Cloning a susceptibility gene for asthma A presentation report

Transcription

1 1 Cloning a susceptibility gene for asthma A presentation report Version Date Course Author S / 2003 Mika Salonoja

2 2 Contents 1 SOME ASTHMA GENETICS MAPPING IN A NUTSHELL NOW WE HAVE A LOCUS. WHAT ABOUT THE GENES? First phase: physical map Second phase: gene prediction Third phase: look for expression products on RNA level Fourth phase: assemble Open Reading Frame (ORF) Fifth phase: classify the gene from peptide sequence Sixth phase: look for gene products in tissues and cells on protein level FUTURE WORK...8

3 3 1 Some asthma genetics Susceptibility to asthma and allergic diseases depends on genetic variation at an unknown number of loci, plus environmental factors. There are many poorly described asthma subgroups. Patients symptoms may differ form each in many ways. There are also several responder nonresponder groups for existing treatments and drugs. The so called common disease common variant hypothesis seems to hold for asthma. There is strong evidence that the main factors elevating the susceptibility for asthma are similar everywhere. There does not seem to be local, population dependent single mutations that would contribute to asthma susceptibility. There is, however, evidence that some of the common variants have been enriched in certain populations due to genetic bottlenecks in the past. In various gene mapping projects several loci with association to asthma have been found. There is, however no known common coding polymorphisms, and we do not expect to find them in future either. Instead we expect to find alternate splicing, polymorphisms in introns, promoter regions, UTR s etc. In the gene mapping project described here we adopted a hierarchical genotyping design to move from linkage to a high-density association study 2 Mapping in a nutshell In the following picture the mapping effort is presented in a nutshell. The study group was collected from Kainuu, and consisted of large families with several asthma patients. Sample were collected also from healthy relatives when possible. The original locus in human chromosome 7 was found using a genome wide scan approach with microsatellite markers with about 10 cm (cent Morgan) intervals. From this data the locus was found using standard linkage analysis tools (like Genehunter2 etc.) From this point new microsatellite markers were designed for the linkage hotspot region, and finally, when no new information could be gained through microsatellites, a number of SNP markers (single nucleotide polymorphisms) were genotyped for association calculation.

4 A: steps taken in the gene mapping, B: a computer program display of the linkage disequilibriums between markers for both patients and healthy controls in Kainuu patient group, C: the same for a population in French Canada, D: phylogenetic tree displaying the relations between different haplotypes found in our association hotspot 4

5 5 3 Now we have a locus. What about the genes? At this point there s a multitude of techniques to apply, especially when gene is large, complex and human disease associated. The process is not necessarily very systematic. Instead there s a more iterative process of creating, testing, rejecting one hypothesis after another. During this process we utilized highly variable wetlab experiments and essential computer tools. The approach could be called classical functional genomics approach, not systems biology in the modern sense of the word. 3.1 First phase: physical map In 1998 there was no reference sequence for our region available, so we had to build it. Random sequencing led to choose a number overlapping BAC s (bacterial artificial chromosomes), each of which contained a random sub-region form of our locus. After months of work (BAC s prone to errors) a complete physical map was finished, which was assembled to a reference sequence. 3.2 Second phase: gene prediction GENSCAN and FGENES software were used, with rather poor results. Porgrams found a number of predicted exons, but no complete ORF (open reading frame). So at this point all predicted exons were treated as separate genes, with strong suspection. PCR primers were designed for predicted exons. 3.3 Third phase: look for expression products on RNA level We looked for endogenic expression of any gene sequence in our linkage region. First, a tissue panel was used with immortalized cells from 8 different tissues (kidney, brain etc.) Reverse transcriptase PCR (RT-PCR) was used to amplify exon regions, which were sequenced. Second, some bacteria was transfected with our exon and suitable phages with DNA sequences from a cdna library. With this method a full cdna can be found, if there s some luck. Third, RACE-PCR (rapid amplification of cdna ends) was used to amplify over exon boundaries, to find out larger regions of cdna.

6 6 3.4 Fourth phase: assemble Open Reading Frame (ORF) PCR products from previous experiments were sequenced, and alternate splicing was found. In 2001 sequence for mouse chromosome 9 became available. It contains regions highly homologous region for human chromosome 7. Homologous ORF was found in mouse, which provided additional evidence of our gene. Finally full sequence of our gene was known. 3.5 Fifth phase: classify the gene from peptide sequence DNA sequence was turned into peptide sequence, which was studied using computer programs PredictProtein and TM-pred. 7 transmembrane domains were found. Protein BLAST was used to look for homologies in other known peptide sequences. A number of conserved amino acids and domains suggested, that our gene coded a GPCR (G-protein coupled receptor) with no exact match to existing 7tm receptors. So it looked like a novel receptor. 3.6 Sixth phase: look for gene products in tissues and cells on protein level Now the questions were the following. Where is our gene expressed? Which tissues? Where within cells? Now four different antibodies were designed for the receptor moleculre: two for the two known splice variants, one for common cytoloop 3 (within the cell) and one for N- terminus (extracellular). A number of methods were tested to get the antibodies through cell membrane, which was very time-comsuming. Two different streams of study were immunohistochemistry (expression in the tissue level) and immunofluoresence (localization of expression within cell). Methods were fine tuned to get good signal-to-noise (antibodies of antibodies). Months and months of labwork was spent duplicating all the experiments for all the tissues and all the antibodies. Finally there was enough information to file a provisional U.S. patent application for our gene, and start preparing a series of articles to publish the findings. The main article for this work is published in Science during spring 2004.

7 An example of results is presented in the picture set below. Expression of the two different splice variants A (left panels) and B (right panels) of our gene as assessed by immunohistochemistry. The blue grains are cell nuclei, and the expression of our gene variants is coloured red. The A variant is found in bronchial smooth muscle cells, basally in colon epithelium and in occasional basal keratinocytes. The B variant stains apical epithelial cells in bronchus and gut and all layers of the epidermis. Negative controls are shown with preimmune sera. 7

8 8 4 Future work Even though the work has been successful in scientific terms, the genetics of asthma is definitely not solved. Think of the following: 75% of carriers of the risk factor in our chromosome 7 locus are healthy role of our gene in asthma onset is still unknown up to date there are 20 human chromosomes with locus associated to asthma or allergy Things to be done in the upcoming years: make and test hypothesis about our genes role in asthma onset perform expression profiling in lung tissue biopsies find ligand (no software to do that automatically) through collaboration make a proper animal disease model perhaps try in vitro gene silencing (sirna) can locus polymorphisms be used as diagnostic or prognostic test? put all major loci together for a multilocus SNP test utilize possible findings through partnerships with larger companies