RNA-SEQUENCING APPLICATIONS: GENE EXPRESSION QUANTIFICATION AND METHYLATOR PHENOTYPE IDENTIFICATION

My dissertation focuses on two aspects of RNA sequencing technology. The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating datasets of mRNA expression level and DNA methylation status. Section 1: The cost of DNA sequencing has reduced dramatically in the past decade. Consequently, genomic research increasingly depends on sequencing technology. However it remains elusive how the sequencing capacity influences the accuracy of mRNA expression measurement. We observe that accuracy improves along with the increasing sequencing depth. To model the overdispersion, we use the beta-binomial distribution with a new parameter indicating the dependency between overdispersion and sequencing depth. Our modified beta-binomial model performs better than the binomial or the pure beta-binomial model with a lower false discovery rate. Section 2: Although a number of methods have been proposed in order to accurately analyze differential RNA expression on the gene level, modeling on the base pair level is required. Here, we find that the overdispersion rate decreases as the sequencing depth increases on the base pair level. Also, we propose four models and compare them with each other. As expected, our beta binomial model with a dynamic overdispersion rate is shown to be superior. Section 3: We investigate biases in RNA-seq by exploring the measurement of the external control, spike-in RNA. This study is based on two datasets with spike-in controls obtained from a recent study. We observe an undiscovered bias in the measurement of the spike-in transcripts that arises from the influence of the sample transcripts in RNA-seq. Also, we find that this influence is related to the local sequence of the random hexamer that is used in priming. We suggest a model of the inequality between samples and to correct this type of bias. Section 4: The expression of a gene can be turned off when its promoter is highly methylated. Several studies have reported that a clear threshold effect exists in gene silencing that is mediated by DNA methylation. It is reasonable to assume the thresholds are specific for each gene. It is also intriguing to investigate genes that are largely controlled by DNA methylation. These genes are called “L-shaped” genes. We develop a method to determine the DNA methylation threshold and identify a new CIMP of BRCA. In conclusion, we provide a detailed understanding of the relationship between the overdispersion rate and sequencing depth. And we reveal a new bias in RNA-seq and provide a detailed understanding of the relationship between this new bias and the local sequence. Also we develop a powerful method to dichotomize methylation status and consequently we identify a new CIMP of breast cancer with a distinct classification of molecular characteristics and clinical features.

Genome-wide association analysis and differential expression analysis of resistance to Sclerotinia stem rot in Brassica napus

Brassica napus is one of the most important oil crops in the world, and stem rot caused by the fungus Sclerotinia sclerotiorum results in major losses in yield and quality. To elucidate resistance genes and pathogenesis-related genes, genome-wide association analysis of 347 accessions was performed using the Illumina 60K Brassica SNP (single nucleotide polymorphism) array. In addition, the detached stem inoculation assay was used to select five highly resistant (R) and susceptible (S) B. napus lines, 48 h postinoculation with S. sclerotiorum for transcriptome sequencing. We identified 17 significant associations for stem resistance on chromosomes A8 and C6, five of which were on A8 and 12 on C6. The SNPs identified on A8 were located in a 409-kb haplotype block, and those on C6 were consistent with previous QTL mapping efforts. Transcriptome analysis suggested that S. sclerotiorum infection activates the immune system, sulphur metabolism, especially glutathione (GSH) and glucosinolates in both R and S genotypes. Genes found to be specific to the R genotype related to the jasmonic acid pathway, lignin biosynthesis, defence response, signal transduction and encoding transcription factors. Twenty-four genes were identified in both the SNP-trait association and transcriptome sequencing analyses, including a tau class glutathione S-transferase (GSTU) gene cluster. This study provides useful insight into the molecular mechanisms underlying the plant's response to S. sclerotiorum.

Differential expression analysis for sequence count data via mixtures of negative binomials

The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in multiple sclerosis

Background Several lines of evidence suggests that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but a complete mapping the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors which may be involved in one subtype may not be in others. We investigated the possibility that this network could be mapped using microarray technologies and modern bioinformatics methods on a dataset from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls, Methodology/Principal Findings We have used two different analytical methodologies: a differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that seem to be statistically overrepresented in genes which are either differentially expressed (or differentially co-expressed) in cases and controls (e.g. V$KROX_Q6, p-value < 3.31E-6; V$CREBP1_Q2, p-value < 9.93E-6, V$YY1_02, p-value < 1.65E-5). Conclusions/significance: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. Analysing the published literature we have found that these transcription factors are involved in the early T-lymphocyte specification and commitment as well as in oligodendrocytes dedifferentiation and development. The most significant transcription factors motifs were for the Early Growth response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families.

Differential expression and characterization analysis of a new gene with WD domains in fish oogenesis

A new gene with WD domains is cloned and characterized according to its differential transcription and expression between previtellogenic oocytes (phase I oocytes) and fully-grown oocytes (phase V oocytes) from natural gynogenetic silver crucian carp (Carassius auratus gibelio) by using the combinative methods of suppressive subtraction hybridization, SMART cDNA synthesis and RACE-PCR. The full-length cDNA is 1870 bp. Its 5 ' untranslated region is 210 bp, followed by an open reading frame of 990 bp, which has the typical vertebrate initiator codon of ANNATG. The open reading frame encodes a protein with 329 amino acids. It has 670 bp of 3 ' untranslated region and an AATAAA polyadenylation signal. Because it has 92% homology to STRAP (serine-threonine kinase receptor-associated protein), a recently reported gene, we named it FSTRAP (fish STRAP). Virtual Northern blotting indicated that the FSTRAP was transcribed in fully-grown oocytes (phase V oocytes), but not in previtellogenic oocytes (phase I oocytes). RT-PCR analysis showed that FSTRAP was transcribed in brain, heart, kidney, muscle, ovary, spleen and testis, but not in liver. And its mRNA could be detected in the oocytes from phase II to phase V. Western blotting also showed that FSTRAP protein could be detected in brain, heart, kidney, muscle, ovary, spleen and testis except liver. Results of Western blotting on various oocytes were also similar to the RT-PCR data. FSTRAP protein was not expressed in the previtellogenic oocytes. Its expression initiated from phase II oocytes after vitellogenesis, and was consistent with the mRNA transcription.

Differential gene expression analysis of iodide-treated rat thyroid follicular cell line PCCl3

The inhibitory effect of supraphysiological iodide concentrations on thyroid hormone synthesis (Wolff - Chaikoff effect) and on thyrocyte proliferation is largely known as iodine autoregulation. However, the molecular mechanisms by which iodide modulates thyroid function remain unclear. In this paper, we analyze the transcriptome profile of the rat follicular cell lineage PCCl3 under untreated and treated conditions with 10 (- 3) M sodium iodide (NaI). Serial analysis of gene expression (SAGE) revealed 84 transcripts differentially expressed in response to iodide (p <= 0.001). We also showed that iodide excess inhibits the expression of essential genes for thyroid differentiation: Tshr, Nis, Tg, and Tpo. Relative expression of 14 of 20 transcripts selected by SAGE was confirmed by real-time PCR. Considering the key role of iodide organification in thyroid physiology, we also observed that both the oxidized form of iodide and iodide per se are responsible for gene expression modulation in response to iodide excess. (c) 2008 Elsevier Inc. All rights reserved.

Differential gene expression analysis of Paracoccidioides brasiliensis during keratinocyte infection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Exequibility of differential gene expression analysis by DDRT-PCR in murine bone marrow cells

Model of study: Experimental study. Introduction: Recently, stem cell research has generated great interest due to its applicability in regenerative medicine. Bone marrow is considered the most important source of adult stem cells and the establishment of new methods towards gene expression analysis regarding stem cells has become necessary. Thus Differential Display Reverse Transcription Polymerase Chain Reaction (DDRT-PCR) may be an accessible tool to investigate small differences in the gene expression of different stem cells in distinct situations. Aim: In the present study, we investigated the exequibility of DDRT-PCR to identify differences in global gene expression of mice bone marrow cells under two conditions. Methods: First, bone marrow cells were isolated fresh and a part was cultivated during one week without medium replacement. Afterwards, both bone marrow cells (fresh and cultivated) were submitted to gene expression analyses by DDRT-PCR. Results: Initially, it was possible to observe in one week-cultured bone marrow cells, changes in morphology (oval cells to fibroblastic-like cells) and protein profile, which was seen through differences in band distribution in SDS-Page gels. Finally through gene expression analysis, we detected three bands (1300, 1000 and 225 bp) exclusively expressed in the fresh bone marrow group and two bands (400 and 300 bp) expressed specifically in the cultivated bone marrow cell group. Conclusions: In summary, the DDRT-PCR method was proved efficient towards the identification of small differences in gene expression of bone marrow cells in two defined conditions. Thus, we expect that DDRT-PCR can be fast and efficiently designed to analyze differential gene expression in several stem cell types under distinct conditions.

Primaquine-induced differential gene expression analysis in mice liver using DNA microarrays

Primaquine (PQ). a clinically important derivative of 8-aminoquinoline used against the hepatic stages (hypnozoites) of Plasmodium vivax and Plasmodium ova Ie. was studied to evaluate and compare between mRNA expression. and biochemical and histological parameters of hepatic stress in adult Swiss mice (Mus musculus). Following single oral dose of PQ (40 mglkg. bw). alanine aminotransferase (ALT) and aspartate aminotransferase (AST) along with hematoxylin and eosin stained liver sections did not show any signs of hepatic stress at 6. 12 and 24 h except for ALT activity at 6 h. However. analysis at RNA transcript level revealed consistent and significant deregulation (p<0.01 and twofold) of 16 probes corresponding to important cellular processes such as protein transportation. transcription regulation. intracellular signaling. protein synthesis, hematopoiesis, cell adhesion and cell proliferation. Pathway analysis identified large number of affected genes corresponding to 40 Gene Ontology terms having a z score greaibr than 2. These results indicate that PQ at high doses may affect gene expression in liver and may produce undesirable outcomes if consumed for longer durations.

Restriction fragment length polymorphism-coupled domain-directed differential display: a highly efficient technique for expression analysis of multigene families.

In this paper, a reverse-transcriptase PCR-based protocol suitable for efficient expression analysis of multigene families is presented. The method combines restriction fragment length polymorphism (RFLP) technology with a gene family-specific version of mRNA differential display and hence is called "RFLP-coupled domain-directed differential display. "With this method, expression of all members of a multigene family at many different developmental stages, in diverse tissues and even in different organisms, can be displayed on one gel. Moreover, bands of interest, representing gene family members, are directly accessible to sequence analysis, without the need for subcloning. The method thus enables a detailed, high-resolution expression analysis of known gene family members as well as the identification and characterization of new ones. Here the technique was used to analyze differential expression of MADS-box genes in male and female inflorescences of maize (Zea mays ssp. mays). Six different MADS-box genes could be identified, being either specifically expressed in the female sex or preferentially expressed in male or female inflorescences, respectively. Other possible applications of the method are discussed.

Genome-wide identification and expression analysis of the NF-Y family of transcription factors in Triticum aestivum

Nuclear Factor Y (NF-Y) is a trimeric complex that binds to the CCAAT box, a ubiquitous eukaryotic promoter element. The three subunits NF-YA, NF-YB and NF-YC are represented by single genes in yeast and mammals. However, in model plant species (Arabidopsis and rice) multiple genes encode each subunit providing the impetus for the investigation of the NF-Y transcription factor family in wheat. A total of 37 NF-Y and Dr1 genes (10 NF-YA, 11 NF-YB, 14 NF-YC and 2 Dr1) in Triticum aestivum were identified in the global DNA databases by computational analysis in this study. Each of the wheat NF-Y subunit families could be further divided into 4-5 clades based on their conserved core region sequences. Several conserved motifs outside of the NF-Y core regions were also identified by comparison of NF-Y members from wheat, rice and Arabidopsis. Quantitative RT-PCR analysis revealed that some of the wheat NF-Y genes were expressed ubiquitously, while others were expressed in an organ-specific manner. In particular, each TaNF-Y subunit family had members that were expressed predominantly in the endosperm. The expression of nine NF-Y and two Dr1 genes in wheat leaves appeared to be responsive to drought stress. Three of these genes were up-regulated under drought conditions, indicating that these members of the NF-Y and Dr1 families are potentially involved in plant drought adaptation. The combined expression and phylogenetic analyses revealed that members within the same phylogenetic clade generally shared a similar expression profile. Organ-specific expression and differential response to drought indicate a plant-specific biological role for various members of this transcription factor family.

Differential expression of chemokine and matrix re-modelling genes is associated with contrasting schistosome-induced hepatopathology in murine models

The pathological outcomes of schistosomiasis are largely dependent on the molecular and cellular mechanisms of the host immune response. In this study, we investigated the contribution of variations in host gene expression to the contrasting hepatic pathology observed between two inbred mouse strains following Schistosoma japonicum infection. Whole genome microarray analysis was employed in conjunction with histological and immunohistochemical analysis to define and compare the hepatic gene expression profiles and cellular composition associated with the hepatopathology observed in S. japonicum-infected BALB/c and CBA mice. We show that the transcriptional profiles differ significantly between the two mouse strains with high statistical confidence. We identified specific genes correlating with the more severe pathology associated with CBA mice, as well as genes which may confer the milder degree of pathology associated with BALB/c mice. In BALB/c mice, neutrophil genes exhibited striking increases in expression, which coincided with the significantly greater accumulation of neutrophils at granulomatous regions seen in histological sections of hepatic tissue. In contrast, up-regulated expression of the eosinophil chemokine CCL24 in CBA mice paralleled the cellular influx of eosinophils to the hepatic granulomas. Additionally, there was greater down-regulation of genes involved in metabolic processes in CBA mice, reflecting the more pronounced hepatic damage in these mice. Profibrotic genes showed similar levels of expression in both mouse strains, as did genes associated with Th1 and Th2 responses. However, imbalances in expression of matrix metalloproteinases (e.g. MMP12, MMP13) and tissue inhibitors of metalloproteinases (TIMP1) may contribute to the contrasting pathology observed in the two strains. Overall, these results provide a more complete picture of the molecular and cellular mechanisms which govern the pathological outcome of hepatic schistosomiasis. This improved understanding of the immunopathogenesis in the murine model schistosomiasis provides the basis for a better appreciation of the complexities associated with chronic human schistosomiasis.

Gene expression analysis of diagnostic biopsies predicts pathological response to neoadjuvant chemoradiotherapy of esophageal cancer

OBJECTIVE: This study explored gene expression differences in predicting response to chemoradiotherapy in esophageal cancer. PURPOSE:: A major pathological response to neoadjuvant chemoradiation is observed in about 40% of esophageal cancer patients and is associated with favorable outcomes. However, patients with tumors of similar histology, differentiation, and stage can have vastly different responses to the same neoadjuvant therapy. This dichotomy may be due to differences in the molecular genetic environment of the tumor cells. BACKGROUND DATA: Diagnostic biopsies were obtained from a training cohort of esophageal cancer patients (13), and extracted RNA was hybridized to genome expression microarrays. The resulting gene expression data was verified by qRT-PCR. In a larger, independent validation cohort (27), we examined differential gene expression by qRT-PCR. The ability of differentially-regulated genes to predict response to therapy was assessed in a multivariate leave-one-out cross-validation model. RESULTS: Although 411 genes were differentially expressed between normal and tumor tissue, only 103 genes were altered between responder and non-responder tumor; and 67 genes differentially expressed >2-fold. These included genes previously reported in esophageal cancer and a number of novel genes. In the validation cohort, 8 of 12 selected genes were significantly different between the response groups. In the predictive model, 5 of 8 genes could predict response to therapy with 95% accuracy in a subset (74%) of patients. CONCLUSIONS: This study has identified a gene microarray pattern and a set of genes associated with response to neoadjuvant chemoradiation in esophageal cancer. The potential of these genes as biomarkers of response to treatment warrants further investigation. Copyright © 2009 by Lippincott Williams & Wilkins.