Transcriptomic responses of the olive fruit fly Bactrocera oleae and its symbiont Candidatus Erwinia dacicola to olive feeding

The olive fruit fly, Bactrocera oleae, is the most destructive pest of olive orchards worldwide. The monophagous larva has the unique capability of feeding on olive mesocarp, coping with high levels of phenolic compounds and utilizing non-hydrolyzed proteins present, particularly in the unripe, green olives. On the molecular level, the interaction between B. oleae and olives has not been investigated as yet. Nevertheless, it has been associated with the gut obligate symbiotic bacterium Candidatus Erwinia dacicola. Here, we used a B. oleae microarray to analyze the gene expression of larvae during their development in artificial diet, unripe (green) and ripe (black) olives. The expression profiles of Ca. E. dacicola were analyzed in parallel, using the Illumina platform. Several genes were found overexpressed in the olive fly larvae when feeding in green olives. Among these, a number of genes encoding detoxification and digestive enzymes, indicating a potential association with the ability of B. oleae to cope with green olives. In addition, a number of biological processes seem to be activated in Ca. E. dacicola during the development of larvae in olives, with the most notable being the activation of amino-acid metabolism

Unique transcriptomic landscapes identified in idiopathic spontaneous and infection related preterm births compared to normal term births.

Preterm birth (PTB) is leading contributor to infant death in the United States and globally, yet the underlying mechanistic causes are not well understood. Histopathological studies of preterm birth suggest advanced villous maturity may have a role in idiopathic spontaneous preterm birth (isPTB). To better understand pathological and molecular basis of isPTB, we compared placental villous transcriptomes from carefully phenotyped cohorts of PTB due to infection or isPTB between 28-36 weeks gestation and healthy term placentas. Transcriptomic analyses revealed a unique expression signature for isPTB distinct from the age-matched controls that were delivered prematurely due to infection. This signature included the upregulation of three IGF binding proteins (IGFBP1, IGFBP2, and IGFBP6), supporting a role for aberrant IGF signaling in isPTB. However, within the isPTB expression signature, we detected secondary signature of inflammatory markers including TNC, C3, CFH, and C1R, which have been associated with placental maturity. In contrast, the expression signature of the gestational age-matched infected samples included upregulation of proliferative genes along with cell cycling and mitosis pathways. Together, these data suggest an isPTB molecular signature of placental hypermaturity, likely contributing to the premature activation of inflammatory pathways associated with birth and providing a molecular basis for idiopathic spontaneous birth

Emerging model spedies driven by transciptomics

This work is focused on 'emerging model species', i.e. question-driven model species which have sufficient molecular resources to investigate a specific phenomenon in molecular biology, developmental biology, molecular ecology and evolution or related molecular fields. This thesis shows how transcriptomic data can be generated, analyzed, and used to investigate such phenomena of interest even in species lacking a reference genome. The initial ButterflyBase resource has proven to be useful to researchers of species without a reference genome but is limited to the Lepidoptera and supports only the older Sanger sequencing technologies. Thanks to Next Generation Sequencing, transcriptome sequencing is more cost effective but the bottleneck of transcriptomic projects is now the bioinformatic analysis and data mining/dissemination. Therefore, this work continues with presenting novel and innovative approaches which effectively overcome this bottleneck. The est2assembly software produces deeply annotated reference transcriptomes stored in the Chado database. The Drupal Bioinformatic Server Framework and genes4all provide species-neutral and an innovative approach in building standardized online databases and associated web services. All public insect mRNA data were analyzed with est2assembly and genes4all to produce the InsectaCentral. With InsectaCentral, a powerful resource is now available to assist molecular biology in any question-driven model insect species. The software presented here was developed according to specifications of the General Model Organism Database (GMOD) community. All software specifications are species-neutral and can be seamlessly deployed to assist any research community. Further through a case studies chapter, it becomes apparent that the transcriptomic approach is more cost-effective than a genomic approach and therefore sequence-driven evolutionary biology will benefit faster with this field

Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro

BACKGROUND: Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. RESULTS: A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. CONCLUSIONS: This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA

Statistical Algorithms and Bioinformatics Tools Development for Computational Analysis of High-throughput Transcriptomic Data

Next-Generation Sequencing technologies allow for a substantial increase in the amount of data available for various biological studies. In order to effectively and efficiently analyze this data, computational approaches combining mathematics, statistics, computer science, and biology are implemented. Even with the substantial efforts devoted to development of these approaches, numerous issues and pitfalls remain. One of these issues is mapping uncertainty, in which read alignment results are biased due to the inherent difficulties associated with accurately aligning RNA-Sequencing reads. GeneQC is an alignment quality control tool that provides insight into the severity of mapping uncertainty in each annotated gene from alignment results. GeneQC used feature extraction to identify three levels of information for each gene and implements elastic net regularization and mixture model fitting to provide insight in the severity of mapping uncertainty and the quality of read alignment. In combination with GeneQC, the Ambiguous Reads Mapping (ARM) algorithm works to re-align ambiguous reads through the integration of motif prediction from metabolic pathways to establish coregulatory gene modules for re-alignment using a negative binomial distribution-based probabilistic approach. These two tools work in tandem to address the issue of mapping uncertainty and provide more accurate read alignments, and thus more accurate expression estimates. Also presented in this dissertation are two approaches to interpreting the expression estimates. The first is IRIS-EDA, an integrated shiny web server that combines numerous analyses to investigate gene expression data generated from RNASequencing data. The second is ViDGER, an R/Bioconductor package that quickly generates high-quality visualizations of differential gene expression results to assist users in comprehensive interpretations of their differential gene expression results, which is a non-trivial task. These four presented tools cover a variety of aspects of modern RNASeq analyses and aim to address bottlenecks related to algorithmic and computational issues, as well as more efficient and effective implementation methods

Shared genes related to aggression, rather than chemical communication, are associated with reproductive dominance in paper wasps (Polistes metricus)

BackgroundIn social groups, dominant individuals may socially inhibit reproduction of subordinates using aggressive interactions or, in the case of highly eusocial insects, pheromonal communication. It has been hypothesized these two modes of reproductive inhibition utilize conserved pathways. Here, we use a comparative framework to investigate the chemical and genomic underpinnings of reproductive dominance in the primitively eusocial wasp Polistes metricus. Our goals were to first characterize transcriptomic and chemical correlates of reproductive dominance and second, to test whether dominance-associated mechanisms in paper wasps overlapped with aggression or pheromone-related gene expression patterns in other species. To explore whether conserved molecular pathways relate to dominance, we compared wasp transcriptomic data to previous studies of gene expression associated with pheromonal communication and queen-worker differences in honey bees, and aggressive behavior in bees, Drosophila, and mice. ResultsBy examining dominant and subordinate females from queen and worker castes in early and late season colonies, we found that cuticular hydrocarbon profiles and genome-wide patterns of brain gene expression were primarily associated with season/social environment rather than dominance status. In contrast, gene expression patterns in the ovaries were associated primarily with caste and ovary activation. Comparative analyses suggest genes identified as differentially expressed in wasp brains are not related to queen pheromonal communication or caste in bees, but were significantly more likely to be associated with aggression in other insects (bees, flies), and even a mammal (mice). ConclusionsThis study provides the first comprehensive chemical and molecular analysis of reproductive dominance in paper wasps. We found little evidence for a chemical basis for reproductive dominance in P. metricus, and our transcriptomic analyses suggest that different pathways regulate dominance in paper wasps and pheromone response in bees. Furthermore, there was a substantial impact of season/social environment on gene expression patterns, indicating the important role of external cues in shaping the molecular processes regulating behavior. Interestingly, genes associated with dominance in wasps were also associated with aggressive behavior in bees, solitary insects and mammals. Thus, genes involved in social regulation of reproduction in Polistes may have conserved functions associated with aggression in insects and other taxa

Interactome comparison of human embryonic stem cell lines with the inner cell mass and trophectoderm

Networks of interacting co-regulated genes distinguish the inner cell mass (ICM) from the differentiated trophectoderm (TE) in the preimplantation blastocyst, in a species specific manner. In mouse the ground state pluripotency of the ICM appears to be maintained in murine embryonic stem cells (ESCs) derived from the ICM. This is not the case for human ESCs. In order to gain insight into this phenomenon, we have used quantitative network analysis to identify how similar human (h)ESCs are to the human ICM. Using the hESC lines MAN1, HUES3 and HUES7 we have shown that all have only a limited overlap with ICM specific gene expression, but that this overlap is enriched for network properties that correspond to key aspects of function including transcription factor activity and the hierarchy of network modules. These analyses provide an important framework which highlights the developmental origins of hESCs

NODAL/TGFβ signalling mediates the self-sustained stemness induced by PIK3CAH1047R homozygosity in pluripotent stem cells

Activating PIK3CA mutations are known “drivers” of human cancer and developmental overgrowth syndromes. We recently demonstrated that the "hotspot" PIK3CAH1047R variant exerts unexpected allele dose-dependent effects on stemness in human pluripotent stem cells (hPSCs). In the present study, we combine high-depth transcriptomics, total proteomics and reverse-phase protein arrays to reveal potentially disease-related alterations in heterozygous cells, and to assess the contribution of activated TGFβ signalling to the stemness phenotype of homozygous PIK3CAH1047R cells. We demonstrate signalling rewiring as a function of oncogenic PI3K signalling strength, and provide experimental evidence that self-sustained stemness is causally related to enhanced autocrine NODAL/TGFβ signalling. A significant transcriptomic signature of TGFβ pathway activation in heterozygous PIK3CAH1047R was observed but was modest and was not associated with the stemness phenotype seen in homozygous mutants. Notably, the stemness gene expression in homozygous PIK3CAH1047R iPSCs was reversed by pharmacological inhibition of NODAL/TGFβ signalling, but not by pharmacological PI3Kα pathway inhibition. Altogether, this provides the first in-depth analysis of PI3K signalling in human pluripotent stem cells and directly links strong PI3K activation to developmental NODAL/TGFβ signalling. This work illustrates the importance of allele dosage and expression when artificial systems are used to model human genetic disease caused by activating PIK3CA mutations