Ziming Weng

3′-End Sequencing for Expression Quantification (3SEQ) from Archival Tumor Samples

Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast majority of archival tumor samples. To address this limitation of gene expression microarrays, we designed a novel procedure (3′-end sequencing for expression quantification (3SEQ)) for gene expression profiling from FFPET using next-generation sequencing. We performed gene expression profiling by 3SEQ and microarray on both frozen tissue and FFPET from two soft tissue tumors (desmoid type fibromatosis (DTF) and solitary fibrous tumor (SFT)) (total n = 23 samples, which were each profiled by at least one of the four platform-tissue preparation combinations). Analysis of 3SEQ data revealed many genes differentially expressed between the tumor types (FDR<0.01) on both the frozen tissue (∼9.6K genes) and FFPET (∼8.1K genes). Analysis of microarray data from frozen tissue revealed fewer differentially expressed genes (∼4.64K), and analysis of microarray data on FFPET revealed very few (69) differentially expressed genes. Functional gene set analysis of 3SEQ data from both frozen tissue and FFPET identified biological pathways known to be important in DTF and SFT pathogenesis and suggested several additional candidate oncogenic pathways in these tumors. These findings demonstrate that 3SEQ is an effective technique for gene expression profiling from archival tumor samples and may facilitate significant advances in translational cancer research.

Genome evolution during progression to breast cancer.

Cancer evolution involves cycles of genomic damage, epigenetic deregulation, and increased cellular proliferation that eventually culminate in the carcinoma phenotype. Early neoplasias, which are often found concurrently with carcinomas and are histologically distinguishable from normal breast tissue, are less advanced in phenotype than carcinomas and are thought to represent precursor stages. To elucidate their role in cancer evolution we performed comparative whole-genome sequencing of early neoplasias, matched normal tissue, and carcinomas from six patients, for a total of 31 samples. By using somatic mutations as lineage markers we built trees that relate the tissue samples within each patient. On the basis of these lineage trees we inferred the order, timing, and rates of genomic events. In four out of six cases, an early neoplasia and the carcinoma share a mutated common ancestor with recurring aneuploidies, and in all six cases evolution accelerated in the carcinoma lineage. Transition spectra of somatic mutations are stable and consistent across cases, suggesting that accumulation of somatic mutations is a result of increased ancestral cell division rather than specific mutational mechanisms. In contrast to highly advanced tumors that are the focus of much of the current cancer genome sequencing, neither the early neoplasia genomes nor the carcinomas are enriched with potentially functional somatic point mutations. Aneuploidies that occur in common ancestors of neoplastic and tumor cells are the earliest events that affect a large number of genes and may predispose breast tissue to eventual development of invasive carcinoma.

Lineage-specific enhancers activate self-renewal genes in macrophages and embryonic stem cells

Genetic programming for self-renewal Instead of repopulating themselves from tissue-resident stem cell pools like most types of differentiated cells, tissue macrophages maintain themselves by self-renewing. The underlying genetic programs that allow for this, however, are unknown. Soucie et al. now report that in macrophages at homeostasis, a pair of transcription factors (MafB and c-Maf) bind to and repress the enhancers of genes regulating self-renewal. When macrophages need to replenish their stocks, for example in response to injury, they transiently decrease MafB and c-Maf expression so they can self-renew. A parallel pathway also operates to control the self-renewal of embryonic stem cells. Science, this issue p. 10.1126/science.aad5510 Tissue macrophages and embryonic stem cells use similar genetic programs to self-renew. INTRODUCTION In many organs of the body, differentiated cells are frequently lost and need to be replaced as part of normal homeostatic tissue maintenance or in response to injury. In most cases, this regeneration is assured by differentiation from tissue-specific stem cells. Together with a few other cell types, tissue macrophages represent a rare exception to this pathway, as they can be maintained independently of blood stem cells by local proliferation. Under certain conditions, mature macrophages can also be expanded and maintained long term in culture without transformation or loss of differentiation status. The gene regulatory mechanisms that allow such differentiated cells to self-renew while maintaining cell type–specific identity have so far remained unknown. Self-renewing macrophages provide a rare opportunity to study this question. RATIONALE Molecularly, cell identity can be defined by the genomic positions of gene regulatory enhancer elements. The cell type–specific signatures and activity status of such elements have been characterized by the analysis of specific histone modifications and the binding of regulatory proteins. To identify the regulatory mechanisms that enable macrophage self-renewal capacity to be integrated into the overall program of epigenetic macrophage identity, we have compared the enhancer repertoires of quiescent and self-renewing macrophages. Based on our previous observations that deletion of MafB and c-Maf transcription factors results in an extended self-renewal capacity of macrophages, we further investigated how the absence of Maf transcription factors affects the enhancers of specific self-renewal genes and how these mechanisms activate macrophage self-renewal under homeostatic and challenge conditions in vivo. RESULTS Compared to quiescent macrophages, self-renewing macrophages showed no appreciable difference with respect to genome-wide enhancer positions but displayed an increase in the activation status of many enhancers that were also bound by the lineage-specifying transcription factor PU.1 in both cell types. This finding suggests that these poised macrophage-specific enhancers became active in self-renewing macrophages. We found activated enhancers to be associated with a network of genes, centered on Myc and Klf2, that were up-regulated and functionally important for self-renewal in these cells. The same genes were also required for embryonic stem (ES) cell self-renewal but were associated with a distinct, ES cell–specific set of enhancers. We observed that activated self-renewal–associated macrophage enhancers were directly repressed by MafB binding. The loss of MafB and c-Maf expression relieved this repression and led to activation of the self-renewal gene network in MafB and cMaf knockout macrophages, as well as in alveolar macrophages that express constitutively low levels of these transcription factors. In vivo single-cell analysis further revealed that, both in the steady state and in response to immune stimulation, proliferating resident macrophages could access this network by transient down-regulation of Maf transcription factors. CONCLUSION Our results demonstrate that self-renewal in macrophages involves down-regulation of MafB and cMaf, as well as concomitant activation of a self-renewal gene network shared with ES cells but controlled from cell type–specific enhancers. Macrophage enhancers associated with self-renewal genes are already present in quiescent cells and can become activated when direct repression by Maf transcription factors is relieved. Our findings provide a general molecular rationale for the compatibility of self-renewal and differentiated cell functions and may also be more generally relevant for the direct activation of self-renewal activity in other differentiated cell types with therapeutic potential. The self-renewal potential of both ES cells and differentiated macrophages is dependent on a shared network of self-renewal genes (left) that are controlled by distinct lineage-specific enhancers (right). In quiescent macrophages, the transcription factor MafB binds and represses these enhancers. The loss of MafB expression results in enhancer activation and enables macrophage self-renewal. At bottom left, red arrows indicate activation; blue bars represent inhibition. Circle size is a function of the number of times the target is affected by other regulators. MΦ, macrophage; E, enhancer; P, promoter. ILLUSTRATION: SERENA BIELLI Differentiated macrophages can self-renew in tissues and expand long term in culture, but the gene regulatory mechanisms that accomplish self-renewal in the differentiated state have remained unknown. Here we show that in mice, the transcription factors MafB and c-Maf repress a macrophage-specific enhancer repertoire associated with a gene network that controls self-renewal. Single-cell analysis revealed that, in vivo, proliferating resident macrophages can access this network by transient down-regulation of Maf transcription factors. The network also controls embryonic stem cell self-renewal but is associated with distinct embryonic stem cell–specific enhancers. This indicates that distinct lineage-specific enhancer platforms regulate a shared network of genes that control self-renewal potential in both stem and mature cells.

Read clouds uncover variation in complex regions of the human genome

Although an increasing amount of human genetic variation is being identified and recorded, determining variants within repeated sequences of the human genome remains a challenge. Most population and genome-wide association studies have therefore been unable to consider variation in these regions. Core to the problem is the lack of a sequencing technology that produces reads with sufficient length and accuracy to enable unique mapping. Here, we present a novel methodology of using read clouds, obtained by accurate short-read sequencing of DNA derived from long fragment libraries, to confidently align short reads within repeat regions and enable accurate variant discovery. Our novel algorithm, Random Field Aligner (RFA), captures the relationships among the short reads governed by the long read process via a Markov Random Field. We utilized a modified version of the Illumina TruSeq synthetic long-read protocol, which yielded shallow-sequenced read clouds. We test RFA through extensive simulations and apply it to discover variants on the NA12878 human sample, for which shallow TruSeq read cloud sequencing data are available, and on an invasive breast carcinoma genome that we sequenced using the same method. We demonstrate that RFA facilitates accurate recovery of variation in 155 Mb of the human genome, including 94% of 67 Mb of segmental duplication sequence and 96% of 11 Mb of transcribed sequence, that are currently hidden from short-read technologies.

Cell-lineage heterogeneity and driver mutation recurrence in pre-invasive breast neoplasia

BackgroundAll cells in an individual are related to one another by a bifurcating lineage tree, in which each node is an ancestral cell that divided into two, each branch connects two nodes, and the root is the zygote. When a somatic mutation occurs in an ancestral cell, all its descendants carry the mutation, which can then serve as a lineage marker for the phylogenetic reconstruction of tumor progression. Using this concept, we investigate cell lineage relationships and genetic heterogeneity of pre-invasive neoplasias compared to invasive carcinomas.MethodsWe deeply sequenced over a thousand phylogenetically informative somatic variants in 66 morphologically independent samples from six patients that represent a spectrum of normal, early neoplasia, carcinoma in situ, and invasive carcinoma. For each patient, we obtained a highly resolved lineage tree that establishes the phylogenetic relationships among the pre-invasive lesions and with the invasive carcinoma.ResultsThe trees reveal lineage heterogeneity of pre-invasive lesions, both within the same lesion, and between histologically similar ones. On the basis of the lineage trees, we identified a large number of independent recurrences of PIK3CA H1047 mutations in separate lesions in four of the six patients, often separate from the diagnostic carcinoma.ConclusionsOur analyses demonstrate that multi-sample phylogenetic inference provides insights on the origin of driver mutations, lineage heterogeneity of neoplastic proliferations, and the relationship of genomically aberrant neoplasias with the primary tumors. PIK3CA driver mutations may be comparatively benign inducers of cellular proliferation.

Culture-free generation of microbial genomes from human and marine microbiomes

Our understanding of natural microbial communities is shaped by the careful investigation of a relatively small number of isolated and cultured organisms, and by analysis of genomic sequences obtained by culture-free metagenomic sequencing approaches. Metagenomic shotgun sequencing has facilitated partial reconstruction of strain-level community structure and functional repertoire. Unfortunately, it remains difficult to cost-effectively produce high quality genome drafts for individual microbes without isolation and culture. Recent molecular techniques that partition long DNA fragments and then barcode short fragments derived from them produce “read clouds”, which are short-read sequences containing long-range information. Here, we present a novel application of a read cloud technique to microbiome samples, as well as Athena, a de novo assembler that uses these barcodes to produce improved metagenomic assemblies. We apply our approach to sequence human stool samples from two healthy individuals, and compare it to existing short read and synthetic long read metagenomic sequencing approaches. We find that read cloud metagenomic sequencing and Athena assembly produce the most complete individual genome drafts. These genome drafts are also highly contiguous (>200kb N50, <10 contigs), even for bacteria that have relatively low (20x) raw short read sequence coverage. We also apply this approach to a significantly more complex marine sediment sample and obtain 23 genome drafts with valuable 16S ribosomal RNA taxonomic marker sequences, nine of which are complete genome drafts. Read cloud metagenomic sequencing allows culture-free generation of high quality microbial genome drafts using only a single shotgun experiment.

Comprehensive Genomic Characterization of Breast Tumors with BRCA1 and BRCA2 Mutations

Background Germline mutations in the BRCA1 and BRCA2 genes predispose carriers to breast and ovarian cancer, and there remains a need to identify the specific genomic mechanisms by which cancer evolves in these patients. Here we present a systematic genomic analysis of breast tumors with BRCA1 and BRCA2 mutations, comparing these to common types of sporadic breast tumors. Results We identify differences between BRCA-mutated and sporadic breast tumors in patterns of point mutation, DNA methylation and structural variation. We show that structural variation disproportionately affects tumor suppressor genes and identify specific driver gene candidates that are enriched for structural variation. Conclusions Compared to sporadic tumors, BRCA-mutated breast tumors show signals of reduced DNA methylation, more ancestral cell divisions, and elevated rates of structural variation that tend to disrupt highly expressed protein-coding genes and known tumor suppressors. Our analysis suggests that BRCA-mutated tumors are more aggressive than sporadic breast cancers because loss of the BRCA pathway causes multiple processes of mutagenesis and gene dysregulation.

High-quality genome sequences of uncultured microbes by assembly of read clouds

Although shotgun metagenomic sequencing of microbiome samples enables partial reconstruction of strain-level community structure, obtaining high-quality microbial genome drafts without isolation and culture remains difficult. Here, we present an application of read clouds, short-read sequences tagged with long-range information, to microbiome samples. We present Athena, a de novo assembler that uses read clouds to improve metagenomic assemblies. We applied this approach to sequence stool samples from two healthy individuals and compared it with existing short-read and synthetic long-read metagenomic sequencing techniques. Read-cloud metagenomic sequencing and Athena assembly produced the most comprehensive individual genome drafts with high contiguity (>200-kb N50, fewer than ten contigs), even for bacteria with relatively low (20×) raw short-read-sequence coverage. We also sequenced a complex marine-sediment sample and generated 24 intermediate-quality genome drafts (>70% complete, <10% contaminated), nine of which were complete (>90% complete, <5% contaminated). Our approach allows for culture-free generation of high-quality microbial genome drafts by using a single shotgun experiment.

Read Clouds Uncover Variation in Complex Regions of the Human Genome

The rapid advance of next-generation sequencing (NGS) technologies has decreased the cost of genomic sequencing dramatically, enabling accurate variant discovery across whole genomes of many individuals. Current large-scale and cost-effective resequencing platforms produce reads of limited length, and as a result, reliable identification of variants within highly homologous regions of a target genome remains challenging.