Genome sequencing and analysis of the Tasmanian devil and its transmissible cancer.

The Tasmanian devil (Sarcophilus harrisii), the largest marsupial carnivore, is endangered due to a transmissible facial cancer spread by direct transfer of living cancer cells through biting. Here we describe the sequencing, assembly, and annotation of the Tasmanian devil genome and whole-genome sequences for two geographically distant subclones of the cancer. Genomic analysis suggests that the cancer first arose from a female Tasmanian devil and that the clone has subsequently genetically diverged during its spread across Tasmania. The devil cancer genome contains more than 17,000 somatic base substitution mutations and bears the imprint of a distinct mutational process. Genotyping of somatic mutations in 104 geographically and temporally distributed Tasmanian devil tumors reveals the pattern of evolution and spread of this parasitic clonal lineage, with evidence of a selective sweep in one geographical area and persistence of parallel lineages in other populations.

Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis.

Monozygotic or 'identical' twins have been widely studied to dissect the relative contributions of genetics and environment in human diseases. In multiple sclerosis (MS), an autoimmune demyelinating disease and common cause of neurodegeneration and disability in young adults, disease discordance in monozygotic twins has been interpreted to indicate environmental importance in its pathogenesis. However, genetic and epigenetic differences between monozygotic twins have been described, challenging the accepted experimental model in disambiguating the effects of nature and nurture. Here we report the genome sequences of one MS-discordant monozygotic twin pair, and messenger RNA transcriptome and epigenome sequences of CD4(+) lymphocytes from three MS-discordant, monozygotic twin pairs. No reproducible differences were detected between co-twins among approximately 3.6 million single nucleotide polymorphisms (SNPs) or approximately 0.2 million insertion-deletion polymorphisms. Nor were any reproducible differences observed between siblings of the three twin pairs in HLA haplotypes, confirmed MS-susceptibility SNPs, copy number variations, mRNA and genomic SNP and insertion-deletion genotypes, or the expression of approximately 19,000 genes in CD4(+) T cells. Only 2 to 176 differences in the methylation of approximately 2 million CpG dinucleotides were detected between siblings of the three twin pairs, in contrast to approximately 800 methylation differences between T cells of unrelated individuals and several thousand differences between tissues or between normal and cancerous tissues. In the first systematic effort to estimate sequence variation among monozygotic co-twins, we did not find evidence for genetic, epigenetic or transcriptome differences that explained disease discordance. These are the first, to our knowledge, female, twin and autoimmune disease individual genome sequences reported.

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.

Monitoring chronic lymphocytic leukemia progression by whole genome sequencing reveals heterogeneous clonal evolution patterns.

Chronic lymphocytic leukemia is characterized by relapse after treatment and chemotherapy resistance. Similarly, in other malignancies leukemia cells accumulate mutations during growth, forming heterogeneous cell populations that are subject to Darwinian selection and may respond differentially to treatment. There is therefore a clinical need to monitor changes in the subclonal composition of cancers during disease progression. Here, we use whole-genome sequencing to track subclonal heterogeneity in 3 chronic lymphocytic leukemia patients subjected to repeated cycles of therapy. We reveal different somatic mutation profiles in each patient and use these to establish probable hierarchical patterns of subclonal evolution, to identify subclones that decline or expand over time, and to detect founder mutations. We show that clonal evolution patterns are heterogeneous in individual patients. We conclude that genome sequencing is a powerful and sensitive approach to monitor disease progression repeatedly at the molecular level. If applied to future clinical trials, this approach might eventually influence treatment strategies as a tool to individualize and direct cancer treatment.

Alternative isoform regulation in human tissue transcriptomes.

Through alternative processing of pre-messenger RNAs, individual mammalian genes often produce multiple mRNA and protein isoforms that may have related, distinct or even opposing functions. Here we report an in-depth analysis of 15 diverse human tissue and cell line transcriptomes on the basis of deep sequencing of complementary DNA fragments, yielding a digital inventory of gene and mRNA isoform expression. Analyses in which sequence reads are mapped to exon-exon junctions indicated that 92-94% of human genes undergo alternative splicing, 86% with a minor isoform frequency of 15% or more. Differences in isoform-specific read densities indicated that most alternative splicing and alternative cleavage and polyadenylation events vary between tissues, whereas variation between individuals was approximately twofold to threefold less common. Extreme or 'switch-like' regulation of splicing between tissues was associated with increased sequence conservation in regulatory regions and with generation of full-length open reading frames. Patterns of alternative splicing and alternative cleavage and polyadenylation were strongly correlated across tissues, suggesting coordinated regulation of these processes, and sequence conservation of a subset of known regulatory motifs in both alternative introns and 3' untranslated regions suggested common involvement of specific factors in tissue-level regulation of both splicing and polyadenylation.

mRNA-seq with agnostic splice site discovery for nervous system transcriptomics tested in chronic pain.

mRNA-seq is a paradigm-shifting technology because of its superior sensitivity and dynamic range and its potential to capture transcriptomes in an agnostic fashion, i.e., independently of existing genome annotations. Implementation of the agnostic approach, however, has not yet been fully achieved. In particular, agnostic mapping of pre-mRNA splice sites has not been demonstrated. The present study pursued dual goals: (1) to advance mRNA-seq bioinformatics toward unbiased transcriptome capture and (2) to demonstrate its potential for discovery in neuroscience by applying the approach to an in vivo model of neurological disease. We have performed mRNA-seq on the L4 dorsal root ganglion (DRG) of rats with chronic neuropathic pain induced by spinal nerve ligation (SNL) of the neighboring (L5) spinal nerve. We found that 12.4% of known genes were induced and 7% were suppressed in the dysfunctional (but anatomically intact) L4 DRG 2 wk after SNL. These alterations persisted chronically (2 mo). Using a read cluster classifier with strong test characteristics (ROC area 97%), we discovered 10,464 novel exons. A new algorithm for agnostic mapping of pre-mRNA splice junctions (SJs) achieved a precision of 97%. Integration of information from all mRNA-seq read classes including SJs led to genome reannotations specifically relevant for the species used (rat), the anatomical site studied (DRG), and the neurological disease considered (pain); for example, a 64-exon coreceptor for the nociceptive transmitter substance P was identified, and 21.9% of newly discovered exons were shown to be dysregulated. Thus, mRNA-seq with agnostic analysis methods appears to provide a highly productive approach for in vivo transcriptomics in the nervous system.

A mutation in TGFB3 associated with a syndrome of low muscle mass, growth retardation, distal arthrogryposis and clinical features overlapping with Marfan and Loeys-Dietz syndrome.

The transforming growth factor ß (TGF-ß) family of growth factors are key regulators of mammalian development and their dysregulation is implicated in human disease, notably, heritable vasculopathies including Marfan (MFS, OMIM #154700) and Loeys-Dietz syndromes (LDS, OMIM #609192). We described a syndrome presenting at birth with distal arthrogryposis, hypotonia, bifid uvula, a failure of normal post-natal muscle development but no evidence of vascular disease; some of these features overlap with MFS and LDS. A de novo mutation in TGFB3 was identified by exome sequencing. Several lines of evidence indicate the mutation is hypomorphic suggesting that decreased TGF-ß signaling from a loss of TGFB3 activity is likely responsible for the clinical phenotype. This is the first example of a mutation in the coding portion of TGFB3 implicated in a clinical syndrome suggesting TGFB3 is essential for both human palatogenesis and normal muscle growth.

Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing.

Defining the transcriptome, the repertoire of transcribed regions encoded in the genome, is a challenging experimental task. Current approaches, relying on sequencing of ESTs or cDNA libraries, are expensive and labor-intensive. Here, we present a general approach for ab initio discovery of the complete transcriptome of the budding yeast, based only on the unannotated genome sequence and millions of short reads from a single massively parallel sequencing run. Using novel algorithms, we automatically construct a highly accurate transcript catalog. Our approach automatically and fully defines 86% of the genes expressed under the given conditions, and discovers 160 previously undescribed transcription units of 250 bp or longer. It correctly demarcates the 5' and 3' UTR boundaries of 86 and 77% of expressed genes, respectively. The method further identifies 83% of known splice junctions in expressed genes, and discovers 25 previously uncharacterized introns, including 2 cases of condition-dependent intron retention. Our framework is applicable to poorly understood organisms, and can lead to greater understanding of the transcribed elements in an explored genome.

Chimeric transcript discovery by paired-end transcriptome sequencing.

Recurrent gene fusions are a prevalent class of mutations arising from the juxtaposition of 2 distinct regions, which can generate novel functional transcripts that could serve as valuable therapeutic targets in cancer. Therefore, we aim to establish a sensitive, high-throughput methodology to comprehensively catalog functional gene fusions in cancer by evaluating a paired-end transcriptome sequencing strategy. Not only did a paired-end approach provide a greater dynamic range in comparison with single read based approaches, but it clearly distinguished the high-level "driving" gene fusions, such as BCR-ABL1 and TMPRSS2-ERG, from potential lower level "passenger" gene fusions. Also, the comprehensiveness of a paired-end approach enabled the discovery of 12 previously undescribed gene fusions in 4 commonly used cell lines that eluded previous approaches. Using the paired-end transcriptome sequencing approach, we observed read-through mRNA chimeras, tissue-type restricted chimeras, converging transcripts, diverging transcripts, and overlapping mRNA transcripts. Last, we successfully used paired-end transcriptome sequencing to detect previously undescribed ETS gene fusions in prostate tumors. Together, this study establishes a highly specific and sensitive approach for accurately and comprehensively cataloguing chimeras within a sample using paired-end transcriptome sequencing.

Ultra-deep sequencing validates safety of CRISPR/Cas9 genome editing in human hematopoietic stem and progenitor cells.

As CRISPR-based therapies enter the clinic, evaluation of safety remains a critical and active area of study. Here, we employ a clinical next generation sequencing (NGS) workflow to achieve high sequencing depth and detect ultra-low frequency variants across exons of genes associated with cancer, all exons, and genome wide. In three separate primary human hematopoietic stem and progenitor cell (HSPC) donors assessed in technical triplicates, we electroporated high-fidelity Cas9 protein targeted to three loci (AAVS1, HBB, and ZFPM2) and harvested genomic DNA at days 4 and 10. Our results demonstrate that clinically relevant delivery of high-fidelity Cas9 to primary HSPCs and ex vivo culture up to 10 days does not introduce or enrich for tumorigenic variants and that even a single SNP in a gRNA spacer sequence is sufficient to eliminate Cas9 off-target activity in primary, repair-competent human HSPCs.

Cross-Comparison of Human iPSC Motor Neuron Models of Familial and Sporadic ALS Reveals Early and Convergent Transcriptomic Disease Signatures.

Induced pluripotent stem cell (iPSC)-derived neural cultures from amyotrophic lateral sclerosis (ALS) patients can model disease phenotypes. However, heterogeneity arising from genetic and experimental variability limits their utility, impacting reproducibility and the ability to track cellular origins of pathogenesis. Here, we present methodologies using single-cell RNA sequencing (scRNA-seq) analysis to address these limitations. By repeatedly differentiating and applying scRNA-seq to motor neurons (MNs) from healthy, familial ALS, sporadic ALS, and genome-edited iPSC lines across multiple patients, batches, and platforms, we account for genetic and experimental variability toward identifying unified and reproducible ALS signatures. Combining HOX and developmental gene expression with global clustering, we anatomically classified cells into rostrocaudal, progenitor, and postmitotic identities. By relaxing statistical thresholds, we discovered genes in iPSC-MNs that were concordantly dysregulated in postmortem MNs and yielded predictive ALS markers in other human and mouse models. Our approach thus revealed early, convergent, and MN-resolved signatures of ALS.

Transcriptome analysis of Pseudomonas syringae identifies new genes, noncoding RNAs, and antisense activity.

To fully understand how bacteria respond to their environment, it is essential to assess genome-wide transcriptional activity. New high-throughput sequencing technologies make it possible to query the transcriptome of an organism in an efficient unbiased manner. We applied a strand-specific method to sequence bacterial transcripts using Illumina's high-throughput sequencing technology. The resulting sequences were used to construct genome-wide transcriptional profiles. Novel bioinformatics analyses were developed and used in combination with proteomics data for the qualitative classification of transcriptional activity in defined regions. As expected, most transcriptional activity was consistent with predictions from the genome annotation. Importantly, we identified and confirmed transcriptional activity in areas of the genome inconsistent with the annotation and in unannotated regions. Further analyses revealed potential RpoN-dependent promoter sequences upstream of several noncoding RNAs (ncRNAs), suggesting a role for these ncRNAs in RpoN-dependent phenotypes. We were also able to validate a number of transcriptional start sites, many of which were consistent with predicted promoter motifs. Overall, our approach provides an efficient way to survey global transcriptional activity in bacteria and enables rapid discovery of specific areas in the genome that merit further investigation.

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

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: a systems approach to disease.

Prostate cancer is initially responsive to androgen ablation therapy and progresses to androgen-unresponsive states that are refractory to treatment. The mechanism of this transition is unknown. A systems approach to disease begins with the quantitative delineation of the informational elements (mRNAs and proteins) in various disease states. We employed two recently developed high-throughput technologies, massively parallel signature sequencing (MPSS) and isotope-coded affinity tag, to gain a comprehensive picture of the changes in mRNA levels and more restricted analysis of protein levels, respectively, during the transition from androgen-dependent LNCaP (model for early-stage prostate cancer) to androgen-independent CL1 cells (model for late-stage prostate cancer). We sequenced >5 million MPSS signatures, obtained >142,000 tandem mass spectra, and built comprehensive MPSS and proteomic databases. The integrated mRNA and protein expression data revealed underlying functional differences between androgen-dependent and androgen-independent prostate cancer cells. The high sensitivity of MPSS enabled us to identify virtually all of the expressed transcripts and to quantify the changes in gene expression between these two cell states, including functionally important low-abundance mRNAs, such as those encoding transcription factors and signal transduction molecules. These data enable us to map the differences onto extant physiologic networks, creating perturbation networks that reflect prostate cancer progression. We found 37 BioCarta and 14 Kyoto Encyclopedia of Genes and Genomes pathways that are up-regulated and 23 BioCarta and 22 Kyoto Encyclopedia of Genes and Genomes pathways that are down-regulated in LNCaP cells versus CL1 cells. Our efforts represent a significant step toward a systems approach to understanding prostate cancer progression.

Massively parallel signature sequencing profiling of fetal human neural precursor cells.

We have examined gene expression in multipotent neural precursor cells (NPCs) derived from human fetal (f) brain tissue and compared its expression profiles with embryonic stem (ESC) cells, embryoid body cell (EBC), and astrocyte precursors using the technique of massively parallel signature sequencing (MPSS). Gene expression profiles show that fNPCs express core neural stem cells markers and share expression profiles with astrocyte precursor cells (APCs) rather than ESC or EBC. Gene expression analysis shows that fNPCs differ from other adult stem and progenitor cells in their marker expression and activation of specific functional networks such as the transforming growth factorbeta (TGFbeta) and Notch signaling pathways. In addition, our results allow us to identify novel genes expressed in fNPCs and provide a detailed profile of fNPCs.

Massively parallel signature sequencing.

Massively parallel signature sequencing is an ultra-high throughput sequencing technology. It can simultaneously sequence millions of sequence tags, and, therefore, is ideal for whole genome analysis. When applied to expression profiling, it reveals almost every transcript in the sample and provides its accurate expression level. This chapter describes the technology and its application in establishing stem cell transcriptome databases.

MPSS profiling of human embryonic stem cells.

BACKGROUND: Pooled human embryonic stem cells (hESC) cell lines were profiled to obtain a comprehensive list of genes common to undifferentiated human embryonic stem cells. RESULTS: Pooled hESC lines were profiled to obtain a comprehensive list of genes common to human ES cells. Massively parallel signature sequencing (MPSS) of approximately three million signature tags (signatures) identified close to eleven thousand unique transcripts, of which approximately 25% were uncharacterised or novel genes. Expression of previously identified ES cell markers was confirmed and multiple genes not known to be expressed by ES cells were identified by comparing with public SAGE databases, EST libraries and parallel analysis by microarray and RT-PCR. Chromosomal mapping of expressed genes failed to identify major hotspots and confirmed expression of genes that map to the X and Y chromosome. Comparison with published data sets confirmed the validity of the analysis and the depth and power of MPSS. CONCLUSIONS: Overall, our analysis provides a molecular signature of genes expressed by undifferentiated ES cells that can be used to monitor the state of ES cells isolated by different laboratories using independent methods and maintained under differing culture conditions

Monitoring early differentiation events in human embryonic stem cells by massively parallel signature sequencing and expressed sequence tag scan.

To identify genes that may be involved in the process of human embryonic stem cell (hESC) differentiation, we profiled gene expression by expressed sequenced tag (EST) enumeration and massively parallel signature sequencing (MPSS) using RNA samples from feeder-free cultures of undifferentiated (passages 40-50) and differentiated (day 14) H1, H7, and H9 lines. MPSS and EST scan analysis showed good concordance and identified a large number of genes that changed rapidly as cultures transition from a pluripotent to a differentiated state. These included known and unknown ES cell-specific genes as well as a large number of known genes that were altered as cells differentiate. A subset of genes that were either up- or down-regulated were selected and their differential expression confirmed by a variety of independent methods, including comparison of expression after further differentiation, publicly available databases, and direct assessments by reverse transcriptase (RT)-PCR and immunocytochemistry. The analysis identified markers unique to the hESC and embryoid bodies (hEBs) stage as well as signaling pathways that likely regulate differentiation. The data generated can be used to monitor the state of hESC isolated by different laboratories using independent methods and maintained under differing culture conditions.

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.

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

Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type­specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a 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 enhances detailed analyses of alternative transcript isoforms and identification of single-nucleotide polymorphisms. We determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. We found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including candidate biomarkers for melanoma circulating tumor cells. Our protocol will be useful for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.