O cancro cítrico é uma doença que afeta diversas espécies de Citrus, cujo agente causal é Xanthomonas axonopodis pv citri (XAC). O genoma desta fitobactéria consiste de um cromossomo de ~5 Mpb e dois plasmídeos, que juntos codificam 4313 CDS (seqüências codificadoras), das quais 2710 apresentam similaridade com proteínas conhecidas. Neste trabalho realizamos uma análise comparativa detalhada do genoma de XAC com genomas de três fitopatógenos, Xanthomonas campestris campestris, Xylella fastidiosa 9a5c e Xylella fastidiosa temecula. Com esta análise identificamos genes espécie e gênero-específicos, potencialmente relevantes para adaptação aos seus respectivos nichos ou hospedeiros, além de ilhas de inserção e deleção genômica putativas. Também identificamos vias metabólicas relacionadas com osmoproteção/osmorregulação e com degradação de compostos aromáticos em XAC, que possivelmente são determinantes na eficácia de sua interação com o hospedeiro. Analisamos o nível de expressão de 9 CDS após crescimento de XAC em diferentes concentrações de glicose e verificamos que este açúcar modula positivamente a expressão de CDS relacionadas à síntese de goma e ao sistema de osmoproteção. Além disso, descrevemos a construção de microarranjos de DNA representando 2760 CDS de XAC, constituindo-se uma nova ferramenta para estudos de genômica comparativa e expressão gênica deste fitopatógeno. / Xanthomonas axonopodis pv citri (XAC) is the bacterial pathogen that causes citrus canker disease in several species of Citrus plants. XAC genome consists of a main cromosome of ~5 Mpb and two plasmids that together encode 4313 CDS (coding sequences). Approximately 63% of the CDS have assigned biological functions. In this work, we present a detailed genomic comparison between the genomes of XAC and of three other phytopathogens, X. campestris campestris, Xylella fastidiosa 9a5c and X. fastidiosa Temecula. Based on this analysis, we identified species and genus-specific genes that might be relevant for adaptation to their niches and hosts. We mapped putative insertion/deletion regions in the XAC genome possibly related to gene gains and losses during the divergence of the four bacterial lineages. We have identified the metabolic pathways related to osmoprotection/osmoregulation and aromatic compound degradation important for XAC efficient host colonization and interaction. Expression levels of 9 CDS were analyzed after XAC growth under different glucose concentrations revealing that this sugar upregulates the expression of CDS related to gum synthesis and to osmoregulation. In addition, we describe here the construction of a DNA microarray representing 2760 CDS of XAC as a new tool for comparative genomic and gene expression studies in this phytopathogen.

The efforts addressed in this thesis refer to assaying the extent of local features in 2D-images for the purpose of recognition and classification. It is based on comparing a test-image against a template in binary format. It is a bioinformatics-inspired approach pursued and presented as deliverables of this thesis as summarized below: 1. By applying the so-called 'Smith-Waterman (SW) local alignment' and 'Needleman-Wunsch (NW) global alignment' approaches of bioinformatics, a test 2D-image in binary format is compared against a reference image so as to recognize the differential features that reside locally in the images being compared 2. SW and NW algorithms based binary comparison involves conversion of one-dimensional sequence alignment procedure (indicated traditionally for molecular sequence comparison adopted in bioinformatics) to 2D-image matrix 3. Relevant algorithms specific to computations are implemented as MatLabTM codes 4. Test-images considered are: Real-world bio-/medical-images, synthetic images, microarrays, biometric finger prints (thumb-impressions) and handwritten signatures. Based on the results, conclusions are enumerated and inferences are made with directions for future studies. / by Deepti Pappusetty. / Thesis (M.S.C.S.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2011. Mode of access: World Wide Web.

目前廣泛應用于胎兒醫學的唐氏綜合症篩查法，即結合早孕期胎兒頸項透明層的超聲檢查，及母體血清生化指標的綜合篩查法。頸項透明層是指在早孕期利用超聲檢測到的胎兒頸后的皮下積水，其作為預測胎兒異常的一項重要“軟指標，其臨床意義，尤其是與胎兒染色體異常及器官結構異常之間的關係，逐漸得到深入的認識，但其形成機制尚未明確。現在已知有一百餘種畸形及遺傳綜合征與胎兒頸項透明層增厚相關，但其染色體異常譜系，尤其是亞顯微的染色體異常仍有待明確。大部分頸項透明層增厚但核型正常的胎兒預後良好，但約3-10%的這部分胎兒會伴有畸形或出生后的神經智力發育缺陷。而傳統核型分析無法檢測到亞顯微的染色體異常，從而無法判斷這部分核型正常卻伴有缺陷的胎兒是否因為這類染色體異常而致病。 / 微陣列比較基因組雜交芯片作為檢測兒童發育遲緩者及器官結構異常原因的重要手段已廣泛應用于臨床。在染色體核型正常的胎兒中，若伴有器官結構異常的胎兒，5-12%被檢出與該畸形相關的微缺失及微重複；若僅伴有孕婦高齡或唐氏篩查高危，則微缺失及微重複檢出率約1%。 / 該課題旨在研究頸項透明層增厚但核型正常的胎兒中，染色體拷貝數變異發生的頻率及頻譜；評估微陣列比較基因組雜交芯片在協助臨床判斷胎兒預後中的作用。因此，我們開展該多中心隊列研究，通過納入449例頸項透明層厚度≧3.5 mm但正常核型胎兒的，檢測其染色體拷貝數變異，監測并記錄其圍產、產後及新生兒期情況。微陣列比較基因組雜交芯片總共檢出2.8%的異常拷貝數變異，其大小範圍為0.1 kb至18Mb。在伴有器官結構異常的胎兒組中，異常拷貝數變異檢出率達7.8%。對於頸項透明層厚度≧4.0 mm的胎兒，異常拷貝數變異檢出率可達7.3%。 / 對於頸項透明層增厚的胎兒，致病拷貝數變異暫未發現特定的頻譜。但，該研究中發現重複的致病拷貝數變異，如22號染色體長臂1區1帶的微重複或微缺失，2號染色體長臂2區2帶的微缺失。未在3號、7號、12號、13號、18號、20號、21號或Y染色體上發現與胎兒頸項透明層增厚相關的致病拷貝數變異。 / 頸項透明層增厚的胎兒79.3%預後良好；若經微陣列比較基因組雜交芯片未檢出致病拷貝數變異，則81.2%預後良好。如果僅頸項透明層增厚不伴有結構異常的胎兒，經微陣列比較基因組雜交芯片未檢出致病拷貝數變異，則93.5%預後良好。 / 綜上所述，微陣列比較基因組雜交芯片顯著提高了致病拷貝數變異的檢出率。可考慮將微陣列比較基因組雜交芯片作為頸項透明層厚度≧4.0 mm的胎兒染色體異常檢查的首要方法。對於僅頸項透明層增厚不伴有結構異常的胎兒，且經微陣列比較基因組雜交芯片未檢出致病拷貝數變異，絶大部分預後良好。對於頸項透明層增厚的胎兒，致病拷貝數變異暫未發現特定的頻譜，但發現重複出現的致病拷貝數變異。通過初步的基因本體分析及基因通路分析，神經嵴細胞的分化遷徙功能異常可作為今後研究頸項透明層增厚的病理生理機制的方向。 / Measurement of nuchal translucency (NT) has been recognized as a sensitive marker for fetal chromosomal disorders for more than a decade, and is presently used as a routine first-trimester screening test. Although over 100 abnormalities and genetic syndromes have been reported to be associated with increased NT, these associations have not been fully explored and the relevant spectrum of associated submicroscopic chromosomal abnormalities has not been sufficiently investigated. The majority of euploid fetuses with increased NT have a good outcome, but around 3-10% of fetuses present with structural or neurodevelopmental abnormalities postnatally. A range of genetic syndromes has been reported, many of which are linked to submicroscopic chromosomal abnormalities that are typically missed by conventional karyotyping. / Microarray-based comparative genomic hybridization (arrayCGH) has been applied as the first-tier diagnostic tool for the evaluation of developmental delay and structural malformations in children. In fetuses with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 5-12% with a structural anomaly and in about 1% of those whose indications were advanced maternal age or positive screening results. / The objectives of this study were to delineate the frequency and spectrum of pathogenic chromosome copy number variants (CNVs) among fetuses with increased NT and normal karyotype; to evaluate the role of arrayCGH to predict the prognosis of the high NT fetuses; to explore the genotype-phenotype correlations of increased NT. Therefore, a multi-centre cohort of 449 fetuses with NT ≧3.5 mm and normal karyotype were further investigated by arrayCGH. Antenatal surveillance, pregnancy outcome and paediatric follow up were documented. ArrayCGH detected abnormal CNVs in 2.8% (14 of 449) of the fetuses with high NT; the size of CNVs ranged from 0.1 kb to 18Mb. Among fetuses with major congenital abnormalities the incidence of abnormal CNV reached 7.8% (4 of 51). By adjusting the NT to ≧4.0 mm as the referral indication, 7.3% (14 of 192) of the fetuses would have abnormal arrayCGH results. The spectrum of pathogenic CNVs found associated with increased NT was diverse. However, there were recurrent ones such as the deletions or duplications at chromosomal region 22q11, and deletions in ZEB2. There was no pathogenic CNV related with increased NT found in chromosomes 3, 7, 12, 13, 18, 20, 21, or Y. The total normal outcome rate of euploid fetuses with an increased NT was 79.3%; for fetuses with normal arrayCGH results 81.2% had a normal outcome. In fetuses with isolated increased NT, normal arrayCGH results predict a favorable prognosis of 93.5%. / In conclusion, arrayCGH significantly increased the diagnostic yield of pathogenic CNVs. In clinical practice arrayCGH may be considered as the first tier investigation in fetuses with an increased NT more than 4.0 mm. In cases with an isolated increased NT with normal arrayCGH results the pregnancy outcome is likely to be favorable. The spectrum of abnormal CNVs found by arrayCGH is diverse but there are recurrent cases such as del/dup 22q11 and del ZEB2. Our preliminary gene ontology and pathway analysis showed that gene pathways related to neural crest cells may be considered as a future study for physiopathologic mechanisms of NT. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Huang, Jin. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 106-120). / Abstracts also in Chinese.

Wong, Ling Yee. / Thesis submitted in: August 2007. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 110-127). / Abstracts in English and Chinese. / Thesis Abstract --- p.i / 論文摘要 --- p.iv / Acknowledgements --- p.vi / Abbreviations --- p.vii / Thesis Content --- p.xii / List of Figures --- p.xv / List of Tables --- p.xvii / Chapter Chapter 1 --- Introduction --- p.1 / Chapter Chapter 2 --- Literature Review --- p.3 / Chapter 2.1. --- Multiple Myeloma (MM) --- p.3 / Chapter 2.1.1 --- Epidemiology --- p.4 / Chapter 2.1.2 --- Cause and Risk Factors --- p.5 / Chapter 2.1.3 --- Pathophysiology --- p.5 / Chapter 2.1.4 --- Diagnosis and Clinical Presentation --- p.6 / Chapter 2.1.5 --- Classification of Plasma Cell Disorders --- p.6 / Chapter 2.1.5.1 --- Monoclonal Gammopathy of Undetermined Significance (MGUS) --- p.6 / Chapter 2.1.5.2 --- Asymptomatic (Smouldering) MM --- p.7 / Chapter 2.1.5.3 --- Indolent MM --- p.7 / Chapter 2.1.5.4 --- Symptomatic MM --- p.8 / Chapter 2.1.6 --- Staging --- p.9 / Chapter 2.1.7 --- Treatment --- p.11 / Chapter 2.1.8 --- Molecular Abnormality --- p.12 / Chapter 2.2 --- DNA Microarray Analysis in MM --- p.13 / Chapter 2.2.1 --- MM Pathogenesis --- p.15 / Chapter 2.2.2 --- Molecular Classification of MM --- p.18 / Chapter 2.2.3 --- Anti-MM Drug Studies --- p.22 / Chapter 2.3 --- Cancer Treatment Response Prediction --- p.24 / Chapter 2.3.1 --- MP Treatment --- p.24 / Chapter 2.3.1.1 --- Melphalan --- p.25 / Chapter 2.3.1.2 --- Prednisone --- p.27 / Chapter 2.3.1.3 --- MP Treatment Response Prediction in MM --- p.29 / Chapter 2.3.2 --- Cancer Prognosis using DNA Microarray --- p.31 / Chapter Chapter 3 --- Materials and Methods --- p.36 / Chapter 3.1. --- Patient Specimens for Gene Expression Profiling and Quantitative Real-time PCR --- p.36 / Chapter 3.2. --- Magnetic Cell Sorting of CD138-positive Plasma Cells --- p.37 / Chapter 3.2.1 --- Density Gradient Centrifugation --- p.37 / Chapter 3.2.2 --- Positive Selection of CD138-positive Cells --- p.37 / Chapter 3.3 --- Generation of Gene Expression Profiles --- p.39 / Chapter 3.3.1 --- RNA Extraction --- p.39 / Chapter 3.3.2 --- RNA Assessment --- p.40 / Chapter 3.3.3 --- Synthesis and Purification of Double-strand cDNA --- p.40 / Chapter 3.3.4 --- In vitro Transcription (IVT) and Recovery of Biotin-labeled cRNA --- p.41 / Chapter 3.3.5 --- cRNA Fragmentation and Hybridization Reaction Mixture Preparation --- p.41 / Chapter 3.3.6 --- Hybridization --- p.42 / Chapter 3.3.7 --- Post-hybridization Wash --- p.42 / Chapter 3.3.8 --- Detection with Streptavidin-dye Conjugate --- p.43 / Chapter 3.3.9 --- Bioarray Scanning and Spot Signal Quantitation --- p.43 / Chapter 3.4 --- Microarray Data Analysis --- p.45 / Chapter 3.4.1 --- Normalization and Filtering --- p.45 / Chapter 3.4.2 --- Unsupervised Clustering Analysis --- p.45 / Chapter 3.4.3 --- Supervised Class Comparison Analysis --- p.46 / Chapter 3.5 --- Microarray Verification and Candidate Gene Validation --- p.47 / Chapter 3.5.1 --- RNA Extraction --- p.47 / Chapter 3.5.2 --- Reverse Transcription PCR --- p.47 / Chapter 3.5.3 --- Quantitative Real-time PCR --- p.48 / Chapter 3.6 --- Predictive Value Calculation --- p.49 / Chapter 3.7 --- Experimental Flow --- p.49 / Chapter Chapter 4 --- Results --- p.53 / Chapter 4.1 --- Gene Expression Profiling of Chinese MM --- p.53 / Chapter 4.1.1 --- Unsupervised Clustering Analysis --- p.53 / Chapter 4.1.1.1 --- Hierarchical Clustering --- p.53 / Chapter 4.1.1.2 --- Principal Component Analysis (PCA) --- p.54 / Chapter 4.1.2 --- Identification of Statistically Differentially Expressed Genes --- p.58 / Chapter 4.1.2.1 --- Two-Sample t-statistics --- p.58 / Chapter 4.1.2.2 --- Significance Analysis of Microarrays (SAM) --- p.58 / Chapter 4.1.2.3 --- Microarray Verification --- p.66 / Chapter 4.2 --- Development of MP Treatment Response Biomarker in MM --- p.70 / Chapter 4.2.1 --- Unsupervised Clustering Analysis --- p.70 / Chapter 4.2.1.1 --- Hierarchical Clustering --- p.70 / Chapter 4.2.1.2 --- PCA --- p.70 / Chapter 4.2.2 --- Identification of Statistically Differentially Expressed Genes --- p.74 / Chapter 4.2.2.1 --- Two sample t-statistics --- p.74 / Chapter 4.2.2.2 --- SAM --- p.74 / Chapter 4.2.3 --- Verification of Candidate Gene CYB5D1 --- p.76 / Chapter Chapter 5 --- Discussion --- p.79 / Chapter 5.1 --- Global Gene Expression Profiling: DNA Microarray --- p.79 / Chapter 5.2 --- Microarray Data Normalization and Gene Filtering --- p.81 / Chapter 5.3 --- Microarray Data Analysis --- p.83 / Chapter 5.3.1 --- Unsupervised Clustering Analysis --- p.83 / Chapter 5.3.1.1 --- Hierarchical Clustering --- p.83 / Chapter 5.3.1.2 --- PCA --- p.85 / Chapter 5.3.2 --- Identification of Statistically Differentially Expressed Genes --- p.86 / Chapter 5.4 --- Verification of Candidate Genes by Quantitative Real-time PCR --- p.89 / Chapter 5.5 --- Gene Expression Profiling of Chinese MM --- p.90 / Chapter 5.5.1 --- Comparison of Gene Expression Patterns of MM and Normal Plasma Cells --- p.90 / Chapter 5.5.2 --- Differentially Expressed Genes between MM and Normal Plasma Cells..… --- p.91 / Chapter 5.5.2.1 --- Common Differentially Expressed Genes with Previous Studies --- p.94 / Chapter 5.5.2.2 --- Potential Tumor Suppressor Genes in Differentially Expressed Genes..… --- p.96 / Chapter 5.5.2.3 --- Verified Differentially Expressed Genes --- p.98 / Chapter 5.5.3 --- Future Studies --- p.101 / Chapter 5.6 --- Development of MP Treatment Response Biomarker in MM --- p.103 / Chapter 5.6.1 --- Comparison of Gene Expression Patterns of MP Good Responders (GR) and Poor Responders (PR) --- p.103 / Chapter 5.6.2 --- Differentially Expressed Gene between MP GR and PR: CYB5D1 --- p.104 / Chapter 5.6.3 --- Possible Role of CYB5D1 in MP Resistance in MM Cells --- p.104 / Chapter 5.6.4 --- Potential Clinical Application of CYB5D1 in MP Treatment Response Prediction in MM --- p.106 / Chapter 5.6.5 --- Future Studies --- p.106 / Chapter Chapter 6 --- Conclusion --- p.108 / Chapter 6.1 --- Gene Expression Profiling of Chinese MM --- p.108 / Chapter 6.2 --- Development of MP Treatment Response Biomarker in MM --- p.108 / References --- p.110 / Appendix --- p.128

Seven years into the postgenomic era, we sit atop a mountain of data whose generation was enabled by gene sequencing. The creation, integration, and analysis of these large scale data sets allow us to move forward toward the complementary goals of determining the individual roles of the thousands of uncharacterized mammalian genes and understanding how they work together to produce a healthy human being -- or, perhaps more importantly, how their malfunction results in disease. Collapsing the results of large-scale assays into gene networks provides a useful framework from which we can glean information that advances both of these goals. However, the utility of networks is limited by the quality of the data that goes into them. This study offers seeks to shed some light on the quality and breadth of protein interaction networks, describes a new experimental technique for functional genetic assays in mammalian cell lines, and ultimately suggests a strategy for how to improve the overall utility of the output generated by the systems biology community. / text

Escherichia coli O157:H7 is an enteric pathogen that can cause severe gastrointestinal disease, sometimes leading to hospitalization and death. These bacteria have a variety of virulence factors that can be encoded for on pathogenicity islands (PAIs). The goal of this study was to characterize specific E. coli O157:H7 PAI deletion mutants using three methods: Phentotype Microarrays (PM), growth curves and survival curves were used to elucidate possible roles for the PAIs. Results from the PM study suggest that PAIs have a role in carbon substrate utilization; i.e., four of the O-island (OI) deletion mutants (OI-87, 98, 102 and 172) and an S-Loop (SL-72) deletion mutant exhibited differences in substrate utilization (gains and losses in utilization) compared to parental O157:H7 strains EDL933 (OI) and Sakai (SL), respectively. All of the mutants with the exception of the OI-135 mutant exhibited differences in level of substrate utilization for substrates shown to have important roles in the bacterium. Cell growth results showed that three OI deletion mutants (OI-55, 87 and 102) and the SL (SL-72) mutant exhibited a difference in rate of growth compared to the parental strains. Cell viability results showed that seven of the OI deletion mutants (OI-51, 55, 98, 108, 135, 172 and 176) exhibited different rates of decline in cell number when transferred to sterile water compared to the parental strain. The results show that removal of PAIs from E. coli O157:H7 can affect carbon utilization, growth and survival demonstrating the importance of PAIs in the ecology of these bacteria. / xx, 208 leaves : ill. (some col.) ; 29 cm

We explored the combination of metagenomic library and DNA microarray technologies into a single platform as a novel way to rapidly screen metagenomic libraries for genetic targets. In the "metagenomic microarray" system, metagenomic library clone DNA is printed on a microarray surface, and clones of interest are detected by hybridization to single-gene probes. This study represents the initial steps in the development of this technology. We constructed two 5,000-clone large-insert metagenomic libraries from two diesel-contaminated Arctic soil samples. We developed and optimized an automated fosmid purification protocol to rapidly-extract clone DNA in a high-throughput 96-well format. We then created a series of small prototype arrays to optimize various parameters of microarray printing and hybridization, to identify and resolve technical challenges, and to provide proof-of-principle of this novel application. Our results suggest that this method shows promise, but more experimentation must be done to establish the feasibility of this approach.

Thesis (Ph. D.)--Carleton University, 2004. / Includes bibliographical references (p. 200-217). Also available in electronic format on the Internet.

Orientador: Marcelo Menossi Teixeira, Andréa Akemi Hoshino / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Biologia / Made available in DSpace on 2018-08-18T07:51:32Z (GMT). No. of bitstreams: 1 Mattos_RaphaeldeSouza_M.pdf: 5526068 bytes, checksum: 090cb9f141a5a7dd324df049c18bf9c1 (MD5) Previous issue date: 2011 / Resumo: A cana-de-açúcar é uma das mais importantes espécies vegetais cultiváveis do mundo, sendo o Brasil o principal produtor. É uma fonte eficiente e de baixo custo para a obtenção de açúcar e etanol, que é considerado o mais promissor substituto do petróleo como fonte de energia a médio prazo, especialmente nos transportes. A seca é um dos principais estresses que reduzem a produtividade da cana e a produção de variedades tolerantes não só representa ganhos econômicos como contribui para a sustentabilidade dos canaviais. Embora a base genética da tolerância à seca ainda seja pouco conhecida, variedades desenvolvidas em programas de melhoramento tem apresentado progresso, apesar do ritmo ser mais lento que o desejado. Genômica funcional e desenvolvimento de marcadores colaboram aumentando a eficiência do melhoramento tradicional, mas ainda existem elementos do genoma que podem ser aproveitados de novas formas. Foram descobertos recentemente genes de função regulatória chamados microRNAs (miRNA) que também desempenham um papel na adaptação de plantas a diferentes estresses. Utilizando ESTs de cana-de-açúcar, sequenciamento de nova geração e microarranjos para avaliar a expressão de miRNAs sobre estresse hídrico foram descobertos novos miRNAs associados à seca e possíveis genes de miRNAs ligados à tolerância a este tipo de estresse / Abstract: Sugarcane (Saccharum spp.) is amongst the most relevant crops in the world and Brazil is the most prominent producer. It is an inexpensive and efficient source for commodities such as sugar and ethanol, the latter being increasingly considered the most promising immediate energy source substitute for oil, mainly in transportation. Apart from being very productive, it is largely affected by stress-related yield losses, notably from abiotic triggers. Drought stress is determinant for every crop field, and this is true for sugarcane as well. Although the molecular basis drought stress tolerance lacks further elucidation, newly developed cultivars have successfully reduced yield loss due to water shortage, albeit not at the desirable pace. Functional genomics and molecular markers development assist new cultivar selection programs by identifying and locating agronomically relevant alleles and QTL's, but there are other elements in the genome which can provide new ways to approach crop field improvement. The recently discovered microRNAs (miRNA) are regulatory genes found to have an important role in plants adaptation under different kinds of stresses. By using sugarcane ESTs, deep-sequencing and microarray technology to access stress induced miRNA expression, we have found novel sugarcane miRNA participating in the drought stress response and identified possible tolerance related miRNA genes / Mestrado / Genetica Vegetal e Melhoramento / Mestre em Genética e Biologia Molecular

O cancro cítrico é uma doença que afeta diversas espécies de Citrus, cujo agente causal é Xanthomonas axonopodis pv citri (XAC). O genoma desta fitobactéria consiste de um cromossomo de ~5 Mpb e dois plasmídeos, que juntos codificam 4313 CDS (seqüências codificadoras), das quais 2710 apresentam similaridade com proteínas conhecidas. Neste trabalho realizamos uma análise comparativa detalhada do genoma de XAC com genomas de três fitopatógenos, Xanthomonas campestris campestris, Xylella fastidiosa 9a5c e Xylella fastidiosa temecula. Com esta análise identificamos genes espécie e gênero-específicos, potencialmente relevantes para adaptação aos seus respectivos nichos ou hospedeiros, além de ilhas de inserção e deleção genômica putativas. Também identificamos vias metabólicas relacionadas com osmoproteção/osmorregulação e com degradação de compostos aromáticos em XAC, que possivelmente são determinantes na eficácia de sua interação com o hospedeiro. Analisamos o nível de expressão de 9 CDS após crescimento de XAC em diferentes concentrações de glicose e verificamos que este açúcar modula positivamente a expressão de CDS relacionadas à síntese de goma e ao sistema de osmoproteção. Além disso, descrevemos a construção de microarranjos de DNA representando 2760 CDS de XAC, constituindo-se uma nova ferramenta para estudos de genômica comparativa e expressão gênica deste fitopatógeno. / Xanthomonas axonopodis pv citri (XAC) is the bacterial pathogen that causes citrus canker disease in several species of Citrus plants. XAC genome consists of a main cromosome of ~5 Mpb and two plasmids that together encode 4313 CDS (coding sequences). Approximately 63% of the CDS have assigned biological functions. In this work, we present a detailed genomic comparison between the genomes of XAC and of three other phytopathogens, X. campestris campestris, Xylella fastidiosa 9a5c and X. fastidiosa Temecula. Based on this analysis, we identified species and genus-specific genes that might be relevant for adaptation to their niches and hosts. We mapped putative insertion/deletion regions in the XAC genome possibly related to gene gains and losses during the divergence of the four bacterial lineages. We have identified the metabolic pathways related to osmoprotection/osmoregulation and aromatic compound degradation important for XAC efficient host colonization and interaction. Expression levels of 9 CDS were analyzed after XAC growth under different glucose concentrations revealing that this sugar upregulates the expression of CDS related to gum synthesis and to osmoregulation. In addition, we describe here the construction of a DNA microarray representing 2760 CDS of XAC as a new tool for comparative genomic and gene expression studies in this phytopathogen.