Hydroxyproline-rich glycoproteins (HRGPs) are a superfamily of plant cell wall proteins that function in diverse aspects of plant growth and development. This superfamily consists of three members: hyperglycosylated arabinogalactan proteins (AGPs), moderately glycosylated extensins (EXTs), and lightly glycosylated proline-rich proteins (PRPs). Hybrid and chimeric versions of HRGP molecules also exist. In order to "mine" genomic databases for HRGPs and to facilitate and guide research in the field, the BIO OHIO software program was developed that identifies and classifies AGPs, EXTs, PRPs, hybrid HRGPs, and chimeric HRGPs from proteins predicted from DNA sequence data. This bioinformatics program is based on searching for biased amino acid compositions and for particular protein motifs associated with known HRGPs. HRGPs identified by the program are subsequently analyzed to elucidate the following: (1) repeating amino acid sequences, (2) signal peptide and glycosylphosphatidylinositol lipid anchor addition sequences, (3) similar HRGPs via Basic Local Alignment Search Tool, (4) expression patterns of their genes, (5) other HRGPs, glycosyl transferase, prolyl 4-hydroxylase, and peroxidase genes coexpressed with their genes, and (6) gene structure and whether genetic mutants exist in their genes. The program was used to identify and classify 166 HRGPs from Arabidopsis (Arabidopsis thaliana) as follows: 85 AGPs (including classical AGPs, lysine-rich AGPs, arabinogalactan peptides, fasciclin-like AGPs, plastocyanin AGPs, and other chimeric AGPs), 59 EXTs (including SP 5 EXTs, SP 5 /SP 4 EXTs, SP 4 EXTs, SP 4 /SP 3 EXTs, a SP 3 EXT, "short" EXTs, leucine-rich repeat-EXTs, proline-rich extensin-like receptor kinases, and other chimeric EXTs), 18 PRPs (including PRPs and chimeric PRPs), and AGP/EXT hybrid HRGPs.

The Arabidopsis Gene Regulatory Information Server (AGRIS; http://arabidopsis.med.ohio-state.edu/) provides a comprehensive resource for gene regulatory studies in the model plant Arabidopsis thaliana. Three interlinked databases, AtTFDB, AtcisDB and AtRegNet, furnish comprehensive and updated information on transcription factors (TFs), predicted and experimentally verified cis-regulatory elements (CREs) and their interactions, respectively. In addition to significant contributions in the identification of the entire set of TF–DNA interactions, which are the key to understand the gene regulatory networks that govern Arabidopsis gene expression, tools recently incorporated into AGRIS include the complete set of words length 5–15 present in the Arabidopsis genome and the integration of AtRegNet with visualization tools, such as the recently developed ReIN application. All the information in AGRIS is publicly available and downloadable upon registration.

The three-dimensional (3D) structure of chromatin is intrinsically associated with gene regulation and cell function1–3. Methods based on chromatin conformation capture have mapped chromatin structures in neuronal systems such as in vitro differentiated neurons, neurons isolated through fluorescence-activated cell sorting from cortical tissues pooled from different animals and from dissociated whole hippocampi4–6. However, changes in chromatin organization captured by imaging, such as the relocation of Bdnf away from the nuclear periphery after activation7, are invisible with such approaches8. Here we developed immunoGAM, an extension of genome architecture mapping (GAM)2,9, to map 3D chromatin topology genome-wide in specific brain cell types, without tissue disruption, from single animals. GAM is a ligation-free technology that maps genome topology by sequencing the DNA content from thin (about 220 nm) nuclear cryosections. Chromatin interactions are identified from the increased probability of co-segregation of contacting loci across a collection of nuclear slices. ImmunoGAM expands the scope of GAM to enable the selection of specific cell types using low cell numbers (approximately 1,000 cells) within a complex tissue and avoids tissue dissociation2,10. We report cell-type specialized 3D chromatin structures at multiple genomic scales that relate to patterns of gene expression. We discover extensive ‘melting’ of long genes when they are highly expressed and/or have high chromatin accessibility. The contacts most specific of neuron subtypes contain genes associated with specialized processes, such as addiction and synaptic plasticity, which harbour putative binding sites for neuronal transcription factors within accessible chromatin regions. Moreover, sensory receptor genes are preferentially found in heterochromatic compartments in brain cells, which establish strong contacts across tens of megabases. Our results demonstrate that highly specific chromatin conformations in brain cells are tightly related to gene regulation mechanisms and specialized functions.

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Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.