Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

Genome-wide transcriptome and proteome profiles indicate an active role of alternative splicing during de-etiolation of maize seedlings

AS events affect genes encoding protein domain composition and make the single gene produce more proteins with a certain number of genes to satisfy the establishment of photosynthesis during de-etiolation. The drastic switch from skotomorphogenic to photomorphogenic development is an excellent system to elucidate rapid developmental responses to environmental stimuli in plants. To decipher the effects of different light wavelengths on de-etiolation, we illuminated etiolated maize seedlings with blue, red, blue-red mixed and white light, respectively. We found that blue light alone has the strongest effect on photomorphogenesis and that this effect can be attributed to the higher number and expression levels of photosynthesis and chlorosynthesis proteins. Deep sequencing-based transcriptome analysis revealed gene expression changes under different light treatments and a genome-wide alteration in alternative splicing (AS) profiles. We discovered 41,188 novel transcript isoforms for annotated genes, which increases the percentage of multi-exon genes with AS to 63% in maize. We provide peptide support for all defined types of AS, especially retained introns. Further in silico prediction revealed that 58.2% of retained introns have changes in domains compared with their most similar annotated protein isoform. This suggests that AS acts as a protein function switch allowing rapid light response through the addition or removal of functional domains. The richness of novel transcripts and protein isoforms also demonstrates the potential and importance of integrating proteomics into genome annotation in maize.

Deep learning for mining protein data

The recent emergence of deep learning to characterize complex patterns of protein big data reveals its potential to address the classic challenges in the field of protein data mining. Much research has revealed the promise of deep learning as a powerful tool to transform protein big data into valuable knowledge, leading to scientific discoveries and practical solutions. In this review, we summarize recent publications on deep learning predictive approaches in the field of mining protein data. The application architectures of these methods include multilayer perceptrons, stacked autoencoders, deep belief networks, two- or three-dimensional convolutional neural networks, recurrent neural networks, graph neural networks, and complex neural networks and are described from five perspectives: residue-level prediction, sequence-level prediction, three-dimensional structural analysis, interaction prediction, and mass spectrometry data mining. The advantages and deficiencies of these architectures are presented in relation to various tasks in protein data mining. Additionally, some practical issues and their future directions are discussed, such as robust deep learning for protein noisy data, architecture optimization for specific tasks, efficient deep learning for limited protein data, multimodal deep learning for heterogeneous protein data, and interpretable deep learning for protein understanding. This review provides comprehensive perspectives on general deep learning techniques for protein data analysis.

Functional annotation of operome from Methanothermobacter thermautotrophicus ΔH: An insight to metabolic gap filling

Methanothermobacter thermautotrophicus ΔH (MTH) is a potential methanogen known to reduce CO₂ with H₂ for producing methane biofuel in thermophilic digesters. The genome of this organism contains ~50.5% conserved hypothetical proteins (HPs; operome) whose function is still not determined precisely. Here, we employed a combined bioinformatics approach to annotate a precise function to HPs and categorize them as enzymes, binding proteins, and transport proteins. Results of our study show that 315 (35.6%) HPs have exhibited well-defined functions contributing imperative roles in diverse cellular metabolism. Some of them are responsible for stress-response mechanisms and cell cycle, membrane transport, and regulatory processes. The genome-neighborhood analysis found five important gene clusters (dsr, ehb, kaiC, cmr, and gas) involving in the energetic metabolism and defense systems. MTH operome contains 223 enzymes with 15 metabolic subsystems, 15 cell cycle proteins, 17 transcriptional regulators and 33 binding proteins. Functional annotation of its operome is thus more fundamental to a profound understanding of the molecular and cellular machinery at systems-level.

Genomic analyses identify agents regulating somatotroph and lactotroph functions

Isolated hormone deficiency might be caused by loss of a specific type of endocrine cells, and regenerating these missing cells may provide a new option for future treatment. It is known that POU1F1 lineage cells can differentiate into thyrotroph, somatotroph, and lactotroph. However, there is no effective way of controlling pituitary stem/progenitor cells to differentiate into a specific type of endocrine cell. We thereby analyzed multiple genomic publications related to POU1F1 and pituitary development in this study to identify genes and agents regulating POU1F1 lineage cell differentiation. ANOVA analyses were performed to obtain differentially expressed genes. Ingenuity pathway analyses were performed to obtain signaling pathways, interaction networks, and upstream regulators. Venn diagram was used to determine the overlapping information between studies. Summary statistics was performed to rank genes according to their frequency of occurrence in these studies. The results from upstream analyses indicated that 326 agents may regulate pituitary cell differentiation. These agents can be categorized into 12 groups, including hormones and related pathways, PKA-cAMP pathways, p53/DNA damaging/cell cycle pathways, immune/inflammation regulators, growth factor and downstream pathways, retinoic/RAR pathways, ROS pathways, histone modifications, CCAAT/enhancer binding protein family, neuron development/degeneration pathways, calcium related and fat acid, and glucose pathways. Additional experiments demonstrated that H₂O₂ and catalase differentially regulate growth hormone and prolactin expression in somatolactotroph cells, confirming potential roles of ROS pathway on regulating somatotroph and lactotroph functions.

Can inferred provenance and its visualisation be used to detect erroneous annotation? A case study using UniProtKB

A constant influx of new data poses a challenge in keeping the annotation in biological databases current. Most biological databases contain significant quantities of textual annotation, which often contains the richest source of knowledge. Many databases reuse existing knowledge; during the curation process annotations are often propagated between entries. However, this is often not made explicit. Therefore, it can be hard, potentially impossible, for a reader to identify where an annotation originated from. Within this work we attempt to identify annotation provenance and track its subsequent propagation. Specifically, we exploit annotation reuse within the UniProt Knowledgebase (UniProtKB), at the level of individual sentences. We describe a visualisation approach for the provenance and propagation of sentences in UniProtKB which enables a large-scale statistical analysis. Initially levels of sentence reuse within UniProtKB were analysed, showing that reuse is heavily prevalent, which enables the tracking of provenance and propagation. By analysing sentences throughout UniProtKB, a number of interesting propagation patterns were identified, covering over sentences. Over sentences remain in the database after they have been removed from the entries where they originally occurred. Analysing a subset of these sentences suggest that approximately are erroneous, whilst appear to be inconsistent. These results suggest that being able to visualise sentence propagation and provenance can aid in the determination of the accuracy and quality of textual annotation.

Source code and supplementary data are available from the authors website at http://homepages.cs.ncl.ac.uk/m.j.bell1/sentence_analysis/.

Identification of salt treated proteins in sorghum using gene ontology linkage

Sorghum bicolor (L.) is an important crop of arid and semi arid zones with most of its varieties tolerant to drought, heat and salt stress. Functional identification of many salt tolerant proteins has been reported in Arabidopsis, rice and other plants, however only little functional information has been predicted in sorghum till date. A 2-D gel electrophoresis based proteomic approach with MALDI-TOF mass spectrometer was utilized to analyze the salt stress response of sorghum. Major changes in protein complement were observed at 200 mM NaCl in hydroponic culture after 96 h of salt-stress. Highly expressed five proteins were excised for functional identification. We developed shortest path (SP) analysis based method on Gene Ontology (GO) hierarchy using sum of GO-term's semantic similarities. In this study, we observed that majority of expressed proteins belonged to the functional category of energy production and conversion, signal transduction mechanisms and ribosome maturation. These identified functions suggest a distinct mechanism of salt-stress adaptation in sorghum plant. The proposed method in this paper potentially has great importance to further understanding of newly identified proteins that can help in plant development.

Poultry genome sequences: progress and outstanding challenges

The first build of the chicken genome sequence appeared in March, 2004 - the first genome sequence of any animal agriculture species. That sequence was done primarily by whole genome shotgun Sanger sequencing, along with the use of an extensive BAC contig-based physical map to assemble the sequence contigs and scaffolds and align them to the known chicken chromosomes and linkage groups. Subsequent sequencing and mapping efforts have improved upon that first build, and efforts continue in search of missing and/or unassembled sequence, primarily on the smaller microchromosomes and the sex chromosomes. In the past year, a draft turkey genome sequence of similar quality has been obtained at a much lower cost primarily due to the development of 'next-generation' sequencing techniques. However, assembly and alignment of the sequence contigs and scaffolds still depended on a detailed BAC contig map of the turkey genome that also utilized comparison to the existing chicken sequence. These 2 land fowl (Galliformes) genomes show a remarkable level of similarity, despite an estimated 30-40 million years of separate evolution since their last common ancestor. Among the advantages offered by these sequences are routine re-sequencing of commercial and research lines to identify the genetic correlates of phenotypic change (for example, selective sweeps), a much improved understanding of poultry diversity and linkage disequilibrium, and access to high-density SNP typing and association analysis, detailed transcriptomic and proteomic studies, and the use of genome-wide marker- assisted selection to enhance genetic gain in commercial stocks.

Investigating protein isoforms via proteomics: a feasibility study

Alternative splicing (AS) and processing of pre-messenger RNAs explains the discrepancy between the number of genes and proteome complexity in multicellular eukaryotic organisms. However, relatively few alternative protein isoforms have been experimentally identified, particularly at the protein level. In this study, we assess the ability of proteomics to inform on differently spliced protein isoforms in human and four other model eukaryotes. The number of Ensembl-annotated genes for which proteomic data exists that informs on AS exceeds 33% of the alternately spliced genes in the human and worm genomes. Examining AS in chicken via proteomics for the first time, we find support for over 600 AS genes. However, although peptide identifications support only a small fraction of alternative protein isoforms that are annotated in Ensembl, many more variants are amenable to proteomic identification. There remains a sizeable gap between these existing identifications (10-52% of AS genes) and those that are theoretically feasible (90-99%). We also compare annotations between Swiss-Prot and Ensembl, recommending use of both to maximize coverage of AS. We propose that targeted proteomic experiments using selected reactions and standards are essential to uncover further alternative isoforms and discuss the issues surrounding these strategies.

Re-annotation is an essential step in systems biology modeling of functional genomics data

One motivation of systems biology research is to understand gene functions and interactions from functional genomics data such as that derived from microarrays. Up-to-date structural and functional annotations of genes are an essential foundation of systems biology modeling. We propose that the first essential step in any systems biology modeling of functional genomics data, especially for species with recently sequenced genomes, is gene structural and functional re-annotation. To demonstrate the impact of such re-annotation, we structurally and functionally re-annotated a microarray developed, and previously used, as a tool for disease research. We quantified the impact of this re-annotation on the array based on the total numbers of structural- and functional-annotations, the Gene Annotation Quality (GAQ) score, and canonical pathway coverage. We next quantified the impact of re-annotation on systems biology modeling using a previously published experiment that used this microarray. We show that re-annotation improves the quantity and quality of structural- and functional-annotations, allows a more comprehensive Gene Ontology based modeling, and improves pathway coverage for both the whole array and a differentially expressed mRNA subset. Our results also demonstrate that re-annotation can result in a different knowledge outcome derived from previous published research findings. We propose that, because of this, re-annotation should be considered to be an essential first step for deriving value from functional genomics data.

Representing ontogeny through ontology: a developmental biologist's guide to the gene ontology

Developmental biology, like many other areas of biology, has undergone a dramatic shift in the perspective from which developmental processes are viewed. Instead of focusing on the actions of a handful of genes or functional RNAs, we now consider the interactions of large functional gene networks and study how these complex systems orchestrate the unfolding of an organism, from gametes to adult. Developmental biologists are beginning to realize that understanding ontogeny on this scale requires the utilization of computational methods to capture, store and represent the knowledge we have about the underlying processes. Here we review the use of the Gene Ontology (GO) to study developmental biology. We describe the organization and structure of the GO and illustrate some of the ways we use it to capture the current understanding of many common developmental processes. We also discuss ways in which gene product annotations using the GO have been used to ask and answer developmental questions in a variety of model developmental systems. We provide suggestions as to how the GO might be used in more powerful ways to address questions about development. Our goal is to provide developmental biologists with enough background about the GO that they can begin to think about how they might use the ontology efficiently and in the most powerful ways possible.

The Chicken Gene Nomenclature Committee report

Comparative genomics is an essential component of the post-genomic era. The chicken genome is the first avian genome to be sequenced and it will serve as a model for other avian species. Moreover, due to its unique evolutionary niche, the chicken genome can be used to understand evolution of functional elements and gene regulation in mammalian species. However comparative biology both within avian species and within amniotes is hampered due to the difficulty of recognising functional orthologs. This problem is compounded as different databases and sequence repositories proliferate and the names they assign to functional elements proliferate along with them. Currently, genes can be published under more than one name and one name sometimes refers to unrelated genes. Standardized gene nomenclature is necessary to facilitate communication between scientists and genomic resources. Moreover, it is important that this nomenclature be based on existing nomenclature efforts where possible to truly facilitate studies between different species. We report here the formation of the Chicken Gene Nomenclature Committee (CGNC), an international and centralized effort to provide standardized nomenclature for chicken genes. The CGNC works in conjunction with public resources such as NCBI and Ensembl and in consultation with existing nomenclature committees for human and mouse. The CGNC will develop standardized nomenclature in consultation with the research community and relies on the support of the research community to ensure that the nomenclature facilitates comparative and genomic studies.

Integrative sequence and tissue expression profiling of chicken and mammalian aquaporins

BACKGROUND

Proteins that selectively transport water across the membranes of cells are recognized as important in the normal functioning of the body systems of vertebrates. There are 13 known mammalian aquaporins (AQP0 to AQP12), some of which have been shown to have unexpected cellular roles beyond transmembrane water transport. The availability of non-mammalian vertebrate animal models has the potential to provide insight into the emergence of diverse function in the aquaporins. The domesticated chicken (Gallus gallus) is the premier avian model for biological research; however, only a limited number of studies have compared chicken and mammalian aquaporins. The identification of aquaporins that share functional motifs or are expressed in the same tissues in human and chicken could allow the further functional analyses of homologous aquaporins in both species. We hypothesize that integrative analyses of protein sequences and body site expression of human, mouse, rat and chicken aquaporins has the potential to yield novel biological hypotheses about the unexpected cellular roles of aquaporins beyond transmembrane water transport.

RESULTS

A total of 76 aquaporin transcript models derived from 47 aquaporin genes were obtained for human, mouse, rat and chicken. Eleven body sites (brain, connective tissue, head, heart, liver, muscle, ovary, pancreas, small intestine, spleen and testis) were identified in which there is suggested expression of at least one mammalian and one chicken aquaporin. This study demonstrates that modern on-line analysis tools, a novel matrix integration technique, and the availability of the chicken genome for comparative genomics and expression analysis enables hypothesis generation in several important areas including: (i) alternative transcription and speciation effects on the conservation of functional motifs in vertebrate aquaporins; (ii) the emergence of basolateral targeting in mammalian species; (iii) the potential of the cysteine-rich AQP11 as a possible target in the pathophysiology of neurodegenerative disorders such as autism that involve Purkinje cells; and (iv) possible impairment of function of pancreas-expressed AQP12 during pancreatotropic necrosis in avian influenza virus infection.

CONCLUSION

The investigation of aquaporin function in chicken and mammalian species has the potential to accelerate the discovery of novel knowledge of aquaporins in both avian and mammalian species.

Overcoming function annotation errors in the Gram-positive pathogen Streptococcus suis by a proteomics-driven approach

Background

Annotation of protein-coding genes is a key step in sequencing projects. Protein functions are mainly assigned on the basis of the amino acid sequence alone by searching of homologous proteins. However, fully automated annotation processes often lead to wrong prediction of protein functions, and therefore time-intensive manual curation is often essential. Here we describe a fast and reliable way to correct function annotation in sequencing projects, focusing on surface proteomes. We use a proteomics approach, previously proven to be very powerful for identifying new vaccine candidates against Gram-positive pathogens. It consists of shaving the surface of intact cells with two proteases, the specific cleavage-site trypsin and the unspecific proteinase K, followed by LC/MS/MS analysis of the resulting peptides. The identified proteins are contrasted by computational analysis and their sequences are inspected to correct possible errors in function prediction.

Results

When applied to the zoonotic pathogen Streptococcus suis, of which two strains have been recently sequenced and annotated, we identified a set of surface proteins without cytoplasmic contamination: all the proteins identified had exporting or retention signals towards the outside and/or the cell surface, and viability of protease-treated cells was not affected. The combination of both experimental evidences and computational methods allowed us to determine that two of these proteins are putative extracellular new adhesins that had been previously attributed a wrong cytoplasmic function. One of them is a putative component of the pilus of this bacterium.

Conclusion

We illustrate the complementary nature of laboratory-based and computational methods to examine in concert the localization of a set of proteins in the cell, and demonstrate the utility of this proteomics-based strategy to experimentally correct function annotation errors in sequencing projects. This approach also contributes to provide strong experimental evidences that can be used to annotate those proteins for which a Gene Ontology (GO) term has not been assigned so far. Function annotation correction would then improve the identification of surface-associated proteins in bacterial pathogens, thus accelerating the discovery of new vaccines in infectious disease research.

The chicken embryo as a model for developmental endocrinology: development of the thyrotropic, corticotropic, and somatotropic axes

The ease of in vivo experimental manipulation is one of the main factors that have made the chicken embryo an important animal model in developmental research, including developmental endocrinology. This review focuses on the development of the thyrotropic, corticotropic and somatotropic axes in the chicken, emphasizing the central role of the pituitary gland in these endocrine systems. Functional maturation of the endocrine axes entails the cellular differentiation and acquisition of cell function and responsiveness of the different glands involved, as well as the establishment of top-down and bottom-up anatomical and functional communication between the control levels. Extensive cross-talk between the above-mentioned axes accounts for the marked endocrine changes observed during the last third of embryonic development. In a final paragraph we shortly discuss how genomic resources and new transgenesis techniques can increase the power of the chicken embryo model in developmental endocrinology research.