Following injury, pathologically activated vocal fold fibroblasts (VFFs) can engage in disordered extracellular matrix (ECM) remodeling, leading to VF fibrosis and impaired voice function. Given the importance of scar VFFs to phenotypically appropriate in vitro modeling of VF fibrosis, we pursued detailed characterization of scar VFFs obtained from surgically injured rat VF mucosae, compared with those obtained from experimentally naïve, age-matched tissue. Scar VFFs initially exhibited a myofibroblast phenotype characterized by increased proliferation, increased Col1a1 transcription and collagen, type I synthesis, increased Acta2 transcription and α-smooth muscle actin synthesis, and enhanced contractile function. These features were most distinct at passage 1 (P1); we observed a coalescence of the scar and naïve VFF phenotypes at later passages. An empirical Bayes statistical analysis of the P1 cell transcriptome identified 421 genes that were differentially expressed by scar, compared with naïve, VFFs. These genes were primarily associated with the wound response, ECM regulation, and cell proliferation. Follow-up comparison of P1 scar VFFs and their in vivo tissue source showed substantial transcriptomic differences. Finally, P1 scar VFFs responded to treatment with hepatocyte growth factor and transforming growth factor-β3, two biologics with reported therapeutic value. Despite the practical limitations inherent to working with early passage cells, this experimental model is easily implemented in any suitably equipped laboratory and has the potential to improve the applicability of preclinical VF fibrosis research.

Previously, we have used clinical and gene expression data from The Cancer Genome Atlas (TCGA) to model a pathway-based index predicting outcomes in ovarian carcinoma. This data were obtained from snap-frozen tissue measured with the Affymetrix U133 platform. In the current study, we correlate the data used to model with data derived from TaqMan qPCR both snap frozen and paraffin embedded (FFPE) samples.

Although markers identified by genome-wide association studies have individually strong statistical significance, their performance in prediction remains limited. Our goal was to use animal breeding genomic prediction models to predict additive genetic contributions for systolic blood pressure (SBP) using whole genome sequencing data with different validation designs. The additive genetic contributions of SBP were estimated via linear mixed model. Rare variants (MAF<0.05) were collapsed through the k-means method to create a "collapsed single-nucleotide polymorphisms." Prediction of the additive genomic contributions of SBP was conducted using genomic Best Linear Unbiased Predictor (GBLUP) and BayesCπ. Estimates of predictive accuracy were compared using common single-nucleotide polymorphisms (SNPs) versus common and collapsed SNPs, and for prediction within and across families. The additive genetic variance of SBP contributed to 18% of the phenotypic variance (h(2) = 0.18). BayesCπ had slightly better prediction accuracies than GBLUP. In both models, within-family predictions had higher accuracies both in the training and testing set than didacross-family design. Collapsing rare variants via the k-means method and adding to the common SNPs did not improve prediction accuracies. The prediction model, including both pedigree and genomic information, achieved a slightly higher accuracy than using either source of information alone. Prediction of genetic contributions to complex traits is feasible using whole genome sequencing and statistical methods borrowed from animal breeding. The relatedness of individuals between the training and testing set strongly affected the performance of prediction models. Methods for inclusion of rare variants in these models need more development.

Oscillatory gene expression is fundamental to development, but technologies for monitoring expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applying Oscope to a number of data sets, we demonstrated its utility and also identified a potential artifact in the Fluidigm C1 platform.

The salamander has the remarkable ability to regenerate its limb after amputation. Cells at the site of amputation form a blastema and then proliferate and differentiate to regrow the limb. To better understand this process, we performed deep RNA sequencing of the blastema over a time course in the axolotl, a species whose genome has not been sequenced. Using a novel comparative approach to analyzing RNA-seq data, we characterized the transcriptional dynamics of the regenerating axolotl limb with respect to the human gene set. This approach involved de novo assembly of axolotl transcripts, RNA-seq transcript quantification without a reference genome, and transformation of abundances from axolotl contigs to human genes. We found a prominent burst in oncogene expression during the first day and blastemal/limb bud genes peaking at 7 to 14 days. In addition, we found that limb patterning genes, SALL genes, and genes involved in angiogenesis, wound healing, defense/immunity, and bone development are enriched during blastema formation and development. Finally, we identified a category of genes with no prior literature support for limb regeneration that are candidates for further evaluation based on their expression pattern during the regenerative process.

Although numerous quantitative trait loci (QTL) influencing disease-related phenotypes have been detected through gene mapping and positional cloning, identification of the individual gene(s) and molecular pathways leading to those phenotypes is often elusive. One way to improve understanding of genetic architecture is to classify phenotypes in greater depth by including transcriptional and metabolic profiling. In the current study, we have generated and analyzed mRNA expression and metabolic profiles in liver samples obtained in an F2 intercross between the diabetes-resistant C57BL/6 leptin(ob/ob) and the diabetes-susceptible BTBR leptin(ob/ob) mouse strains. This cross, which segregates for genotype and physiological traits, was previously used to identify several diabetes-related QTL. Our current investigation includes microarray analysis of over 40,000 probe sets, plus quantitative mass spectrometry-based measurements of sixty-seven intermediary metabolites in three different classes (amino acids, organic acids, and acyl-carnitines). We show that liver metabolites map to distinct genetic regions, thereby indicating that tissue metabolites are heritable. We also demonstrate that genomic analysis can be integrated with liver mRNA expression and metabolite profiling data to construct causal networks for control of specific metabolic processes in liver. As a proof of principle of the practical significance of this integrative approach, we illustrate the construction of a specific causal network that links gene expression and metabolic changes in the context of glutamate metabolism, and demonstrate its validity by showing that genes in the network respond to changes in glutamine and glutamate availability. Thus, the methods described here have the potential to reveal regulatory networks that contribute to chronic, complex, and highly prevalent diseases and conditions such as obesity and diabetes.

From bacteria to humans, individual cells within isogenic populations can show significant variation in stress tolerance, but the nature of this heterogeneity is not clear. To investigate this, we used single-cell RNA sequencing to quantify transcript heterogeneity in single Saccharomyces cerevisiae cells treated with and without salt stress to explore population variation and identify cellular covariates that influence the stress-responsive transcriptome. Leveraging the extensive knowledge of yeast transcriptional regulation, we uncovered significant regulatory variation in individual yeast cells, both before and after stress. We also discovered that a subset of cells appears to decouple expression of ribosomal protein genes from the environmental stress response in a manner partly correlated with the cell cycle but unrelated to the yeast ultradian metabolic cycle. Live-cell imaging of cells expressing pairs of fluorescent regulators, including the transcription factor Msn2 with Dot6, Sfp1, or MAP kinase Hog1, revealed both coordinated and decoupled nucleocytoplasmic shuttling. Together with transcriptomic analysis, our results suggest that cells maintain a cellular filter against decoupled bursts of transcription factor activation but mount a stress response upon coordinated regulation, even in a subset of unstressed cells.

During vertebrate development, progenitor cells give rise to tissues and organs through a complex choreography that commences at gastrulation. A hallmark event of gastrulation is the formation of the primitive streak, a linear assembly of cells along the anterior-posterior (AP) axis of the developing organism. To examine the primitive streak at a single-cell resolution, we measured the transcriptomes of individual chick cells from the streak or the surrounding tissue (the rest of the area pellucida) in Hamburger-Hamilton stage 4 embryos. The single-cell transcriptomes were then ordered by the statistical method Wave-Crest to deduce both the relative position along the AP axis and the prospective lineage of single cells. The ordered transcriptomes reveal intricate patterns of gene expression along the primitive streak.

The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach.

Human pluripotent stem cells hold significant promise for regenerative medicine. However, long differentiation protocols and immature characteristics of stem cell-derived cell types remain challenges to the development of many therapeutic applications. In contrast to the slow differentiation of human stem cells in vitro that mirrors a nine-month gestation period, mouse stem cells develop according to a much faster three-week gestation timeline. Here, we tested if co-differentiation with mouse pluripotent stem cells could accelerate the differentiation speed of human embryonic stem cells. Following a six-week RNA-sequencing time course of neural differentiation, we identified 929 human genes that were upregulated earlier and 535 genes that exhibited earlier peaked expression profiles in chimeric cell cultures than in human cell cultures alone. Genes with accelerated upregulation were significantly enriched in Gene Ontology terms associated with neurogenesis, neuron differentiation and maturation, and synapse signaling. Moreover, chimeric mixed samples correlated with in utero human embryonic samples earlier than human cells alone, and acceleration was dose-dependent on human-mouse co-culture ratios. The altered gene expression patterns and developmental rates described in this report have implications for accelerating human stem cell differentiation and the use of interspecies chimeric embryos in developing human organs for transplantation.

Development of treatments for vocal dysphonia has been inhibited by lack of human vocal fold (VF) mucosa models because of difficulty in procuring VF epithelial cells, epithelial cells' limited proliferative capacity and absence of cell lines. Here we report development of engineered VF mucosae from hiPSC, transfected via TALEN constructs for green fluorescent protein, that mimic development of VF epithelial cells in utero. Modulation of FGF signaling achieves stratified squamous epithelium from definitive and anterior foregut derived cultures. Robust culturing of these cells on collagen-fibroblast constructs produces three-dimensional models comparable to in vivo VF mucosa. Furthermore, we demonstrate mucosal inflammation upon exposure of these constructs to 5% cigarette smoke extract. Upregulation of pro-inflammatory genes in epithelium and fibroblasts leads to aberrant VF mucosa remodeling. Collectively, our results demonstrate that hiPSC-derived VF mucosa is a versatile tool for future investigation of genetic and molecular mechanisms underlying epithelium-fibroblasts interactions in health and disease.

Defects in somitogenesis result in vertebral malformations at birth known as spondylocostal dysostosis (SCDO). Somites are formed with a species-specific periodicity controlled by the "segmentation clock," which comprises a group of oscillatory genes in the presomitic mesoderm. Here, we report that a segmentation clock model derived from human embryonic stem cells shows many hallmarks of the mammalian segmentation clock in vivo, including a dependence on the NOTCH and WNT signaling pathways. The gene expression oscillations are highly synchronized, displaying a periodicity specific to the human clock. Introduction of a point of mutation into HES7, a specific mutation previously associated with clinical SCDO, eliminated clock gene oscillations, successfully reproducing the defects in the segmentation clock. Thus, we provide a model for studying the previously inaccessible human segmentation clock to better understand the mechanisms contributing to congenital skeletal defects.

The larynx, trachea, and esophagus share origin and proximity during embryonic development. Clinical and experimental evidence support the existence of neurophysiological, structural, and functional interdependencies before birth. This investigation provides the first comprehensive transcriptional profile of all three organs during embryonic organogenesis, where differential gene expression gradually assembles the identity and complexity of these proximal organs from a shared origin in the anterior foregut. By applying bulk RNA sequencing and gene network analysis of differentially expressed genes (DEGs) within and across developing embryonic mouse larynx, esophagus, and trachea, we identified co-expressed modules of genes enriched for key biological processes. Organ-specific temporal patterns of gene activity corresponding to gene modules within and across shared tissues during embryonic development (E10.5-E18.5) are described, and the laryngeal transcriptome during vocal fold development and maturation from birth to adulthood is characterized in the context of laryngeal organogenesis. The findings of this study provide new insights into interrelated gene sets governing the organogenesis of this tripartite organ system within the aerodigestive tract. They are relevant to multiple families of disorders defined by cardiocraniofacial syndromes.

Normalization to remove technical or experimental artifacts is critical in the analysis of single-cell RNA-sequencing experiments, even those for which unique molecular identifiers are available. The majority of methods for normalizing single-cell RNA-sequencing data adjust average expression for library size (LS), allowing the variance and other properties of the gene-specific expression distribution to be non-constant in LS. This often results in reduced power and increased false discoveries in downstream analyses, a problem which is exacerbated by the high proportion of zeros present in most datasets.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity is observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC are molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A is identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis reveals molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

With improvements in next-generation sequencing technologies and reductions in price, ordered RNA-seq experiments are becoming common. Of primary interest in these experiments is identifying genes that are changing over time or space, for example, and then characterizing the specific expression changes. A number of robust statistical methods are available to identify genes showing differential expression among multiple conditions, but most assume conditions are exchangeable and thereby sacrifice power and precision when applied to ordered data.

Reprogramming of somatic cells to induced pluripotent stem cells (iPSCs) represents a profound change in cell fate. Here, we show that combining ascorbic acid (AA) and 2i (MAP kinase and GSK inhibitors) increases the efficiency of reprogramming from fibroblasts and synergistically enhances conversion of partially reprogrammed intermediates to the iPSC state. AA and 2i induce differential transcriptional responses, each leading to the activation of specific pluripotency loci. A unique cohort of pluripotency genes including Esrrb require both stimuli for activation. Temporally, AA-dependent histone demethylase effects are important early, whereas Tet enzyme effects are required throughout the conversion. 2i function could partially be replaced by depletion of components of the epidermal growth factor (EGF) and insulin growth factor pathways, indicating that they act as barriers to reprogramming. Accordingly, reduction in the levels of the EGF receptor gene contributes to the activation of Esrrb. These results provide insight into the rewiring of the pluripotency network at the late stage of reprogramming.

In this study, we demonstrate a newly derived mouse model that supports engraftment of human hematopoietic stem cells (HSCs) in the absence of irradiation. We cross the NOD.Cg-Prkdc(scid)Il2rg(tm1Wjl)/SzJ (NSG) strain with the C57BL/6J-Kit(W-41J)/J (C57BL/6.Kit(W41)) strain and engraft, without irradiation, the resulting NBSGW strain with human cord blood CD34+ cells. At 12-weeks postengraftment in NBSGW mice, we observe human cell chimerism in marrow (97% ± 0.4%), peripheral blood (61% ± 2%), and spleen (94% ± 2%) at levels observed with irradiation in NSG mice. We also detected a significant number of glycophorin-A-positive expressing cells in the developing NBSGW marrow. Further, the observed levels of human hematopoietic chimerism mimic those reported for both irradiated NSG and NSG-transgenic strains. This mouse model permits HSC engraftment while avoiding the complicating hematopoietic, gastrointestinal, and neurological side effects associated with irradiation and allows investigators without access to radiation to pursue engraftment studies with human HSCs.

Early life respiratory viral infections and atopic characteristics are significant risk factors for the development of childhood asthma. It is hypothesized that repeated respiratory viral infections might induce structural remodeling by interfering with the normal process of lung maturation; however, the specific molecular processes that underlie these pathological changes are not understood. To investigate the molecular basis for these changes, we used an established Sendai virus infection model in weanling rats to compare the post-infection transcriptomes of an atopic asthma susceptible strain, Brown Norway, and a non-atopic asthma resistant strain, Fischer 344. Specific to this weanling infection model and not described in adult infection models, Sendai virus in the susceptible, but not the resistant strain, results in morphological abnormalities in distal airways that persist into adulthood. Gene expression data from infected and control lungs across five time points indicated that specific features of the immune response following viral infection were heightened and prolonged in lungs from Brown Norway rats compared with Fischer 344 rats. These features included an increase in macrophage cell number and related gene expression, which then transitioned to an increase in mast cell number and related gene expression. In contrast, infected Fischer F344 lungs exhibited more efficient restoration of the airway epithelial morphology, with transient appearance of basal cell pods near distal airways. Together, these findings indicate that the pronounced macrophage and mast cell responses and abnormal re-epithelialization precede the structural defects that developed and persisted in Brown Norway, but not Fischer 344 lungs.

Here we report the isolation of a murine model for heritable T cell lymphoblastic leukemia/lymphoma (T-ALL) called Spontaneous dominant leukemia (Sdl). Sdl heterozygous mice develop disease with a short latency and high penetrance, while mice homozygous for the mutation die early during embryonic development. Sdl mice exhibit an increase in the frequency of micronucleated reticulocytes, and T-ALLs from Sdl mice harbor small amplifications and deletions, including activating deletions at the Notch1 locus. Using exome sequencing it was determined that Sdl mice harbor a spontaneously acquired mutation in Mcm4 (Mcm4(D573H)). MCM4 is part of the heterohexameric complex of MCM2-7 that is important for licensing of DNA origins prior to S phase and also serves as the core of the replicative helicase that unwinds DNA at replication forks. Previous studies in murine models have discovered that genetic reductions of MCM complex levels promote tumor formation by causing genomic instability. However, Sdl mice possess normal levels of Mcms, and there is no evidence for loss-of-heterozygosity at the Mcm4 locus in Sdl leukemias. Studies in Saccharomyces cerevisiae indicate that the Sdl mutation produces a biologically inactive helicase. Together, these data support a model in which chromosomal abnormalities in Sdl mice result from the ability of MCM4(D573H) to incorporate into MCM complexes and render them inactive. Our studies indicate that dominantly acting alleles of MCMs can be compatible with viability but have dramatic oncogenic consequences by causing chromosomal abnormalities.