38 research outputs found
The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.
X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution
Batf2/Irf1 Induces Inflammatory Responses in Classically Activated Macrophages, Lipopolysaccharides, and Mycobacterial Infection
Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics
Data Descriptor : FANTOM5 CAGE profiles of human and mouse samples
In the FANTOM5 project, transcription initiation events across the human and mouse genomes were mapped at a single base-pair resolution and their frequencies were monitored by CAGE (Cap Analysis of Gene Expression) coupled with single-molecule sequencing. Approximately three thousands of samples, consisting of a variety of primary cells, tissues, cell lines, and time series samples during cell activation and development, were subjected to a uniform pipeline of CAGE data production. The analysis pipeline started by measuring RNA extracts to assess their quality, and continued to CAGE library production by using a robotic or a manual workflow, single molecule sequencing, and computational processing to generate frequencies of transcription initiation. Resulting data represents the consequence of transcriptional regulation in each analyzed state of mammalian cells. Non-overlapping peaks over the CAGE profiles, approximately 200,000 and 150,000 peaks for the human and mouse genomes, were identified and annotated to provide precise location of known promoters as well as novel ones, and to quantify their activities.Peer reviewe
Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells
While it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then mRNAs encoding transcription factors dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously over-represented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation
Sistematización de la experiencia de un ambiente de aprendizaje enriquecido por TIC durante la práctica clínica en fisioterapia cardiopulmonar en un hospital de nivel II de la ciudad de Cali
Esta investigación se centra en la caracterización de la experiencia de 4 estudiantes de fisioterapia de IX semestre de la Institución Universitaria Escuela Nacional del Deporte (IUEND) durante la implementación de un ambiente de aprendizaje enriquecido con Tecnologías de la Información y la Comunicación (TIC) en la práctica clínico – asistencial en Salud Cardiopulmonar; la cual se fundamenta en el hacer y pone a prueba las bases conceptuales del ciclo de fundamentación; todo esto con el fin de identificar las experiencias significativas que facilitan el aprendizaje y desarrollo de competencias clínicas, además analizar si este tipo de estrategias de enseñanza -aprendizaje permite al estudiante y al docente asesor superar inconvenientes propios de la práctica clínica como: optimizar tiempos de atención a pacientes, estudio independiente y trabajo colaborativo, retomar e integrar gran cantidad de conceptos y procedimientos aprendidos en IV semestre con las nuevas experiencias y la realidad del paciente; y a la vez cumplir con funciones administrativas propios del rol del fisioterapeuta asistencial (estadística, indicadores, desarrollo de guías, etc.) que dificultan el proceso de aprendizaje; concluyendo que los ambientes mediados por TIC pueden lograr superar estas dificultades y favorecer finalmente el aprendizaje significativo (juicio clínico), en el que se fundamenta el ciclo de práctica profesional
Collision detection on transmission lines with optical interferometer
V diplomski nalogi skušamo ugotoviti, v kolikšni meri je možno zaznavati in klasificirati trke na jeklenicah daljnovodov z optičnim interferometrom. Na začetku predstavimo osnovne pojme interferometrije in opišemo uporabljen optični interferometer. V jedru diplomske naloge natančneje opišemo eksperimentalni protokol in obdelavo signalov. Nadaljujemo z implementacijo algoritmov za segmentacijo in klasifikacijo zajetih signalov ter predstavimo dobljene rezultate. Segmentacijo izvedemo v domeni števila prehodov signala skozi ničlo, za klasifikacijo pa uporabimo večplastno nevronsko mrežo z algoritmom vzvratnega učenja. Rezultati študije nakazujejo, da sta implementirani segmentacija in klasifikacija uspešni v 77 % izvedenih trkov različnih predmetov.We analyse feasibility of collision detection on transmission lines with optical interferometer. We first provide a brief introduction into interferometry, along with a description of the optical interferometer used for measurements in this study. Afterwards, we describe the conducted experimental protocol and signal processing methodology. The focus is on implementation of algorithms for signal segmentation and collision classification. We used zero-crossing algorithm to transform signals into segmentation domain. Classification of collisions is done with a multilayer neural network trained by the backpropagation algorithm. The results demonstrate an average success rate of 77% for segmentation and classification of collision with five different objects