PySmooth: a Python tool for the removal and correction of genotyping errors

In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes. AVAILABILITY AND IMPLEMENTATION: PySmooth is available at https://github.com/lncRNAAddict/PySmooth .

Drosophila genotypes can be predicted from their exploration locomotive trajectories using supervised machine learning

This study employs supervised machine learning algorithms to test whether locomotive features during exploratory activity in open field arenas can serve as predictors for the genotype of fruit flies. Because of the nonlinearity in locomotive trajectories, traditional statistical methods that are used to compare exploratory activity between genotypes of fruit flies may not reveal all insights. 10-minute-long trajectories of four different genotypes of fruit flies in an open-field arena environment were captured. Turn angles and step size features extracted from the trajectories were used for training supervised learning models to predict the genotype of the fruit flies. Using the first five minute locomotive trajectories, an accuracy of 83% was achieved in differentiating wild-type flies from three other mutant genotypes. Using the final 5 min and the entire ten minute duration decreased the performance indicating that the most variations between the genotypes in their exploratory activity are exhibited in the first few minutes. Feature importance analysis revealed that turn angle is a better predictor than step size in predicting fruit fly genotype. Overall, this study demonstrates that features of trajectories can be used to predict the genotype of fruit flies through supervised machine learning methods.

ChromNetMotif: a Python tool to extract chromatin-sate marked motifs in a chromatin interaction network

Motivation

Analysis of network motifs is crucial to studying the robustness, stability, and functions of complex networks. Genome organization can be viewed as a biological network that consists of interactions between different chromatin regions. These interacting regions are also marked by epigenetic or chromatin states which can contribute to the overall organization of the chromatin and proper genome function. Therefore, it is crucial to integrate the chromatin states of the nodes when performing motif analysis in chromatin interaction networks. Even though there has been increasing production of chromatin interaction and genome-wide epigenetic modification data, there is a lack of publicly available tools to extract chromatin state-marked motifs from genome organization data.

Results

We develop a Python tool, ChromNetMotif, offering an easy-to-use command line interface to extract chromatin-state-marked motifs from a chromatin interaction network. The tool can extract occurrences, frequencies, and statistical enrichment of the chromatin state-marked motifs. Visualization files are also generated which allow the user to interpret the motifs easily. ChromNetMotif also allows the user to leverage the features of a multicore processor environment to reduce computation time for larger networks. The output files generated can be used to perform further downstream analysis. ChromNetMotif aims to serve as an important tool to comprehend the interplay between epigenetics and genome organization.

Availability and implementation

ChromNetMotif is available at https://github.com/lncRNAAddict/ChromNetworkMotif.

H19X-encoded miR-322(424)/miR-503 regulates muscle mass by targeting translation initiation factors

BACKGROUND

Skeletal muscle atrophy is a debilitating complication of many chronic diseases, disuse conditions, and ageing. Genome-wide gene expression analyses have identified that elevated levels of microRNAs encoded by the H19X locus are among the most significant changes in skeletal muscles in a wide scope of human cachectic conditions. We have previously reported that the H19X locus is important for the establishment of striated muscle fate during embryogenesis. However, the role of H19X-encoded microRNAs in regulating skeletal mass in adults is unknown.

METHODS

We have created a transgenic mouse strain in which ectopic expression of miR-322/miR-503 is driven by the skeletal muscle-specific muscle creatine kinase promoter. We also used an H19X mutant mouse strain in which transcription from the locus is interrupted by a gene trap. Animal phenotypes were analysed by standard histological methods. Underlying mechanisms were explored by using transcriptome profiling and validated in the two animal models and cultured myotubes.

RESULTS

Our results demonstrate that the levels of H19X microRNAs are inversely related to postnatal skeletal muscle growth. Targeted overexpression of miR-322/miR-503 impeded skeletal muscle growth. The weight of gastrocnemius muscles of transgenic mice was only 54.5% of the counterparts of wild-type littermates. By contrast, interruption of transcription from the H19X locus stimulates postnatal muscle growth by 14.4-14.9% and attenuates the loss of skeletal muscle mass in response to starvation by 12.8-21.0%. Impeded muscle growth was not caused by impaired IGF1/AKT/mTOR signalling or a hyperactive ubiquitin-proteasome system, instead accompanied by markedly dropped abundance of translation initiation factors in transgenic mice. miR-322/miR-503 directly targets eIF4E, eIF4G1, eIF4B, eIF2B5, and eIF3M.

CONCLUSIONS

Our study illustrates a novel pathway wherein H19X microRNAs regulate skeletal muscle growth and atrophy through regulating the abundance of translation initiation factors, thereby protein synthesis. The study highlights how translation initiation factors lie at the crux of multiple signalling pathways that control skeletal muscle mass.

LncRNA:DNA triplex-forming sites are positioned at specific areas of genome organization and are predictors for Topologically Associated Domains

BACKGROUND

Chromosomes are organized into units called topologically associated domains (TADs). TADs dictate regulatory landscapes and other DNA-dependent processes. Even though various factors that contribute to the specification of TADs have been proposed, the mechanism is not fully understood. Understanding the process for specification and maintenance of these units is essential in dissecting cellular processes and disease mechanisms.

RESULTS

In this study, we report a genome-wide study that considers the idea of long noncoding RNAs (lncRNAs) mediating chromatin organization using lncRNA:DNA triplex-forming sites (TFSs). By analyzing the TFSs of expressed lncRNAs in multiple cell lines, we find that they are enriched in TADs, their boundaries, and loop anchors. However, they are evenly distributed across different regions of a TAD showing no preference for any specific portions within TADs. No relationship is observed between the locations of these TFSs and CTCF binding sites. However, TFSs are located not just in promoter regions but also in intronic, intergenic, and 3'UTR regions. We also show these triplex-forming sites can be used as predictors in machine learning models to discriminate TADs from other genomic regions. Finally, we compile a list of important "TAD-lncRNAs" which are top predictors for TADs identification.

CONCLUSIONS

Our observations advocate the idea that lncRNA:DNA TFSs are positioned at specific areas of the genome organization and are important predictors for TADs. LncRNA:DNA triplex formation most likely is a general mechanism of action exhibited by some lncRNAs, not just for direct gene regulation but also to mediate 3D chromatin organization.

Accurate prediction of boundaries of high resolution topologically associated domains (TADs) in fruit flies using deep learning

Genomes are organized into self-interacting chromatin regions called topologically associated domains (TADs). A significant number of TAD boundaries are shared across multiple cell types and conserved across species. Disruption of TAD boundaries may affect the expression of nearby genes and could lead to several diseases. Even though detection of TAD boundaries is important and useful, there are experimental challenges in obtaining high resolution TAD locations. Here, we present computational prediction of TAD boundaries from high resolution Hi-C data in fruit flies. By extensive exploration and testing of several deep learning model architectures with hyperparameter optimization, we show that a unique deep learning model consisting of three convolution layers followed by a long short-term-memory layer achieves an accuracy of 96%. This outperforms feature-based models’ accuracy of 91% and an existing method's accuracy of 73–78% based on motif TRAP scores. Our method also detects previously reported motifs such as Beaf-32 that are enriched in TAD boundaries in fruit flies and also several unreported motifs.

Aberrant expression of embryonic mesendoderm factor MESP1 promotes tumorigenesis

Background

Mesoderm Posterior 1 (MESP1) belongs to the family of basic helix-loop-helix transcription factors. It is a master regulator of mesendoderm development, leading to formation of organs such as heart and lung. However, its role in adult pathophysiology remains unknown. Here, we report for the first time a previously-unknown association of MESP1 with non-small cell lung cancer (NSCLC).

Methods

MESP1 mRNA and protein levels were measured in NSCLC-derived cells by qPCR and immunoblotting respectively. Colony formation assay, colorimetric cell proliferation assay and soft agar colony formation assays were used to assess the effects of MESP1 knockdown and overexpression in vitro. RNA-sequencing and chromatin immunoprecipitation (ChIP)-qPCR were used to determine direct target genes of MESP1. Subcutaneous injection of MESP1-depleted NSCLC cells in immuno-compromised mice was done to study the effects of MESP1 mediated tumor formation in vivo.

Findings

We found that MESP1 expression correlates with poor prognosis in NSCLC patients, and is critical for proliferation and survival of NSCLC-derived cells, thus implicating MESP1 as a lung cancer oncogene. Ectopic MESP1 expression cooperates with loss of tumor suppressor ARF to transform murine fibroblasts. Xenografts from MESP1-depleted cells showed decreased tumor growth in vivo. Global transcriptome analysis revealed a MESP1 DNA-binding-dependent gene signature associated with various hallmarks of cancer, suggesting that transcription activity of MESP1 is most likely responsible for its oncogenic abilities.

Interpretation

Our study demonstrates MESP1 as a previously-unknown lineage-survival oncogene in NSCLC which may serve as a potential prognostic marker and therapeutic target for lung cancer in the future.

H19X-encoded miR-424(322)/-503 cluster: emerging roles in cell differentiation, proliferation, plasticity and metabolism

miR-424(322)/-503 are mammal-specific members of the extended miR-15/107 microRNA family. They form a co-expression network with the imprinted lncRNA H19 in tetrapods. miR-424(322)/-503 regulate fundamental cellular processes including cell cycle, epithelial-to-mesenchymal transition, hypoxia and other stress response. They control tissue differentiation (cardiomyocyte, skeletal muscle, monocyte) and remodeling (mammary gland involution), and paradoxically participate in tumor initiation and progression. Expression of miR-424(322)/-503 is governed by unique mechanisms involving sex hormones. Here, we summarize current literature and provide a primer for future endeavors.

Coregulatory long non-coding RNA and protein-coding genes in serum starved cells

Serum starvation is widely used in cell biology to trigger cell cycle arrest, apoptosis, autophagy, and metabolic adaptations. Serum starvation-related molecular events have been well characterized at protein level but not at transcript level: how long non-coding RNAs contribute to the regulation of protein-coding genes is largely unknown. Here, we captured the lncRNA transcriptome in serum starved mouse embryonic fibroblasts and identified three main modes of action: cis-acting/coregulatory, trans-acting, and "miRNA-carrier". Whole-genome and individual gene level analyses support that our annotation provides an important platform for understanding lncRNA/protein-coding gene coregulatory mechanisms in serum starvation.

Deep learning identifies genome-wide DNA binding sites of long noncoding RNAs

Long noncoding RNAs (lncRNAs) can exert their function by interacting with the DNA via triplex structure formation. Even though this has been validated with a handful of experiments, a genome-wide analysis of lncRNA-DNA binding is needed. In this paper, we develop and interpret deep learning models that predict the genome-wide binding sites deciphered by ChIRP-Seq experiments of 12 different lncRNAs. Among the several deep learning architectures tested, a simple architecture consisting of two convolutional neural network layers performed the best suggesting local sequence patterns as determinants of the interaction. Further interpretation of the kernels in the model revealed that these local sequence patterns form triplex structures with the corresponding lncRNAs. We uncovered several novel triplexes forming domains (TFDs) of these 12 lncRNAs and previously experimentally verified TFDs of lncRNAs HOTAIR and MEG3. We experimentally verified such two novel TFDs of lncRNAs HOTAIR and TUG1 predicted by our method (but previously unreported) using Electrophoretic mobility shift assays. In conclusion, we show that simple deep learning architecture can accurately predict genome-wide binding sites of lncRNAs and interpretation of the models suggest RNA:DNA:DNA triplex formation as a viable mechanism underlying lncRNA-DNA interactions at genome-wide level.

Transient activation of AMPK preceding left ventricular pressure overload reduces adverse remodeling and preserves left ventricular function

Coordinated changes in signaling pathways and gene expression in hearts subjected to prolonged stress maintain cardiac function. Loss of steroid receptor coactivator-2 (SRC-2) results in a reversal to the fetal gene program and disrupts the response to pressure overload, accompanied by prominent effects on metabolism and growth signaling, including increased AMPK activation. We proposed that early metabolic stress driven by AMPK activation induces contractile dysfunction in mice lacking SRC-2. We used 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) to activate AMPK transiently before transverse aortic constriction (TAC) in wild-type and cardiomyocyte-specific SRC-2 knockout (CKO) animals. In contrast to AMPK activities during stress, in unstressed hearts, AICAR induced a mild activation of Akt signaling, and, in SRC-2-CKO mice, partially relieved an NAD⁺ deficiency and increased antioxidant signaling. These molecular changes translated to a mild hypertrophic response to TAC with decreased maladaptive remodeling, including markedly decreased fibrosis. Additionally, preactivation of AMPK in SRC-2-CKO mice was accompanied by a dramatic improvement in cardiac function compared with saline-treated SRC-2-CKO mice. Our results show that altered molecular signaling before stress onset has extended effects on sustained cardiac stress responses, and prestress modulation of transient growth and metabolism pathways may control those effects.-Nam, D. H., Kim, E., Benham, A., Park, H.-K., Soibam, B., Taffet, G. E., Kaelber, J. T., Suh, J. H., Taegtmeyer, H., Entman, M. L., Reineke, E. L. Transient activation of AMPK preceding left ventricular pressure overload reduces adverse remodeling and preserves left ventricular function.

Abstract 5437: MESP1 cooperates with loss of ARF in malignant transformation

Cancer is a highly complex disease involving multiple genetic and epigenetic abnormalities. Inactivation or expression of key regulators can be critical for the maintenance and survival of tumor. My research aims at characterizing one such novel gene, Mesoderm Posterior Basic Helix-Loop-Helix transcription factor-1 (MESP1), in lung cancer initiation and progression. MESP1 is transiently expressed during embryonic development and is the first sign of nascent mesoderm. It is a master regulator of cardiovascular development. Our lab has discovered through genome-wide identification of MESP1 targets that it is required in mesendoderm lineage development. However, whether MESP1 plays any role in adult physiology, diseases and cancer, has never been investigated. The Cancer Genome Atlas (TCGA) data show that MESP1 expression is upregulated in cancers of all mesendoderm-derived tissues. Bioinformatic gene expression analysis of clinical lung adenocarcinoma patient samples (396) showed that MESP1 was highly overexpressed in lung cancer. Similarly, RT-qPCR analysis of patient RNA samples from various stages of lung cancer showed that MESP1 expression was induced in early stages of lung cancer. It was found that MESP1 stable overexpression in ARF-null MEFs leads to oncogenic transformation of cells. This was evidenced by changes in various hallmarks of cancer such as increased cell proliferation, colony formation and anchorage-independent growth (about 6-fold increase in no. of colonies per field). In order to determine if the MESP1-induced oncogenic transformation was p53 dependent, we overexpressed MESP1 in p53-null MEFs. Interestingly, we saw no significant change in cell proliferation, colony formation and anchorage-independent growth in MESP1-overexpressing p53 null MEFs, suggesting that these effects are p53-independent. Upon performing global transcriptomic analyses in MESP1-overexpressing ARF-null MEFs, we found that cell adhesion and cell migration were among the top pathways that were significantly altered. Future studies will focus on in vivo studies to check for effect of MESP1-overexpression and/or knockdown on tumor formation and investigate the mechanism of MESP1-induced oncogenic transformation linked with increased cellular adhesion and migration. Lung cancer is the leading cause of cancer-related deaths in both men and women. More than 50% of cases are diagnosed only at an advanced stage, for which the survival rate of the patient is only 4%. Hence, knowledge of new driver oncogenes of lung cancer is imperative. These results suggest that MESP1 plays an important role in cancer initiation and progression. Ultimately, this research would pave the way for therapeutic intervention of key processes regulated by MESP1 involved in lung cancer.

Citation Format: Neha Tandon, Benjamin Soibam, Robert Schwartz, Yu Liu. MESP1 cooperates with loss of ARF in malignant transformation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5437.

ERβ alters the chemosensitivity of luminal breast cancer cells by regulating p53 function

Estrogen receptor α (ERα)-positive breast cancers tend to develop resistance to both endocrine therapy and chemotherapy. Despite recent progress in defining molecular pathways that confer endocrine resistance, the mechanisms that regulate chemotherapy response in luminal tumors remain largely elusive. Luminal tumors often express wild-type p53 that is a major determinant of the cellular DNA damage response. Similar to p53, the second ER subtype, ERβ, has been reported to inhibit breast tumorigenesis by acting alone or in collaboration with p53. However, a synergistic mechanism of action has not been described. Here, we suggest that ERβ relies on p53 to elicit its tumor repressive actions in ERα-positive breast cancer cells. Upregulation of ERβ and treatment with ERβ agonists potentiates the tumor suppressor function of p53 resulting in decreased survival. This effect requires molecular interaction between the two proteins that disrupts the inhibitory action of ERα on p53 leading to increased transcriptional activity of p53. In addition, we show that the same interaction alters the chemosensitivity of endocrine-resistant cells including their response to tamoxifen therapy. Our results suggest a collaboration of ERβ and p53 tumor suppressor activity in breast cancer cells that indicates the importance of ligand-regulated ERβ as a tool to target p53 activity and improve the clinical management of resistant disease.

Predictors of breast cancer cell types and their prognostic power in breast cancer patients

BACKGROUND

Comprehensive understanding of intratumor heterogeneity requires identification of molecular markers, which are capable of differentiating different subpopulations and which also have clinical significance. One important tool that has been addressing this issue is single cell RNA-Sequencing (scRNASeq) that allows the quantification of expression profiles of transcripts in individual cells in a population of cancer cells. Using the expression profiles from scRNASeq, current studies conduct analysis to group cells into different subpopulations using clustering algorithms. In this study, we explore scRNASeq cancer data from a different perspective. We focus on scRNASeq data originating from cancer cells pertaining to a particular cancer type, where the cell type or the subpopulation to which each cell belongs is known. We investigate if the "cell type" of a cancer cell can be predicted based on the expression profiles of a small set of transcripts.

RESULTS

We outline a predictive analytics pipeline to accurately predict 6 breast cancer cell types using single cell gene expression profiles. Instead of building predictive models using the complete human transcripts, the pipeline first eliminates predictors with low expression and low variance. A multinomial penalized logistic regression further reduces the size of the predictors to only 308, out of which 34 are long non-coding RNAs. Tuning of predictive models shows support vector machines and neural networks as the most accurate models achieving close to 98% prediction accuracies. We also find that mixture of protein coding genes and long non-coding RNAs are better predictors compared to when the two sets of transcripts are treated separately. A signature risk score originating from 65 protein coding genes and 5 lncRNA predictors is associated with prognostic survival of TCGA breast cancer patients. This association was maintained when the risk scores were generated using 65 PCGs and 5 lncRNA separately. We further show that predictors restricted to a particular cell type serve as better prognostic markers for the respective patient subtype.

CONCLUSION

Our results show that in general, the breast cancer cell type predictors are also associated with patient survivability and hence have clinical significance.

Recellularization of rat liver: An in vitro model for assessing human drug metabolism and liver biology

Liver-like organoids that recapitulate the complex functions of the whole liver by combining cells, scaffolds, and mechanical or chemical cues are becoming important models for studying liver biology and drug metabolism. The advantages of growing cells in three-dimensional constructs include enhanced cell-cell and cell-extracellular matrix interactions and preserved cellular phenotype including, prevention of de-differentiation. In the current study, biomimetic liver constructs were made via perfusion decellularization of rat liver, with the goal of maintaining the native composition and structure of the extracellular matrix. We optimized our decellularization process to produce liver scaffolds in which immunogenic residual DNA was removed but glycosaminoglycans were maintained. When the constructs were recellularized with rat or human liver cells, the cells remained viable, capable of proliferation, and functional for 28 days. Specifically, the cells continued to express cytochrome P450 genes and maintained their ability to metabolize a model drug, midazolam. Microarray analysis showed an upregulation of genes involved in liver regeneration and fibrosis. In conclusion, these liver constructs have the potential to be used as test beds for studying liver biology and drug metabolism.

Super-lncRNAs: identification of lncRNAs that target super-enhancers via RNA:DNA:DNA triplex formation

Super-enhancers are characterized by high levels of Mediator binding and are major contributors to the expression of their associated genes. They exhibit high levels of local chromatin interactions and a higher order of local chromatin organization. On the other hand, lncRNAs can localize to specific DNA sites by forming a RNA:DNA:DNA triplex, which in turn can contribute to local chromatin organization. In this paper, we characterize a new class of lncRNAs called super-lncRNAs that target super-enhancers and which can contribute to the local chromatin organization of the super-enhancers. Using a logistic regression model based on the number of RNA:DNA:DNA triplex sites a lncRNA forms within the super-enhancer, we identify 442 unique super-lncRNA transcripts in 27 different human cell and tissue types; 70% of these super-lncRNAs were tissue restricted. They primarily harbor a single triplex-forming repeat domain, which forms an RNA:DNA:DNA triplex with multiple anchor DNA sites (originating from transposable elements) within the super-enhancers. Super-lncRNAs can be grouped into 17 different clusters based on the tissue or cell lines they target. Super-lncRNAs in a particular cluster share common short structural motifs and their corresponding super-enhancer targets are associated with gene ontology terms pertaining to the tissue or cell line. Super-lncRNAs may use these structural motifs to recruit and transport necessary regulators (such as transcription factors and Mediator complexes) to super-enhancers, influence chromatin organization, and act as spatial amplifiers for key tissue-specific genes associated with super-enhancers.

HIRA deficiency in muscle fibers causes hypertrophy and susceptibility to oxidative stress

Nucleosome assembly proceeds through DNA replication-coupled or replication-independent mechanisms. For skeletal myocytes, whose nuclei have permanently exited the cell cycle, replication-independent assembly is the only mode available for chromatin remodeling. For this reason, any nucleosome composition alterations accompanying transcriptional responses to physiological signals must occur through a DNA replication-independent pathway. HIRA is the histone chaperone primarily responsible for replication-independent incorporation of histone variant H3.3 across gene bodies and regulatory regions. Thus, HIRA would be expected to play an important role in epigenetically regulating myocyte gene expression. The objective of this study was to determine the consequence of eliminating HIRA from mouse skeletal myocytes. At 6 weeks of age, myofibers lacking HIRA showed no pathological abnormalities; however, genes involved in transcriptional regulation were downregulated. By 6 months of age, myofibers lacking HIRA exhibited hypertrophy, sarcolemmal perforation and oxidative damage. Genes involved in muscle growth and development were upregulated, but those associated with responses to cellular stresses were downregulated. These data suggest that elimination of HIRA produces a hypertrophic response in skeletal muscle and leaves myofibers susceptible to stress-induced degeneration.

Cardiomyocyte-specific conditional knockout of the histone chaperone HIRA in mice results in hypertrophy, sarcolemmal damage and focal replacement fibrosis

HIRA is the histone chaperone responsible for replication-independent incorporation of histone variant H3.3 within gene bodies and regulatory regions of actively transcribed genes, and within the bivalent promoter regions of developmentally regulated genes. The HIRA gene lies within the 22q11.2 deletion syndrome critical region; individuals with this syndrome have multiple congenital heart defects. Because terminally differentiated cardiomyocytes have exited the cell cycle, histone variants should be utilized for the bulk of chromatin remodeling. Thus, HIRA is likely to play an important role in epigenetically defining the cardiac gene expression program. In this study, we determined the consequence of HIRA deficiency in cardiomyocytes in vivo by studying the phenotype of cardiomyocyte-specific Hira conditional-knockout mice. Loss of HIRA did not perturb heart development, but instead resulted in cardiomyocyte hypertrophy and susceptibility to sarcolemmal damage. Cardiomyocyte degeneration gave way to focal replacement fibrosis and impaired cardiac function. Gene expression was widely altered in Hira conditional-knockout hearts. Significantly affected pathways included responses to cellular stress, DNA repair and transcription. Consistent with heart failure, fetal cardiac genes were re-expressed in the Hira conditional knockout. Our results suggest that transcriptional regulation by HIRA is crucial for cardiomyocyte homeostasis.

Mouse myofibers lacking the SMYD1 methyltransferase are susceptible to atrophy, internalization of nuclei and myofibrillar disarray

The Smyd1 gene encodes a lysine methyltransferase specifically expressed in striated muscle. Because Smyd1-null mouse embryos die from heart malformation prior to formation of skeletal muscle, we developed a Smyd1 conditional-knockout allele to determine the consequence of SMYD1 loss in mammalian skeletal muscle. Ablation of SMYD1 specifically in skeletal myocytes after myofiber differentiation using Myf6(cre) produced a non-degenerative myopathy. Mutant mice exhibited weakness, myofiber hypotrophy, prevalence of oxidative myofibers, reduction in triad numbers, regional myofibrillar disorganization/breakdown and a high percentage of myofibers with centralized nuclei. Notably, we found broad upregulation of muscle development genes in the absence of regenerating or degenerating myofibers. These data suggest that the afflicted fibers are in a continual state of repair in an attempt to restore damaged myofibrils. Disease severity was greater for males than females. Despite equivalent expression in all fiber types, loss of SMYD1 primarily affected fast-twitch muscle, illustrating fiber-type-specific functions for SMYD1. This work illustrates a crucial role for SMYD1 in skeletal muscle physiology and myofibril integrity.

Data on microRNAs and microRNA-targeted mRNAs in Xenopus ectoderm

Small RNAs from early neural (i.e., Noggin-expressing, or NOG) and epidermal (expressing a constitutively active BMP4 receptor, CABR) ectoderm in Xenopus laevis were sequenced to identify microRNAs (miRs) expressed in each tissue. Argonaute-associated mRNAs were isolated and sequenced to identify genes that are regulated by microRNAs in these tissues. Interactions between these ectodermal miRs and selected miR-regulated mRNAs were predicted using the PITA algorithm; PITA predictions for over 600 mRNAs are presented. All sequencing data are available at NCBI (NCBI Bioproject Accession number: PRJNA325834). This article accompanies the manuscript “MicroRNAs and ectodermal specification I. Identification of miRs and miR-targeted mRNAs in early anterior neural and epidermal ectoderm” (V.V. Shah, B. Soibam, R.A. Ritter, A. Benham, J. Oomen, A.K. Sater, 2016) [1].

MicroRNAs and ectodermal specification I. Identification of miRs and miR-targeted mRNAs in early anterior neural and epidermal ectoderm

The establishment of cell lineages occurs via a dynamic progression of gene regulatory networks (GRNs) that underlie developmental commitment and differentiation. To investigate how microRNAs (miRs) function in this process, we compared miRs and miR targets at the initiation of the two major ectodermal lineages in Xenopus. We used next-generation sequencing to identify over 170 miRs expressed in midgastrula ectoderm expressing either noggin or a constitutively active BMP receptor, reflecting anterior neural or epidermal ectoderm, respectively; 125 had not previously been identified in Xenopus. We identified the locations of the pre-miR sequences in the X. laevis genome. Neural and epidermal ectoderm express broadly similar sets of miRs. To identify targets of miR-dependent translational control, we co-immunoprecipitated Argonaute-Ribonucleoprotein (Ago-RNP) complexes from early neural and epidermal ectoderm and sequenced the associated RNA. The Ago-RNP RNAs from these tissues represent overlapping, yet distinct, subsets of genes. Moreover, the profile of Ago-RNP associated genes differs substantially from the profile of total RNAs in these tissues. We generated target predictions for the "high confidence" Ago-RNP RNAs using the identified ectodermal miRs; These RNAs generally had target sites for multiple miRs. Oct4 orthologues, as well as many of their previously identified transcriptional targets, are represented in the Ago-RNP pool in both tissues, suggesting that miR-dependent regulation contributes to the downregulation of the oct4 gene regulatory network and the reduction in ectodermal pluripotency.

Mesp1 Marked Cardiac Progenitor Cells Repair Infarcted Mouse Hearts

Mesp1 directs multipotential cardiovascular cell fates, even though it's transiently induced prior to the appearance of the cardiac progenitor program. Tracing Mesp1-expressing cells and their progeny allows isolation and characterization of the earliest cardiovascular progenitor cells. Studying the biology of Mesp1-CPCs in cell culture and ischemic disease models is an important initial step toward using them for heart disease treatment. Because of Mesp1's transitory nature, Mesp1-CPC lineages were traced by following EYFP expression in murine Mesp1(Cre/+); Rosa26(EYFP/+) ES cells. We captured EYFP+ cells that strongly expressed cardiac mesoderm markers and cardiac transcription factors, but not pluripotent or nascent mesoderm markers. BMP2/4 treatment led to the expansion of EYFP+ cells, while Wnt3a and Activin were marginally effective. BMP2/4 exposure readily led EYFP+ cells to endothelial and smooth muscle cells, but inhibition of the canonical Wnt signaling was required to enter the cardiomyocyte fate. Injected mouse pre-contractile Mesp1-EYFP+ CPCs improved the survivability of injured mice and restored the functional performance of infarcted hearts for at least 3 months. Mesp1-EYFP+ cells are bona fide CPCs and they integrated well in infarcted hearts and emerged de novo into terminally differentiated cardiac myocytes, smooth muscle and vascular endothelial cells.

Genome-Wide Identification of MESP1 Targets Demonstrates Primary Regulation Over Mesendoderm Gene Activity

MESP1 is considered the first sign of the nascent cardiac mesoderm and plays a critical role in the appearance of cardiac progenitors, while exhibiting a transient expression in the developing embryo. We profiled the transcriptome of a pure population of differentiating MESP1-marked cells and found that they chiefly contribute to the mesendoderm lineage. High-throughput sequencing of endogenous MESP1-bound DNA revealed that MESP1 preferentially binds to two variants of E-box sequences and activates critical mesendoderm modulators, including Eomes, Gata4, Wnt5a, Wnt5b, Mixl1, T, Gsc, and Wnt3. These mesendoderm markers were enriched in the MESP1 marked population before the appearance of cardiac progenitors and myocytes. Further, MESP1-binding is globally associated with H(3)K(27) acetylation, supporting a novel pivotal role of it in regulating target gene epigenetics. Therefore, MESP1, the pioneer cardiac factor, primarily directs the appearance of mesendoderm, the intermediary of the earliest progenitors of mesoderm and endoderm organogenesis.

Steroid receptor coactivator-2 is a dual regulator of cardiac transcription factor function

We have previously demonstrated the potential role of steroid receptor coactivator-2 (SRC-2) as a co-regulator in the transcription of critical molecules modulating cardiac function and metabolism in normal and stressed hearts. The present study seeks to extend the previous information by demonstrating SRC-2 fulfills this role by serving as a critical coactivator for the transcription and activity of critical transcription factors known to control cardiac growth and metabolism as well as in their downstream signaling. This knowledge broadens our understanding of the mechanism by which SRC-2 acts in normal and stressed hearts and allows further investigation of the transcriptional modifications mediating different types and degrees of cardiac stress. Moreover, the genetic manipulation of SRC-2 in this study is specific for the heart and thereby eliminating potential indirect effects of SRC-2 deletion in other organs. We have shown that SRC-2 is critical to transcriptional control modulated by MEF2, GATA-4, and Tbx5, thereby enhancing gene expression associated with cardiac growth. Additionally, we describe SRC-2 as a novel regulator of PPARα expression, thus controlling critical steps in metabolic gene expression. We conclude that through regulation of cardiac transcription factor expression and activity, SRC-2 is a critical transcriptional regulator of genes important for cardiac growth, structure, and metabolism, three of the main pathways altered during the cardiac stress response.

Modeling novelty habituation during exploratory activity in Drosophila

Habituation is a common form of non-associative learning in which the organism gradually decreases its response to repeated stimuli. The decrease in exploratory activity of many animal species during exposure to a novel open field arena is a widely studied habituation paradigm. However, a theoretical framework to quantify how the novelty of the arena is learned during habituation is currently missing. Drosophila melanogaster display a high mean absolute activity and a high probability for directional persistence when first introduced to a novel arena. Both measures decrease during habituation to the arena. Here, we propose a phenomenological model of habituation for Drosophila exploration based on two principles: Drosophila form a spatial representation of the arena edge as a set of connected local patches, and repeated exposure to these patches is essential for the habituation of the novelty. The level of exposure depends on the number of visitations and is quantified by a variable referred to as "coverage". This model was tested by comparing predictions against the experimentally measured behavior of wild type Drosophila. The novelty habituation of wild type Canton-S depends on coverage and is specifically independent of the arena radius. Our model describes the time dependent locomotor activity, ΔD, of Canton-S using an experimentally established stochastic process Pn(ΔD), which depends on the coverage. The quantitative measures of exploration and habituation were further applied to three mutant genotypes. Consistent with a requirement for vision in novelty habituation, blind no receptor potential A(7) mutants display a failure in the decay of probability for directional persistence and mean absolute activity. The rutabaga(2080) habituation mutant also shows defects in these measures. The kurtz(1) non-visual arrestin mutant demonstrates a rapid decay in these measures, implying reduced motivation. The model and the habituation measures offer a powerful framework for understanding mechanisms associated with open field habituation.

Modeling Drosophila positional preferences in open field arenas with directional persistence and wall attraction

In open field arenas, Drosophila adults exhibit a preference for arena boundaries over internal walls and open regions. Herein, we investigate the nature of this preference using phenomenological modeling of locomotion to determine whether local arena features and constraints on movement alone are sufficient to drive positional preferences within open field arenas of different shapes and with different internal features. Our model has two components: directional persistence and local wall force. In regions far away from walls, the trajectory is entirely characterized by a directional persistence probability, , for each movement defined by the step size, , and the turn angle, . In close proximity to walls, motion is computed from and a local attractive force which depends on the distance between the fly and points on the walls. The directional persistence probability was obtained experimentally from trajectories of wild type Drosophila in a circular open field arena and the wall force was computed to minimize the difference between the radial distributions from the model and Drosophila in the same circular arena. The two-component model for fly movement was challenged by comparing the positional preferences from the two-component model to wild type Drosophila in a variety of open field arenas. In most arenas there was a strong concordance between the two-component model and Drosophila. In more complex arenas, the model exhibits similar trends, but some significant differences were found. These differences suggest that there are emergent features within these complex arenas that have significance for the fly, such as potential shelter. Hence, the two-component model is an important step in defining how Drosophila interact with their environment.

Open-field arena boundary is a primary object of exploration for Drosophila

Drosophila adults, when placed into a novel open-field arena, initially exhibit an elevated level of activity followed by a reduced stable level of spontaneous activity and spend a majority of time near the arena edge, executing motions along the walls. In order to determine the environmental features that are responsible for the initial high activity and wall-following behavior exhibited during exploration, we examined wild-type and visually impaired mutants in arenas with different vertical surfaces. These experiments support the conclusion that the wall-following behavior of Drosophila is best characterized by a preference for the arena boundary, and not thigmotaxis or centrophobicity. In circular arenas, Drosophila mostly move in trajectories with low turn angles. Since the boundary preference could derive from highly linear trajectories, we further developed a simulation program to model the effects of turn angle on the boundary preference. In an hourglass-shaped arena with convex-angled walls that forced a straight versus wall-following choice, the simulation with constrained turn angles predicted general movement across a central gap, whereas Drosophila tend to follow the wall. Hence, low turn angled movement does not drive the boundary preference. Lastly, visually impaired Drosophila demonstrate a defect in attenuation of the elevated initial activity. Interestingly, the visually impaired w(1118) activity decay defect can be rescued by increasing the contrast of the arena's edge, suggesting that the activity decay relies on visual detection of the boundary. The arena boundary is, therefore, a primary object of exploration for Drosophila.

miRNA data analysis: next-gen sequencing

MicroRNAs (miRNAs) are short, noncoding RNAs that have the capacity to bind, capture, and silence hundreds of genes within and across diverse signaling pathways 1(Bartel, Cell 136:215-33, 2009) Specific sets of miRNAs characterize specific cell lineages of normal organisms and an increasing number of diseases have been shown to be associated with the dysregulation of specific miRNAs. Deep sequencing platforms have revealed unexpected complexity in relation to miRNAs, including 5' and 3'-end-length heterogeneity and RNA editing. These insights not uncovered by previous microarray-based studies underscore the importance of data analysis tools that enable users to rapidly and easily analyze the unprecedented amounts of small RNA sequencing data that is emerging from next-generation sequencing platforms, such as Illumina/Solexa, SOLiD, and 454. In this chapter, we summarize the increasing number of analysis platforms that are available for miRNA discovery and profiling and the identification of functional miRNA-mRNA pairs in the context of biology and disease. We also discuss in greater detail our contributions to this effort.

Proinflammatory role for let-7 microRNAS in experimental asthma

MicroRNAs (miRNAs) are short, non-coding RNAs that target and silence protein coding genes through 3'-UTR elements. Evidence increasingly assigns an immunosuppressive role for miRNAs in immunity, but relatively few miRNAs have been studied, and an overall understanding of the importance of these regulatory transcripts in complex in vivo systems is lacking. Here we have applied multiple technologies to globally analyze miRNA expression and function in allergic lung disease, an experimental model of asthma. Deep sequencing and microarray analyses of the mouse lung short RNAome revealed numerous extant and novel miRNAs and other transcript classes. Similar to mRNAs, lung miRNA expression changed dynamically during the transition from the naive to the allergic state, suggesting numerous functional relationships. A possible role for miRNA editing in altering the lung mRNA target repertoire was also identified. Multiple members of the highly conserved let-7 miRNA family were the most abundant lung miRNAs, and we confirmed in vitro that interleukin 13 (IL-13), a cytokine essential for expression for allergic lung disease, is regulated by mmu-let-7a. However, inhibition of let-7 miRNAs in vivo using a locked nucleic acid profoundly inhibited production of allergic cytokines and the disease phenotype. Our findings thus reveal unexpected complexity in the miRNAome underlying allergic lung disease and demonstrate a proinflammatory role for let-7 miRNAs.