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Gene Hunting Natália F. Martins. Resumo Motivação Estratégia Automatização (?) Exemplos Referências.

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Presentation on theme: "Gene Hunting Natália F. Martins. Resumo Motivação Estratégia Automatização (?) Exemplos Referências."— Presentation transcript:

1 Gene Hunting Natália F. Martins

2 Resumo Motivação Estratégia Automatização (?) Exemplos Referências

3 Motivação A Busca de genes pode ser motivada pela necessidade de desenvolvimento de drogas inibidoras, Por aplicações biotecnológicas, biofábricas Ciência básica.

4 Traditional Organization of Gene Hunting Physicians - working with families, gather medical information Biomedical scientists -- analyzing DNA, disease biochemistry Families - cooperating thru an interest in their own families Coordination -- informal, based on the medical & scientific norms of the professions, with complex patterns of cooperation. Generating public knowledge on the disease -- publication key

5 Methodology 1.A qualitative phase Selection of words, therms and related literature 2. A quantitative phase Expression levels, microarray data, experimental data. Combinatorial chemistry, drug design

6 Whole genomes Key words interactions References Arrays data Top10 listExperimental phase

7 Automatização é Possível

8 Exemplos Cell signaling Zebra fish Virulence

9 Cell signaling pathways in Paracoccidioides brasiliensis - inferred from comparisons with other fungi The identification of putative genes involved in the cellular signaling pathways was performed by the “search by key word” service provided by the bioinformatics group of the PbGenome project (Felipe et al., 2003). The classification of candidates according to the signaling category families was performed by a BLASTx (Zhang, 2003) comparison of sequences against a database with all the signaling protein sequences from Genbank (Benson et al., 2004). The analyzed clusters were assembled by CAP3 software in the sequence-processing pipeline from the PbGenome project. The multiple sequence alignment of the candidates was performed using CLUSTAL W software (Aiyar, 2000).

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12 Transcriptome Analysis of Zebrafish Embryogenesis Using Microarrays PLoS Genet. 2005 August; 1(2): e29. Published online 2005 August 26. doi: 10.1371/journal.pgen.0010029. Methods –Embryo collection –RNA isolation and reference RNA –Zebrafish oligonucleotide probe design and microarray construction –Data acquisition and statistical analysis

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16 Vibrio cholerae recovered directly from patient specimens Methodology –Collection of clinical samples –RNA and genomic DNA extraction. –Microarrays and hybridization –Statistical analysis

17 Differential expression of genes in the TCP island during early compared with late human infection, represented as log 10 fold change. Expression of the transposase sequence (tnp) of the TCP island is shown at the left, and that of the integrase gene

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19 Gene Hunting and Drug Design

20 Genetic basis of disease Phenotype Disease state –Complex, often contested definitions & diagnoses, arising at different ages etc. Genotype Genetic mutations (polymorphisms) –Located over 50,000- 80,000 genes, subject to high levels of natural variation or noise

21 Added Statistical complexity Two types of disease Monogenic -- mutation in one gene leads to disease follows Mendelian inheritance Polygenic -- mutations in several genes lead to disease follows complex inheritance patterns Susceptibility -- genes may confer susceptibility rather than necessarily the disease itself (penetrance) Very high levels of background noise making the search for mutations difficult Population genetics projects very complex and difficult – access to desirable population a key

22 Key Types of Knowledge for Population Genetics Medical Records: Provides information on phenotypes, but this can be complex, difficult to define, not available to the patient in full detail. Genetic Records: Also known as genetic maps. Developed from tissue samples, blood etc. using a range of different techniques including search for genetic markers. Genealogical Records: Given the complexity of finding statistical correlation, family records provide improved “roadmaps” by reducing the background noise, using inheritance information & common markers.

23 Summary and Implications A market exists for genetics exists, but is constrained –Very little buying and selling of property rights to populations –The “borrowing” strategy has, along with fears of group revolts, necessitated the imposition of medical research norms that limit the degree to which information can be exploited A “moral economy” surrounds this market Competition between public and commercial projects may be increasing Fonte : www.genomeprairie.ca/gels/news/crsgovrdocs/Casper.ppt 2005

24 Future

25 What the bleep do we know?


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