Transcription factor protein interactomes reveal genetic determinants in heart disease.

Congenital heart disease (CHD) is present in 1% of live births, yet identification of causal mutations remains challenging. We hypothesized that genetic determinants for CHDs may lie in the protein interactomes of transcription factors whose mutations cause CHDs. Defining the interactomes of two transcription factors haplo-insufficient in CHD, GATA4 and TBX5, within human cardiac progenitors, and integrating the results with nearly 9,000 exomes from proband-parent trios revealed an enrichment of de novo missense variants associated with CHD within the interactomes. Scoring variants of interactome members based on residue, gene, and proband features identified likely CHD-causing genes, including the epigenetic reader GLYR1. GLYR1 and GATA4 widely co-occupied and co-activated cardiac developmental genes, and the identified GLYR1 missense variant disrupted interaction with GATA4, impairing in vitro and in vivo function in mice. This integrative proteomic and genetic approach provides a framework for prioritizing and interrogating genetic variants in heart disease.

Moving bar of light evokes vectorial spatial selectivity in the immobile rat hippocampus.

Visual cortical neurons encode the position and motion direction of specific stimuli retrospectively, without any locomotion or task demand1. The hippocampus, which is a part of the visual system, is hypothesized to require self-motion or a cognitive task to generate allocentric spatial selectivity that is scalar, abstract2,3 and prospective4-7. Here we measured rodent hippocampal selectivity to a moving bar of light in a body-fixed rat to bridge these seeming disparities. About 70% of dorsal CA1 neurons showed stable activity modulation as a function of the angular position of the bar, independent of behaviour and rewards. One-third of tuned cells also encoded the direction of revolution. In other experiments, neurons encoded the distance of the bar, with preference for approaching motion. Collectively, these demonstrate visually evoked vectorial selectivity (VEVS). Unlike place cells, VEVS was retrospective. Changes in the visual stimulus or its predictability did not cause remapping but only caused gradual changes. Most VEVS-tuned neurons behaved like place cells during spatial exploration and the two selectivities were correlated. Thus, VEVS could form the basic building block of hippocampal activity. When combined with self-motion, reward or multisensory stimuli8, it can generate the complexity of prospective representations including allocentric space9, time10,11 and episodes12.

A Mesp1-dependent developmental breakpoint in transcriptional and epigenomic specification of early cardiac precursors.

Transcriptional networks governing cardiac precursor cell (CPC) specification are incompletely understood owing, in part, to limitations in distinguishing CPCs from non-cardiac mesoderm in early gastrulation. We leveraged detection of early cardiac lineage transgenes within a granular single-cell transcriptomic time course of mouse embryos to identify emerging CPCs and describe their transcriptional profiles. Mesp1, a transiently expressed mesodermal transcription factor, is canonically described as an early regulator of cardiac specification. However, we observed perdurance of CPC transgene-expressing cells in Mesp1 mutants, albeit mislocalized, prompting us to investigate the scope of the role of Mesp1 in CPC emergence and differentiation. Mesp1 mutant CPCs failed to robustly activate markers of cardiomyocyte maturity and crucial cardiac transcription factors, yet they exhibited transcriptional profiles resembling cardiac mesoderm progressing towards cardiomyocyte fates. Single-cell chromatin accessibility analysis defined a Mesp1-dependent developmental breakpoint in cardiac lineage progression at a shift from mesendoderm transcriptional networks to those necessary for cardiac patterning and morphogenesis. These results reveal Mesp1-independent aspects of early CPC specification and underscore a Mesp1-dependent regulatory landscape required for progression through cardiogenesis.

Transient Cell Cycle Induction in Cardiomyocytes to Treat Subacute Ischemic Heart Failure.

BACKGROUND: The regenerative capacity of the heart after myocardial infarction is limited. Our previous study showed that ectopic introduction of 4 cell cycle factors (4F; CDK1 [cyclin-dependent kinase 1], CDK4 [cyclin-dependent kinase 4], CCNB [cyclin B1], and CCND [cyclin D1]) promotes cardiomyocyte proliferation in 15% to 20% of infected cardiomyocytes in vitro and in vivo and improves cardiac function after myocardial infarction in mice. METHODS: Using temporal single-cell RNA sequencing, we aimed to identify the necessary reprogramming stages during the forced cardiomyocyte proliferation with 4F on a single cell basis. Using rat and pig models of ischemic heart failure, we aimed to start the first preclinical testing to introduce 4F gene therapy as a candidate for the treatment of ischemia-induced heart failure. RESULTS: Temporal bulk and single-cell RNA sequencing and further biochemical validations of mature human induced pluripotent stem cell-derived cardiomyocytes treated with either LacZ or 4F adenoviruses revealed full cell cycle reprogramming in 15% of the cardiomyocyte population at 48 hours after infection with 4F, which was associated mainly with sarcomere disassembly and metabolic reprogramming (n=3/time point/group). Transient overexpression of 4F, specifically in cardiomyocytes, was achieved using a polycistronic nonintegrating lentivirus (NIL) encoding 4F; each is driven by a TNNT2 (cardiac troponin T isoform 2) promoter (TNNT2-4Fpolycistronic-NIL). TNNT2-4Fpolycistronic-NIL or control virus was injected intramyocardially 1 week after myocardial infarction in rats (n=10/group) or pigs (n=6-7/group). Four weeks after injection, TNNT2-4Fpolycistronic-NIL-treated animals showed significant improvement in left ventricular ejection fraction and scar size compared with the control virus-treated animals. At 4 months after treatment, rats that received TNNT2-4Fpolycistronic-NIL still showed a sustained improvement in cardiac function and no obvious development of cardiac arrhythmias or systemic tumorigenesis (n=10/group). CONCLUSIONS: This study provides mechanistic insights into the process of forced cardiomyocyte proliferation and advances the clinical feasibility of this approach by minimizing the oncogenic potential of the cell cycle factors owing to the use of a novel transient and cardiomyocyte-specific viral construct.

Transcription Factor GATA4 Regulates Cell Type-Specific Splicing Through Direct Interaction With RNA in Human Induced Pluripotent Stem Cell-Derived Cardiac Progenitors.

BACKGROUND: GATA4 (GATA-binding protein 4), a zinc finger-containing, DNA-binding transcription factor, is essential for normal cardiac development and homeostasis in mice and humans, and mutations in this gene have been reported in human heart defects. Defects in alternative splicing are associated with many heart diseases, yet relatively little is known about how cell type- or cell state-specific alternative splicing is achieved in the heart. Here, we show that GATA4 regulates cell type-specific splicing through direct interaction with RNA and the spliceosome in human induced pluripotent stem cell-derived cardiac progenitors. METHODS: We leveraged a combination of unbiased approaches including affinity purification of GATA4 and mass spectrometry, enhanced cross-linking with immunoprecipitation, electrophoretic mobility shift assays, in vitro splicing assays, and unbiased transcriptomic analysis to uncover GATA4's novel function as a splicing regulator in human induced pluripotent stem cell-derived cardiac progenitors. RESULTS: We found that GATA4 interacts with many members of the spliceosome complex in human induced pluripotent stem cell-derived cardiac progenitors. Enhanced cross-linking with immunoprecipitation demonstrated that GATA4 also directly binds to a large number of mRNAs through defined RNA motifs in a sequence-specific manner. In vitro splicing assays indicated that GATA4 regulates alternative splicing through direct RNA binding, resulting in functionally distinct protein products. Correspondingly, knockdown of GATA4 in human induced pluripotent stem cell-derived cardiac progenitors resulted in differential alternative splicing of genes involved in cytoskeleton organization and calcium ion import, with functional consequences associated with the protein isoforms. CONCLUSIONS: This study shows that in addition to its well described transcriptional function, GATA4 interacts with members of the spliceosome complex and regulates cell type-specific alternative splicing via sequence-specific interactions with RNA. Several genes that have splicing regulated by GATA4 have functional consequences and many are associated with dilated cardiomyopathy, suggesting a novel role for GATA4 in achieving the necessary cardiac proteome in normal and stress-responsive conditions.

Current Scenario and Future Prospects of Endophytic Microbes: Promising Candidates for Abiotic and Biotic Stress Management for Agricultural and Environmental Sustainability.

Globally, substantial research into endophytic microbes is being conducted to increase agricultural and environmental sustainability. Endophytic microbes such as bacteria, actinomycetes, and fungi inhabit ubiquitously within the tissues of all plant species without causing any harm or disease. Endophytes form symbiotic relationships with diverse plant species and can regulate numerous host functions, including resistance to abiotic and biotic stresses, growth and development, and stimulating immune systems. Moreover, plant endophytes play a dominant role in nutrient cycling, biodegradation, and bioremediation, and are widely used in many industries. Endophytes have a stronger predisposition for enhancing mineral and metal solubility by cells through the secretion of organic acids with low molecular weight and metal-specific ligands (such as siderophores) that alter soil pH and boost binding activity. Finally, endophytes synthesize various bioactive compounds with high competence that are promising candidates for new drugs, antibiotics, and medicines. Bioprospecting of endophytic novel secondary metabolites has given momentum to sustainable agriculture for combating environmental stresses. Biotechnological interventions with the aid of endophytes played a pivotal role in crop improvement to mitigate biotic and abiotic stress conditions like drought, salinity, xenobiotic compounds, and heavy metals. Identification of putative genes from endophytes conferring resistance and tolerance to crop diseases, apart from those involved in the accumulation and degradation of contaminants, could open new avenues in agricultural research and development. Furthermore, a detailed molecular and biochemical understanding of endophyte entry and colonization strategy in the host would better help in manipulating crop productivity under changing climatic conditions. Therefore, the present review highlights current research trends based on the SCOPUS database, potential biotechnological interventions of endophytic microorganisms in combating environmental stresses influencing crop productivity, future opportunities of endophytes in improving plant stress tolerance, and their contribution to sustainable remediation of hazardous environmental contaminants.

Urn models for stochastic gene expression yield intuitive insights into the probability distributions of single-cell mRNA and protein counts.

Fitting the probability mass functions from analytical solutions of stochastic models of gene expression to the single-cell count distributions of mRNA and protein molecules can yield valuable insights into mechanisms underlying gene expression. Solutions of chemical master equations are available for various kinetic schemes but, even for the basic ON-OFF genetic switch, they take complex forms with generating functions given as hypergeometric functions. Interpretation of gene expression dynamics in terms of bursts is not consistent with the complete range of parameters for these functions. Physical insights into the probability mass functions are essential to ensure proper interpretations but are lacking for models considering genetic switches. To fill this gap, we develop urn models for stochastic gene expression. We sample RNA polymerases or ribosomes from a master urn, which represents the cytosol, and assign them to recipient urns of two or more colors, which represent time intervals in which no switching occurs. Colors of the recipient urns represent sub-systems of the promoter states, and the assignments to urns of a specific color represent gene expression. We use elementary principles of discrete probability theory to solve a range of kinetic models without feedback, including the Peccoud-Ycart model, the Shahrezaei-Swain model, and models with an arbitrary number of promoter states. In the last case, we obtain a novel result for the protein distribution. For activated genes, we show that transcriptional lapses, which are events of gene inactivation for short time intervals separated by long active intervals, quantify the transcriptional dynamics better than bursts. We show that the intuition gained from our urn models may also be useful in understanding existing solutions for models with feedback. We contrast our models with urn models for related distributions, discuss a generalization of the Delaporte distribution for single-cell data analysis, and highlight the limitations of our models.

Probing of RNA structures in a positive sense RNA virus reveals selection pressures for structural elements.

In single stranded (+)-sense RNA viruses, RNA structural elements (SEs) play essential roles in the infection process from replication to encapsidation. Using selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq) and covariation analysis, we explore the structural features of the third genome segment of cucumber mosaic virus (CMV), RNA3 (2216 nt), both in vitro and in plant cell lysates. Comparing SHAPE-Seq and covariation analysis results revealed multiple SEs in the coat protein open reading frame and 3' untranslated region. Four of these SEs were mutated and serially passaged in Nicotiana tabacum plants to identify biologically selected changes to the original mutated sequences. After passaging, loop mutants showed partial reversion to their wild-type sequence and SEs that were structurally disrupted by mutations were restored to wild-type-like structures via synonymous mutations in planta. These results support the existence and selection of virus open reading frame SEs in the host organism and provide a framework for further studies on the role of RNA structure in viral infection. Additionally, this work demonstrates the applicability of high-throughput chemical probing in plant cell lysates and presents a new method for calculating SHAPE reactivities from overlapping reverse transcriptase priming sites.

Analytical Expressions and Physics for Single-Cell mRNA Distributions of the lac Operon of E. coli.

Mechanistic models of stochastic gene expression are of considerable interest, but their complexity often precludes tractable analytical expressions for messenger RNA (mRNA) and protein distributions. The lac operon of Escherichia coli is a model system with regulatory elements such as multiple operators and DNA looping that are shared by many operons. Although this system is complex, intuition suggests that fast DNA looping may simplify it by causing the repressor-bound states of the operon to equilibrate rapidly, thus ensuring that the subsequent dynamics are governed by slow transitions between the repressor-free and the equilibrated repressor-bound states. Here, we show that this intuition is correct by applying singular perturbation theory to a mechanistic model of lac transcription with the scaled time constant of DNA looping as the perturbation parameter. We find that at steady state, the repressor-bound states satisfy detailed balance and are dominated by the looped states; moreover, the interaction between the repressor-free and the equilibrated repressor-bound states is described by an extension of the Peccoud-Ycart two-state model in which both (repressor-free and repressor-bound) states support transcription. The solution of this extended two-state model reveals that the steady-state mRNA distribution is a mixture of the Poisson and negative hypergeometric distributions, which reflects mRNAs obtained by transcription from the repressor-bound and repressor-free states. Finally, we show that the physics revealed by perturbation theory makes it easy to derive the extended two-state model equations for complex regulatory architectures.

SEQualyzer: interactive tool for quality control and exploratory analysis of high-throughput RNA structural profiling data.

Summary: To serve numerous functional roles, RNA must fold into specific structures. Determining these structures is thus of paramount importance. The recent advent of high-throughput sequencing-based structure profiling experiments has provided important insights into RNA structure and widened the scope of RNA studies. However, as a broad range of approaches continues to emerge, a universal framework is needed to quantitatively ensure consistent and high-quality data. We present SEQualyzer, a visual and interactive application that makes it easy and efficient to gauge data quality, screen for transcripts with high-quality information and identify discordant replicates in structure profiling experiments. Our methods rely on features common to a wide range of protocols and can serve as standards for quality control and analyses. Availability and Implementation: SEQualyzer is written in R, is platform-independent, and is freely available at http://bme.ucdavis.edu/aviranlab/SEQualyzer. Contact: saviran@ucdavis.edu Supplementary Informantion: Supplementary data are available at Bioinformatics online.

Metrics for rapid quality control in RNA structure probing experiments.

MOTIVATION: The diverse functionalities of RNA can be attributed to its capacity to form complex and varied structures. The recent proliferation of new structure probing techniques coupled with high-throughput sequencing has helped RNA studies expand in both scope and depth. Despite differences in techniques, most experiments face similar challenges in reproducibility due to the stochastic nature of chemical probing and sequencing. As these protocols expand to transcriptome-wide studies, quality control becomes a more daunting task. General and efficient methodologies are needed to quantify variability and quality in the wide range of current and emerging structure probing experiments. RESULTS: We develop metrics to rapidly and quantitatively evaluate data quality from structure probing experiments, demonstrating their efficacy on both small synthetic libraries and transcriptome-wide datasets. We use a signal-to-noise ratio concept to evaluate replicate agreement, which has the capacity to identify high-quality data. We also consider and compare two methods to assess variability inherent in probing experiments, which we then utilize to evaluate the coverage adjustments needed to meet desired quality. The developed metrics and tools will be useful in summarizing large-scale datasets and will help standardize quality control in the field. AVAILABILITY AND IMPLEMENTATION: The data and methods used in this article are freely available at: http://bme.ucdavis.edu/aviranlab/SPEQC_software CONTACT: saviran@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Application of ethylene diurea (EDU) in assessing the response of a tropical soybean cultivar to ambient O3: nitrogen metabolism, antioxidants, reproductive development and yield.

The present study deals with assessment of response of a tropical soybean cultivar to O3 in relation to photosynthetic pigments, chlorophyll fluorescence kinetics, antioxidative capacity, N assimilation enzymes, metabolites, growth and yield using ethylene diurea (EDU) given as a soil drench (400) ppm at an interval of 10 days after germination up to maturity. Mean O3 concentration was 42 ppb and accumulated threshold above 40 ppb (AOT 40) was 9.07 ppm h. Lipid peroxidation and total phenolics reduced, while increases in activities of antioxidative and nitrogen assimilation enzymes, ascorbic acid, protein, photosynthetic pigments, Fv/Fm ratio, number of leaves, flowers, pods, branches and yield attributes were found in EDU treated plants. EDU alleviated the negative effects of O3 by enhancing the first line of defense against ROS and protecting N assimilation enzymes at flowering and maintaining adequate supply of photosynthates to developing pods during pod filling stage. EDU provided maximum protection between flowering to pod filling stage.

Ultraviolet-B induced changes in morphological, physiological and biochemical parameters of two cultivars of pea (Pisum sativum L.).

Increase in perception of solar ultraviolet-B (UV-B) radiation on Earth's surface due to anthropogenic activities has potential in causing detrimental effects on plants. The present study was performed to evaluate the effect of elevated UV-B on Pisum sativum L., a leguminous plant with emphasis on nitrogen metabolism, flavonoids and hormonal changes. Elevated UV-B (ambient+7.2 kJ m(-2) day(-1)) negatively affected the growth, biomass, yield and its quality by generating oxidative stress directly or due to elevation of salicylic acid in two cultivars with higher magnitude being observed in HUP-2 as compared to HUDP-15. The increased accumulation of flavonoids (quercetin and kaempferol) under elevated UV-B neither provided sufficient protection to the photosynthetic machinery nor helped in elevation of biological nitrogen fixation. Nitrogen fixation and its assimilation were negatively affected under elevated UV-B as observed by the decline in nitrogenase, nitrate reductase, nitrite reductase activities and leghaemoglobin contents. Higher accumulation of salicylic acid in HUP-2 might be associated with its higher degree of sensitivity against UV-B, while higher induction of jasmonic acid and antioxidative enzymes (superoxide dismutase, catalase and ascorbate peroxidase activities) provided resistance to HUDP-15 against applied stress vis-a-vis exhibited less reduction in biomass, yield and quality of produce.

Spontaneous persistent activity and inactivity in vivo reveals differential cortico-entorhinal functional connectivity.

Understanding the functional connectivity between brain regions and its emergent dynamics is a central challenge. Here we present a theory-experiment hybrid approach involving iteration between a minimal computational model and in vivo electrophysiological measurements. Our model not only predicted spontaneous persistent activity (SPA) during Up-Down-State oscillations, but also inactivity (SPI), which has never been reported. These were confirmed in vivo in the membrane potential of neurons, especially from layer 3 of the medial and lateral entorhinal cortices. The data was then used to constrain two free parameters, yielding a unique, experimentally determined model for each neuron. Analytic and computational analysis of the model generated a dozen quantitative predictions about network dynamics, which were all confirmed in vivo to high accuracy. Our technique predicted functional connectivity; e. g. the recurrent excitation is stronger in the medial than lateral entorhinal cortex. This too was confirmed with connectomics data. This technique uncovers how differential cortico-entorhinal dialogue generates SPA and SPI, which could form an energetically efficient working-memory substrate and influence the consolidation of memories during sleep. More broadly, our procedure can reveal the functional connectivity of large networks and a theory of their emergent dynamics.

Effectiveness of bio-effectors on maize, wheat and tomato performance and phosphorus acquisition from greenhouse to field scales in Europe and Israel: a meta-analysis.

Biostimulants (Bio-effectors, BEs) comprise plant growth-promoting microorganisms and active natural substances that promote plant nutrient-acquisition, stress resilience, growth, crop quality and yield. Unfortunately, the effectiveness of BEs, particularly under field conditions, appears highly variable and poorly quantified. Using random model meta-analyses tools, we summarize the effects of 107 BE treatments on the performance of major crops, mainly conducted within the EU-funded project BIOFECTOR with a focus on phosphorus (P) nutrition, over five years. Our analyses comprised 94 controlled pot and 47 field experiments under different geoclimatic conditions, with variable stress levels across European countries and Israel. The results show an average growth/yield increase by 9.3% (n=945), with substantial differences between crops (tomato > maize > wheat) and growth conditions (controlled nursery + field (Seed germination and nursery under controlled conditions and young plants transplanted to the field) > controlled > field). Average crop growth responses were independent of BE type, P fertilizer type, soil pH and plant-available soil P (water-P, Olsen-P or Calcium acetate lactate-P). BE effectiveness profited from manure and other organic fertilizers, increasing soil pH and presence of abiotic stresses (cold, drought/heat or salinity). Systematic meta-studies based on published literature commonly face the inherent problem of publication bias where the most suspected form is the selective publication of statistically significant results. In this meta-analysis, however, the results obtained from all experiments within the project are included. Therefore, it is free of publication bias. In contrast to reviews of published literature, our unique study design is based on a common standardized protocol which applies to all experiments conducted within the project to reduce sources of variability. Based on data of crop growth, yield and P acquisition, we conclude that application of BEs can save fertilizer resources in the future, but the efficiency of BE application depends on cropping systems and environments.

Salt stress resilience in plants mediated through osmolyte accumulation and its crosstalk mechanism with phytohormones.

Salinity stress is one of the significant abiotic stresses that influence critical metabolic processes in the plant. Salinity stress limits plant growth and development by adversely affecting various physiological and biochemical processes. Enhanced generation of reactive oxygen species (ROS) induced via salinity stress subsequently alters macromolecules such as lipids, proteins, and nucleic acids, and thus constrains crop productivity. Due to which, a decreasing trend in cultivable land and a rising world population raises a question of global food security. In response to salt stress signals, plants adapt defensive mechanisms by orchestrating the synthesis, signaling, and regulation of various osmolytes and phytohormones. Under salinity stress, osmolytes have been investigated to stabilize the osmotic differences between the surrounding of cells and cytosol. They also help in the regulation of protein folding to facilitate protein functioning and stress signaling. Phytohormones play critical roles in eliciting a salinity stress adaptation response in plants. These responses enable the plants to acclimatize to adverse soil conditions. Phytohormones and osmolytes are helpful in minimizing salinity stress-related detrimental effects on plants. These phytohormones modulate the level of osmolytes through alteration in the gene expression pattern of key biosynthetic enzymes and antioxidative enzymes along with their role as signaling molecules. Thus, it becomes vital to understand the roles of these phytohormones on osmolyte accumulation and regulation to conclude the adaptive roles played by plants to avoid salinity stress.

Introducing R as a smart version of calculators enables beginners to explore it on their own.

Rapid technological advances in the past decades have enabled molecular biologists to generate large-scale and complex data with affordable resource investments, or obtain such data from public repositories. Yet, many graduate students, postdoctoral scholars, and senior researchers in the biosciences find themselves ill-equipped to analyze large-scale data. Global surveys have revealed that active researchers prefer short training workshops to fill their skill gaps. In this article, we focus on the challenge of delivering a short data analysis workshop to absolute beginners in computer programming. We propose that introducing R or other programming languages for data analysis as smart versions of calculators can help lower the communication barrier with absolute beginners. We describe this comparison with a few analogies and hope that other instructors will find them useful. We utilized these in our four-hour long training workshops involving participatory live coding, which we delivered in person and via videoconferencing. Anecdotal evidence suggests that our exposition made R programming seem easy and enabled beginners to explore it on their own.

Trends of adult height in India from 1998 to 2015: Evidence from the National Family and Health Survey.

AIM: The aim of the study is to investigate the trends in adult height between two consecutive surveys of NHFS and explore differences across variables such as gender, wealth, social groups etc. METHODS: We used the NFHS-II (1998-99), NFHS-III (2005-2006) and NFHS-IV (2015-16) (all three for women and last two for men) data to examine the trends in average height. Comparison was done between the two age strata of 15-25 and 26-50 years, across both male and female, to assess the trends. RESULTS: Between NFHS-III and NFHS-IV, the average height of women in the age group of 15-25 showed a decline by 0.12 cm [95% CI, -0.24 to 0.00, p-0.051] while in the 26-50 years age strata it demonstrated significant improvement in the mean height by 0.13 cm [95% CI, 0.02 to 0.023, p-0.015]. However, Between NFHS III and IV, the average height of women in the poorest wealth index category registered a significant decline [-0.57cm, 95% CI, -076 to -0.37, p-0.000]. Between NFHS III and IV, the average height of Scheduled Tribe (ST) women in the age group of 15-25 years also exhibited a significant decline by 0.42 cm, [95% CI, -0.73 to -0.12, p-0.007]. Among men, between the two surveys, both the age groups of 15-25 years and 26-50 years showed significant decline in average height: 1.10 cm [95% CI, -1.31 to -.099 cm, p-0.00] and 0.86 cm [95% CI, -1.03 to -0.69, p-0.000], respectively. CONCLUSION: In the context of an overall increase in average heights worldwide the decline in average height of adults in India is alarming and demands an urgent enquiry. The argument for different standards of height for Indian population as different genetic group needs further scrutiny. However, the trends from India clearly underline the need to examine the non-genetic factors also to understand the interplay of genetic, nutritional and other social and environmental determinants on height.

scNetViz: from single cells to networks using Cytoscape.

Single-cell RNA-sequencing (scRNA-seq) has revolutionized molecular biology and medicine by enabling high-throughput studies of cellular heterogeneity in diverse tissues. Applying network biology approaches to scRNA-seq data can provide useful insights into genes driving heterogeneous cell-type compositions of tissues. Here, we present scNetViz-  a Cytoscape app to aid biological interpretation of cell clusters in scRNA-seq data using network analysis. scNetViz calculates the differential expression of each gene across clusters and then creates a cluster-specific gene functional interaction network between the significantly differentially expressed genes for further analysis, such as pathway enrichment analysis. To automate a complete data analysis workflow, scNetViz integrates parts of the Scanpy software, which is a popular Python package for scRNA-seq data analysis, with Cytoscape apps such as stringApp, cyPlot, and enhancedGraphics. We describe our implementation of methods for accessing data from public single cell atlas projects, differential expression analysis, visualization, and automation. scNetViz enables users to analyze data from public atlases or their own experiments, which we illustrate with two use cases. Analysis can be performed via the Cytoscape GUI or CyREST programming interface using R (RCy3) or Python (py4cytoscape).

Phenotypic Differences between the Alzheimer's Disease-Related hAPP-J20 Model and Heterozygous Zbtb20 Knock-Out Mice.

Diverse gene products contribute to the pathogenesis of Alzheimer's disease (AD). Experimental models have helped elucidate their mechanisms and impact on brain functions. Human amyloid precursor protein (hAPP) transgenic mice from line J20 (hAPP-J20 mice) are widely used to simulate key aspects of AD. However, they also carry an insertional mutation in noncoding sequence of one Zbtb20 allele, a gene involved in neural development. We demonstrate that heterozygous hAPP-J20 mice have reduced Zbtb20 expression in some AD-relevant brain regions, but not others, and that Zbtb20 levels are higher in hAPP-J20 mice than heterozygous Zbtb20 knock-out (Zbtb20+/-) mice. Whereas hAPP-J20 mice have premature mortality, severe deficits in learning and memory, other behavioral alterations, and prominent nonconvulsive epileptiform activity, Zbtb20+/- mice do not. Thus, the insertional mutation in hAPP-J20 mice does not ablate the affected Zbtb20 allele and is unlikely to account for the AD-like phenotype of this model.