The identification and classification of endogenous retroviruses in the horse genome

Endogenous retroviruses (ervs) are sequences that derived from ancient retroviral infections of germ cells and integrated in humans, mammals and other vertebrates millions years ago. These ervs are inherited according to Mendelian expectations as all other genes in the genome. Coding sequences are flanked by two ltrs (long terminal repeat sequences). Most ervs are defective however some ervs still have open reading frames in their genome. These ervs settle close to functional genes or within the genes and can influence or control functions of the host genes using their ltrs. Most integration has deleterious effects. However some integration could be example of positive co-adaptation as syncitin. The first equine endogenous beta retrovirus which is ecerv-beta1 has been found in 2011 by Antoinette C.van der Kuyl1. The first known beta retrovirus and few pol gene similar to foamy retrovirus were only known endogenous retroviruses fixed in the domestic horse (equuscaballus) genome. Our aim of the study was to identify other endogenous retrovirus sequences in an equine genome and classify them into groups. Based on the high number of sines (equine repetitive element) in the horse genome we hypothesized that certain ervs will be located sufficiently close to sines that they will be amplified using an unbiased sine-pcr approach with degenerate primers. The nearest sine element was located 5.5 kbp upstream at the 5’of the ecerv-beta1. Pan-pol pcr was also used to find novel ervs based on 640 bp long region of pol gene which is the most conserved region of ervs. 27 complete and novel ervs that are 13 beta, 13 gamma, 1 spuma and 249 candidate endogenous retroviruses have been revealed using ltr_struc tool and double checked by retrotector online tool and ncbi-blast tool. It was proven that ecerv-beta1, which has 2 ltrs with 1% divergence between ltrs has a polymorphism among 13 different breeds

Transcriptional responses are oriented towards different components of the rearing environment in two Drosophila sibling species

Background The chance to compare patterns of differential gene expression in related ecologically distinct species can be particularly fruitful to investigate the genetics of adaptation and phenotypic plasticity. In this regard, a powerful technique such as RNA-Seq applied to ecologically amenable taxa allows to address issues that are not possible in classic model species. Here, we study gene expression profiles and larval performance of the cactophilic siblings Drosophila buzzatii and D. koepferae reared in media that approximate natural conditions and evaluate both chemical and nutritional components of the diet. These closely related species are complementary in terms of host-plant use since the primary host of one is the secondary of the other. D. koepferae is mainly a columnar cactus dweller while D. buzzatii prefers Opuntia hosts. Results Our comparative study shows that D. buzzatii and D. koepferae have different transcriptional strategies to face the challenges posed by their natural resources. The former has greater transcriptional plasticity, and its response is mainly modulated by alkaloids of its secondary host, while the latter has a more canalized genetic response, and its transcriptional plasticity is associated with the cactus species. Conclusions Our study unveils a complex pleiotropic genetic landscape in both species, with functional links that relate detox responses and redox mechanisms with developmental and neurobiological processes. These results contribute to deepen our understanding of the role of host plant shifts and natural stress driving ecological specialization

The GOBLET training portal: A global repository of bioinformatics training materials, courses and trainers

Summary: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide

From segment to somite: segmentation to epithelialization analyzed within quantitative frameworks

One of the most visually striking patterns in the early developing embryo is somite segmentation. Somites form as repeated, periodic structures in pairs along nearly the entire caudal vertebrate axis. The morphological process involves short- and long-range signals that drive cell rearrangements and cell shaping to create discrete, epithelialized segments. Key to developing novel strategies to prevent somite birth defects that involve axial bone and skeletal muscle development is understanding how the molecular choreography is coordinated across multiple spatial scales and in a repeating temporal manner. Mathematical models have emerged as useful tools to integrate spatiotemporal data and simulate model mechanisms to provide unique insights into somite pattern formation. In this short review, we present two quantitative frameworks that address the morphogenesis from segment to somite and discuss recent data of segmentation and epithelialization

Data integration in the era of omics: current and future challenges

To integrate heterogeneous and large omics data constitutes not only a conceptual challenge but a practical hurdle in the daily analysis of omics data. With the rise of novel omics technologies and through large-scale consortia projects, biological systems are being further investigated at an unprecedented scale generating heterogeneous and often large data sets. These data-sets encourage researchers to develop novel data integration methodologies. In this introduction we review the definition and characterize current efforts on data integration in the life sciences. We have used a web-survey to assess current research projects on data-integration to tap into the views, needs and challenges as currently perceived by parts of the research community

A Pilot Study Assessing the Potential Role of non-CD133 Colorectal Cancer Stem Cells as Biomarkers

Introduction: Over 50% of patients with colorectal cancer (CRC) will progress and/or develop metastases. Biomarkers capable of predicting progression, risk stratification and therapeutic benefit are needed. Cancer stem cells are thought to be responsible for tumor initiation, dissemination and treatment failure. Therefore, we hypothesized that CRC cancer stem cell markers (CRCSC) will identify a group of patients at high risk for progression

EpiCass and CassavaNet4Dev advanced bioinformatics workshop

Open Access ArticleEpiCass and CassavaNet4Dev are collaborative projects funded by the Swedish Research Council between the Swedish University of Agriculture (SLU) and the International Institute of Tropical Agriculture (IITA). The projects aim to investigate the influence of epigenetic changes on agricultural traits such as yield and virus resistance while also providing African students and researchers with advanced bioinformatics training and opportunities to participate in big data analysis events. The first advanced bioinformatics training workshop took place from May 16th to May 18th, 2022, followed by an online mini-symposium titled "Epigenetics and crop improvement" on May 19th. The symposium featured international speakers covering a wide range of topics related to plant epigenetics, cassava viral diseases, and cassava breeding strategies. A new online and on-site teaching concept was developed for the three-day workshop to ensure maximum student participation across Western, Eastern, and Southern Africa. Initially planned in Nigeria, Kenya, Ethiopia, Tanzania, and Zambia, the workshop ultimately focused on Nigeria, Kenya, and Ethiopia due to a lack of qualified candidates in the other countries. Each classroom hosted 20 to 25 students, with at least one bioinformatician present for support. The classrooms were connected via video conferencing, whereas teachers located in different places in Africa and Europe joined the video stream to conduct teaching sessions. The workshop was divided into theoretical classes and hands-on sessions, where participants could run data analysis with support from online teachers and local bioinformaticians. To enable participants to run guided, CPU and RAM-intensive data analysis workflows and overcome local computing and internet access restrictions, a system of virtual machines (VMs) hosted in the cloud was developed. The teaching platform provided teaching and exercise materials to support the use of the VMs. Although some students could not run heavy data analysis workflows due to unforeseen restrictions in the cloud, these issues were solved. All participants had the opportunity to run the analysis steps independently in the cloud using the protocols hosted on the teaching platform