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1.
J Biomol Tech ; 31(2): 66-73, 2020 07.
Article in English | MEDLINE | ID: mdl-32382253

ABSTRACT

Over the last decade, the cost of -omics data creation has decreased 10-fold, whereas the need for analytical support for those data has increased exponentially. Consequently, bioinformaticians face a second wave of challenges: novel applications of existing approaches (e.g., single-cell RNA sequencing), integration of -omics data sets of differing size and scale (e.g., spatial transcriptomics), as well as novel computational and statistical methods, all of which require more sophisticated pipelines and data management. Nonetheless, bioinformatics cores are often asked to operate under primarily a cost-recovery model, with limited institutional support. Seeing the need to assess bioinformatics core operations, the Association of Biomolecular Resource Facilities Genomics Bioinformatics Research Group conducted a survey to answer questions about staffing, services, financial models, and challenges to better understand the challenges bioinformatics core facilities are currently faced with and will need to address going forward. Of the respondent groups, we chose to focus on the survey data from smaller cores, which made up the majority. Although all cores indicated similar challenges in terms of changing technologies and analysis needs, small cores tended to have the added challenge of funding their operations largely through cost-recovery models with heavy administrative burdens.


Subject(s)
Biomedical Research/standards , Computational Biology/standards , Genomics/standards , Humans , Single-Cell Analysis/standards
2.
BMC Genomics ; 20(1): 1031, 2019 Dec 30.
Article in English | MEDLINE | ID: mdl-31888477

ABSTRACT

BACKGROUND: The proximal femoral head separation (FHS) or epiphysiolysis is a prevalent disorder affecting the chicken femur epiphysis, being considered a risk factor to infection which can cause bacterial chondronecrosis with osteomyelitis in broilers. To identify the genetic mechanisms involved in epiphysiolysis, differentially expressed (DE) genes in the femur of normal and FHS-affected broilers were identified using RNA-Seq technology. Femoral growth plate (GP) samples from 35-day-old commercial male broilers were collected from 4 healthy and 4 FHS-affected broilers. Sequencing was performed using an Illumina paired-end protocol. Differentially expressed genes were obtained using the edgeR package based on the False Discovery Rate (FDR < 0.05). RESULTS: Approximately 16 million reads/sample were generated with 2 × 100 bp paired-end reads. After data quality control, approximately 12 million reads/sample were mapped to the reference chicken genome (Galgal5). A total of 12,645 genes were expressed in the femur GP. Out of those, 314 were DE between groups, being 154 upregulated and 160 downregulated in FHS-affected broilers. In the functional analyses, several biological processes (BP) were overrepresented. Among them, those related to cell adhesion, extracellular matrix (ECM), bone development, blood circulation and lipid metabolism, which are more related to chicken growth, are possibly involved with the onset of FHS. On the other hand, BP associated to apoptosis or cell death and immune response, which were also found in our study, could be related to the consequence of the FHS. CONCLUSIONS: Genes with potential role in the epiphysiolysis were identified through the femur head transcriptome analysis, providing a better understanding of the mechanisms that regulate bone development in fast-growing chickens. In this study, we highlighted the importance of cell adhesion and extracellular matrix related genes in triggering FHS. Furthermore, we have shown new insights on the involvement of lipidemia and immune response/inflammation with FHS in broilers. Understanding the changes in the GP transcriptome might support breeding strategies to address poultry robustness and to obtain more resilient broilers.


Subject(s)
Chickens/genetics , Epiphyses, Slipped/veterinary , Femur Head/metabolism , Genetic Predisposition to Disease , Poultry Diseases/genetics , Transcriptome , Animals , Computational Biology/methods , Gene Expression Profiling , Gene Ontology , Gene Regulatory Networks , Genetic Association Studies , Reproducibility of Results
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