197 research outputs found
Long non-coding RNA SENCR is a positive regulator of ETV2
Department of Biological SciencesAlthough long non-coding RNAs (lncRNAs) have emerged as novel regulator of cell fate and gene expression, the regulation of vascular specific transcription factor by lncRNA in generation of induced endothelial cells (iEndo) has not been studied yet. In this study, ETS variant 2 (ETV2) converts human fibroblasts into iEndo, and smooth muscle and endothelial cell enriched migration/differentiationassociated long non-coding RNA (SENCR) was identified as a regulator of ETV2. iEndo showed similar morphology, endothelial cell markers, and tubular structure formation compared to human umbilical vein endothelial cell (HUVEC). Furthermore, over-expression of SENCR increased ETV2 gene and protein expression by enhancing ETV2 promoter activity through recruitment of PSPC1. This is the first study demonstrates the role of SENCR contributed to ETV2 activation in generation of iEndo.ope
Audit market concentration and audit fees: an international investigation
Several large auditor consolidations in the late 1980s-early 1990s, along with Arthur Andersenās collapse in 2001, facilitated global audit market concentration. Subsequently, regulators have expressed serious concern over the potential detrimental effects of this concentration, including cartel pricing. This study investigates the association between audit market concentration and audit fees. Using a large sample from 17 countries, our study yields three principal findings. First, consistent with regulatorsā concern, a significantly positive association exists between market concentration and fees. Second, the country-level legal regime changes this association dramatically: while significant and positive in countries with a weak legal regime, the association weakens and eventually becomes negative as the legal regime strengthens. Third, these associations are more pronounced among clients of non-Big 4 auditors than those of Big 4 auditors. These findings provide regulators and other stakeholders with important insights into the effects of audit market structure on audit pricing
A recentering approach for interpreting interaction effects from logit, probit, and other nonlinear models
Research SummaryStrategic management has seen numerous studies analyzing interaction terms in nonlinear models since Hoetkerās (Strat Mgmt J., 2007, 28(4), 331- 343) best- practice recommendations and Zelnerās (Strat Mgmt J., 2009, 30(12), 1335- 1348) simulation- based approach. We suggest an alternative recentering approach to assess the statistical and economic importance of interaction terms in nonlinear models. Our approach does not rely on making assumptions about the values of the control variables; it takes the existing model and data as is and requires fewer computational steps. The recentering approach not only provides a consistent answer about statistical meaningfulness of the interaction term at a given point of interest, but also helps to assess the effect size using the template that we offer in this study. We demonstrate how to implement our approach and discuss the implications for strategy researchers.Managerial SummaryIn industry settings, the relationship between multiple corporate strategy- related inputs and corporate performance is often nonlinear in nature. Furthermore, such relationships tend to vary for different types of firms represented within the broader population of firms in a given industry. It is thus imperative for managers to know how to take nonlinear relationships between related business factors into account when they make strategic decisions. We suggest a simple and easily implementable way of assessing and interpreting interactions in a nonlinear setting, which we term a recentering approach. We demonstrate how to apply our approach to a strategic management setting.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/3/smj3202.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/2/smj3202-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163421/1/smj3202_am.pd
Comparative analysis of organelle genomes provides conflicting evidence between morphological similarity and phylogenetic relationship in diatoms
Diatoms (Bacillariophyta) are abundant phytoplankton groups in marine environments, which contribute approximately 20% of global carbon fixation through photosynthesis. Moreover, diatoms exhibit the highest species diversity (approximately 18,000 diatom species) among marine photosynthetic eukaryotes, which were identified by morphological characteristics. Molecular phylogenetic analyses could shed new insights into the evolutionary relationships of diverse diatom species. Nevertheless, a comprehensive understanding of the phylogenetic relationships of diatom species still remains unclear because the available molecular data are insufficient compared with their high species diversity. Furthermore, several novel diatom species were reported from field samples with no molecular evidence. In particular, the phylogenies of diatom species constructed using organelle genomes revealed that several diatom genera are paraphyletic with high supporting values. We constructed high-resolution phylogenetic trees of diatom species using organelle genomes (plastids and mitochondria) and compared the morphologies in several paraphyletic diatom genera. Especially, the clades Nitzschia and Thalassiosira include several different diatom genera with high phylogenetic supports. Our study demonstrated that some morphological characteristics (e.g., genus characters) of several diatom genera could not represent current genus boundaries. Based on the results, we highlight the necessity for taxonomic reinvestigation. To reestablish this in diatoms, it will be essential to incorporate more genome data from a broader range of taxon samples, along with a comparison of morphological characteristics
The Power of Sound (TPoS): Audio Reactive Video Generation with Stable Diffusion
In recent years, video generation has become a prominent generative tool and
has drawn significant attention. However, there is little consideration in
audio-to-video generation, though audio contains unique qualities like temporal
semantics and magnitude. Hence, we propose The Power of Sound (TPoS) model to
incorporate audio input that includes both changeable temporal semantics and
magnitude. To generate video frames, TPoS utilizes a latent stable diffusion
model with textual semantic information, which is then guided by the sequential
audio embedding from our pretrained Audio Encoder. As a result, this method
produces audio reactive video contents. We demonstrate the effectiveness of
TPoS across various tasks and compare its results with current state-of-the-art
techniques in the field of audio-to-video generation. More examples are
available at https://ku-vai.github.io/TPoS/Comment: ICCV202
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CWAS-Plus: estimating category-wide association of rare noncoding variation from whole-genome sequencing data with cell-type-specific functional data.
Variants in cis-regulatory elements link the noncoding genome to human pathology; however, detailed analytic tools for understanding the association between cell-level brain pathology and noncoding variants are lacking. CWAS-Plus, adapted from a Python package for category-wide association testing (CWAS), enhances noncoding variant analysis by integrating both whole-genome sequencing (WGS) and user-provided functional data. With simplified parameter settings and an efficient multiple testing correction method, CWAS-Plus conducts the CWAS workflow 50 times faster than CWAS, making it more accessible and user-friendly for researchers. Here, we used a single-nuclei assay for transposase-accessible chromatin with sequencing to facilitate CWAS-guided noncoding variant analysis at cell-type-specific enhancers and promoters. Examining autism spectrum disorder WGS data (nā=ā7280), CWAS-Plus identified noncoding de novo variant associations in transcription factor binding sites within conserved loci. Independently, in Alzheimers disease WGS data (nā=ā1087), CWAS-Plus detected rare noncoding variant associations in microglia-specific regulatory elements. These findings highlight CWAS-Pluss utility in genomic disorders and scalability for processing large-scale WGS data and in multiple-testing corrections. CWAS-Plus and its user manual are available at https://github.com/joonan-lab/cwas/ and https://cwas-plus.readthedocs.io/en/latest/, respectively
The dynamic transcriptional and translational landscape of the model antibiotic producer Streptomyces coelicolor A3(2)
Individual Streptomyces species have the genetic potential to produce a diverse array of natural products of commercial, medical and veterinary interest. However, these products are often not detectable under laboratory culture conditions. To harness their full biosynthetic potential, it is important to develop a detailed understanding of the regulatory networks that orchestrate their metabolism. Here we integrate nucleotide resolution genome-scale measurements of the transcriptome and translatome of Streptomyces coelicolor, the model antibiotic-producing actinomycete. Our systematic study determines 3,570 transcription start sites and identifies 230 small RNAs and a considerable proportion (ā¼21%) of leaderless mRNAs; this enables deduction of genome-wide promoter architecture. Ribosome profiling reveals that the translation efficiency of secondary metabolic genes is negatively correlated with transcription and that several key antibiotic regulatory genes are translationally induced at transition growth phase. These findings might facilitate the design of new approaches to antibiotic discovery and development
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Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome
Determining transcriptional and translational regulatory elements in GC-rich Streptomyces genomes is essential to elucidating the complex regulatory networks that govern secondary metabolite biosynthetic gene cluster (BGC) expression. However, information about such regulatory elements has been limited for Streptomyces genomes. To address this limitation, a high-quality genome sequence of Ī²-lactam antibiotic-producing Streptomyces clavuligerus ATCC 27Ā 064 is completed, which contains 7163 newly annotated genes. This provides a fundamental reference genome sequence to integrate multiple genome-scale data types, including dRNA-Seq, RNA-Seq and ribosome profiling. Data integration results in the precise determination of 2659 transcription start sites which reveal transcriptional and translational regulatory elements, including -10 and -35 promoter components specific to sigma (Ļ) factors, and 5'-untranslated region as a determinant for translation efficiency regulation. Particularly, sequence analysis of a wide diversity of the -35 components enables us to predict potential Ļ-factor regulons, along with various spacer lengths between the -10 and -35 elements. At last, the primary transcriptome landscape of the Ī²-lactam biosynthetic pathway is analyzed, suggesting temporal changes in metabolism for the synthesis of secondary metabolites driven by transcriptional regulation. This comprehensive genetic information provides a versatile genetic resource for rational engineering of secondary metabolite BGCs in Streptomyces
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