Evolutionary origin of regulatory regions of retrogenes in Drosophila

<p>Abstract</p> <p>Background</p> <p>Retrogenes are processed copies of other genes. This duplication mechanism produces a copy of the parental gene that should not contain introns, and usually does not contain cis-regulatory regions. Here, we computationally address the evolutionary origin of promoter and other cis-regulatory regions in retrogenes using a total of 94 <it>Drosophila </it>retroposition events we recently identified. Previous tissue expression data has revealed that a large fraction of these retrogenes are specifically and/or highly expressed in adult testes of <it>Drosophila</it>.</p> <p>Results</p> <p>In this work, we infer that retrogenes do not generally carry regulatory regions from aberrant upstream or normal transcripts of their parental genes, and that expression patterns of neighboring genes are not consistently shared by retrogenes. Additionally, transposable elements do not appear to substantially provide regulatory regions to retrogenes. Interestingly, we find that there is an excess of retrogenes in male testis neighborhoods that is not explained by insertional biases of the retroelement machinery used for retroposition.</p> <p>Conclusion</p> <p>We conclude that retrogenes' regulatory regions mostly do not represent a random set of existing regulatory regions. On the contrary, our conclusion is that selection is likely to have played an important role in the persistence of autosomal testis biased retrogenes. Selection in favor of retrogenes inserted in male testis neighborhoods and at the sequence level to produce testis expression is postulated to have occurred.</p

Current status and future perspectives for sequencing livestock genomes

Abstract Only in recent years, the draft sequences for several agricultural animals have been assembled. Assembling an individual animal's entire genome sequence or specific region(s) of interest is increasingly important for agricultural researchers to perform genetic comparisons between animals with different performance. We review the current status for several sequenced agricultural species and suggest that next generation sequencing (NGS) technology with decreased sequencing cost and increased speed of sequencing can benefit agricultural researchers. By taking advantage of advanced NGS technologies, genes and chromosomal regions that are more labile to the influence of environmental factors could be pinpointed. A more long term goal would be addressing the question of how animals respond at the molecular and cellular levels to different environmental models (e.g. nutrition). Upon revealing important genes and gene-environment interactions, the rate of genetic improvement can also be accelerated. It is clear that NGS technologies will be able to assist animal scientists to efficiently raise animals and to better prevent infectious diseases so that overall costs of animal production can be decreased.http://deepblue.lib.umich.edu/bitstream/2027.42/112448/1/40104_2012_Article_2.pd

Modeling Spare Parts Demands Forecast under Two-Dimensional Preventive Maintenance Policy

In maintenance practice, there is such a situation where the spare parts replacement should be carried out at the scheduling time of calendar or usage for whichever comes first. The issue of two-dimensional preventive maintenance usually was not addressed by traditional methods, and at present, few studies were focused on this very topic. Based on these considerations, this paper presented the two-dimensional preventive policy where replacements of spare parts are based on both calendar time and usage time. A novel model was developed to forecast spare parts demands under two-dimensional preventive maintenance policy, and a discrete algorithm was presented for solving the mathematical model. A case study was given to demonstrate its applicability and validity, and it was showed that the presented model can be used to forecast spare parts demands as well as to optimize spare parts and preventive maintenance jointly

Comparative genomics reveals a constant rate of origination and convergent acquisition of functional retrogenes in Drosophila

BACKGROUND: Processed copies of genes (retrogenes) are duplicate genes that originated through the reverse-transcription of a host transcript and insertion in the genome. This type of gene duplication, as any other, could be a source of new genes and functions. Using whole genome sequence data for 12 Drosophila species, we dated the origin of 94 retroposition events that gave rise to candidate functional genes in D. melanogaster. RESULTS: Based on this analysis, we infer that functional retrogenes have emerged at a fairly constant rate of 0.5 genes per million years per lineage over the last approximately 63 million years of Drosophila evolution. The number of functional retrogenes and the rate at which they are recruited in the D. melanogaster lineage are of the same order of magnitude as those estimated in the human lineage, despite the higher deletion bias in the Drosophila genome. However, unlike primates, the rate of retroposition in Drosophila seems to be fairly constant and no burst of retroposition can be inferred from our analyses. In addition, our data also support an important role for retrogenes as a source of lineage-specific male functions, in agreement with previous hypotheses. Finally, we identified three cases of functional retrogenes in D. melanogaster that have been independently retroposed and recruited in parallel as new genes in other Drosophila lineages. CONCLUSION: Together, these results indicate that retroposition is a persistent mechanism and a recurrent pathway for the emergence of new genes in Drosophila

Orthogonal analysis of variants in APOE gene using in-silico approaches reveals novel disrupting variants

Introduction: Alzheimer’s disease (AD) is one of the most prominent medical conditions in the world. Understanding the genetic component of the disease can greatly advance our knowledge regarding its progression, treatment and prognosis. Single amino-acid variants (SAVs) in the APOE gene have been widely investigated as a risk factor for AD Studies, including genome-wide association studies, meta-analysis based studies, and in-vivo animal studies, were carried out to investigate the functional importance and pathogenesis potential of APOE SAVs. However, given the high cost of such large-scale or experimental studies, there are only a handful of variants being reported that have definite explanations. The recent development of in-silico analytical approaches, especially large-scale deep learning models, has opened new opportunities for us to probe the structural and functional importance of APOE variants extensively.Method: In this study, we are taking an ensemble approach that simultaneously uses large-scale protein sequence-based models, including Evolutionary Scale Model and AlphaFold, together with a few in-silico functional prediction web services to investigate the known and possibly disease-causing SAVs in APOE and evaluate their likelihood of being functional and structurally disruptive.Results: As a result, using an ensemble approach with little to no prior field-specific knowledge, we reported 5 SAVs in APOE gene to be potentially disruptive, one of which (C112R) was classificed by previous studies as a key risk factor for AD.Discussion: Our study provided a novel framework to analyze and prioritize the functional and structural importance of SAVs for future experimental and functional validation

Dissecting the biological relationship between TCGA miRNA and mRNA sequencing data using MMiRNA-Viewer

Abstract Background MicroRNAs (miRNA) are short nucleotides that interact with their target genes through 3′ untranslated regions (UTRs). The Cancer Genome Atlas (TCGA) harbors an increasing amount of cancer genome data for both tumor and normal samples. However, there are few visualization tools focusing on concurrently displaying important relationships and attributes between miRNAs and mRNAs of both cancer tumor and normal samples. Moreover, a deep investigation of miRNA-mRNA target and biological relationships across multiple cancer types by integrating web-based analysis has not been thoroughly conducted. Results We developed an interactive visualization tool called MMiRNA-Viewer that can concurrently present the co-relationships of expression between miRNA-mRNA pairs of both tumor and normal samples into a single graph. The input file of MMiRNA-Viewer contains the expression information including fold changes between normal and tumor samples for mRNAs and miRNAs, the correlation between mRNA and miRNA, and the predicted target relationship by a number of databases. Users can also load their own input data into MMiRNA-Viewer and visualize and compare detailed information about cancer-related gene expression changes, and also changes in the expression of transcription-regulating miRNAs. To validate the MMiRNA-Viewer, eight types of TCGA cancer datasets with both normal and control samples were selected in this study and three filter steps were applied subsequently. We performed Gene Ontology (GO) analysis for genes available in final selected 238 pairs and also for genes in the top 5 % (95 percentile) for each of eight cancer types to report a significant number of genes involved in various biological functions and pathways. We also calculated various centrality measurement matrices for the largest connected component(s) in each of eight cancers and reported top genes and miRNAs with high centrality measurements. Conclusions With its user-friendly interface, dynamic visualization and advanced queries, we also believe MMiRNA-Viewer offers an intuitive approach for visualizing and elucidating co-relationships between miRNAs and mRNAs of both tumor and normal samples. We suggest that miRNA and mRNA pairs with opposite fold changes of their expression and with inverted correlation values between tumor and normal samples might be most relevant for explaining the decoupling of mRNAs and their targeting miRNAs in tumor samples for certain cancer types.http://deepblue.lib.umich.edu/bitstream/2027.42/134658/1/12859_2016_Article_1219.pd

Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller

Prevalence of Postpartum Depression Based on Diagnostic Interviews:A Systematic Review and Meta-Analysis

Background. Postpartum depression (PPD) is common after childbirth. Previous reviews on the prevalence of PPD have mainly included results that relied on screening instruments or a mixture of such instruments and diagnostic interviews. In this study, we aimed to assess the prevalence of PPD based exclusively on studies using diagnostic interviews, as they provide the most reliable and valid approach for defining “caseness.” Methods. Using PubMed, Web of Science, Cochrane Library, Embase, CNKI, WANFANG DATA, and CBM up to September 18, 2022, we searched for original articles reporting data that could be used to calculate the prevalence of PPD based on diagnostic interviews. A random-effect meta-analysis model was then used to estimate the pooled prevalence. In addition, we assessed quality, heterogeneity, and publication bias across studies. Also, we did subgroup analyses to explore the pooled prevalence at different time points and settings. This study was registered with PROSPERO, CRD42021244539. Results. Of 17,115 articles retrieved, 54 studies were included (total sample size=15,586 women). The pooled prevalence of all depression and major depression within one year postpartum was 12.1% (95% CI 10.3%-14.1%; I2=91.0%) and 7.0% (95% CI 5.7%-8.4%; I2=83.0%), respectively. The peaks of all depression occurred during the first 6 months postpartum, especially 2-3 weeks and 6-8 weeks. Subgroup analyses showed that the prevalence of major depression was associated with the income level of countries (higher in low- and middle-income countries (LMICs) than in high-income countries (HICs)) and diagnostic criteria (higher using ICD than using DSM and RDC). No evidence of publication bias was found. Conclusions. Approximately one in eight postpartum women experiences a depressive condition, with one in fifteen suffering major depression. The pooled prevalence based on diagnostic interviews was lower than the existing consensus, which was largely based on self-reported screening instruments. The higher prevalence in LMICs underlines the importance of strengthening research and service provision among these populations