottom). The other cluster was composed of nearly all mutant cells from the relapse sample and about 1/3 of mutant cells from diagnosis, which we termed “immature myeloid cell signature” (left) (Fig C).When investigating further, C3 cells with immature myeloid cell signature (98/287 cells, 34.1%) exhibited much higher allelic burden of (mean 73% vs. 56%, adj. p < 1.1e-6) and were significantly enriched with homozygous 21bp FLT3-ITDs compared to C3 cells with monocyte-like signature (189/287 cells, 65.9%) (41/98 cells, 42% vs. 11/189 cells, 5.8%, adj. p = 2.7e-13). No other mutations showed similar patterns. It indicates that C3R existed from the initial diagnosis at low frequency, instead of losing heterozygosity during relapse. Without the single cell proteogenomic analyses, C3R cells, present in <5% cells at the initial diagnosis could have not been detected.The multi-omic information elucidates the complete clonal history of this AML (Fig D). Starting with WT1 and NPM1 mutations (C1), 3 FLT3 mutations (2 ITDs and D835Y) were subsequently acquired in 3 subclones (C2-4). A subset of C3 cells (WT1+/NPM1+/21bp FLT3-ITD+) further gained CN-LOH in chr13q (C3R at diagnosis). When treated, AML cells without homozygous 21bp FLT3-ITD were cleared. Cells with homozygous 21bp FLT3-ITD survived/escaped from the treatment and became the dominant clone at relapse (C3R at relapse).ConclusionThe current study demonstrates that ScPGseq allows1) simultaneous and comprehensive analyses of multiple FLT3-ITDs at the single-cell level2) early detection of relapse clone with subclonal homozygous 21bp FLT3-ITD from the initial diagnosis, which explains one of the mechanisms of relapse in AML cases with low FLT3-ITD AR3) multi-omic clonal analyses, which further refine clonal models relying only on mutation profiles. [Display omitted] DisclosuresMinden: Astellas: Consultancy. Kim: Pfizer: Honoraria, Research Funding; Bristol-Meier Squibb: Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Paladin: Honoraria, Research Funding.

Transcriptional Profile Investigation Identified Aberrant CD34 Isoforms and Apela As a Hub Gene in IGH-DUX4 Subtype B-Cell Precursor Acute Lymphoblastic Leukemia

BackgroundCD34, a transmembrane sialoglycoprotein, is expressed in hematopoietic stem and progenitor cells, endothelial cells, and bone marrow stromal cells. Therefore, in the clinical diagnosis and classification of leukemia, high expression of CD34 is customized as a marker for the immature phenotype. Although alternative splicing is a common oncogenic mechanism in various cancers, abnormal splicing of CD34 has not been revealed in hematological malignancies.MethodsHere, we investigated the transcriptional profile of CD34, including expression level and alternative splicing, by RNA sequencing (RNA-seq) analysis from hematological malignancies and normal bone marrow samples. The raw sequencing reads were aligned to human reference genome hg38 using HISAT2, followed by featureCounts quantification, and co-expressed and differentially expressed genes (DEGs) were detected by WGCNA and DESeq2, respectively. Alternative splicing events were calculated by rMATS, and further validated by reverse transcriptase PCR (RT-PCR).ResultsThe transcriptome characteristics of hematological malignancies, including AML, B-ALL, T-ALL, and MPAL, were elaborately investigated. We found that two accompanying novel in-frame splicing isoforms of CD34 were exclusively detected in B-ALL. Furthermore, we focused on B-ALL (n = 504) to systematically explore the transcriptional profile of CD34. The two novel splicing isoforms share a common first exon at the 5' untranslated region of CD34 (Figure 1B), suggesting an alternative promoter that mediated the splicing.We further observe that the novel aberrant CD34 isoforms are mainly accompanied by IGH-DUX4 gene fusion, which has been reported characterized by high expression of CD34 and intragenic ERG deletion. All IGH-DUX4 B-ALL cases (n = 20) in our cohort were positive with the novel aberrant CD34 isoforms and validated by RT-PCR (Figure 1A). We also validated the negative result for the aberrant CD34 isoforms in ZNF384-r (n = 32) B-ALL in our cohort, which is also characterized by high CD34 expression.According to the RNA-seq based pseudo-time analysis of our B-ALL cohort, IGH-DUX4 cases mostly tended to be common-B ALL, while ZNF384-r cases presented with more Pro-B ALL, which is also in accordance with the previous report based on immunophenotype analysis. To further discover the discrepancy between DUX4-r and ZNF384-r B-ALL subtypes, we compared DEGs and functional enrichment analysis between these two subtypes with B-other ALL as control, respectively (Figure 2). Activation of JAK-STAT signaling and downregulation of SOCS2, which acts as a negative controller of JAK-STAT signaling, were observed in both subtypes (Figure 2). The hematopoietic cell lineage gene set was enriched in ZNF384-r, consistent with its more immature phenotype. The co-expression gene network for IGH-DUX4 was constructed, and the hub gene APELA was emphasized among the closely related genes (Figure 3).DiscussionIn this study, we firstly identified two novel in-frame CD34 isoforms that share a common alternative first exon at its 5'UTR and are highly enriched in the IGH-DUX4 subtype B-ALL. It has been reported that intragenic focal ERG deletion is characteristically co-occurred with IGH-DUX4, and ERG targets CD34 through regulates its super-enhancer to affect the transcription program. It needs further investigation whether ERG deletion contributes to the aberrant transcription of CD34 in IGH-DUX4 subtype B-ALL. We also emphasized APELA as a hub gene in the transcription regulation network of IGH-DUX4. As it currently lacks effective targeted therapy for IGH-DUX4 subtype B-ALL, the potential therapeutic significance of the closely accompanied aberrant CD34 isoforms and APELA as a hub gene deserves further investigation. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Exploring Ribosome-Positioning on Translating Transcripts with Ribosome Profiling.

The emergence of ribosome profiling as a tool for measuring the translatome has provided researchers with valuable insights into the post-transcriptional regulation of gene expression. Despite the biological insights and technical improvements made since the technique was initially described by Ingolia et al. (Science 324(5924):218-223, 2009), ribosome profiling measurements and subsequent data analysis remain challenging. Here, we describe our lab's protocol for performing ribosome profiling in bacteria, yeast, and mammalian cells. This protocol has integrated elements from three published ribosome profiling methods. In addition, we describe a tool called RiboViz (Carja et al., BMC Bioinformatics 18:461, 2017) ( https://github.com/riboviz/riboviz ) for the analysis and visualization of ribosome profiling data. Given raw sequencing reads and transcriptome information (e.g., FASTA, GFF) for a species, RiboViz performs the necessary pre-processing and mapping of the raw sequencing reads. RiboViz also provides the user with various quality control visualizations.

Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design.

BackgroundPooling cells from multiple biological samples prior to library preparation within the same single-cell RNA sequencing experiment provides several advantages, including lower library preparation costs and reduced unwanted technological variation, such as batch effects. Computational demultiplexing tools based on natural genetic variation between individuals provide a simple approach to demultiplex samples, which does not require complex additional experimental procedures. However, to our knowledge these tools have not been evaluated in cancer, where somatic variants, which could differ between cells from the same sample, may obscure the signal in natural genetic variation.ResultsHere, we performed in silico benchmark evaluations by combining raw sequencing reads from multiple single-cell samples in high-grade serous ovarian cancer, which has a high copy number burden, and lung adenocarcinoma, which has a high tumor mutational burden. Our results confirm that genetic demultiplexing tools can be effectively deployed on cancer tissue using a pooled experimental design, although high proportions of ambient RNA from cell debris reduce performance.ConclusionsThis strategy provides significant cost savings through pooled library preparation. To facilitate similar analyses at the experimental design phase, we provide freely accessible code and a reproducible Snakemake workflow built around the best-performing tools found in our in silico benchmark evaluations, available at https://github.com/lmweber/snp-dmx-cancer.

PRINCESS: comprehensive detection of haplotype resolved SNVs, SVs, and methylation

Long-read sequencing has been shown to have advantages in structural variation (SV) detection and methylation calling. Many studies focus either on SV, methylation, or phasing of SNV; however, only the combination of variants provides a comprehensive insight into the sample and thus enables novel findings in biology or medicine. PRINCESS is a structured workflow that takes raw sequence reads and generates a fully phased SNV, SV, and methylation call set within a few hours. PRINCESS achieves high accuracy and long phasing even on low coverage datasets and can resolve repetitive, complex medical relevant genes that often escape detection. PRINCESS is publicly available at https://github.com/MeHelmy/princess under the MIT license.

Differentially Amplified Repetitive Sequences Among Aegilops tauschii Subspecies and Genotypes.

Genomic repetitive sequences commonly show species-specific sequence type, abundance, and distribution patterns, however, their intraspecific characteristics have been poorly described. We quantified the genomic repetitive sequences and performed single nucleotide polymorphism (SNP) analysis between 29 Ae. tauschii genotypes and subspecies using publicly available raw genomic Illumina sequence reads and used fluorescence in situ hybridization (FISH) to experimentally analyze some repeats. The majority of the identified repetitive sequences had similar contents and proportions between anathera, meyeri, and strangulata subspecies. However, two Ty3/gypsy retrotransposons (CL62 and CL87) showed significantly higher abundances, and CL1, CL119, CL213, CL217 tandem repeats, and CL142 retrotransposon (Ty1/copia type) showed significantly lower abundances in subspecies strangulata compared with the subspecies anathera and meyeri. One tandem repeat and 45S ribosomal DNA (45S rDNA) abundances showed a high variation between genotypes but their abundances were not subspecies specific. Phylogenetic analysis using the repeat abundances of the aforementioned clusters placed the strangulata subsp. in a distinct clade but could not discriminate anathera and meyeri. A near complete differentiation of anathera and strangulata subspecies was observed using SNP analysis; however, var. meyeri showed higher genetic diversity. FISH using major tandem repeats couldn’t detect differences between subspecies, although (GAA)10 signal patterns generated two different karyotype groups. Taken together, the different classes of repetitive DNA sequences have differentially accumulated between strangulata and the other two subspecies of Ae. tauschii that is generally in agreement with spike morphology, implying that factors affecting repeatome evolution are variable even among highly closely related lineages.

DAnIEL: A User-Friendly Web Server for Fungal ITS Amplicon Sequencing Data

Trillions of microbes representing all kingdoms of life are resident in, and on, humans holding essential roles for the host development and physiology. The last decade over a dozen online tools and servers, accessible via public domain, have been developed for the analysis of bacterial sequences; however, the analysis of fungi is still in its infancy. Here, we present a web server dedicated to the comprehensive analysis of the human mycobiome for (i) translating raw sequencing reads to data tables and high-standard figures, (ii) integrating statistical analysis and machine learning with a manually curated relational database and (iii) comparing the user’s uploaded datasets with publicly available from the Sequence Read Archive. Using 1,266 publicly available Internal transcribed spacers (ITS) samples, we demonstrated the utility of DAnIEL web server on large scale datasets and show the differences in fungal communities between human skin and soil sites.

Patterns of Genetic Variation in a Soybean Germplasm Collection as Characterized with Genotyping-by-Sequencing.

Genomic characterization is playing an increasing role in plant germplasm conservation and utilization, as it can provide higher resolution with genome-wide SNP markers than before to identify and analyze genetic variation. A genotyping-by-sequencing technique was applied to genotype 541 soybean accessions conserved at Plant Gene Resources of Canada and 30 soybean cultivars and breeding lines developed by the Ottawa soybean breeding program of Agriculture and Agri-Food Canada. The sequencing generated an average of 952,074 raw sequence reads per sample. SNP calling identified 43,891 SNPs across 20 soybean chromosomes and 69 scaffolds with variable levels of missing values. Based on 19,898 SNPs with up to 50% missing values, three distinct genetic groups were found in the assayed samples. These groups were a mixture of the samples that originated from different countries and the samples of known maturity groups. The samples that originated from Canada were clustered into all three distinct groups, but 30 Ottawa breeding lines fell into two groups only. Based on the average pairwise dissimilarity estimates, 40 samples with the most genetic distinctness were identified from three genetic groups with diverse sample origin and known maturity. Additionally, 40 samples with the highest genetic redundancy were detected and they consisted of different sample origins and maturity groups, largely from one genetic group. Moreover, some genetically duplicated samples were identified, but the overall level of genetic duplication was relatively low in the collection. These findings are useful for soybean germplasm management and utilization.

Characteristics and Philogenetic Analysis of &lt;I&gt;Yersinia pseudotuberculosis&lt;/I&gt; Strains from the Sarydzhaz High-Mountain Focus in the Tien-Shan

The aim of the study was to characterize and carry out molecular-genetic identification of Yersinia pseudotuberculosis strains isolated in the Sarydzhaz high-mountain focus of the Tien-Shan.Materials and methods. The Y. pestis and Y. pseudotuberculosis cultures were differentiated according to their sensitivity to diagnostic bacteriophages, motility, urea fermentation, and pesticin production. Whole genome sequencing was performed using the Ion S5 XL System (Thermo Fischer Scientific). Ion Torrent Suite software package, 5.12 and Newbler gsAssembler 2.6 were used for data processing and de novo assembly of raw read sequences. The dendrogram was constructed using the Maximum Likelihood method applying the PhyML 3.1 software.Results and discussion. Strains of Y. pseudotuberculosis were isolated from museum mixed with Y. pestis cultures obtained from marmots in the Sarydzhaz high-mountain focus. According to whole genome SNP analysis, they belong to the phylogenetic group O:3 serovar, which is widespread throughout the world. Y. pseudotuberculosis is often present in mixed with Y. pestis cultures, isolated from rodents, which should be taken into account when carrying out laboratory diagnostics of plague in natural foci.

HAVoC, a bioinformatic pipeline for reference-based consensus assembly and lineage assignment for SARS-CoV-2 sequences

BackgroundSARS-CoV-2 related research has increased in importance worldwide since December 2019. Several new variants of SARS-CoV-2 have emerged globally, of which the most notable and concerning currently are the UK variant B.1.1.7, the South African variant B1.351 and the Brazilian variant P.1. Detecting and monitoring novel variants is essential in SARS-CoV-2 surveillance. While there are several tools for assembling virus genomes and performing lineage analyses to investigate SARS-CoV-2, each is limited to performing singular or a few functions separately.ResultsDue to the lack of publicly available pipelines, which could perform fast reference-based assemblies on raw SARS-CoV-2 sequences in addition to identifying lineages to detect variants of concern, we have developed an open source bioinformatic pipeline called HAVoC (Helsinki university Analyzer for Variants of Concern). HAVoC can reference assemble raw sequence reads and assign the corresponding lineages to SARS-CoV-2 sequences.ConclusionsHAVoC is a pipeline utilizing several bioinformatic tools to perform multiple necessary analyses for investigating genetic variance among SARS-CoV-2 samples. The pipeline is particularly useful for those who need a more accessible and fast tool to detect and monitor the spread of SARS-CoV-2 variants of concern during local outbreaks. HAVoC is currently being used in Finland for monitoring the spread of SARS-CoV-2 variants. HAVoC user manual and source code are available at https://www.helsinki.fi/en/projects/havoc and https://bitbucket.org/auto_cov_pipeline/havoc, respectively.

Abstract 447: Circulating TP53 tumor DNA as a potential biomarker for pre-operative identification of uterine leiomyosarcoma

Abstract Uterine leiomyosarcoma (LMS) is a highly aggressive but rare malignancy with a dismal prognosis. In nearly all cases, LMS is unsuspected prior to resection for a presumed leiomyoma. The risk of occult uterine LMS is reported to be 0.2% (1 in 500) in the largest cohort study of women undergoing surgery for presumed fibroid disease. The major problem is that there is no reliable preoperative method to distinguish LMS from a leiomyoma (LM) or STUMP (smooth muscle tumor of uncertain malignant potential), and the patient's prognosis for LMS is even poorer if the tumor is transected, which occurs in procedures performed for LM. Effective therapy for LMS is lacking and most patients eventually succumb to the disease. Thus, there is a considerable need for a reliable preoperative test to triage patients into the proper surgical procedure for LMS. TP53 alterations are reportedly associated with uterine LMS in about 40% of cases. We screened plasma for TP53 variants in patients with pathologically confirmed LMS. We evaluated TP53 circulating tumor DNA (ctDNA) by deep next-generation sequencing in a cohort of 7 patients with LMS, 1 patient with STUMP, and 3 patients with LM. Clinical data were reviewed to assess disease burden. LMS patients' tumor burden ranged from no evidence to extensive metastatic disease. DNA extraction was performed using the QIAamp DNA Micro Kit, QIAamp DNA FFPE Tissue Kit, or QIAamp MinElute ccfDNA Mini Kit. DNA quality was assessed using the TapeStation Genomic DNA kit. NGS libraries targeting the entire exonic region of the p53 gene were prepared using the QIASeq Targeted DNA Custom Panel. Sequencing was performed on the MiSeq system using 150bp paired end sequencing with a minimum read depth of 2x0.5M reads for plasma and 2x1M reads for formalin-fixed paraffin embedded and fresh-frozen tissue samples. Raw sequencing data were demultiplexed by bcl2fastq to generate the FASTQ files. Then raw sequencing reads were aligned to the human reference genome GRCh38 by BWA-MEM 0.7.9a-r786. SmCounter2 was used for p53 variants calling and variants quality control. We discovered TP53 ctDNA variants in 5 of 7 (71.4%) LMS cases including p.E258V, p.R248Q, P.R337C, p.E221*, p.R174_R175delinsWC, but not in the control cases of LM or STUMP. In the 5 plasma samples with TP53 mutated LMS, the patients had extensive metastatic disease and in the 2 TP53 wild-type LMS and STUMP cases, the patients had no evidence of disease. To our knowledge, this is the first pilot study to demonstrate the comparative use of TP53 ctDNA in patients with LMS, LM, and STUMP. Further study of these rare LMS is needed to determine the preoperative utility of NGS TP53 ctDNA mutational status as a useful molecular biomarker to help guide surgery and avoid unwarranted manipulation and pelvic contamination of undetected LMS. Supported by the Gottlieb, Buss and Snyder Endowments in Surgical Oncology Citation Format: Jean R. Lopategui, Bonnie Balzer, Yizhou Wang, Chintda Santiskulvong, Carissa A. Hyunh, Chun Yat Ong, Manuel Arana, Matthew Gayhart, Farin Amersi, Allan W. Silberman. Circulating TP53 tumor DNA as a potential biomarker for pre-operative identification of uterine leiomyosarcoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 447.

Using alignment-free methods as preprocessing stage to classification whole genomes

In bioinformatics systems, the study of genetics is a popular research discipline. These systems depend on the amount of similarity between the biological data. These data are based on DNA sequences or raw sequencing reads. In the preprocessing stage, there are several methods for measuring similarity between sequences. The most popular of these methods is the alignment method and alignment-free method, which are applied to determine the amount of functional matching between sequences of nucleotides DNA, ribosome RNA, or proteins. Alignment-based methods pose a great challenge in terms of computational complexity, In addition to delaying the time to search for a match, especially if the data is heterogeneous and its size is huge, and thus the classification accuracy decreases in the post-processing stage. Alignment-free methods have overcome the challenges of alignment-based methods for measuring the distance between sequences, The size of the data used is 1000 genomes uploaded from National Center for Biotechnology Information (NCBI), after eliminating the missing and irrelevant values, it becomes 860 genomes, ready to be segmented into words by the k-mer analysis, after which the frequency of each word is counted for each query. The size of a word depends on a value of k. In this paper we used a value of k =3 ….8, for each iteration will count times of frequencies words.

First report of Potato spindle tuber viroid infecting tree tomato in Kenya in mixed infection with Potato virus Y

First report of <i>Potato spindle tuber viroid</i> infecting tree tomato in Kenya in mixed infection with <i>Potato virus Y</i>

A SARS-CoV-2 sequence submission tool for the European Nucleotide Archive.

SummaryMany aspects of the global response to the COVID-19 pandemic are enabled by the fast and open publication of SARS-CoV-2 genetic sequence data. The European Nucleotide Archive (ENA) is the European recommended open repository for genetic sequences. In this work, we present a tool for submitting raw sequencing reads of SARS-CoV-2 to ENA. The tool features a single-step submission process, a graphical user interface, tabular-formatted metadata and the possibility to remove human reads prior to submission. A Galaxy wrap of the tool allows users with little or no bioinformatics knowledge to do bulk sequencing read submissions. The tool is also packed in a Docker container to ease deployment.Availability and implementationCLI ENA upload tool is available at github.com/usegalaxy-eu/ena-upload-cli (DOI 10.5281/zenodo.4537621); Galaxy ENA upload tool at toolshed.g2.bx.psu.edu/view/iuc/ena_upload/382518f24d6d and github.com/galaxyproject/tools-iuc/tree/master/tools/ena_upload (development); and ENA upload Galaxy container at github.com/ELIXIR-Belgium/ena-upload-container (DOI 10.5281/zenodo.4730785).

Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments.

The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as ‘Amplicon Sequence Variants’ (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.

FINDER: an automated software package to annotate eukaryotic genes from RNA-Seq data and associated protein sequences

BackgroundGene annotation in eukaryotes is a non-trivial task that requires meticulous analysis of accumulated transcript data. Challenges include transcriptionally active regions of the genome that contain overlapping genes, genes that produce numerous transcripts, transposable elements and numerous diverse sequence repeats. Currently available gene annotation software applications depend on pre-constructed full-length gene sequence assemblies which are not guaranteed to be error-free. The origins of these sequences are often uncertain, making it difficult to identify and rectify errors in them. This hinders the creation of an accurate and holistic representation of the transcriptomic landscape across multiple tissue types and experimental conditions. Therefore, to gauge the extent of diversity in gene structures, a comprehensive analysis of genome-wide expression data is imperative.ResultsWe present FINDER, a fully automated computational tool that optimizes the entire process of annotating genes and transcript structures. Unlike current state-of-the-art pipelines, FINDER automates the RNA-Seq pre-processing step by working directly with raw sequence reads and optimizes gene prediction from BRAKER2 by supplementing these reads with associated proteins. The FINDER pipeline (1) reports transcripts and recognizes genes that are expressed under specific conditions, (2) generates all possible alternatively spliced transcripts from expressed RNA-Seq data, (3) analyzes read coverage patterns to modify existing transcript models and create new ones, and (4) scores genes as high- or low-confidence based on the available evidence across multiple datasets. We demonstrate the ability of FINDER to automatically annotate a diverse pool of genomes from eight species.ConclusionsFINDER takes a completely automated approach to annotate genes directly from raw expression data. It is capable of processing eukaryotic genomes of all sizes and requires no manual supervision—ideal for bench researchers with limited experience in handling computational tools.

The National Ecological Observatory Network’s soil metagenomes: assembly and basic analysis

The National Ecological Observatory Network (NEON) annually performs shotgun metagenomic sequencing to sample genes within soils at 47 sites across the United States. NEON serves as a valuable educational resource, thanks to its open data policies and programming tutorials, but there is currently no introductory tutorial for performing analyses with the soil shotgun metagenomic dataset. Here, we describe a workflow for processing raw soil metagenome sequencing reads using the Sunbeam bioinformatics pipeline. The workflow includes cleaning and processing raw reads, taxonomic classification, assembly into contigs, annotation of predicted genes using custom protein databases, and exporting assemblies to the KBase platform for downstream analysis. This workflow is designed to be robust to annual data releases from NEON, and the underlying Snakemake framework can manage complex software dependencies. The workflow presented here aims to increase the accessibility of NEON's shotgun metagenome data, which can provide important clues about soil microbial communities and their ecological roles.

De novo transcriptome sequencing of triton shell Charonia lampas sauliae: Identification of genes related to neurotoxins and discovery of genetic markers.

Charonia lampas sauliae (triton snails, triton shells or tritons; Mollusca, Caenogastropoda, Littorinimorpha, Ranellidae) is a marine species with a wide distribution. In Korea, this species is listed as vulnerable and is regionally protected as an endangered species. Here, we report the first comprehensive transcriptome dataset of C. lampas sauliae obtained using the Illumina HiSeq 2500 platform. In total, 97.68% of raw read sequences were processed as clean reads. Of the 577,478 contigs obtained, 146,026 sequences were predicted to contain coding regions. About 89.34% of all annotated unigene sequences showed homologous matches to protein sequences in PANM DB (Protostome database). Further, about one-third of the unigene sequences were annotated using the UniGene, Swiss-Prot, Clusters of Orthologous Groups (COG) and Gene Ontology (GO) databases. In total, 190 enzymes were predicted under key metabolic pathways under stood through Kyoto Encyclopedia of Genes and Genomes (KEGG) database annotation. Repetitive elements such as long terminal repeats (LTRs), short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs), and DNA elements were enriched in the unigene sequences. Among the identified transcripts were the channel proteins, some of which were blocked by tetrodotoxin, which is thought to be synthesized by symbiotic bacteria inhabiting the shells. In addition, conotoxin superfamily peptides, such as B-conotoxin, conotoxin superfamily T and alpha-conotoxin, were identified, which may have relevance to biomedical and evolutionary research. A transcriptome-wide search for polymorphic loci identified 21,568 simple sequence repeats (SSRs) in the unigene sequences. Most SSRs were dinucleotides, among which AC/GT was the dominant SSR type. The molecular and genetic resources revealed in this study could be utilized for investigations on the fitness of the species in the marine environment and sustainability in a changing habitat.

KATK: Fast genotyping of rare variants directly from unmapped sequencing reads.

KATK is a fast and accurate software tool for calling variants directly from raw next-generation sequencing reads. It uses predefined k-mers to retrieve only the reads of interest from the FASTQ file and calls genotypes by aligning retrieved reads locally. KATK does not use data about known polymorphisms and has NC (no call) as the default genotype. The reference or variant allele is called only if there is sufficient evidence for their presence in data. Thusit is not biased against rare variants or de-novo mutations. With simulated datasets, we achieved a false-negative rate of 0.23% (sensitivity 99.77%) and a false discovery rate of 0.19%. Calling all human exonic regions with KATK requires 1-2 h, depending on sequencing coverage.

Panoramic: A package for constructing eukaryotic pan-genomes.

The study of intraspecific genomic variation in eukaryotic species has been the focus of numerous genome resequencing projects in recent years. One emerging approach for the analysis of intraspecific diversity uses the concept of a pan-genome, which theoretically represents the full set of genomic sequences and coding genes from all individuals of a given species. This approach has many advantages over reference-based methods and has been successfully applied to study both prokaryotic and eukaryotic species. However, the process of pan-genome construction still presents considerable scientific and technical challenges, especially for eukaryotic species with large and complex genomes. Although general approaches for the construction of pan-genomes have been devised, currently available software tools implement only certain modules of the entire computational procedure. Therefore, each pan-genome project requires the development of tailored analysis pipelines, thus complicating and prolonging the process and impairing research reproducibility and comparison across studies. Here, we present Panoramic, a software package for the automatic construction of eukaryotic pan-genomes. Panoramic takes raw sequencing reads as input and applies two alternative approaches for pan-genome construction. Panoramic makes pan-genome construction a considerably easier task by providing simple user interface and efficient data processing algorithms. We demonstrate the use of Panoramic by constructing the pan-genome of the model plant species Arabidopsis thaliana from sequencing data of 20 diverse ecotypes.