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September 22, 2019

Proteomic detection of immunoglobulin light chain variable region peptides from amyloidosis patient biopsies.

Immunoglobulin light chain (LC) amyloidosis (AL) is caused by deposition of clonal LCs produced by an underlying plasma cell neoplasm. The clonotypic LC sequences are unique to each patient, and they cannot be reliably detected by either immunoassays or standard proteomic workflows that target the constant regions of LCs. We addressed this issue by developing a novel sequence template-based workflow to detect LC variable (LCV) region peptides directly from AL amyloid deposits. The workflow was implemented in a CAP/CLIA compliant clinical laboratory dedicated to proteomic subtyping of amyloid deposits extracted from either formalin-fixed paraffin-embedded tissues or subcutaneous fat aspirates. We evaluated the performance of the workflow on a validation cohort of 30 AL patients, whose amyloidogenic clone was identified using a novel proteogenomics method, and 30 controls. The recall and negative predictive values of the workflow, when identifying the gene family of the AL clone, were 93 and 98%, respectively. Application of the workflow on a clinical cohort of 500 AL amyloidosis samples highlighted a bias in the LCV gene families used by the AL clones. We also detected similarity between AL clones deposited in multiple organs of systemic AL patients. In summary, AL proteomic data sets are rich in LCV region peptides of potential clinical significance that are recoverable with advanced bioinformatics.

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September 22, 2019

wtf genes are prolific dual poison-antidote meiotic drivers.

Meiotic drivers are selfish genes that bias their transmission into gametes, defying Mendelian inheritance. Despite the significant impact of these genomic parasites on evolution and infertility, few meiotic drive loci have been identified or mechanistically characterized. Here, we demonstrate a complex landscape of meiotic drive genes on chromosome 3 of the fission yeasts Schizosaccharomyces kambucha and S. pombe. We identify S. kambucha wtf4 as one of these genes that acts to kill gametes (known as spores in yeast) that do not inherit the gene from heterozygotes. wtf4 utilizes dual, overlapping transcripts to encode both a gamete-killing poison and an antidote to the poison. To enact drive, all gametes are poisoned, whereas only those that inherit wtf4 are rescued by the antidote. Our work suggests that the wtf multigene family proliferated due to meiotic drive and highlights the power of selfish genes to shape genomes, even while imposing tremendous costs to fertility.

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September 22, 2019

Community profiling of Fusarium in combination with other plant associated fungi in different crop species using SMRT Sequencing.

Fusarium head blight, caused by fungi from the genus Fusarium, is one of the most harmful cereal diseases, resulting not only in severe yield losses but also in mycotoxin contaminated and health-threatening grains. Fusarium head blight is caused by a diverse set of species that have different host ranges, mycotoxin profiles and responses to agricultural practices. Thus, understanding the composition of Fusarium communities in the field is crucial for estimating their impact and also for the development of effective control measures. Up to now, most molecular tools that monitor Fusarium communities on plants are limited to certain species and do not distinguish other plant associated fungi. To close these gaps, we developed a sequencing-based community profiling methodology for crop-associated fungi with a focus on the genus Fusarium. By analyzing a 1600 bp long amplicon spanning the highly variable segments ITS and D1-D3 of the ribosomal operon by PacBio SMRT sequencing, we were able to robustly quantify Fusarium down to species level through clustering against reference sequences. The newly developed methodology was successfully validated in mock communities and provided similar results as the culture-based assessment of Fusarium communities by seed health tests in grain samples from different crop species. Finally, we exemplified the newly developed methodology in a field experiment with a wheat-maize crop sequence under different cover crop and tillage regimes. We analyzed wheat straw residues, cover crop shoots and maize grains and we could reveal that the cover crop hairy vetch (Vicia villosa) acts as a potent alternative host for Fusarium (OTU F.ave/tri) showing an eightfold higher relative abundance compared with other cover crop treatments. Moreover, as the newly developed methodology also allows to trace other crop-associated fungi, we found that vetch and green fallow hosted further fungal plant pathogens including Zymoseptoria tritici. Thus, besides their beneficial traits, cover crops can also entail phytopathological risks by acting as alternative hosts for Fusarium and other noxious plant pathogens. The newly developed sequencing based methodology is a powerful diagnostic tool to trace Fusarium in combination with other fungi associated to different crop species.

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September 22, 2019

Reduction in fecal microbiota diversity and short-chain fatty acid producers in Methicillin-resistant Staphylococcus aureus infected individuals as revealed by PacBio single molecule, real-time sequencing technology.

Methicillin-resistant Staphylococcus aureus (MRSA) may cause potentially lethal infections. Increasing evidence suggests that the gut microbiota is associated with human health. Yet, whether patients with MRSA infections carry specific signatures in their fecal microbiota composition has not been determined. Thus, this study aimed to compare the fecal microbiota profile of MRSA-positive patients (n=15) with individuals without MRSA infection (n=15) by using the PacBio single molecule, real-time (SMRT) DNA sequencing system and real-time quantitative polymerase chain reaction (qPCR). Mann-Whitney tests and unweighted UniFrac principal coordinate analysis (PCoA) showed that the profile of fecal microbiota was apparently different between the two populations. Both the community richness and diversity were reduced in the MRSA-positive group (p<0.050). The genera Acinetobacter and Enterococcus were highly enriched in the MRSA-positive group, whereas less short-chain fatty acid (SCFA)-producing bacteria, including Butyricimonas, Faecalibacterium, Roseburia, Ruminococcus, Megamonas and Phascolarctobacterium, were detected in the MRSA-positive group. At species level, the species Acinetobacter baumannii and Bacteroides thetaiotaomicron were prevalent in the MRSA-positive group, whereas opposite trends were observed in 17 other species, such as Faecalibacterium prausnitzii, Lactobacillus rogosae, Megamonas rupellensis and Phascolarctobacterium faecium. Positive correlations were observed between Acinetobacter baumannii and erythrocyte sedimentation rate (ESR) (R=0.554, p=0.001), as well as hypersensitive C reactive protein (hsCRP) (R=0.406, p=0.026). Faecalibacterium prausnitzii was negatively associated with ESR (R=-0.545, p=0.002), hsCRP (R=-0.401, p=0.028) and total bile acids (TBA) (R=-0.364, p=0.048). In conclusion, the fecal microbiota structure was different between MRSA-positive and -negative patients. The increase in potential pathogens with the reduction of beneficial populations, such as SCFA-producing bacteria, in MRSA-positive patients may affect prognosis.

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September 22, 2019

PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.

High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing.We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and lncRNA transcripts. 10-fold cross-validation tests on human RefSeq mRNAs and GENCODE lncRNAs indicated that our tool could achieve accuracy of up to 95.6%. We demonstrated the utility of PLEK on transcripts from other vertebrates using the model built from human datasets. PLEK attained >90% accuracy on most of these datasets. PLEK also performed well using a simulated dataset and two real de novo assembled transcriptome datasets (sequenced by PacBio and 454 platforms) with relatively high indel sequencing errors. In addition, PLEK is approximately eightfold faster than a newly developed alignment-free tool, named Coding-Non-Coding Index (CNCI), and 244 times faster than the most popular alignment-based tool, Coding Potential Calculator (CPC), in a single-threading running manner.PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes. PLEK is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data. Its open-source software can be freely downloaded from https://sourceforge.net/projects/plek/files/.

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September 22, 2019

Long-read, Single Molecule, Real-Time (SMRT) DNA Sequencing for metagenomic applications

In this chapter, we describe applications of single molecule, real-time (SMRT) DNA sequencing toward metagenomic research. The long sequence reads, combined with a lack of bias with respect to DNA sequence context or GC content, facilitate a more comprehensive analysis of the genomic constitution of microbial communities. Full-length 16S RNA gene sequencing at high (>99%) accuracy allows for species-level characterization of community members concomitant with the determination of community structure. The application of SMRT sequencing to whole-community shotgun microbial metagenomics has also been discussed.

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September 22, 2019

Cataloguing over-expressed genes in Epstein Barr Virus immortalized lymphoblastoid cell lines through consensus analysis of PacBio transcriptomes corroborates hypomethylation of chromosome 1

The ability of Epstein Barr Virus (EBV) to transform resting cell B-cells into immortalized lymphoblastoid cell lines (LCL) provides a continuous source of peripheral blood lymphocytes that are used to model conditions in which these lymphocytes play a key role. Here, the PacBio generated transcriptome of three LCLs from a parent-daughter trio (SRAid:SRP036136) provided by a previous study [1] were analyzed using a kmer-based version of YeATS (KEATS). The set of over-expressed genes in these cell lines were determined based on a comparison with the PacBio transcriptome of twenty tissues pro- vided by another study (hOPTRS) [2]. MIR155 long non-coding RNA (MIR155HG), Fc fragment of IgE receptor II (FCER2), T-cell leukemia/lymphoma 1A (TCL1A), and germinal center associated signaling and motility (GCSAM) were genes having the highest expression counts in the three LCLs with no expression in hOPTRS. Other over-expressed genes, having low expression in hOPTRS, were membrane spanning 4-domains A1 (MS4A1) and ribosomal protein S2 pseudogene 55 (RPS2P55). While some of these genes are known to be over-expressed in LCLs, this study provides a comprehensive cataloguing of such genes. A recent work involving a patient with EBV-positive large B-cell lymphoma was “unusually lacking various B-cell markers”, but over-expressing CD30 [3] – a gene ranked 79 among uniquely expressed genes here. Hypomethylation of chromosome 1 observed in EBV immortalized LCLs [4, 5] is also corroborated here by mapping the genes to chromosomes. Extending previous work identifying un-annotated genes [6], 80 genes were identified which are expressed in the three LCLs, not in hOPTRS, and missing in the GENCODE, RefSeq and RefSeqGene databases. KEATS introduces a method of determining expression counts based on a partitioning of the known annotated genes, has runtimes of a few hours on a personal workstation and provides detailed reports enabling proper debugging.

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September 22, 2019

Next-generation sequencing for pathogen detection and identification

Over the past decade, the field of genomics has seen such drastic improvements in sequencing chemistries that high-throughput sequencing, or next-generation sequencing (NGS), is being applied to generate data across many disciplines. NGS instruments are becoming less expensive, faster, and smaller, and therefore are being adopted in an increasing number of laboratories, including clinical laboratories. Thus far, clinical use of NGS has been mostly focused on the human genome, for purposes such as characterizing the molecular basis of cancer or for diagnosing and understanding the basis of rare genetic disorders. There are, however, an increasing number of examples whereby NGS is employed to discover novel pathogens, and these cases provide precedent for the use of NGS in microbial diagnostics. NGS has many advantages over traditional microbial diagnostic methods, such as unbiased rather than pathogen-specific protocols, ability to detect fastidious or non-culturable organisms, and ability to detect co-infections. One of the most impressive advantages of NGS is that it requires little or no prior knowledge of the pathogen, unlike many other diagnostic assays; therefore for pathogen discovery, NGS is very valuable. However, despite these advantages, there are challenges involved in implementing NGS for routine clinical microbiological diagnosis. We discuss these advantages and challenges in the context of recently described research studies.

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September 22, 2019

Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics.

Short read massive parallel sequencing has emerged as a standard diagnostic tool in the medical setting. However, short read technologies have inherent limitations such as GC bias, difficulties mapping to repetitive elements, trouble discriminating paralogous sequences, and difficulties in phasing alleles. Long read single molecule sequencers resolve these obstacles. Moreover, they offer higher consensus accuracies and can detect epigenetic modifications from native DNA. The first commercially available long read single molecule platform was the RS system based on PacBio’s single molecule real-time (SMRT) sequencing technology, which has since evolved into their RSII and Sequel systems. Here we capsulize how SMRT sequencing is revolutionizing constitutional, reproductive, cancer, microbial and viral genetic testing.© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

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September 22, 2019

Metataxonomic and metagenomic approaches vs. culture-based techniques for clinical pathology.

Diagnoses that are both timely and accurate are critically important for patients with life-threatening or drug resistant infections. Technological improvements in High-Throughput Sequencing (HTS) have led to its use in pathogen detection and its application in clinical diagnoses of infectious diseases. The present study compares two HTS methods, 16S rRNA marker gene sequencing (metataxonomics) and whole metagenomic shotgun sequencing (metagenomics), in their respective abilities to match the same diagnosis as traditional culture methods (culture inference) for patients with ventilator associated pneumonia (VAP). The metagenomic analysis was able to produce the same diagnosis as culture methods at the species-level for five of the six samples, while the metataxonomic analysis was only able to produce results with the same species-level identification as culture for two of the six samples. These results indicate that metagenomic analyses have the accuracy needed for a clinical diagnostic tool, but full integration in diagnostic protocols is contingent on technological improvements to decrease turnaround time and lower costs.

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September 22, 2019

Next-generation approaches to advancing eco-immunogenomic research in critically endangered primates.

High-throughput sequencing platforms are generating massive amounts of genomic data from nonmodel species, and these data sets are valuable resources that can be mined to advance a number of research areas. An example is the growing amount of transcriptome data that allow for examination of gene expression in nonmodel species. Here, we show how publicly available transcriptome data from nonmodel primates can be used to design novel research focused on immunogenomics. We mined transcriptome data from the world’s most endangered group of primates, the lemurs of Madagascar, for sequences corresponding to immunoglobulins. Our results confirmed homology between strepsirrhine and haplorrhine primate immunoglobulins and allowed for high-throughput sequencing of expressed antibodies (Ig-seq) in Coquerel’s sifaka (Propithecus coquereli). Using both Pacific Biosciences RS and Ion Torrent PGM sequencing, we performed Ig-seq on two individuals of Coquerel’s sifaka. We generated over 150 000 sequences of expressed antibodies, allowing for molecular characterization of the antigen-binding region. Our analyses suggest that similar VDJ expression patterns exist across all primates, with sequences closely related to the human VH 3 immunoglobulin family being heavily represented in sifaka antibodies. Moreover, the antigen-binding region of sifaka antibodies exhibited similar amino acid variation with respect to haplorrhine primates. Our study represents the first attempt to characterize sequence diversity of the expressed antibody repertoire in a species of lemur. We anticipate that methods similar to ours will provide the framework for investigating the adaptive immune response in wild populations of other nonmodel organisms and can be used to advance the burgeoning field of eco-immunology. © 2014 John Wiley & Sons Ltd.

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September 22, 2019

G&T-seq: parallel sequencing of single-cell genomes and transcriptomes.

The simultaneous sequencing of a single cell’s genome and transcriptome offers a powerful means to dissect genetic variation and its effect on gene expression. Here we describe G&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from single cells. By applying G&T-seq to over 220 single cells from mice and humans, we discovered cellular properties that could not be inferred from DNA or RNA sequencing alone.

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September 22, 2019

SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantification.

High-throughput sequencing of full-length transcripts using long reads has paved the way for the discovery of thousands of novel transcripts, even in well-annotated mammalian species. The advances in sequencing technology have created a need for studies and tools that can characterize these novel variants. Here, we present SQANTI, an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline using 47 unique descriptors. We apply SQANTI to a neuronal mouse transcriptome using Pacific Biosciences (PacBio) long reads and illustrate how the tool is effective in characterizing and describing the composition of the full-length transcriptome. We perform extensive evaluation of ToFU PacBio transcripts by PCR to reveal that an important number of the novel transcripts are technical artifacts of the sequencing approach and that SQANTI quality descriptors can be used to engineer a filtering strategy to remove them. Most novel transcripts in this curated transcriptome are novel combinations of existing splice sites, resulting more frequently in novel ORFs than novel UTRs, and are enriched in both general metabolic and neural-specific functions. We show that these new transcripts have a major impact in the correct quantification of transcript levels by state-of-the-art short-read-based quantification algorithms. By comparing our iso-transcriptome with public proteomics databases, we find that alternative isoforms are elusive to proteogenomics detection. SQANTI allows the user to maximize the analytical outcome of long-read technologies by providing the tools to deliver quality-evaluated and curated full-length transcriptomes.© 2018 Tardaguila et al.; Published by Cold Spring Harbor Laboratory Press.

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September 22, 2019

Elevated expression of a minor isoform of ANK3 is a risk factor for bipolar disorder.

Ankyrin-3 (ANK3) is one of the few genes that have been consistently identified as associated with bipolar disorder by multiple genome-wide association studies. However, the exact molecular basis of the association remains unknown. A rare loss-of-function splice-site SNP (rs41283526*G) in a minor isoform of ANK3 (incorporating exon ENSE00001786716) was recently identified as protective of bipolar disorder and schizophrenia. This suggests that an elevated expression of this isoform may be involved in the etiology of the disorders. In this study, we used novel approaches and data sets to test this hypothesis. First, we strengthen the statistical evidence supporting the allelic association by replicating the protective effect of the minor allele of rs41283526 in three additional large independent samples (meta-analysis p-values: 6.8E-05 for bipolar disorder and 8.2E-04 for schizophrenia). Second, we confirm the hypothesis that both bipolar and schizophrenia patients have a significantly higher expression of this isoform than controls (p-values: 3.3E-05 for schizophrenia and 9.8E-04 for bipolar type I). Third, we determine the transcription start site for this minor isoform by Pacific Biosciences sequencing of full-length cDNA and show that it is primarily expressed in the corpus callosum. Finally, we combine genotype and expression data from a large Norwegian sample of psychiatric patients and controls, and show that the risk alleles in ANK3 identified by bipolar disorder GWAS are located near the transcription start site of this isoform and are significantly associated with its elevated expression. Together, these results point to the likely molecular mechanism underlying ANK3´s association with bipolar disorder.

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September 22, 2019

Single-molecule DNA sequencing of acute myeloid leukemia and myelodysplastic syndromes with multiple TP53 alterations.

Although the frequency of TP53 mutations in hemato- logic malignancies is low, these mutations have a high clinical relevance and are usually associated with poor prognosis. Somatic TP53 mutations have been detected in up to 73.3% of cases of acute myeloid leukemia (AML) with complex karyotype and 18.9% of AML with other unfavorable cytogenetic risk factors. AML with TP53 mutations, and/or chromosomal aneuploidy, has been defined as a distinct AML subtype. In low-risk myelodysplastic syndromes (MDS), TP53 mutations occur at an early disease stage and predict disease progression. TP53 mutation diagnosis is now part of the revised European LeukemiaNet (ELN) guidelines.

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