Rational probe design for efficient rRNA depletion and improved metatranscriptomic analysis of human microbiomes

The microbiota that colonize the human gut and other tissues are dynamic, varying both in composition and functional state between individuals and over time. Gene expression measurements can provide insights into microbiome composition and function. However, efficient and unbiased removal of microbial ribosomal RNA (rRNA) presents a barrier to acquiring metatranscriptomic data. Here we describe a probe set that achieves efficient enzymatic rRNA removal of complex human-associated microbial communities. We demonstrate that the custom probe set can be further refined through an iterative design process to efficiently deplete rRNA from a range of human microbiome samples. Using synthetic nucleic acid spike-ins, we show that the rRNA depletion process does not introduce substantial quantitative error in gene expression profiles. Successful rRNA depletion allows for efficient characterization of taxonomic and functional profiles, including during the development of the human gut microbiome. The pan-human microbiome enzymatic rRNA depletion probes described here provide a powerful tool for studying the transcriptional dynamics and function of the human microbiome.

Endotype reversal as a novel strategy for screening drugs targeting familial Alzheimer's disease

While amyloid-β (Aβ) plaques are considered a hallmark of Alzheimer's disease, clinical trials focused on targeting gamma secretase, an enzyme involved in aberrant Aβ peptide production, have not led to amelioration of AD symptoms or synaptic dysregulation. Screening strategies based on mechanistic, multi-omics approaches that go beyond pathological readouts can aid in the evaluation of therapeutics. Using early-onset Alzheimer's (EOFAD) disease patient lineage PSEN1^A246E iPSC-derived neurons, we performed RNA-seq to characterize AD-associated endotypes, which are in turn used as a screening evaluation metric for two gamma secretase drugs, the inhibitor Semagacestat and the modulator BPN-15606. We demonstrate that drug treatment partially restores the neuronal state while concomitantly inhibiting cell cycle re-entry and dedifferentiation endotypes to different degrees depending on the mechanism of gamma secretase engagement. Our endotype-centric screening approach offers a new paradigm by which candidate AD therapeutics can be evaluated for their overall ability to reverse disease endotypes.

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

High-Throughput Next-Generation Sequencing Respiratory Viral Panel: A Diagnostic and Epidemiologic Tool for SARS-CoV-2 and Other Viruses

Two serious public health challenges have emerged in the current COVID-19 pandemic namely, deficits in SARS-CoV-2 variant monitoring and neglect of other co-circulating respiratory viruses. Additionally, accurate assessment of the evolution, extent, and dynamics of the outbreak is required to understand the transmission of the virus. To address these challenges, we evaluated 533 samples using a high-throughput next-generation sequencing (NGS) respiratory viral panel (RVP) that includes 40 viral pathogens. The performance metrics revealed a PPA, NPA, and accuracy of 95.98%, 85.96%, and 94.4%, respectively. The clade for pangolin lineage B that contains certain distant variants, including P4715L in ORF1ab, Q57H in ORF3a, and S84L in ORF8 covarying with the D614G spike protein mutation, were the most prevalent early in the pandemic in Georgia, USA. The isolates from the same county formed paraphyletic groups, indicating virus transmission between counties. The study demonstrates the clinical and public health utility of the NGS-RVP to identify novel variants that can provide actionable information to prevent or mitigate emerging viral threats and models that provide insights into viral transmission patterns and predict transmission/resurgence of regional outbreaks as well as providing critical information on co-circulating respiratory viruses that might be independent factors contributing to the global disease burden.

Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study

Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.

Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.

Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

The RNA Atlas expands the catalog of human non-coding RNAs

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

The RNA Atlas expands the catalog of human non-coding RNAs

Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.

Messenger RNA capture sequencing of extracellular RNA from human biofluids using a comprehensive set of spike-in controls

Comprehensive transcriptome analysis of extracellular RNA (exRNA) purified from human biofluids is challenging because of the low RNA concentration and compromised RNA integrity. Here, we describe an optimized workflow to (1) isolate exRNA from different types of biofluids and (2) to prepare messenger RNA (mRNA)-enriched sequencing libraries using complementary hybridization probes. Importantly, the workflow includes 2 sets of synthetic spike-in RNA molecules as processing controls for RNA purification and sequencing library preparation and as an alternative data normalization strategy.

For complete details on the use and execution of this protocol, please refer to Hulstaert et al. (2020).

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Extracellular RNA from biofluids has a low concentration and a compromised integrity

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An optimized workflow for mRNA capture sequencing of human biofluids is provided

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Synthetic spike-in RNA molecules serve as processing controls

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Spike-in RNAs allow for data normalization and calculation of mRNA concentration

Dedifferentiation and neuronal repression define familial Alzheimer's disease

Identifying the systems-level mechanisms that lead to Alzheimer's disease, an unmet need, is an essential step toward the development of therapeutics. In this work, we report that the key disease-causative mechanisms, including dedifferentiation and repression of neuronal identity, are triggered by changes in chromatin topology. Here, we generated human induced pluripotent stem cell (hiPSC)-derived neurons from donor patients with early-onset familial Alzheimer's disease (EOFAD) and used a multiomics approach to mechanistically characterize the modulation of disease-associated gene regulatory programs. We demonstrate that EOFAD neurons dedifferentiate to a precursor-like state with signatures of ectoderm and nonectoderm lineages. RNA-seq, ATAC-seq, and ChIP-seq analysis reveals that transcriptional alterations in the cellular state are orchestrated by changes in histone methylation and chromatin topology. Furthermore, we demonstrate that these mechanisms are observed in EOFAD-patient brains, validating our hiPSC-derived neuron models. The mechanistic endotypes of Alzheimer's disease uncovered here offer key insights for therapeutic interventions.

2018 Ebola virus disease outbreak in Équateur Province, Democratic Republic of the Congo: a retrospective genomic characterisation

BACKGROUND

The 2018 Ebola virus disease (EVD) outbreak in Équateur Province, Democratic Republic of the Congo, began on May 8, and was declared over on July 24; it resulted in 54 documented cases and 33 deaths. We did a retrospective genomic characterisation of the outbreak and assessed potential therapeutic agents and vaccine (medical countermeasures).

METHODS

We used target-enrichment sequencing to produce Ebola virus genomes from samples obtained in the 2018 Équateur Province outbreak. Combining these genomes with genomes associated with known outbreaks from GenBank, we constructed a maximum-likelihood phylogenetic tree. In-silico analyses were used to assess potential mismatches between the outbreak strain and the probes and primers of diagnostic assays and the antigenic sites of the experimental rVSVΔG-ZEBOV-GP vaccine and therapeutics. An in-vitro flow cytometry assay was used to assess the binding capability of the individual components of the monoclonal antibody cocktail ZMapp.

FINDINGS

A targeted sequencing approach produced 16 near-complete genomes. Phylogenetic analysis of these genomes and 1011 genomes from GenBank revealed a distinct cluster, confirming a new Ebola virus variant, for which we propose the name "Tumba". This new variant appears to have evolved at a slower rate than other Ebola virus variants (0·69 × 10^-3 substitutions per site per year with "Tumba" vs 1·06 × 10^-3 substitutions per site per year without "Tumba"). We found few sequence mismatches in the assessed assay target regions and antigenic sites. We identified nine amino acid changes in the Ebola virus surface glycoprotein, of which one resulted in reduced binding of the 13C6 antibody within the ZMapp cocktail.

INTERPRETATION

Retrospectively, we show the feasibility of using genomics to rapidly characterise a new Ebola virus variant within the timeframe of an outbreak. Phylogenetic analysis provides further indications that these variants are evolving at differing rates. Rapid in-silico analyses can direct in-vitro experiments to quickly assess medical countermeasures.

FUNDING

Defense Biological Product Assurance Office.

Medical countermeasures during the 2018 Ebola virus disease outbreak in the North Kivu and Ituri Provinces of the Democratic Republic of the Congo: a rapid genomic assessment

BACKGROUND

The real-time generation of information about pathogen genomes has become a vital goal for transmission analysis and characterisation in rapid outbreak responses. In response to the recently established genomic capacity in the Democratic Republic of the Congo, we explored the real-time generation of genomic information at the start of the 2018 Ebola virus disease (EVD) outbreak in North Kivu Province.

METHODS

We used targeted-enrichment sequencing to produce two coding-complete Ebola virus genomes 5 days after declaration of the EVD outbreak in North Kivu. Subsequent sequencing efforts yielded an additional 46 genomes. Genomic information was used to assess early transmission, medical countermeasures, and evolution of Ebola virus.

FINDINGS

The genomic information demonstrated that the EVD outbreak in the North Kivu and Ituri Provinces was distinct from the 2018 EVD outbreak in Équateur Province of the Democratic Republic of the Congo. Primer and probe mismatches to Ebola virus were identified in silico for all deployed diagnostic PCR assays, with the exception of the Cepheid GeneXpert GP assay.

INTERPRETATION

The first two coding-complete genomes provided actionable information in real-time for the deployment of the rVSVΔG-ZEBOV-GP Ebola virus envelope glycoprotein vaccine, available therapeutics, and sequence-based diagnostic assays. Based on the mutations identified in the Ebola virus surface glycoprotein (GP₁₂) observed in all 48 genomes, deployed monoclonal antibody therapeutics (mAb114 and ZMapp) should be efficacious against the circulating Ebola virus variant. Rapid Ebola virus genomic characterisation should be included in routine EVD outbreak response procedures to ascertain efficacy of medical countermeasures.

FUNDING

Defense Biological Product Assurance Office.

Bead-linked transposomes enable a normalization-free workflow for NGS library preparation

BACKGROUND

Transposome-based technologies have enabled the streamlined production of sequencer-ready DNA libraries; however, current methods are highly sensitive to the amount and quality of input nucleic acid.

RESULTS

We describe a new library preparation technology (Nextera DNA Flex) that utilizes a known concentration of transposomes conjugated directly to beads to bind a fixed amount of DNA, and enables direct input of blood and saliva using an integrated extraction protocol. We further report results from libraries generated outside the standard parameters of the workflow, highlighting novel applications for Nextera DNA Flex, including human genome builds and variant calling from below 1 ng DNA input, customization of insert size, and preparation of libraries from short fragments and severely degraded FFPE samples. Using this bead-linked library preparation method, library yield saturation was observed at an input amount of 100 ng. Preparation of libraries from a range of species with varying GC levels demonstrated uniform coverage of small genomes. For large and complex genomes, coverage across the genome, including difficult regions, was improved compared with other library preparation methods. Libraries were successfully generated from amplicons of varying sizes (from 50 bp to 11 kb), however, a decrease in efficiency was observed for amplicons smaller than 250 bp. This library preparation method was also compatible with poor-quality DNA samples, with sequenceable libraries prepared from formalin-fixed paraffin-embedded samples with varying levels of degradation.

CONCLUSIONS

In contrast to solution-based library preparation, this bead-based technology produces a normalized, sequencing-ready library for a wide range of DNA input types and amounts, largely obviating the need for DNA quantitation. The robustness of this bead-based library preparation kit and flexibility of input DNA facilitates application across a wide range of fields.

Comprehensive viral enrichment enables sensitive respiratory virus genomic identification and analysis by next generation sequencing

Next generation sequencing (NGS) technologies have revolutionized the genomics field and are becoming more commonplace for identification of human infectious diseases. However, due to the low abundance of viral nucleic acids (NAs) in relation to host, viral identification using direct NGS technologies often lacks sufficient sensitivity. Here, we describe an approach based on two complementary enrichment strategies that significantly improves the sensitivity of NGS-based virus identification. To start, we developed two sets of DNA probes to enrich virus NAs associated with respiratory diseases. The first set of probes spans the genomes, allowing for identification of known viruses and full genome sequencing, while the second set targets regions conserved among viral families or genera, providing the ability to detect both known and potentially novel members of those virus groups. Efficiency of enrichment was assessed by NGS testing reference virus and clinical samples with known infection. We show significant improvement in viral identification using enriched NGS compared to unenriched NGS. Without enrichment, we observed an average of 0.3% targeted viral reads per sample. However, after enrichment, 50%–99% of the reads per sample were the targeted viral reads for both the reference isolates and clinical specimens using both probe sets. Importantly, dramatic improvements on genome coverage were also observed following virus-specific probe enrichment. The methods described here provide improved sensitivity for virus identification by NGS, allowing for a more comprehensive analysis of disease etiology.

RNA sequencing of esophageal adenocarcinomas identifies novel fusion transcripts, including NPC1-MELK, arising from a complex chromosomal rearrangement

BACKGROUND

Studies of chromosomal rearrangements and fusion transcripts have elucidated mechanisms of tumorigenesis and led to targeted cancer therapies. This study was aimed at identifying novel fusion transcripts in esophageal adenocarcinoma (EAC).

METHODS

To identify new fusion transcripts associated with EAC, targeted RNA sequencing and polymerase chain reaction (PCR) verification were performed in 40 EACs and matched nonmalignant specimens from the same patients. Genomic PCR and Sanger sequencing were performed to find the breakpoint of fusion genes.

RESULTS

Five novel in-frame fusion transcripts were identified and verified in 40 EACs and in a validation cohort of 15 additional EACs (55 patients in all): fibroblast growth factor receptor 2 (FGFR2)-GRB2-associated binding protein 2 (GAB2) in 2 of 55 or 3.6%, Niemann-Pick C1 (NPC1)-maternal embryonic leucine zipper kinase (MELK) in 2 of 55 or 3.6%, ubiquitin-specific peptidase 54 (USP54)-calcium/calmodulin dependent protein kinase II γ (CAMK2G) in 2 of 55 or 3.6%, megakaryoblastic leukemia (translocation) 1 (MKL1)-fibulin 1 (FBLN1) in 1 of 55 or 1.8%, and CCR4-NOT transcription complex subunit 2 (CNOT2)-chromosome 12 open reading frame 49 (C12orf49) in 1 of 55 or 1.8%. A genomic analysis indicated that NPC1-MELK arose from a complex interchromosomal translocation event involving chromosomes 18, 3, and 9 with 3 rearrangement points, and this was consistent with chromoplexy.

CONCLUSIONS

These data indicate that fusion transcripts occur at a stable frequency in EAC. Furthermore, our results indicate that chromoplexy is an underlying mechanism that generates fusion transcripts in EAC. These and other fusion transcripts merit further study as diagnostic markers and potential therapeutic targets in EAC. Cancer 2017;123:3916-24. © 2017 American Cancer Society.

Complete genome sequence of a KI polyomavirus isolated from an otherwise healthy child with severe lower respiratory tract infection

Unbiased, deep sequencing of a nasal specimen from an otherwise healthy 13-month-old boy hospitalized in intensive care revealed high gene expression and the complete genome of a novel isolate of KI polyomavirus (KIPyV). Further investigation detected minimal gene expression of additional viruses, suggesting that KIPyV was potentially the causal agent. Analysis of the complete genome of isolate NMKI001 revealed it is different from all previously reported genomes and contains two amino acid differences as compared to the closest virus isolate, Stockholm 380 (EF127908). J. Med. Virol. 89:926-930, 2017. © 2016 Wiley Periodicals, Inc.

Cloche is a bHLH-PAS transcription factor that drives haemato-vascular specification

Vascular and haematopoietic cells organize into specialized tissues during early embryogenesis to supply essential nutrients to all organs and thus play critical roles in development and disease. At the top of the haemato-vascular specification cascade lies cloche, a gene that when mutated in zebrafish leads to the striking phenotype of loss of most endothelial and haematopoietic cells and a significant increase in cardiomyocyte numbers. Although this mutant has been analysed extensively to investigate mesoderm diversification and differentiation and continues to be broadly used as a unique avascular model, the isolation of the cloche gene has been challenging due to its telomeric location. Here we used a deletion allele of cloche to identify several new cloche candidate genes within this genomic region, and systematically genome-edited each candidate. Through this comprehensive interrogation, we succeeded in isolating the cloche gene and discovered that it encodes a PAS-domain-containing bHLH transcription factor, and that it is expressed in a highly specific spatiotemporal pattern starting during late gastrulation. Gain-of-function experiments show that it can potently induce endothelial gene expression. Epistasis experiments reveal that it functions upstream of etv2 and tal1, the earliest expressed endothelial and haematopoietic transcription factor genes identified to date. A mammalian cloche orthologue can also rescue blood vessel formation in zebrafish cloche mutants, indicating a highly conserved role in vertebrate vasculogenesis and haematopoiesis. The identification of this master regulator of endothelial and haematopoietic fate enhances our understanding of early mesoderm diversification and may lead to improved protocols for the generation of endothelial and haematopoietic cells in vivo and in vitro.

Abstract LB-329: Enhancing the resolution and accelerating the pace of translational fusion characterization in oncology by RNA sequencing

Chromosomal rearrangements are common markers of cancer progression across a wide range of cancer types, and therefore, identification of fusion transcripts in cancer biopsies may have potential to provide tumor-specific insight toward diagnosis, prognosis and precision treatment. Currently, routine methods for fusion detection using fluorescent in-situ hybridization (FISH) provide a low-resolution view of the aberrant fusion transcript. We describe an RNA-Seq approach designed to survey cancer fusions in a single assay by selectively enriching the cancer transcriptome using probes that target the coding regions of over 1385 cancer-associated genes.

We tested the performance of the 1385 gene, RNA-Seq Pan-Cancer panel on RNA extracted from 47 patient-derived samples from brain, sarcoma and leukemia, including blood, bone marrow, and formalin-fixed paraffin-embedded (FFPE) samples. Each sample harbored at least one orthogonally verified gene fusion transcript, previously confirmed by FISH or Reverse Transcriptase PCR (RT-PCR). RNA-Seq libraries were prepared from 10-100 ng of total RNA from blood or bone marrow and 20-200 ng total RNA from FFPE tissue and subsequently enriched by hybridization to the Pan-Cancer panel. All samples yielded sufficient library and were sequenced with 76 base-pair paired-end reads on an Illumina MiSeq at 8 samples per flow cell (∼3 million reads per sample). Sequencing data was analyzed using RNA-Seq with STAR aligner and Manta fusion caller. Using this capture-based single-assay approach, we successfully detected fusions commonly associated with leukemia (BCR-ABL1, MLL-MLLT3, MLL-AFF1, RUNX1-ETV6, EBF1-PDGFRB, TCF3-PBX1, IKZF1-PAX5), sarcoma (EWSR1-ATF1, EWSR1-FLI1, JAZF1-SUZ12, SS18-SSX, FUS-DDIT3, FUS-KLF17, YWHAE-FAM22B) and brain cancer (KIAA1459-BRAF) consistent with previously confirmed RT-PCR or FISH results. Several examples of previously unknown fusion partners or additional structural information that were not identified from the FISH or RT-PCR testing were also uncovered in this study. These cases are described in detail.

In summary, we show that selective enrichment of RNA-Seq libraries with cancer-specific probes enables detection of known and novel fusions across a broad range of cancer pathologies in a single reaction, creating new opportunities for discovery and translational cancer studies.

Citation Format: Lisa C. Watson, Stephen M. Gross, Felix Schlesinger, Anthony Mai, Mariko Kellogg, Steve Lee, Claire Attwooll, Monica Brenca, David Swanson, Andrew Wong, Angelo P. Dei Tos, Claudia Haferlach, Torsten Haferlach, Wolfgang Kern, Roberta Maestro, Manja Meggendorfer, Niroshan Nadarajah, Maurizio Polano, Sabrina Rossi, Marta Sbaraglia, George S. Charames, Gary P. Schroth, Grace DeSantis. Enhancing the resolution and accelerating the pace of translational fusion characterization in oncology by RNA sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr LB-329.

Molecular Evidence of Sexual Transmission of Ebola Virus

A suspected case of sexual transmission from a male survivor of Ebola virus disease (EVD) to his female partner (the patient in this report) occurred in Liberia in March 2015. Ebola virus (EBOV) genomes assembled from blood samples from the patient and a semen sample from the survivor were consistent with direct transmission. The genomes shared three substitutions that were absent from all other Western African EBOV sequences and that were distinct from the last documented transmission chain in Liberia before this case. Combined with epidemiologic data, the genomic analysis provides evidence of sexual transmission of EBOV and evidence of the persistence of infective EBOV in semen for 179 days or more after the onset of EVD. (Funded by the Defense Threat Reduction Agency and others.).

Plasticity of DNA methylation in a nerve injury model of pain

The response of the peripheral nervous system (PNS) to injury may go together with alterations in epigenetics, a conjecture that has not been subjected to a comprehensive, genome-wide test. Using reduced representation bisulfite sequencing, we report widespread remodeling of DNA methylation in the rat dorsal root ganglion (DRG) occurring within 24 h of peripheral nerve ligation, a neuropathy model of allodynia. Significant (P < 10(-4)) cytosine hyper- and hypo-methylation was found at thousands of CpG sites. Remodeling occurred outside of CpG islands. Changes affected genes with known roles in the PNS, yet methylome remodeling also involved genes that were not linked to neuroplasticity by prior evidence. Consistent with emerging models relying on genome-wide methylation and RNA-seq analysis of promoter regions and gene bodies, variation of methylation was not tightly linked with variation of gene expression. Furthermore, approximately 44% of the dynamically changed CpGs were located outside of genes. We compared their positions with the intergenic, tissue-specific differentially methylated CpGs (tDMCs) of an independent experimental set consisting of liver, spleen, L4 control DRG, and muscle. Dynamic changes affected those intergenic CpGs that were different between tissues (P < 10(-15)) and almost never the invariant portion of the methylome (those CpGs that were identical across all tissues). Our findings-obtained in mixed tissue-show that peripheral nerve injury leads to methylome remodeling in the DRG. Future studies may address which of the cell types found in the DRG, such as specific groups of neurons or non-neuronal cells are affected by which aspect of the observed methylome remodeling.

The genome of the vervet (Chlorocebus aethiops sabaeus)

We describe a genome reference of the African green monkey or vervet (Chlorocebus aethiops). This member of the Old World monkey (OWM) superfamily is uniquely valuable for genetic investigations of simian immunodeficiency virus (SIV), for which it is the most abundant natural host species, and of a wide range of health-related phenotypes assessed in Caribbean vervets (C. a. sabaeus), whose numbers have expanded dramatically since Europeans introduced small numbers of their ancestors from West Africa during the colonial era. We use the reference to characterize the genomic relationship between vervets and other primates, the intra-generic phylogeny of vervet subspecies, and genome-wide structural variations of a pedigreed C. a. sabaeus population. Through comparative analyses with human and rhesus macaque, we characterize at high resolution the unique chromosomal fission events that differentiate the vervets and their close relatives from most other catarrhine primates, in whom karyotype is highly conserved. We also provide a summary of transposable elements and contrast these with the rhesus macaque and human. Analysis of sequenced genomes representing each of the main vervet subspecies supports previously hypothesized relationships between these populations, which range across most of sub-Saharan Africa, while uncovering high levels of genetic diversity within each. Sequence-based analyses of major histocompatibility complex (MHC) polymorphisms reveal extremely low diversity in Caribbean C. a. sabaeus vervets, compared to vervets from putatively ancestral West African regions. In the C. a. sabaeus research population, we discover the first structural variations that are, in some cases, predicted to have a deleterious effect; future studies will determine the phenotypic impact of these variations.

Single-cell transcriptome analysis reveals dynamic changes in lncRNA expression during reprogramming

Cellular reprogramming highlights the epigenetic plasticity of the somatic cell state. Long noncoding RNAs (lncRNAs) have emerging roles in epigenetic regulation, but their potential functions in reprogramming cell fate have been largely unexplored. We used single-cell RNA sequencing to characterize the expression patterns of over 16,000 genes, including 437 lncRNAs, during defined stages of reprogramming to pluripotency. Self-organizing maps (SOMs) were used as an intuitive way to structure and interrogate transcriptome data at the single-cell level. Early molecular events during reprogramming involved the activation of Ras signaling pathways, along with hundreds of lncRNAs. Loss-of-function studies showed that activated lncRNAs can repress lineage-specific genes, while lncRNAs activated in multiple reprogramming cell types can regulate metabolic gene expression. Our findings demonstrate that reprogramming cells activate defined sets of functionally relevant lncRNAs and provide a resource to further investigate how dynamic changes in the transcriptome reprogram cell state.

Quantitative assessment of RNA-protein interactions with high-throughput sequencing-RNA affinity profiling

Because RNA-protein interactions have a central role in a wide array of biological processes, methods that enable a quantitative assessment of these interactions in a high-throughput manner are in great demand. Recently, we developed the high-throughput sequencing-RNA affinity profiling (HiTS-RAP) assay that couples sequencing on an Illumina GAIIx genome analyzer with the quantitative assessment of protein-RNA interactions. This assay is able to analyze interactions between one or possibly several proteins with millions of different RNAs in a single experiment. We have successfully used HiTS-RAP to analyze interactions of the EGFP and negative elongation factor subunit E (NELF-E) proteins with their corresponding canonical and mutant RNA aptamers. Here we provide a detailed protocol for HiTS-RAP that can be completed in about a month (8 d hands-on time). This includes the preparation and testing of recombinant proteins and DNA templates, clustering DNA templates on a flowcell, HiTS and protein binding with a GAIIx instrument, and finally data analysis. We also highlight aspects of HiTS-RAP that can be further improved and points of comparison between HiTS-RAP and two other recently developed methods, quantitative analysis of RNA on a massively parallel array (RNA-MaP) and RNA Bind-n-Seq (RBNS), for quantitative analysis of RNA-protein interactions.

Abstract 4884: Highly sensitive fusion transcript detection and quantification in cancer

Gene fusion detection in cancer samples can provide tumor-specific information for cancer research, clinical diagnosis and targeted treatment. Common fusion detection methods such as qPCR and FISH are restricted to known fusion junctions and limited in the number of genes that can be detected in parallel. In contrast, RNA sequencing is a powerful approach for simultaneous discovery of all possible fusion junctions in a single reaction. But, the sequencing depth required for sensitive detection of fusions from whole-transcriptome libraries can be cost-prohibitive. Here we describe a cancer-specific capture-based approach for fusion detection by RNA sequencing that requires only a fraction of the sequencing depth of whole-transcriptome methods. We designed oligo probes that densely target coding regions of over 200 clinically relevant gene fusions and cancer-associated genes. This oligo panel was used to capture cancer-specific fusions from total RNA-Seq libraries. We used commonly studied cancer cell lines including MCF-7, K562, PC-3, LnCAP, A431 and Universal Human Reference RNA (UHRR) to compare the sensitivity of fusion detection across three RNA-Seq library prep methods: (1) cancer panel library capture (2) whole-transcriptome library capture and (3) PolyA selection. We show that probes targeting individual exons can robustly capture well-characterized cancer gene fusions such as BCR-ABL and BCAS4-BCAS3, as well as translocations where fusion junctions are unknown. Furthermore, these comparisons demonstrate the enhanced sequencing efficiency of the targeted cancer panel, while maintaining highly accurate quantitation of gene expression. We show that selective enrichment of RNA-Seq libraries with cancer-specific capture probes enables high-resolution mapping of genomic rearrangements in patient cancer samples, even those derived from FFPE, facilitating sequencing studies that were not previously possible.

Citation Format: Lisa C. Watson, Stephen M. Gross, Irina Khrevtukova, Smita Pathak, Claire Attwooll, Jason Goode, Anthony Mai, Gary P. Schroth. Highly sensitive fusion transcript detection and quantification in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4884. doi:10.1158/1538-7445.AM2015-4884

Structural annotation of equine protein-coding genes determined by mRNA sequencing

The horse, like the majority of animal species, has a limited amount of species-specific expressed sequence data available in public databases. As a result, structural models for the majority of genes defined in the equine genome are predictions based on ab initio sequence analysis or the projection of gene structures from other mammalian species. The current study used Illumina-based sequencing of messenger RNA (RNA-seq) to help refine structural annotation of equine protein-coding genes and for a preliminary assessment of gene expression patterns. Sequencing of mRNA from eight equine tissues generated 293,758105 sequence tags of 35 bases each, equalling 10.28 gbp of total sequence data. The tag alignments represent approximately 207 × coverage of the equine mRNA transcriptome and confirmed transcriptional activity for roughly 90% of the protein-coding gene structures predicted by Ensembl and NCBI. Tag coverage was sufficient to refine the structural annotation for 11,356 of these predicted genes, while also identifying an additional 456 transcripts with exon/intron features that are not listed by either Ensembl or NCBI. Genomic locus data and intervals for the protein-coding genes predicted by the Ensembl and NCBI annotation pipelines were combined with 75,116 RNA-seq-derived transcriptional units to generate a consensus equine protein-coding gene set of 20,302 defined loci. Gene ontology annotation was used to compare the functional and structural categories of genes expressed in either a tissue-restricted pattern or broadly across all tissue samples.

Tissue-specific transcriptome sequencing analysis expands the non-human primate reference transcriptome resource (NHPRTR)

The non-human primate reference transcriptome resource (NHPRTR, available online at http://nhprtr.org/) aims to generate comprehensive RNA-seq data from a wide variety of non-human primates (NHPs), from lemurs to hominids. In the 2012 Phase I of the NHPRTR project, 19 billion fragments or 3.8 terabases of transcriptome sequences were collected from pools of ∼20 tissues in 15 species and subspecies. Here we describe a major expansion of NHPRTR by adding 10.1 billion fragments of tissue-specific RNA-seq data. For this effort, we selected 11 of the original 15 NHP species and subspecies and constructed total RNA libraries for the same ∼15 tissues in each. The sequence quality is such that 88% of the reads align to human reference sequences, allowing us to compute the full list of expression abundance across all tissues for each species, using the reads mapped to human genes. This update also includes improved transcript annotations derived from RNA-seq data for rhesus and cynomolgus macaques, two of the most commonly used NHP models and additional RNA-seq data compiled from related projects. Together, these comprehensive reference transcriptomes from multiple primates serve as a valuable community resource for genome annotation, gene dynamics and comparative functional analysis.

Sequencing of Charcot-Marie-Tooth disease genes in a toxic polyneuropathy

OBJECTIVE

Mutations in Charcot-Marie-Tooth disease (CMT) genes are the cause of rare familial forms of polyneuropathy. Whether allelic variability in CMT genes is also associated with common forms of polyneuropathy-considered "acquired" in medical parlance-is unknown. Chemotherapy-induced peripheral neuropathy (CIPN) occurs commonly in cancer patients and is individually unpredictable. We used CIPN as a clinical model to investigate the association of non-CMT polyneuropathy with CMT genes.

METHODS

A total of 269 neurologically asymptomatic cancer patients were enrolled in the clinical trial Alliance N08C1 to receive the neurotoxic drug paclitaxel, while undergoing prospective assessments for polyneuropathy. Forty-nine CMT genes were analyzed by targeted massively parallel sequencing of genomic DNA from patient blood.

RESULTS

A total of 119 (of 269) patients were identified from the 2 ends of the polyneuropathy phenotype distribution: patients that were most and least susceptible to paclitaxel polyneuropathy. The CMT gene PRX was found to be deleteriously mutated in patients who were susceptible to CIPN but not in controls (p = 8 × 10(-3)). Genetic variation in another CMT gene, ARHGEF10, was highly significantly associated with CIPN (p = 5 × 10(-4)). Three nonsynonymous recurrent single nucleotide variants contributed to the ARHGEF10 signal: rs9657362, rs2294039, and rs17683288. Of these, rs9657362 had the strongest effect (odds ratio = 4.8, p = 4 × 10(-4)).

INTERPRETATION

The results reveal an association of CMT gene allelic variability with susceptibility to CIPN. The findings raise the possibility that other acquired polyneuropathies may also be codetermined by genetic etiological factors, of which some may be related to genes already known to cause the phenotypically related Mendelian disorders of CMT.

Metagenomic shotgun sequencing of a Bunyavirus in wild-caught Aedes aegypti from Thailand informs the evolutionary and genomic history of the Phleboviruses

Arthropod-borne viruses significantly impact human health. They span multiple families, all of which include viruses not known to cause disease. Characterizing these representatives could provide insights into the origins of their disease-causing counterparts. Field-caught Aedes aegypti mosquitoes from Nakhon Nayok, Thailand, underwent metagenomic shotgun sequencing to reveal a Bunyavirus closely related to Phasi Charoen (PhaV) virus, isolated in 2009 from Ae. aegypti near Bangkok. Phylogenetic analysis of this virus suggests it is basal to the Phlebovirus genus thus making it ideally positioned phylogenetically for understanding the evolution of these clinically important viruses. Genomic analysis finds that a gene necessary for virulence in vertebrates, but not essential for viral replication in arthropods, is missing. The sequencing of this phylogenetically-notable and genomically-unique Phlebovirus from wild mosquitoes exemplifies the utility and efficacy of metagenomic shotgun sequencing for virus characterization in arthropod vectors of human diseases.

Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts

The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb).

Assessment and improvement of Indian-origin rhesus macaque and Mauritian-origin cynomolgus macaque genome annotations using deep transcriptome sequencing data

Background

The genome annotations of rhesus (Macaca mulatta) and cynomolgus (Macaca fascicularis) macaques, two of the most common non‐human primate animal models, are limited.

Methods

We analyzed large‐scale macaque RNA‐based next‐generation sequencing (RNAseq) data to identify un‐annotated macaque transcripts.

Results

For both macaque species, we uncovered thousands of novel isoforms for annotated genes and thousands of un‐annotated intergenic transcripts enriched with non‐coding RNAs. We also identified thousands of transcript sequences which are partially or completely ‘missing’ from current macaque genome assemblies. We showed that many newly identified transcripts were differentially expressed during SIV infection of rhesus macaques or during Ebola virus infection of cynomolgus macaques.

Conclusions

For two important macaque species, we uncovered thousands of novel isoforms and un‐annotated intergenic transcripts including coding and non‐coding RNAs, polyadenylated and non‐polyadenylated transcripts. This resource will greatly improve future macaque studies, as demonstrated by their applications in infectious disease studies.

Systematic mapping of occluded genes by cell fusion reveals prevalence and stability of cis-mediated silencing in somatic cells

Both diffusible factors acting in trans and chromatin components acting in cis are implicated in gene regulation, but the extent to which either process causally determines a cell's transcriptional identity is unclear. We recently used cell fusion to define a class of silent genes termed "cis-silenced" (or "occluded") genes, which remain silent even in the presence of trans-acting transcriptional activators. We further showed that occlusion of lineage-inappropriate genes plays a critical role in maintaining the transcriptional identities of somatic cells. Here, we present, for the first time, a comprehensive map of occluded genes in somatic cells. Specifically, we mapped occluded genes in mouse fibroblasts via fusion to a dozen different rat cell types followed by whole-transcriptome profiling. We found that occluded genes are highly prevalent and stable in somatic cells, representing a sizeable fraction of silent genes. Occluded genes are also highly enriched for important developmental regulators of alternative lineages, consistent with the role of occlusion in safeguarding cell identities. Alongside this map, we also present whole-genome maps of DNA methylation and eight other chromatin marks. These maps uncover a complex relationship between chromatin state and occlusion. Furthermore, we found that DNA methylation functions as the memory of occlusion in a subset of occluded genes, while histone deacetylation contributes to the implementation but not memory of occlusion. Our data suggest that the identities of individual cell types are defined largely by the occlusion status of their genomes. The comprehensive reference maps reported here provide the foundation for future studies aimed at understanding the role of occlusion in development and disease.

Cohesin-mediated interactions organize chromosomal domain architecture

To ensure proper gene regulation within constrained nuclear space, chromosomes facilitate access to transcribed regions, while compactly packaging all other information. Recent studies revealed that chromosomes are organized into megabase-scale domains that demarcate active and inactive genetic elements, suggesting that compartmentalization is important for genome function. Here, we show that very specific long-range interactions are anchored by cohesin/CTCF sites, but not cohesin-only or CTCF-only sites, to form a hierarchy of chromosomal loops. These loops demarcate topological domains and form intricate internal structures within them. Post-mitotic nuclei deficient for functional cohesin exhibit global architectural changes associated with loss of cohesin/CTCF contacts and relaxation of topological domains. Transcriptional analysis shows that this cohesin-dependent perturbation of domain organization leads to widespread gene deregulation of both cohesin-bound and non-bound genes. Our data thereby support a role for cohesin in the global organization of domain structure and suggest that domains function to stabilize the transcriptional programmes within them.

From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing

Single-cell RNA-seq mammalian transcriptome studies are at an early stage in uncovering cell-to-cell variation in gene expression, transcript processing and editing, and regulatory module activity. Despite great progress recently, substantial challenges remain, including discriminating biological variation from technical noise. Here we apply the SMART-seq single-cell RNA-seq protocol to study the reference lymphoblastoid cell line GM12878. By using spike-in quantification standards, we estimate the absolute number of RNA molecules per cell for each gene and find significant variation in total mRNA content: between 50,000 and 300,000 transcripts per cell. We directly measure technical stochasticity by a pool/split design and find that there are significant differences in expression between individual cells, over and above technical variation. Specific gene coexpression modules were preferentially expressed in subsets of individual cells, including one enriched for mRNA processing and splicing factors. We assess cell-to-cell variation in alternative splicing and allelic bias and report evidence of significant differences in splice site usage that exceed splice variation in the pool/split comparison. Finally, we show that transcriptomes from small pools of 30–100 cells approach the information content and reproducibility of contemporary RNA-seq from large amounts of input material. Together, our results define an experimental and computational path forward for analyzing gene expression in rare cell types and cell states.

Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells

In the last decade, genome-wide transcriptome analyses have been routinely used to monitor tissue-, disease- and cell type-specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a novel and robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which significantly enhances detailed analyses of alternative transcript isoforms and identification of SNPs. We have determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including new candidate biomarkers for melanoma circulating tumor cells. Importantly, our protocol can easily be utilized for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

The non-human primate reference transcriptome resource (NHPRTR) for comparative functional genomics

RNA-based next-generation sequencing (RNA-Seq) provides a tremendous amount of new information regarding gene and transcript structure, expression and regulation. This is particularly true for non-coding RNAs where whole transcriptome analyses have revealed that the much of the genome is transcribed and that many non-coding transcripts have widespread functionality. However, uniform resources for raw, cleaned and processed RNA-Seq data are sparse for most organisms and this is especially true for non-human primates (NHPs). Here, we describe a large-scale RNA-Seq data and analysis infrastructure, the NHP reference transcriptome resource (http://nhprtr.org); it presently hosts data from12 species of primates, to be expanded to 15 species/subspecies spanning great apes, old world monkeys, new world monkeys and prosimians. Data are collected for each species using pools of RNA from comparable tissues. We provide data access in advance of its deposition at NCBI, as well as browsable tracks of alignments against the human genome using the UCSC genome browser. This resource will continue to host additional RNA-Seq data, alignments and assemblies as they are generated over the coming years and provide a key resource for the annotation of NHP genomes as well as informing primate studies on evolution, reproduction, infection, immunity and pharmacology.

Transcriptome-wide regulation of pre-mRNA splicing and mRNA localization by muscleblind proteins

The muscleblind-like (Mbnl) family of RNA-binding proteins plays important roles in muscle and eye development and in myotonic dystrophy (DM), in which expanded CUG or CCUG repeats functionally deplete Mbnl proteins. We identified transcriptome-wide functional and biophysical targets of Mbnl proteins in brain, heart, muscle, and myoblasts by using RNA-seq and CLIP-seq approaches. This analysis identified several hundred splicing events whose regulation depended on Mbnl function in a pattern indicating functional interchangeability between Mbnl1 and Mbnl2. A nucleotide resolution RNA map associated repression or activation of exon splicing with Mbnl binding near either 3' splice site or near the downstream 5' splice site, respectively. Transcriptomic analysis of subcellular compartments uncovered a global role for Mbnls in regulating localization of mRNAs in both mouse and Drosophila cells, and Mbnl-dependent translation and protein secretion were observed for a subset of mRNAs with Mbnl-dependent localization. These findings hold several new implications for DM pathogenesis.

Single-neuron RNA-Seq: technical feasibility and reproducibility

Understanding brain function involves improved knowledge about how the genome specifies such a large diversity of neuronal types. Transcriptome analysis of single neurons has been previously described using gene expression microarrays. Using high-throughput transcriptome sequencing (RNA-Seq), we have developed a method to perform single-neuron RNA-Seq. Following electrophysiology recording from an individual neuron, total RNA was extracted by aspirating the cellular contents into a fine glass electrode tip. The mRNAs were reverse transcribed and amplified to construct a single-neuron cDNA library, and subsequently subjected to high-throughput sequencing. This approach was applied to both individual neurons cultured from embryonic mouse hippocampus, as well as neocortical neurons from live brain slices. We found that the average pairwise Spearman’s rank correlation coefficient of gene expression level expressed as RPKM (reads per kilobase of transcript per million mapped reads) was 0.51 between five cultured neuronal cells, whereas the same measure between three cortical layer 5 neurons in situ was 0.25. The data suggest that there may be greater heterogeneity of the cortical neurons, as compared to neurons in vitro. The results demonstrate the technical feasibility and reproducibility of RNA-Seq in capturing a part of the transcriptome landscape of single neurons, and confirmed that morphologically identical neurons, even from the same region, have distinct gene expression patterns.

Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia

We have developed an enhanced form of reduced representation bisulfite sequencing with extended genomic coverage, which resulted in greater capture of DNA methylation information of regions lying outside of traditional CpG islands. Applying this method to primary human bone marrow specimens from patients with Acute Myelogeneous Leukemia (AML), we demonstrated that genetically distinct AML subtypes display diametrically opposed DNA methylation patterns. As compared to normal controls, we observed widespread hypermethylation in IDH mutant AMLs, preferentially targeting promoter regions and CpG islands neighboring the transcription start sites of genes. In contrast, AMLs harboring translocations affecting the MLL gene displayed extensive loss of methylation of an almost mutually exclusive set of CpGs, which instead affected introns and distal intergenic CpG islands and shores. When analyzed in conjunction with gene expression profiles, it became apparent that these specific patterns of DNA methylation result in differing roles in gene expression regulation. However, despite this subtype-specific DNA methylation patterning, a much smaller set of CpG sites are consistently affected in both AML subtypes. Most CpG sites in this common core of aberrantly methylated CpGs were hypermethylated in both AML subtypes. Therefore, aberrant DNA methylation patterns in AML do not occur in a stereotypical manner but rather are highly specific and associated with specific driving genetic lesions.

Acute myeloid leukemias (AML) are a group of malignancies that originate in the bone marrow. While many different genetic lesions have been linked to the different forms of this disease, it is also clear that these genetic lesions are not always sufficient to cause AML. DNA methylation plays a role in gene expression regulation, and abnormal distribution of DNA methylation has been observed in many cancers, including AML. Here we demonstrate that changes in DNA methylation in AML are not uniform across all AML subtypes, but rather they display unique patterns, which are closely linked to the underlying genetic lesions of each of the different forms of AML. Furthermore, these unique patterns of DNA methylation have different impacts on gene expression regulation in each AML subtype.

Circulating melanoma cells isolated from clinical blood samples and characterized by full-length mRNA sequencing at single-cell level

10539

Background: Melanoma is the most aggressive type of skin cancer. Late-stage melanoma is highly metastatic and currently lacks effective treatment. This discouraging clinical observation highlights the need for a better understanding of the molecular mechanisms underlying melanoma initiation and progression and for developing new therapeutic approaches based on novel targets. Although genome-wide transcriptome analyses have been frequently used to study molecular alterations in clinical samples, it has been technically challenging to obtain the transcriptomic profiles at single-cell level. Methods: Using antibody-mediated magnetic activated cell separation (MACS), we isolated and individualized putative circulating melanoma cells (CMCs) from the blood samples of the melanoma patients at advance stages. The transcriptomic analysis based on a novel and robust mRNA-Seq protocol (Smart-Seq) was established and applied to the putative CMCs for single-cell profiling. Results: We have discovered distinct gene expression patterns, including new putative markers for CMCs. Meanwhile, the gene expression profiles derived of the CMC candidates isolated from the patient’s blood samples are closely-related to the expression profiles of other cells originated from human melanocytes, including normal melanocytes in primary culture and melanoma cell lines. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which provides advantage for better analyzing transcript isoforms and SNPs. Conclusions: Our results suggest that the techniques developed in this research for cell isolation and transcriptomic analyses can potentially be used for addressing many biological and clinical questions requiring genomewide transcriptome profiling in rare cells.

Diametrically opposite methylome-transcriptome relationships in high- and low-CpG promoter genes in postmitotic neural rat tissue

DNA methylation can control some CpG-poor genes but unbiased studies have not found a consistent genome-wide association with gene activity outside of CpG islands or shores possibly due to use of cell lines or limited bioinformatics analyses. We performed reduced representation bisulfite sequencing (RRBS) of rat dorsal root ganglia encompassing postmitotic primary sensory neurons (n = 5, r > 0.99; orthogonal validation p < 10(-19)). The rat genome suggested a dichotomy of genes previously reported in other mammals: low CpG content (< 3.2%) promoter (LCP) genes and high CpG content (≥ 3.2%) promoter (HCP) genes. A genome-wide integrated methylome-transcriptome analysis showed that LCP genes were markedly hypermethylated when repressed, and hypomethylated when active with a 40% difference in a broad region at the 5' of the transcription start site (p < 10(-87) for -6000 bp to -2000 bp, p < 10(-73) for -2000 bp to +2000 bp, no difference in gene body p = 0.42). HCP genes had minimal TSS-associated methylation regardless of transcription status, but gene body methylation appeared to be lost in repressed HCP genes. Therefore, diametrically opposite methylome-transcriptome associations characterize LCP and HCP genes in postmitotic neural tissue in vivo.

Detection of redundant fusion transcripts as biomarkers or disease-specific therapeutic targets in breast cancer

Fusion genes and fusion gene products are widely employed as biomarkers and therapeutic targets in hematopoietic cancers, but their applications have yet to be appreciated in solid tumors. Here, we report the use of SnowShoes-FTD, a powerful new analytic pipeline that can identify fusion transcripts and assess their redundancy and tumor subtype-specific distribution in primary tumors. In a study of primary breast tumors, SnowShoes-FTD was used to analyze paired-end mRNA-Seq data from a panel of estrogen receptor (ER)(+), HER2(+), and triple-negative primary breast tumors, identifying tumor-specific fusion transcripts by comparison with mRNA-Seq data from nontransformed human mammary epithelial cell cultures plus the Illumina Body Map data from normal tissues. We found that every primary breast tumor that was analyzed expressed one or more fusion transcripts. Of the 131 tumor-specific fusion transcripts identified, 86 were "private" (restricted to a single tumor) and 45 were "redundant" (distributed among multiple tumors). Among the redundant fusion transcripts, 7 were unique to ER(+) tumors and 8 were unique to triple-negative tumors. In contrast, none of the redundant fusion transcripts were unique to HER2(+) tumors. Both private and redundant fusion transcripts were widely expressed in primary breast tumors, with many mapping to genomic loci implicated in breast carcinogenesis and/or risk. Our finding that some fusion transcripts are tumor subtype-specific suggests that these entities may be critical determinants in the etiology of breast cancer subtypes, useful as biomarkers for tumor stratification, or exploitable as cancer-specific therapeutic targets.

P3-06-02: Identification of Redundant, Tumor Subtype Specific Fusion Transcripts in Primary Breast Tumors

Background: The role of fusion genes and associated fusion transcripts has long been recognized in hematopoietic malignancies. Until quite recently it has been difficult to detect such events on a genomic scale in solid tumors. Consequently, little is known about the potential role of fusion genes, transcripts, and proteins as driver mutations, biomarkers, or therapeutic targets in breast cancer.

Methods: We have developed a novel analytical pipeline, Snowshoes-FTD, for detection of fusion transcripts in breast cancer cell lines and tumor samples (Asmann, et al. NAR 2011; May 27 ePub ahead of print). Preliminary analyses have been carried out with a panel of 8 each ER+, HER2+, and triple negative (TN) primary breast tumors, 8 primary human mammary epithelial cell (HMEC) lines from biopsy samples, plus 16 normal tissues from the Illumina Body Map dataset.

Results: We have identified 120 redundant, tumor-specific fusion transcripts, expressed in two or more tumors and in no non-transformed samples. Sixteen of these represent intrachromosomal fusions and 104 arise from fusion of transcripts that map to two different chromosomes. Every breast tumor expressed one or more fusion transcripts. Twenty-nine fusion transcripts appeared to be tumor subtype specific. Among these, we have identified 2 HER2+, 10 ER+, and 17 triple negative specific redundant transcripts. In general, HER2+ tumors expressed fewer fusion transcripts (range 4 to 28/tumor) compared to TN (range11 to 44/tumor). Chromosomal distribution patterns were also markedly different among the tumor subtypes. For example, ER+ tumors expressed a preponderance of redundant fusion transcripts that involve chr1 and 2, whereas TN tumors had no fusion transcripts that map to either chromosome. Conversely, the predominant locus for TN fusion transcripts was chr19, which contains only one HER2+ fusion and no ER+ fusion transcripts.

Conclusions: Primary breast tumors express many chimaeric transcripts, which we presume to arise primarily from genomic rearrangements. The majority of these transcripts are redundant, and a subset are tumor subtype specific. These transcripts may mark regions of chromosomal instability. HER2+ tumors, in general, appear to evidence less chromosomal instability, as inferred from fusion transcripts; although some HER2+ tumors appear to be quite unstable. TN tumors contain many more redundant fusion transcripts, implying increased genomic instability, particularly in chr19. We conclude that these fusion transcripts represent a class of heretofore unrecognized biomarkers that may be used for sub-classification of breast tumors. Some of these transcripts appear to encode proteins that may function as tumor-subtype-specific driver mutations and may have potential as therapeutic targets in breast cancer.

Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P3-06-02.

Phyloepigenomic comparison of great apes reveals a correlation between somatic and germline methylation states

We have determined methylation state differences in the epigenomes of uncultured cells purified from human, chimpanzee, and orangutan, using digestion with a methylation-sensitive enzyme, deep sequencing, and computational analysis of the sequence data. The methylomes show a high degree of conservation, but the methylation states of ~10% of CpG island-like regions differ significantly between human and chimp. The differences are not associated with changes in CG content and recapitulate the known phylogenetic relationship of the three species, indicating that they are stably maintained within each species. Inferences about the relationship between somatic and germline methylation states can be made by an analysis of CG decay, derived from methylation and sequence data. This indicates that somatic methylation states are highly related to germline states and that the methylation differences between human and chimp have occurred in the germline. These results provide evidence for epigenetic changes that occur in the germline and distinguish closely related species and suggest that germline epigenetic states might constrain somatic states.

Duplex-specific nuclease efficiently removes rRNA for prokaryotic RNA-seq

Next-generation sequencing has great potential for application in bacterial transcriptomics. However, unlike eukaryotes, bacteria have no clear mechanism to select mRNAs over rRNAs; therefore, rRNA removal is a critical step in sequencing-based transcriptomics. Duplex-specific nuclease (DSN) is an enzyme that, at high temperatures, degrades duplex DNA in preference to single-stranded DNA. DSN treatment has been successfully used to normalize the relative transcript abundance in mRNA-enriched cDNA libraries from eukaryotic organisms. In this study, we demonstrate the utility of this method to remove rRNA from prokaryotic total RNA. We evaluated the efficacy of DSN to remove rRNA by comparing it with the conventional subtractive hybridization (Hyb) method. Illumina deep sequencing was performed to obtain transcriptomes from Escherichia coli grown under four growth conditions. The results clearly showed that our DSN treatment was more efficient at removing rRNA than the Hyb method was, while preserving the original relative abundance of mRNA species in bacterial cells. Therefore, we propose that, for bacterial mRNA-seq experiments, DSN treatment should be preferred to Hyb-based methods.