Unlike arteries, in which regionally distinct hemodynamics are associated with phenotypic heterogeneity, the relationships between endocardial endothelial cell phenotype and intraventricular flow remain largely unexplored. We investigated regional differences in left ventricular wall shear stress and their association with endocardial endothelial cell gene expression.

A complete molecular understanding of β-cell mass expansion will be useful for the improvement of therapies to treat diabetic patients. During normal periods of metabolic challenges, such as pregnancy, β-cells proliferate, or self-renew, to meet the new physiological demands. The transcription factor Forkhead box D3 (Foxd3) is required for maintenance and self-renewal of several diverse progenitor cell lineages, and Foxd3 is expressed in the pancreatic primordium beginning at 10.5 d postcoitum, becoming localized predominantly to β-cells after birth. Here, we show that mice carrying a pancreas-specific deletion of Foxd3 have impaired glucose tolerance, decreased β-cell mass, decreased β-cell proliferation, and decreased β-cell size during pregnancy. In addition, several genes known to regulate proliferation, Foxm1, Skp2, Ezh2, Akt2, and Cdkn1a, are misregulated in islets isolated from these Foxd3 mutant mice. Together, these data place Foxd3 upstream of several pathways critical for β-cell mass expansion in vivo.

Extracellular signals in development, physiology, homeostasis and disease often act by regulating transcription. Herein we describe a general method and specific resources for determining where and when such signaling occurs in live animals and for systematically comparing the timing and extent of different signals in different cellular contexts. We used recombinase-mediated cassette exchange (RMCE) to test the effect of successively deleting conserved genomic regions of the ubiquitously active Rosa26 promoter and substituting the deleted regions for regulatory sequences that respond to diverse extracellular signals. We thereby created an allelic series of embryonic stem cells and mice, each containing a signal-responsive sentinel with different fluorescent reporters that respond with sensitivity and specificity to retinoic acids, bone morphogenic proteins, activin A, Wnts or Notch, and that can be adapted to any pathway that acts via DNA elements.

Atherosclerosis is a heterogeneously distributed disease of arteries in which the endothelium plays an important central role. Spatial transcriptome profiling of endothelium in pre-lesional arteries has demonstrated differential phenotypes primed for athero-susceptibility at hemodynamic sites associated with disturbed blood flow. DNA methylation is a powerful epigenetic regulator of endothelial transcription recently associated with flow characteristics. We investigated differential DNA methylation in flow region-specific aortic endothelial cells in vivo in adult domestic male and female swine.

The mechanisms that restrict regeneration and maintain cell identity following injury are poorly characterized in higher vertebrates. Following β-cell loss, 1-2% of the glucagon-producing α-cells spontaneously engage in insulin production in mice. Here we explore the mechanisms inhibiting α-cell plasticity. We show that adaptive α-cell identity changes are constrained by intra-islet insulin- and Smoothened-mediated signalling, among others. The combination of β-cell loss or insulin-signalling inhibition, with Smoothened inactivation in α- or δ-cells, stimulates insulin production in more α-cells. These findings suggest that the removal of constitutive 'brake signals' is crucial to neutralize the refractoriness to adaptive cell-fate changes. It appears that the maintenance of cell identity is an active process mediated by repressive signals, which are released by neighbouring cells and curb an intrinsic trend of differentiated cells to change.

Insulinoma associated 1 (Insm1) plays an important role in regulating the development of cells in the central and peripheral nervous systems, olfactory epithelium and endocrine pancreas. To better define the role of Insm1 in pancreatic endocrine cell development we generated mice with an Insm1(GFPCre) reporter allele and used them to study Insm1-expressing and null populations. Endocrine progenitor cells lacking Insm1 were less differentiated and exhibited broad defects in hormone production, cell proliferation and cell migration. Embryos lacking Insm1 contained greater amounts of a non-coding Neurog3 mRNA splice variant and had fewer Neurog3/Insm1 co-expressing progenitor cells, suggesting that Insm1 positively regulates Neurog3. Moreover, endocrine progenitor cells that express either high or low levels of Pdx1, and thus may be biased towards the formation of specific cell lineages, exhibited cell type-specific differences in the genes regulated by Insm1. Analysis of the function of Ripply3, an Insm1-regulated gene enriched in the Pdx1-high cell population, revealed that it negatively regulates the proliferation of early endocrine cells. Taken together, these findings indicate that in developing pancreatic endocrine cells Insm1 promotes the transition from a ductal progenitor to a committed endocrine cell by repressing a progenitor cell program and activating genes essential for RNA splicing, cell migration, controlled cellular proliferation, vasculogenesis, extracellular matrix and hormone secretion.

Neurodegenerative diseases pose an extraordinary threat to the world's aging population, yet no disease-modifying therapies are available. Although genome-wide association studies (GWASs) have identified hundreds of risk loci for neurodegeneration, the mechanisms by which these loci influence disease risk are largely unknown. Here, we investigated the association between common genetic variants at the 7p21 locus and risk of the neurodegenerative disease frontotemporal lobar degeneration. We showed that variants associated with disease risk correlate with increased expression of the 7p21 gene TMEM106B and no other genes; co-localization analyses implicated a common causal variant underlying both association with disease and association with TMEM106B expression in lymphoblastoid cell lines and human brain. Furthermore, increases in the amount of TMEM106B resulted in increases in abnormal lysosomal phenotypes and cell toxicity in both immortalized cell lines and neurons. We then combined fine-mapping, bioinformatics, and bench-based approaches to functionally characterize all candidate causal variants at this locus. This approach identified a noncoding variant, rs1990620, that differentially recruits CTCF in lymphoblastoid cell lines and human brain to influence CTCF-mediated long-range chromatin-looping interactions between multiple cis-regulatory elements, including the TMEM106B promoter. Our findings thus provide an in-depth analysis of the 7p21 locus linked by GWASs to frontotemporal lobar degeneration, nominating a causal variant and causal mechanism for allele-specific expression and disease association at this locus. Finally, we show that genetic variants associated with risk of neurodegenerative diseases beyond frontotemporal lobar degeneration are enriched in CTCF-binding sites found in brain-relevant tissues, implicating CTCF-mediated gene regulation in risk of neurodegeneration more generally.

Pancreatic multipotent progenitor cells (MPCs) produce acinar, endocrine and duct cells during organogenesis, but their existence and location in the mature organ remain contentious. We used inducible lineage-tracing from the MPC-instructive gene Ptf1a to define systematically in mice the switch of Ptf1a(+) MPCs to unipotent proacinar competence during the secondary transition, their rapid decline during organogenesis, and absence from the mature organ. Between E11.5 and E15.5, we describe tip epithelium heterogeneity, suggesting that putative Ptf1a(+)Sox9(+)Hnf1β(+) MPCs are intermingled with Ptf1a(HI)Sox9(LO) proacinar progenitors. In the adult, pancreatic duct ligation (PDL) caused facultative reactivation of multipotency factors (Sox9 and Hnf1β) in Ptf1a(+) acini, which undergo rapid reprogramming to duct cells and longer-term reprogramming to endocrine cells, including insulin(+) β-cells that are mature by the criteria of producing Pdx1(HI), Nkx6.1(+) and MafA(+). These Ptf1a lineage-derived endocrine/β-cells are likely formed via Ck19(+)/Hnf1β(+)/Sox9(+) ductal and Ngn3(+) endocrine progenitor intermediates. Acinar to endocrine/β-cell transdifferentiation was enhanced by combining PDL with pharmacological elimination of pre-existing β-cells. Thus, we show that acinar cells, without exogenously introduced factors, can regain aspects of embryonic multipotentiality under injury, and convert into mature β-cells.

Pancreatic beta cells, organized in the islets of Langerhans, sense glucose and secrete appropriate amounts of insulin. We have studied the roles of LKB1, a conserved kinase implicated in the control of cell polarity and energy metabolism, in adult beta cells. LKB1-deficient beta cells show a dramatic increase in insulin secretion in vivo. Histologically, LKB1-deficient beta cells have striking alterations in the localization of the nucleus and cilia relative to blood vessels, suggesting a shift from hepatocyte-like to columnar polarity. Additionally, LKB1 deficiency causes a 65% increase in beta cell volume. We show that distinct targets of LKB1 mediate these effects. LKB1 controls beta cell size, but not polarity, via the mTOR pathway. Conversely, the precise position of the beta cell nucleus, but not cell size, is controlled by the LKB1 target Par1b. Insulin secretion and content are restricted by LKB1, at least in part, via AMPK. These results expose a molecular mechanism, orchestrated by LKB1, for the coordinated maintenance of beta cell size, form, and function.

Neural networks are balanced by inhibitory and excitatory neuronal activity. The formation of these networks is initially generated through neuronal subtype specification controlled by transcription factors. The basic helix-loop-helix (bHLH) transcription factor Ptf1a is essential for the generation of GABAergic inhibitory neurons in the dorsal spinal cord, cerebellum, and retina. The transcription factor Rbpj is a transducer of the Notch signaling pathway that functions to maintain neural progenitor cells. Here we demonstrate Ptf1a and Rbpj interact in a complex that is required in vivo for specification of the GABAergic neurons, a function that cannot be substituted by the classical form of the bHLH heterodimer with E-protein or Notch signaling through Rbpj. We show that a mutant form of Ptf1a without the ability to bind Rbpj, while retaining its ability to interact with E-protein, is incapable of inducing GABAergic (Pax2)- and suppressing glutamatergic (Tlx3)-expressing cells in the chick and mouse neural tube. Moreover, we use an Rbpj conditional mutation to demonstrate that Rbpj function is essential for GABAergic specification, and that this function is independent of the Notch signaling pathway. Together, these findings demonstrate the requirement for a Ptf1a-Rbpj complex in controlling the balanced formation of inhibitory and excitatory neurons in the developing spinal cord, and point to a novel Notch-independent function for Rbpj in nervous system development.

Myelin transcription factor 1 (Myt1) is one of the three vertebrate C2HC-type zinc finger transcription factors that include Myt1 (Nzf1), Myt1L (Png1), and Myt3 (Nzf3, St18). All three paralogs are widely expressed in developing neuronal cells. Yet their function for mammalian development has not been investigated directly. Here we report that only Myt1 is expressed in the embryonic pancreas, in both endocrine progenitors and differentiated islet cells. Myt1(-/-) animals die postnatally, likely due to confounding effects in multiple tissues. The endocrine tissues in the embryonic Myt1(-/-) pancreas contained abnormal islet cells that expressed multiple hormones; although hormone levels were normal. We also created pancreas-specific Myt1 knockout mice. These mutant animals had no obvious physical defects from their wild-type littermates. Male mutant animals had reduced glucose-clearing abilities and abnormal multi-hormone-expressing cells present in their endocrine islets. In addition, they also had reduced Glut2 expression, and attenuated glucose-induced insulin secretion in the adult islets. Surprisingly, the expression of the Myt1 paralogs, Myt1l and Myt3, was induced in the embryonic Myt1(-/-) pancreas. The consequences of Myt1 inactivation in the developing pancreas could be masked by activation of its paralogs, Myt1l and Myt3. These findings suggest Myt1 is involved in proper endocrine differentiation and function.

Islet β cells from newborn mammals exhibit high basal insulin secretion and poor glucose-stimulated insulin secretion (GSIS). Here we show that β cells of newborns secrete more insulin than adults in response to similar intracellular Ca2+ concentrations, suggesting differences in the Ca2+ sensitivity of insulin secretion. Synaptotagmin 4 (Syt4), a non-Ca2+ binding paralog of the β cell Ca2+ sensor Syt7, increased by ∼8-fold during β cell maturation. Syt4 ablation increased basal insulin secretion and compromised GSIS. Precocious Syt4 expression repressed basal insulin secretion but also impaired islet morphogenesis and GSIS. Syt4 was localized on insulin granules and Syt4 levels inversely related to the number of readily releasable vesicles. Thus, transcriptional regulation of Syt4 affects insulin secretion; Syt4 expression is regulated in part by Myt transcription factors, which repress Syt4 transcription. Finally, human SYT4 regulated GSIS in EndoC-βH1 cells, a human β cell line. These findings reveal the role that altered Ca2+ sensing plays in regulating β cell maturation.

Transcription factors positively and/or negatively impact gene expression by recruiting coregulatory factors, which interact through protein-protein binding. Here we demonstrate that mouse pancreas size and islet β-cell function are controlled by the ATP-dependent Swi/Snf chromatin remodeling coregulatory complex that physically associates with Pdx1, a diabetes-linked transcription factor essential to pancreatic morphogenesis and adult islet cell function and maintenance. Early embryonic deletion of just the Swi/Snf Brg1 ATPase subunit reduced multipotent pancreatic progenitor cell proliferation and resulted in pancreas hypoplasia. In contrast, removal of both Swi/Snf ATPase subunits, Brg1 and Brm, was necessary to compromise adult islet β-cell activity, which included whole-animal glucose intolerance, hyperglycemia, and impaired insulin secretion. Notably, lineage-tracing analysis revealed Swi/Snf-deficient β-cells lost the ability to produce the mRNAs for Ins and other key metabolic genes without effecting the expression of many essential islet-enriched transcription factors. Swi/Snf was necessary for Pdx1 to bind to the Ins gene enhancer, demonstrating the importance of this association in mediating chromatin accessibility. These results illustrate how fundamental the Pdx1:Swi/Snf coregulator complex is in the pancreas, and we discuss how disrupting their association could influence type 1 and type 2 diabetes susceptibility.

The genetic analysis of complex traits has been dominated by parametric statistical methods due to their theoretical properties, ease of use, computational efficiency, and intuitive interpretation. However, there are likely to be patterns arising from complex genetic architectures which are more easily detected and modeled using machine learning methods. Unfortunately, selecting the right machine learning algorithm and tuning its hyperparameters can be daunting for experts and non-experts alike. The goal of automated machine learning (AutoML) is to let a computer algorithm identify the right algorithms and hyperparameters thus taking the guesswork out of the optimization process. We review the promises and challenges of AutoML for the genetic analysis of complex traits and give an overview of several approaches and some example applications to omics data. It is our hope that this review will motivate studies to develop and evaluate novel AutoML methods and software in the genetics and genomics space. The promise of AutoML is to enable anyone, regardless of training or expertise, to apply machine learning as part of their genetic analysis strategy.

A gain-of-function mutation in the TALK-1 K+ channel (p.L114P) associated with maturity-onset diabetes of the young (MODY) was recently reported in two distinct families. TALK-1 is a key regulator of β-cell electrical activity and glucose-stimulated insulin secretion (GSIS). KCNK16, the gene that encodes TALK-1, is the most abundant and β-cell-restricted K+ channel transcript; polymorphisms in the KCNK16 locus are also associated with an increased risk of type-2 diabetes. To investigate the impact of TALK-1-L114P on glucose homeostasis and confirm its association with MODY, a mouse model containing the Kcnk16 L114P mutation was generated. Heterozygous and homozygous Kcnk16 L114P mice exhibit increased neonatal lethality in the C57BL/6J and the mixed C57BL/6J:CD-1(ICR) genetic background, respectively. Lethality is likely a result of severe hyperglycemia observed in the homozygous Kcnk16 L114P neonates due to lack of GSIS and can be reduced with insulin treatment. TALK-1-L114P drastically increased whole-cell β-cell K+ currents resulting in blunted glucose-stimulated Ca2+ entry and loss of glucose-induced Ca2+ oscillations. Thus, adult Kcnk16 L114P mice have reduced GSIS and plasma insulin levels, which significantly impaired glucose homeostasis. Taken together, this study determined that the MODY-associated TALK-1-L114P mutation disrupts glucose homeostasis in adult mice resembling a MODY phenotype and causes neonatal lethality by altering islet hormone secretion during development. These data strongly suggest that TALK-1 is an islet-restricted target for the treatment of diabetes.

Type 2 diabetes (T2D) is associated with compromised identity of insulin-producing pancreatic islet β cells, characterized by inappropriate production of other islet cell-enriched hormones. Here, we examined how hormone misexpression was influenced by the MAFA and MAFB transcription factors, closely related proteins that maintain islet cell function. Mice specifically lacking MafA in β cells demonstrated broad, population-wide changes in hormone gene expression with an overall gene signature closely resembling islet gastrin+ (Gast+) cells generated under conditions of chronic hyperglycemia and obesity. A human β cell line deficient in MAFB, but not one lacking MAFA, also produced a GAST+ gene expression pattern. In addition, GAST was detected in human T2D β cells with low levels of MAFB. Moreover, evidence is provided that human MAFB can directly repress GAST gene transcription. These results support a potentially novel, species-specific role for MafA and MAFB in maintaining adult mouse and human β cell identity, respectively. Here, we discuss the possibility that induction of Gast/GAST and other non-β cell hormones, by reduction in the levels of these transcription factors, represents a dysfunctional β cell signature.

The ever-increasing scale of biological data sets, particularly those arising in the context of high-throughput technologies, requires the development of rich data exploration tools. In this article, we present AnnotCompute, an information discovery platform for repositories of functional genomics experiments such as ArrayExpress. Our system leverages semantic annotations of functional genomics experiments with controlled vocabulary and ontology terms, such as those from the MGED Ontology, to compute conceptual dissimilarities between pairs of experiments. These dissimilarities are then used to support two types of exploratory analysis-clustering and query-by-example. We show that our proposed dissimilarity measures correspond to a user's intuition about conceptual dissimilarity, and can be used to support effective query-by-example. We also evaluate the quality of clustering based on these measures. While AnnotCompute can support a richer data exploration experience, its effectiveness is limited in some cases, due to the quality of available annotations. Nonetheless, tools such as AnnotCompute may provide an incentive for richer annotations of experiments. Database URL: http://www.cbil.upenn.edu/annotCompute/

Pancreatic alpha-cells, like beta-cells, express ATP-sensitive K(+) (K(ATP)) channels. To determine the physiological role of K(ATP) channels in alpha-cells, we examined glucagon secretion in mice lacking the type 1 sulfonylurea receptor (Sur1). Plasma glucagon levels, which were increased in wild-type mice after an overnight fast, did not change in Sur1 null mice. Pancreas perfusion studies showed that Sur1 null pancreata lacked glucagon secretory responses to hypoglycemia and to synergistic stimulation by arginine. Pancreatic alpha-cells isolated from wild-type animals exhibited oscillations of intracellular free Ca(2+) concentration ([Ca(2+)](i)) in the absence of glucose that became quiescent when the glucose concentration was increased. In contrast, Sur1 null alpha-cells showed continuous oscillations in [Ca(2+)](i) regardless of the glucose concentration. These findings indicate that K(ATP) channels in alpha-cells play a key role in regulating glucagon secretion, thereby adding to the paradox of how mice that lack K(ATP) channels maintain euglycemia.

Using a transgenic mouse model to express MafA, Pdx1, and Neurog3 (3TF) in a pancreatic acinar cell- and doxycycline-dependent manner, we discovered that the outcome of transcription factor-mediated acinar to β-like cellular reprogramming is dependent on both the magnitude of 3TF expression and on reprogramming-induced inflammation. Overly robust 3TF expression causes acinar cell necrosis, resulting in marked inflammation and acinar-to-ductal metaplasia. Generation of new β-like cells requires limiting reprogramming-induced inflammation, either by reducing 3TF expression or by eliminating macrophages. The new β-like cells were able to reverse streptozotocin-induced diabetes 6 days after inducing 3TF expression but failed to sustain their function after removal of the reprogramming factors.

The principal line of investigation in Genome Wide Association Studies (GWAS) is the identification of main effects, that is individual Single Nucleotide Polymorphisms (SNPs) which are associated with the trait of interest, independent of other factors. A variety of methods have been proposed to this end, mostly statistical in nature and differing in assumptions and type of model employed. Moreover, for a given model, there may be multiple choices for the SNP genotype encoding. As an alternative to statistical methods, machine learning methods are often applicable. Typically, for a given GWAS, a single approach is selected and utilized to identify potential SNPs of interest. Even when multiple GWAS are combined through meta-analyses within a consortium, each GWAS is typically analyzed with a single approach and the resulting summary statistics are then utilized in meta-analyses.