PP009. A follow-up study of Finnish pre-eclampsia families identifies a new fetal susceptibility locus on chromosome 18.

INTRODUCTION: According to the epidemiological research both maternal and fetal genes influence in predisposition to pre-eclampsia (PE). We have previously detected linkage signals in Finnish families on chromosomes 2p25, 4q32, and 9p13 using maternal phenotypes. OBJECTIVES: Our aim was to perform a follow-up linkage analysis using updated maternal phenotypes and an unprecedented linkage analysis using fetal phenotypes. METHODS: We performed a non-parametric linkage analysis using the same sample set and microsatellite markers as reported in the original linkage study (Laivuori et al., [1]). Markers genotyped were available from 237 individuals in 15 Finnish families including 72 affected mothers (pregnancy complicated by PE n=54, eclampsia n=1, or gestational hypertension [GHT] n=17), and 49 affected fetuses (born from a pregnancy complicated by PE n=45, or GHT n=4). MERLIN software (Abecasis et al., 2002) was used for sample and marker quality control and linkage analysis. Results from this study were compared against the original results obtained by using GENEHUNTER 2.1 software. RESULTS: The maximum nonparametric linkage (NPL) scores on chromosome 2 were at 21.70cM near marker D2S168 using maternal and fetal phenotypes (NPL score 3.79, p=0.00008, and NPL score 2.95, p=0.002, respectively). On chromosome 4 the highest peak was at 158.20 cM near marker D4S413 using maternal phenotypes (NPL score 3.13 p=0.0009), and at 109.60 cM near marker D4S1572 using fetal phenotypes (NPL score 2.50, p=0.006). On chromosome 9 the highest peaks using maternal phenotypes were at 38.90cM near marker D9S169 (NPL=3.76, p=0.00008), and at 120.80 cM near marker D9S1811 (NPL=2.74, p=0.003). The maximum peak on chromosome 9 using fetal phenotypes was found at 59.20cM near marker D9S175 (NPL=2.69, p=0.004). We found a suggestive linkage on chromosome 18 at 86.80cM near marker D18S64 using fetal phenotypes (NPL score of 2.51, p=0.006), but the highest peak using maternal phenotypes did not reach significance. CONCLUSION: In this follow-up study we have confirmed the linkage signals identified in the original linkage analysis using maternal phenotypes. Linkage to chromosome 2 was also supported by analysis using fetal phenotypes. Chromosome 18 may harbour a new fetal susceptibility locus for PE.

ROCK2 allelic variants are not associated with pre-eclampsia susceptibility in the Finnish population.

The rho-associated coiled-coil protein kinase 2 (ROCK2) gene has been suggested to associate with general hypertension and is therefore a plausible functional candidate gene for pre-eclampsia. ROCK2 maps to chromosome 2p25, which we have implicated previously in a linkage study of pre-eclampsia. We have re-sequenced exons and putative promoter region of ROCK2 in up to 30 pre-eclampsia patients and 22 controls and genotyped putative functional single-nucleotide polymorphisms (SNPs) as well as tagging SNPs from HapMap in a Finnish case-control data set-340 affected and 357 matched control individuals-for a genetic association study of ROCK2 in pre-eclampsia. Even though several new SNPs were discovered, we did not detect significant allelic or haplotypic association between ROCK2 and pre-eclampsia. We assessed ROCK2 expression in placentas by microarray analysis, but no significant expression differences were observed when comparing preeclamptic and normotensive pregnancies. We conclude that common genetic variation in ROCK2 is unlikely to make a major contribution to the risk of pre-eclampsia, but cannot exclude the possibility of having missed non-coding functional variants or rare coding variants.

Global analysis of uniparental disomy using high density genotyping arrays.

BACKGROUND: Uniparental disomy (UPD), the inheritance of both copies of a chromosome from a single parent, has been identified as the cause for congenital disorders such as Silver-Russell, Prader-Willi, and Angelman syndromes. Detection of UPD has largely been performed through labour intensive screening of DNA from patients and their parents, using microsatellite markers. METHODS: We applied high density single nucleotide polymorphism (SNP) microarrays to diagnose whole chromosome and segmental UPD and to study the occurrence of continuous or interspersed heterodisomic and isodisomic regions in six patients with Silver-Russell syndrome patients who had maternal UPD for chromosome 7 (matUPD7). RESULTS: We have devised a new high precision and high-throughput computational method to confirm UPD and to localise segments where transitions of UPD status occur. Our method reliably confirmed and mapped the matUPD7 regions in all patients in our study. CONCLUSION: Our results suggest that high density SNP arrays can be reliably used for rapid and efficient diagnosis of both segmental and whole chromosome UPD across the entire genome.

Characterization of the sec1-1 and sec1-11 mutations.

Sec1 proteins are implicated in positive and negative regulation of SNARE complex formation. To better understand the function of Sec1 proteins we have identified the nature of the temperature-sensitive mutations in sec1-1 and sec1-11. The sec1-1 mutation changes a conserved glycine(443) to glutamic acid. The sec1-11 mutation changes a highly conserved arginine(432) to proline. Based on homology and the crystal structure of the mammalian nSec1p, the corresponding amino acids localize to the 3b domain of nSec1p. Compared to the wild-type Sec1p the mutant proteins are less abundant even at the permissive temperature. Thus, the R432P and G443E mutations may cause structural alterations that affect folding and make the mutant proteins more susceptible to degradation. The remaining part is sufficient for growth and protein secretion at 24 degrees C and thus is likely to be properly folded. At 37 degrees C the mutant proteins become non-functional. In pulse-chase-type experiments the newly synthesized Sec1-1 and Sec1-11 proteins decayed similarly with the wild-type protein. Thus, the non-functionality of the mutant proteins cannot be explained by denaturation-induced degradation only. It is possible that the newly synthesized mutant proteins fold slowly and are susceptible to degradation before they have managed to fold and associate with other proteins. The mutant proteins were unable to interact with the Sec1p-interacting proteins Mso1p and Sso2p in the two-hybrid assay, even at the permissive temperature. These results localize sec1-1 and sec1-11 mutations to a domain of Sec1p and suggest a mechanism by which sec1-1 and sec1-11 cells become temperature-sensitive.

Regulatory sequence analysis: application to the interpretation of gene expression.

Microarray technologies for measuring mRNA abundances in cells allow monitoring of gene expression levels for tens of thousands of genes in parallel. By measuring expression responses across hundreds of different conditions or timepoints a relatively detailed gene expression map starts to emerge. Using cluster analysis techniques, it is possible to identify genes that are consistently coexpressed under several different conditions or treatments. These sets of coexpressed genes can then be compared to existing knowledge about biochemical or signalling pathways, the function of unknown genes can be hypothesised by comparing them to other genes with characterised function, or from trends in expression profiles in general - why cell needs to transcribe or silence the genes during particular treatment. The regulation of genes on the DNA level is largely guided by particular sequence features, the transcription factor binding sites, and other signals encaptured in DNA. By analyzing the regulatory regions of the DNA of the genes consistently coexpressed, we can discover the potential signals hidden in DNA by computational analysis methods. The prerequisite for this kind of analysis is the existence of genomic DNA sequence, knowledge about gene locations, and experimental gene expression measurements for a variety of conditions. This article surveys some of the analysis methods and studies for such a computational discovery approach for yeast Saccharomyces cerevisiae.