Explore the vast range of titles available.

Key Points There are two major paradigms in next-generation sequencing (NGS) technology: short-read sequencing and long-read sequencing. Short-read sequencing approaches provide lower-cost, higher-accuracy data that are useful for population-level research and clinical variant discovery. By contrast, long-read approaches provide read lengths that are well suited for de novo genome assembly applications and full-length isoform sequencing. NGS technologies have been evolving over the past 10 years, leading to substantial improvements in quality and yield; however, certain approaches have proven to be more effective and adaptable than others. Recent improvements in chemistry, costs, throughput and accessibility are driving the emergence of new, varied technologies to address applications that were not previously possible. These include integrated long-read and short-read sequencing studies, routine clinical DNA sequencing, real-time pathogen DNA monitoring and massive population-level projects. Although massive strides are being made in this technology, several notable limitations remain. The time required to sequence and analyse data limits the use of NGS in clinical applications in which time is an important factor; the costs and error rates of long-read sequencing make it prohibitive for routine use, and ethical considerations can limit the public and private use of genetic data. We can expect increasing democratization and options for NGS in the future. Many new instruments with varied chemistries and applications are being released or being developed. Advances in DNA sequencing technologies have led to vast increases in the diversity of sequencing-based applications and in the amount of data generated. This Review discusses the current state-of-the-art technologies in both short-read and long-read DNA sequencing, their underlying mechanisms, relative strengths and limitations, and emerging applications. Since the completion of the human genome project in 2003, extraordinary progress has been made in genome sequencing technologies, which has led to a decreased cost per megabase and an increase in the number and diversity of sequenced genomes. An astonishing complexity of genome architecture has been revealed, bringing these sequencing technologies to even greater advancements. Some approaches maximize the number of bases sequenced in the least amount of time, generating a wealth of data that can be used to understand increasingly complex phenotypes. Alternatively, other approaches now aim to sequence longer contiguous pieces of DNA, which are essential for resolving structurally complex regions. These and other strategies are providing researchers and clinicians a variety of tools to probe genomes in greater depth, leading to an enhanced understanding of how genome sequence variants underlie phenotype and disease.

In adults, more than 300 billion blood cells are replenished daily. This output arises from a cellular hierarchy where stem cells differentiate into a series of multilineage progenitors, culminating in unilineage progenitors that generate over 10 different mature blood cell types. Notta et al. mapped the lineage potential of nearly 3000 single cells from 33 different cell populations of stem and progenitor cells from fetal liver, cord blood, and adult bone marrow (see the Perspective by Cabezas-Wallscheid and Trumpp). Prenatally, stem cell and progenitor populations were multilineage with few unilineage progenitors. In adults, multilineage cell potential was only seen in stem cell populations. Science , this issue p. 10.1126/science.aab2116 ; see also p. 126 As humans age, progenitor cells take over from stem cells the task of producing a steady supply of blood cells. [Also see Perspective by Cabezas-Wallscheid and Trumpp ] In a classical view of hematopoiesis, the various blood cell lineages arise via a hierarchical scheme starting with multipotent stem cells that become increasingly restricted in their differentiation potential through oligopotent and then unipotent progenitors. We developed a cell-sorting scheme to resolve myeloid (My), erythroid (Er), and megakaryocytic (Mk) fates from single CD34 + cells and then mapped the progenitor hierarchy across human development. Fetal liver contained large numbers of distinct oligopotent progenitors with intermingled My, Er, and Mk fates. However, few oligopotent progenitor intermediates were present in the adult bone marrow. Instead, only two progenitor classes predominate, multipotent and unipotent, with Er-Mk lineages emerging from multipotent cells. The developmental shift to an adult “two-tier” hierarchy challenges current dogma and provides a revised framework to understand normal and disease states of human hematopoiesis.

There is a growing gap between the generation of massively parallel sequencing output and the ability to process and analyze the resulting data. New users are left to navigate a bewildering maze of base calling, alignment, assembly and analysis tools with often incomplete documentation and no idea how to compare and validate their outputs. Bridging this gap is essential, or the coveted $1,000 genome will come with a $20,000 analysis price tag.

miRNAs are a class of regulatory molecules involved in a wide range of cellular functions, including growth, development and apoptosis. Given their widespread roles in biological processes, understanding their patterns of expression in normal and diseased states will provide insights into the consequences of aberrant expression. As such, global miRNA expression profiling of human malignancies is gaining popularity in both basic and clinically driven research. However, to date, the majority of such analyses have used microarrays and quantitative real-time PCR. With the introduction of digital count technologies, such as next-generation sequencing (NGS) and the NanoString nCounter System, we have at our disposal many more options. To make effective use of these different platforms, the strengths and pitfalls of several miRNA profiling technologies were assessed, including a microarray platform, NGS technologies and the NanoString nCounter System. Overall, NGS had the greatest detection sensitivity, largest dynamic range of detection and highest accuracy in differential expression analysis when compared with gold-standard quantitative real-time PCR. Its technical reproducibility was high, with intrasample correlations of at least 0.95 in all cases. Furthermore, miRNA analysis of formalin-fixed, paraffin-embedded (FFPE) tissue was also evaluated. Expression profiles between paired frozen and FFPE samples were similar, with Spearman's ρ>0.93. These results show the superior sensitivity, accuracy and robustness of NGS for the comprehensive profiling of miRNAs in both frozen and FFPE tissues.

Paul Boutros, Robert Bristow and colleagues report a molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer. They find that multifocal tumors are highly heterogeneous, and they identify a novel recurrent amplification of MYCL1 . Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL , which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Identification of the cell types from which relapse arises in acute myeloid leukaemia, by following leukaemia propagation from patient-derived leukaemia samples. AML relapse can develop from stem cells Relapse is frequently seen in patients with acute myeloid leukemia (AML). John Dick and colleagues now uncover the cell types from which relapse arises by following leukaemia propagation from patient-derived leukaemia samples. Surprisingly, they found that relapse can arise from two distinct leukaemia cell populations, both of which display stemness features. The first group consisted of rare leukaemia stem cells with a haematopoietic stem/progenitor cell phenotype, and the second were larger subclones of immunophenotypically committed leukaemia cells. These findings may help to better monitor and target relapse AML. In acute myeloid leukaemia, long-term survival is poor as most patients relapse despite achieving remission 1 . Historically, the failure of therapy has been thought to be due to mutations that produce drug resistance, possibly arising as a consequence of the mutagenic properties of chemotherapy drugs 2 . However, other lines of evidence have pointed to the pre-existence of drug-resistant cells 3 . For example, deep sequencing of paired diagnosis and relapse acute myeloid leukaemia samples has provided direct evidence that relapse in some cases is generated from minor genetic subclones present at diagnosis that survive chemotherapy 3 , 4 , 5 , suggesting that resistant cells are generated by evolutionary processes before treatment 3 and are selected by therapy 6 , 7 , 8 . Nevertheless, the mechanisms of therapy failure and capacity for leukaemic regeneration remain obscure, as sequence analysis alone does not provide insight into the cell types that are fated to drive relapse. Although leukaemia stem cells 9 , 10 have been linked to relapse owing to their dormancy and self-renewal properties 11 , 12 , 13 , and leukaemia stem cell gene expression signatures are highly predictive of therapy failure 14 , 15 , experimental studies have been primarily correlative 7 and a role for leukaemia stem cells in acute myeloid leukaemia relapse has not been directly proved. Here, through combined genetic and functional analysis of purified subpopulations and xenografts from paired diagnosis/relapse samples, we identify therapy-resistant cells already present at diagnosis and two major patterns of relapse. In some cases, relapse originated from rare leukaemia stem cells with a haematopoietic stem/progenitor cell phenotype, while in other instances relapse developed from larger subclones of immunophenotypically committed leukaemia cells that retained strong stemness transcriptional signatures. The identification of distinct patterns of relapse should lead to improved methods for disease management and monitoring in acute myeloid leukaemia. Moreover, the shared functional and transcriptional stemness properties that underlie both cellular origins of relapse emphasize the importance of developing new therapeutic approaches that target stemness to prevent relapse.

Bin Tean Teh, Patrick Tan, Steven Rozen, Irinel Popescu and colleagues report exome sequencing of cholangiocarcinomas, including cases caused by liver fluke ( Opisthorchis viverrini ) infection and cases caused by non– O. viverrini etiologies. They identify recurrent somatic mutations in BAP1 and ARID1A and demonstrate different mutation patterns in liver fluke infection–related and non-infection-related cancers. The impact of different carcinogenic exposures on the specific patterns of somatic mutation in human tumors remains unclear. To address this issue, we profiled 209 cholangiocarcinomas (CCAs) from Asia and Europe, including 108 cases caused by infection with the liver fluke Opisthorchis viverrini and 101 cases caused by non– O. viverrini –related etiologies. Whole-exome sequencing ( n = 15) and prevalence screening ( n = 194) identified recurrent somatic mutations in BAP1 and ARID1A , neither of which, to our knowledge, has previously been reported to be mutated in CCA. Comparisons between intrahepatic O. viverrini –related and non– O. viverrini –related CCAs demonstrated statistically significant differences in mutation patterns: BAP1 , IDH1 and IDH2 were more frequently mutated in non– O. viverrini CCAs, whereas TP53 mutations showed the reciprocal pattern. Functional studies demonstrated tumor suppressive functions for BAP1 and ARID1A , establishing the role of chromatin modulators in CCA pathogenesis. These findings indicate that different causative etiologies may induce distinct somatic alterations, even within the same tumor type.

The use of liquid biopsies for cancer detection and management is rapidly gaining prominence 1 . Current methods for the detection of circulating tumour DNA involve sequencing somatic mutations using cell-free DNA, but the sensitivity of these methods may be low among patients with early-stage cancer given the limited number of recurrent mutations 2 – 5 . By contrast, large-scale epigenetic alterations—which are tissue- and cancer-type specific—are not similarly constrained 6 and therefore potentially have greater ability to detect and classify cancers in patients with early-stage disease. Here we develop a sensitive, immunoprecipitation-based protocol to analyse the methylome of small quantities of circulating cell-free DNA, and demonstrate the ability to detect large-scale DNA methylation changes that are enriched for tumour-specific patterns. We also demonstrate robust performance in cancer detection and classification across an extensive collection of plasma samples from several tumour types. This work sets the stage to establish biomarkers for the minimally invasive detection, interception and classification of early-stage cancers based on plasma cell-free DNA methylation patterns. An immunoprecipitation-based protocol is developed to analyse DNA methylation in small quantities of circulating cell-free DNA, and can detect and classify cancers in plasma samples from several tumour types.

Germline mutations in the BRCA2 tumour suppressor are associated with both an increased lifetime risk of developing prostate cancer (PCa) and increased risk of aggressive disease. To understand this aggression, here we profile the genomes and methylomes of localized PCa from 14 carriers of deleterious germline BRCA2 mutations ( BRCA2 -mutant PCa). We show that BRCA2 -mutant PCa harbour increased genomic instability and a mutational profile that more closely resembles metastastic than localized disease. BRCA2 -mutant PCa shows genomic and epigenomic dysregulation of the MED12L / MED12 axis, which is frequently dysregulated in metastatic castration-resistant prostate cancer (mCRPC). This dysregulation is enriched in BRCA2 -mutant PCa harbouring intraductal carcinoma (IDC). Microdissection and sequencing of IDC and juxtaposed adjacent non-IDC invasive carcinoma in 10 patients demonstrates a common ancestor to both histopathologies. Overall we show that localized castration-sensitive BRCA2 -mutant tumours are uniquely aggressive, due to de novo aberration in genes usually associated with metastatic disease, justifying aggressive initial treatment. Men that carrier BRCA2 germline mutations are at risk of developing prostate cancer. Here, the authors analyse the genomes of prostate cancer from these individuals and demonstrate increased genomic instability in comparison to sporadic prostate cancer.

The incidence of acute myeloid leukaemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 65. Most cases arise without any detectable early symptoms and patients usually present with the acute complications of bone marrow failure 1 . The onset of such de novo AML cases is typically preceded by the accumulation of somatic mutations in preleukaemic haematopoietic stem and progenitor cells (HSPCs) that undergo clonal expansion 2 , 3 . However, recurrent AML mutations also accumulate in HSPCs during ageing of healthy individuals who do not develop AML, a phenomenon referred to as age-related clonal haematopoiesis (ARCH) 4 – 8 . Here we use deep sequencing to analyse genes that are recurrently mutated in AML to distinguish between individuals who have a high risk of developing AML and those with benign ARCH. We analysed peripheral blood cells from 95 individuals that were obtained on average 6.3 years before AML diagnosis (pre-AML group), together with 414 unselected age- and gender-matched individuals (control group). Pre-AML cases were distinct from controls and had more mutations per sample, higher variant allele frequencies, indicating greater clonal expansion, and showed enrichment of mutations in specific genes. Genetic parameters were used to derive a model that accurately predicted AML-free survival; this model was validated in an independent cohort of 29 pre-AML cases and 262 controls. Because AML is rare, we also developed an AML predictive model using a large electronic health record database that identified individuals at greater risk. Collectively our findings provide proof-of-concept that it is possible to discriminate ARCH from pre-AML many years before malignant transformation. This could in future enable earlier detection and monitoring, and may help to inform intervention. Individuals who are at high risk of developing acute myeloid leukaemia can be identified years before diagnosis using genetic information from blood samples.