Computational identification of strain-, species- and genus-specific proteins

BACKGROUND: The identification of unique proteins at different taxonomic levels has both scientific and practical value. Strain-, species- and genus-specific proteins can provide insight into the criteria that define an organism and its relationship with close relatives. Such proteins can also serve as taxon-specific diagnostic targets. DESCRIPTION: A pipeline using a combination of computational and manual analyses of BLAST results was developed to identify strain-, species-, and genus-specific proteins and to catalog the closest sequenced relative for each protein in a proteome. Proteins encoded by a given strain are preliminarily considered to be unique if BLAST, using a comprehensive protein database, fails to retrieve (with an e-value better than 0.001) any protein not encoded by the query strain, species or genus (for strain-, species- and genus-specific proteins respectively), or if BLAST, using the best hit as the query (reverse BLAST), does not retrieve the initial query protein. Results are manually inspected for homology if the initial query is retrieved in the reverse BLAST but is not the best hit. Sequences unlikely to retrieve homologs using the default BLOSUM62 matrix (usually short sequences) are re-tested using the PAM30 matrix, thereby increasing the number of retrieved homologs and increasing the stringency of the search for unique proteins. The above protocol was used to examine several food- and water-borne pathogens. We find that the reverse BLAST step filters out about 22% of proteins with homologs that would otherwise be considered unique at the genus and species levels. Analysis of the annotations of unique proteins reveals that many are remnants of prophage proteins, or may be involved in virulence. The data generated from this study can be accessed and further evaluated from the CUPID (Core and Unique Protein Identification) system web site (updated semi-annually) at . CONCLUSION: CUPID provides a set of proteins specific to a genus, species or a strain, and identifies the most closely related organism

Identification of Anchor Genes during Kidney Development Defines Ontological Relationships, Molecular Subcompartments and Regulatory Pathways

The development of the mammalian kidney is well conserved from mouse to man. Despite considerable temporal and spatial data on gene expression in mammalian kidney development, primarily in rodent species, there is a paucity of genes whose expression is absolutely specific to a given anatomical compartment and/or developmental stage, defined here as ‘anchor’ genes. We previously generated an atlas of gene expression in the developing mouse kidney using microarray analysis of anatomical compartments collected via laser capture microdissection. Here, this data is further analysed to identify anchor genes via stringent bioinformatic filtering followed by high resolution section in situ hybridisation performed on 200 transcripts selected as specific to one of 11 anatomical compartments within the midgestation mouse kidney. A total of 37 anchor genes were identified across 6 compartments with the early proximal tubule being the compartment richest in anchor genes. Analysis of minimal and evolutionarily conserved promoter regions of this set of 25 anchor genes identified enrichment of transcription factor binding sites for Hnf4a and Hnf1b, RbpJ (Notch signalling), PPARγ:RxRA and COUP-TF family transcription factors. This was reinforced by GO analyses which also identified these anchor genes as targets in processes including epithelial proliferation and proximal tubular function. As well as defining anchor genes, this large scale validation of gene expression identified a further 92 compartment-enriched genes able to subcompartmentalise key processes during murine renal organogenesis spatially or ontologically. This included a cohort of 13 ureteric epithelial genes revealing previously unappreciated compartmentalisation of the collecting duct system and a series of early tubule genes suggesting that segmentation into proximal tubule, loop of Henle and distal tubule does not occur until the onset of glomerular vascularisation. Overall, this study serves to illuminate previously ill-defined stages of patterning and will enable further refinement of the lineage relationships within mammalian kidney development

Refining transcriptional programs in kidney development by integration of deep RNA-sequencing and array-based spatial profiling

<p>Abstract</p> <p>Background</p> <p>The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic <it>in situ </it>screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on "gene-centric" models.</p> <p>Results</p> <p>To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section <it>in situ </it>hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs.</p> <p>Conclusion</p> <p>The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed "transcript-centric" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.</p

A Transcriptome Atlas of the Developing Mouse Urogenital System

Organ development is a complex process which involves precise orchestration of multiple cell types across time and space. Understanding of urogenital organ development has benefited from the use of mouse models, as it is ideal for laboratory-based genetic manipulations. Recent advances in highthroughput strategies and genomic technologies have enabled global surveys of the transcriptome, and improved characterization of dynamic gene expression states. Such resources can be used to compile gene expression atlases to obtain information of mRNA levels and localization as a basis to understand cellular fate-decision pathways and networks during development. This thesis describes the temporal and spatial transcriptome atlas of the developing mouse urogenital system, with emphasis on the renal system, as a resource to study the cellular and molecular blueprint required for organogenesis. The analyses that encompass this atlas relied heavily upon resources from the GenitoUrinary Development Molecular Anatomy Project (GUDMAP) from which this thesis stems from. The underlying foundation of this atlas provides the basis to understand what is encoded in the transcriptome during organ development. What are the genes required for dynamic regulation of organ development? What cell-types do they represent? How is their expression controlled? And how do these genes and their transcriptional structure encode the instructions to build complex, multi-cellular organs. The first results chapter describes the integration of microarray profiling to identify genome-wide temporal and spatial markers of ovary and testis during gonad development accompanied by in situ hybridization to validate expression and capture the domain-specific expression patterns exhibited by these genes. The second chapter presents a high-resolution investigation of 11 embryonic kidney subcompartment-specific genes which revealed additional molecularly-defined compartments specific cell types within complex heterogeneous compartments. These ‘anchor genes’ formed the basis to model gene expression networks during tissue ligand-receptor interactions and transcription factors regulating tissue specific expression. The final chapter sets the scene for the next phase of analyses towards the survey of transcriptional complexity driving temporal and spatial regulation of gene expression programs in the embryonic kidney using RNA-sequencing. This study provided the basis to update current gene models of developmental programs to include transcriptional dynamics regulating these processes. Together, the outcomes of this thesis provide a valuable resource of genetic markers that can be formally used for cell lineage tracing to map the fate of each cell type in the developmental history of the genitourinary system and facilitate functional studies through transgenic tools. The transcriptome atlas forms a comprehensive dynamic survey of the developing mouse urogenital system, and represents an important resource for functional studies into organ development which will ultimately lead to strategies for tissue regeneration to treat organ damage and disease

The epigenome in pluripotency and differentiation.

The ability to culture pluripotent stem cells and direct their differentiation into specific cell types in vitro provides a valuable experimental system for modeling pluripotency, development and cellular differentiation. High-throughput profiling of the transcriptomes and epigenomes of pluripotent stem cells and their differentiated derivatives has led to identification of patterns characteristic of each cell type, discovery of new regulatory features in the epigenome and early insights into the complexity of dynamic interactions among regulatory elements. This work has also revealed potential limitations of the use of pluripotent stem cells as in vitro models of developmental events, due to epigenetic variability among different pluripotent stem cell lines and epigenetic instability during derivation and culture, particularly at imprinted and X-inactivated loci. This review focuses on the two most well-studied epigenetic mechanisms, DNA methylation and histone modifications, within the context of pluripotency and differentiation

Identification of novel markers of mouse fetal ovary development

In contrast to the developing testis, molecular pathways driving fetal ovarian development have been difficult to characterise. To date no single master regulator of ovarian development has been identified that would be considered the female equivalent of Sry. Using a genomic approach we identified a number of novel protein-coding as well as non-coding genes that were detectable at higher levels in the ovary compared to testis during early mouse gonad development. We were able to cluster these ovarian genes into different temporal expression categories. Of note, Lrrc34 and AK015184 were detected in XX but not XY germ cells before the onset of sex-specific germ cell differentiation marked by entry into meiosis in an ovary and mitotic arrest in a testis. We also defined distinct spatial expression domains of somatic cell genes in the developing ovary. Our data expands the set of markers of early mouse ovary differentiation and identifies a classification of early ovarian genes, thus providing additional avenues with which to dissect this process

Expression analysis of somatic cell genes.

<p>ISH with sagittal section of XX and XY mouse embryos from 11.5 to 13.5 dpc, 5 weeks (wk) postnatal mouse ovaries and testes showed that <i>Slitrk1</i> (<b>A</b>) and <i>oncRNA3</i> (<b>B</b>) are expressed in ovarian somatic cells at 11.5 and 12.5 dpc. <i>Slitrk1</i> is also expressed in the granulosa cells of the mature ovary. Scale bars, 100 µm.</p