Norma F. Neff

Clinical assessment incorporating a personal genome

BACKGROUND The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context. METHODS We assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patients full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks. FINDINGS Analysis of 2.6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death-TMEM43, DSP, and MYBPC3. A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported. INTERPRETATION Although challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients. FUNDING National Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Childrens Health; Hewlett Packard Foundation; Breetwor Family Foundation.

Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq

The mammalian lung is a highly branched network in which the distal regions of the bronchial tree transform during development into a densely packed honeycomb of alveolar air sacs that mediate gas exchange. Although this transformation has been studied by marker expression analysis and fate-mapping, the mechanisms that control the progression of lung progenitors along distinct lineages into mature alveolar cell types are still incompletely known, in part because of the limited number of lineage markers and the effects of ensemble averaging in conventional transcriptome analysis experiments on cell populations. Here we show that single-cell transcriptome analysis circumvents these problems and enables direct measurement of the various cell types and hierarchies in the developing lung. We used microfluidic single-cell RNA sequencing (RNA-seq) on 198 individual cells at four different stages encompassing alveolar differentiation to measure the transcriptional states which define the developmental and cellular hierarchy of the distal mouse lung epithelium. We empirically classified cells into distinct groups by using an unbiased genome-wide approach that did not require a priori knowledge of the underlying cell types or the previous purification of cell populations. The results confirmed the basic outlines of the classical model of epithelial cell-type diversity in the distal lung and led to the discovery of many previously unknown cell-type markers, including transcriptional regulators that discriminate between the different populations. We reconstructed the molecular steps during maturation of bipotential progenitors along both alveolar lineages and elucidated the full life cycle of the alveolar type 2 cell lineage. This single-cell genomics approach is applicable to any developing or mature tissue to robustly delineate molecularly distinct cell types, define progenitors and lineage hierarchies, and identify lineage-specific regulatory factors.

The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

Chinese hamster ovary (CHO)–derived cell lines are the preferred host cells for the production of therapeutic proteins. Here we present a draft genomic sequence of the CHO-K1 ancestral cell line. The assembly comprises 2.45 Gb of genomic sequence, with 24,383 predicted genes. We associate most of the assembled scaffolds with 21 chromosomes isolated by microfluidics to identify chromosomal locations of genes. Furthermore, we investigate genes involved in glycosylation, which affect therapeutic protein quality, and viral susceptibility genes, which are relevant to cell engineering and regulatory concerns. Homologs of most human glycosylation-associated genes are present in the CHO-K1 genome, although 141 of these homologs are not expressed under exponential growth conditions. Many important viral entry genes are also present in the genome but not expressed, which may explain the unusual viral resistance property of CHO cell lines. We discuss how the availability of this genome sequence may facilitate genome-scale science for the optimization of biopharmaceutical protein production.

Single-cell dissection of transcriptional heterogeneity in human colon tumors.

Cancer is often viewed as a caricature of normal developmental processes, but the extent to which its cellular heterogeneity truly recapitulates multilineage differentiation processes of normal tissues remains unknown. Here we implement single-cell PCR gene-expression analysis to dissect the cellular composition of primary human normal colon and colon cancer epithelia. We show that human colon cancer tissues contain distinct cell populations whose transcriptional identities mirror those of the different cellular lineages of normal colon. By creating monoclonal tumor xenografts from injection of a single (n = 1) cell, we demonstrate that the transcriptional diversity of cancer tissues is largely explained by in vivo multilineage differentiation and not only by clonal genetic heterogeneity. Finally, we show that the different gene-expression programs linked to multilineage differentiation are strongly associated with patient survival. We develop two-gene classifier systems (KRT20 versus CA1, MS4A12, CD177, SLC26A3) that predict clinical outcomes with hazard ratios superior to those of pathological grade and comparable to those of microarray-derived multigene expression signatures.

Single-molecule sequencing of an individual human genome

Recent advances in high-throughput DNA sequencing technologies have enabled order-of-magnitude improvements in both cost and throughput. Here we report the use of single-molecule methods to sequence an individual human genome. We aligned billions of 24- to 70-bp reads (32 bp average) to ∼90% of the National Center for Biotechnology Information (NCBI) reference genome, with 28× average coverage. Our results were obtained on one sequencing instrument by a single operator with four data collection runs. Single-molecule sequencing enabled analysis of human genomic information without the need for cloning, amplification or ligation. We determined ∼2.8 million single nucleotide polymorphisms (SNPs) with a false-positive rate of less than 1% as validated by Sanger sequencing and 99.8% concordance with SNP genotyping arrays. We identified 752 regions of copy number variation by analyzing coverage depth alone and validated 27 of these using digital PCR. This milestone should allow widespread application of genome sequencing to many aspects of genetics and human health, including personal genomics.

Quantitative assessment of single-cell RNA-sequencing methods

Interest in single-cell whole-transcriptome analysis is growing rapidly, especially for profiling rare or heterogeneous populations of cells. We compared commercially available single-cell RNA amplification methods with both microliter and nanoliter volumes, using sequence from bulk total RNA and multiplexed quantitative PCR as benchmarks to systematically evaluate the sensitivity and accuracy of various single-cell RNA-seq approaches. We show that single-cell RNA-seq can be used to perform accurate quantitative transcriptome measurement in individual cells with a relatively small number of sequencing reads and that sequencing large numbers of single cells can recapitulate bulk transcriptome complexity.

Tracking single hematopoietic stem cells in vivo using high-throughput sequencing in conjunction with viral genetic barcoding

Disentangling cellular heterogeneity is a challenge in many fields, particularly in the stem cell and cancer biology fields. Here we demonstrate how to combine viral genetic barcoding with high-throughput sequencing to track single cells in a heterogeneous population. We use this technique to track the in vivo differentiation of unitary hematopoietic stem cells (HSCs). The results are consistent with single-cell transplantation studies but require two orders of magnitude fewer mice. In addition to its high throughput, the high sensitivity of the technique allows for a direct examination of the clonality of sparse cell populations such as HSCs. We show how these capabilities offer a clonal perspective of the HSC differentiation process. In particular, our data suggest that HSCs do not equally contribute to blood cells after irradiation-mediated transplantation, and that two distinct HSC differentiation patterns co-exist in the same recipient mouse after irradiation. This technique can be applied to any virus-accessible cell type for both in vitro and in vivo processes.

The genome sequence of the colonial chordate, Botryllus schlosseri

Botryllus schlosseri is a colonial urochordate that follows the chordate plan of development following sexual reproduction, but invokes a stem cell-mediated budding program during subsequent rounds of asexual reproduction. As urochordates are considered to be the closest living invertebrate relatives of vertebrates, they are ideal subjects for whole genome sequence analyses. Using a novel method for high-throughput sequencing of eukaryotic genomes, we sequenced and assembled 580 Mbp of the B. schlosseri genome. The genome assembly is comprised of nearly 14,000 intron-containing predicted genes, and 13,500 intron-less predicted genes, 40% of which could be confidently parceled into 13 (of 16 haploid) chromosomes. A comparison of homologous genes between B. schlosseri and other diverse taxonomic groups revealed genomic events underlying the evolution of vertebrates and lymphoid-mediated immunity. The B. schlosseri genome is a community resource for studying alternative modes of reproduction, natural transplantation reactions, and stem cell-mediated regeneration. DOI: http://dx.doi.org/10.7554/eLife.00569.001

Circulating Cell-Free DNA Enables Noninvasive Diagnosis of Heart Transplant Rejection

In a prospective cohort study of heart transplant recipients, sequencing-based quantification of donor-derived DNA in plasma of recipients noninvasively diagnosed transplant rejection. Donor DNA Indicates Transplant Rejection Not all heart transplants succeed, but early detection of organ rejection could spare the patient severe adverse events and graft dysfunction. De Vlaminck et al. devised a noninvasive, sequencing-based method to monitor and predict rejection, relying on the presence of donor DNA in recipient blood plasma. The fraction of donor DNA is naturally elevated 1 day after transplant (because organ transplants are essentially genome transplants), and these levels decline exponentially over the course of the week, if the organ is accepted. The authors noted that patients who rejected their new heart had high levels of donor DNA even months after transplant. In a prospective trial, elevated donor DNA was detected months before the rejection episode, suggesting that such noninvasive analysis tools could be used in lieu of an invasive biopsy, to let doctors know which patients are likely to reject their transplanted organ. Monitoring allograft health is an important component of posttransplant therapy. Endomyocardial biopsy is the current gold standard for cardiac allograft monitoring but is an expensive and invasive procedure. Proof of principle of a universal, noninvasive diagnostic method based on high-throughput screening of circulating cell-free donor-derived DNA (cfdDNA) was recently demonstrated in a small retrospective cohort. We present the results of a prospective cohort study (65 patients, 565 samples) that tested the utility of cfdDNA in measuring acute rejection after heart transplantation. Circulating cell-free DNA was purified from plasma and sequenced (mean depth, 1.2 giga–base pairs) to quantify the fraction of cfdDNA. Through a comparison with endomyocardial biopsy results, we demonstrate that cfdDNA enables diagnosis of acute rejection after heart transplantation, with an area under the receiver operating characteristic curve of 0.83 and sensitivity and specificity that are comparable to the intrinsic performance of the biopsy itself. This noninvasive genome transplant dynamics approach is a powerful and informative method for routine monitoring of allograft health without incurring the risk, discomfort, and expense of an invasive biopsy.

Dissecting direct reprogramming from fibroblast to neuron using single-cell RNA-seq

Direct lineage reprogramming represents a remarkable conversion of cellular and transcriptome states1–3. However, the intermediates through which individual cells progress are largely undefined. Here we used single-cell RNA-seq4–7 at multiple time points to dissect direct reprogramming from mouse embryonic fibroblasts (MEFs) to induced neuronal (iN) cells. By deconstructing heterogeneity at each time point and ordering cells by transcriptome similarity, we find that the molecular reprogramming path is remarkably continuous. Overexpression of the proneural pioneer factor Ascl1 results in a well-defined initialization, causing cells to exit the cell cycle and re-focus gene expression through distinct neural transcription factors. The initial transcriptional response is relatively homogeneous among fibroblasts suggesting the early steps are not limiting for productive reprogramming. Instead, the later emergence of a competing myogenic program and variable transgene dynamics over time appear to be the major efficiency limits of direct reprogramming. Moreover, a transcriptional state, distinct from donor and target cell programs, is transiently induced in cells undergoing productive reprogramming. Our data provide a high-resolution approach for understanding transcriptome states during lineage differentiation.