Staff

Group leader: GIUSEPPE NOVELLI

Universita' degli Studi di ROMA "Tor Vergata"
Medicina e Chirurgia
Dipartimento di Biopatologia e Diagnostica per Immagini

1. CAPON FRANCESCA Tor Vergata University Dept of Biopathology and Diagnostic Imaging
2. SEMPRINI SABRINA Tor Vergata University Dept Biopathology and Diagnostic Imaging

 

 

Research activity

The workpackage's objective is to set up a reliable and reproducible test for variant identification and screening in complex disease candidate genes. Since it has been hypothesized (Collins et al., 1997; Lander, 1996) that common genetic variants may contribute significantly to the genetic risk of complex disease, searching SNPs in candidate genes could be of importance in identifying causative variants predisposing to the disease. Is now emerging a new genetic approach using gene-based haplotype which is predicted to have more power than individual SNP to track the disease causative site (Judson et al., 2000). The methods is consisting in sequencing a DNA region, including 5' and 3' regolative regions, splice junction sites and coding exons, in some unrelated subjects to discover a collection of SNPs, that can be organised into haplotypes computationally or using molecular techniques. Even if the causative site is not observed, the collection of haplotypes in the population allows some degree of sensitivity. The population having the phenotype of interest will be enriched in those haplotypes carrying the causative SNP. These haplotypes are phylogenetically more closely related to each other than they are to the other haplotypes not carrying the causative SNP (Judson et al., 2000). This approach will be applied to putative candidate genes for inflammatory bowel disease, multiple sclerosis and chronic obstructive pulmonary disease, predicted on the basis of their involvement in possible pathogenetic processes. The proposed genes are: IL-12 genes for inflammatory bowel disease, CD1b for multiple sclerosis and CFTR and a1-antitrypsin for chronic obstructive pulmonary disease (see backgroud). The method will be extended also to full-length cDNAs isolated by the library-free approach and then structurally characterized in Research line 2 for Type 2 diabetes.
The proposed method to identify SNPs is applied to all the candidate genes and cDNAs mentioned above, and is based on the following steps:
- Collect a minimum of 100 blood samples (10-20 ml) of unrelated patients for each of the diseases under analysis and 50 blood samples of well matched controls. All subjects will be phenotipically well characterized by expert clinicians (Workpackage 1).
- DNA extraction by phenol-chloroform standard techniques and storage. This will require separation of the sample into working dilution and concentrate samples to maximise longevity of samples.
- Creation of a DNA bank.
- Silicio search in SNPs resources will be performed initially to select existing SNPs within selected genes (http://www.ncbi.nlm.nih.gov/SNP/ and http://snp.cshl.org/db/snp/map) (Schork et al., 2000).
- Capture information on genomic 5' UTR, 3' UTR, exon-intron boundaries and exon sequences of the candidate genes on GenBank (http://ncbi.nlm.nih.gov).
- Amplification of each genomic region by PCR in multiple overlapping segments (about 200bp) by conventional PCR protocols.
- Analysis of PCR products by Denaturing high-performance liquid chromatography (DHPLC) carried out on automated HPLC instrumentation (Transgenomic Inc., San Jose, CA)
- Sequence of DNA fragments, showing DNA variations, to further characterise them.
- Organisation of the collection of SNPs, discovered in a gene locus, into haplotypes computationally by HAPLO software (Hawley and Kidd, 1995).
- Stratification of the population in a case-control format on the basis of identified haplotypes.
- Prediction of any possible association between the disease and the candidate gene genotype by statistical analysis.
- Every interesting DNA variant or haplotype will be further characterised by functional analysis by Workpackage3.

References:

· Collins et al. Variations on a theme: cataloging human DNA sequence variation. Science 1997, 278:1580-1581.
· Lander. The new genomics: global views of biology. Science 1996, 274:536-539.
· Judson et al., The predictive power of haplotypes in clinical response. Ashley Publications 2000, 1:5-16.
. Schork et al. Single nucleotide polymorphisms and the future of genetic epidemiology. Clinical Genetics 2000, 58, 250-264.
· Havley & Kidd. HAPLO: a program using the EM algorithm to estimate the frequencies of multi-site haplotype. J Hered 1995, 86:409-411.

Financial support

Amount (ML) 155
Source(s) Italian Ministry of Health

Five recent papers

1) Pizzuti A., Novelli G., Ratti A., Amati F., Mari A., Calabrese G., Nicolis S., Silani V., Marino B., Scarlato G., Ottolenghi S., Dallapiccola B.:
UFD1L, a developmentally expressed ubiquitination gene, is deleted in CATCH 22 syndrome. Human Molecular Genetics 6, 259-265 (1997).
2)Capon F., Novelli G., Semprini S., Clementi M., Nudo M., Vultaggio P., Mazzanti C., Gobello T., Botta A., Fabrizi G., Dallapiccola B.:
Searching for psoriasis susceptibility genes in Italy: genome scan and evidence for a new locus on chromosome 1. Journal of Investigative Dermatology 112, 32-35 (1999).
3)Mangino M., Sanchez O., Torrente I., De Luca A., Capon F., Novelli G., Dallapiccola B.:
Localization of a gene for familial patella aplasia-hypoplasia (PTLAH) to chromosome 17q21-22. American Journal of Human Genetics 65, 247-249 (1999).
4)Novelli G. , Amati F., Dallapiccola B.:
UFD1L AND CDC45L: Role of either, neither or both in DiGeorge syndrome and related phenotypes?
Trends in Genetics 15, 251-252 (1999).
5)Capon F., Semprini S., Dallapiccola B., Novelli G.:
Evidence for interaction between psoriasis susceptibility loci on chromosomes 6p21 and 1q21. American Journal of Human Genetics, 65:1798-1800 (1999).