Post-transcriptional processes contribute significantly towards the generation of proteomic diversity. An increasing number of mutations have been described that affect genes encoding components of the post-transcriptional machinery. In particular, multifunctional proteins that link transcription with post-transcriptional processes have been implicated in several human diseases including cancer. A predominant feature of these proteins is the zinc finger, an ancient structural motif that mediates protein[ratio ]protein interactions and is capable of interacting with both DNA and RNA. Zinc finger proteins are the most abundant class of proteins in the human proteome, yet the majority remain uncharacterised. Here we describe multifunctional zinc finger proteins linked to human development and disease. The examples discussed are WT1, ZNF74, EWS, TLS, TAFII68, YY1, CTCF and the GLI proteins. The study of these and other zinc finger proteins provides insights into the functional versatility of the zinc finger motif and suggests that both alternative splicing and sub-cellular compartmentalisation may modulate their multifunctionality.

Smoking is a major risk factor for coronary heart disease (CHD), but this risk may be modified by an individual's genotype. A common functional 5A/6A polymorphism in the promoter of the stromelysin-1 (matrix metalloproteinase 3, MMP3) gene has been identified. The 6A allele has been consistently associated with faster progression of angiographically determined CHD, while the 5A allele has recently been associated with risk of acute myocardial infarction (MI) in patients with unstable angina. To date there has been no prospective study of the relationship of this genotype to CHD risk in smokers and non-smokers.

DNA was available from 2743 middle-aged men, free of CHD at baseline, recruited through nine general practices in the UK for prospective surveillance. To date there have been almost 24000 person-years of follow-up with 125 CHD events (fatal and non-fatal MI, sudden coronary death, need for coronary artery surgery or new major ECG Q-wave abnormality). Men with events were each matched for age, practice and cholesterol level with three healthy men. Smoking habit was determined by questionnaire. 5A/6A genotype was determined using a heteroduplex generator method. Associations between genotype and disease outcome, according to smoking status, were assessed using conditional logistic regression. Overall, current smoking was associated with a relative risk (RR) of 1.99 (95% CI 1.30–3.06) as compared with never-smokers and ex-smokers combined (p<0.002). In non-smoking men, and after adjustment for conventional risk factors, compared with the 5A5A group, the RR was 1.37 (0.64–2.94) in those with the genotype 5A6A and 3.02 (1.38–6.61) in those with the genotype 6A6A. Smoking increased risk 1.4 fold in the 5A6A group to 1.91 (1.84–4.36), by 1.3 fold in the 6A6A group to 4.01 (1.57–10.24), but by 3.81 fold (1.54–9.40) in the 5A5A group (smoking–genotype interaction p = 0.01). The data indicate a key role for stromelysin in the atherosclerotic process. Men with the stromelysin genotype 5A5A represent 29% of the general population, and their high risk, if smokers, provides a further strong argument for smoking avoidance.

We looked for NBS1 gene (602667) alterations and changes in nibrin expression in 162 human gynaecological tumours, mostly ovarian. Exons 6–8 and 10 of the NBS1 gene were evaluated by the SSCP and direct sequencing method. Nibrin expression was detected immunohistochemically with the use of the p95NBS1 (Ab-1) antibody. The 657del5 mutation (Slavic mutation) was found in two of 117 carcinomas studied (1.7%) – in both cases it was present in the germline; one of these tumours showed loss of heterozygosity (LOH) for the 657del5 mutation and loss of nibrin expression. We have found three types of novel germline intron variants: (1) two concomitant transitions (G to A) at bases 14009 and 14256; (2) C to T transition at base 13998; (3) G to C transversion at base 20035. Among the carcinomas studied, the intron variants were associated with a clear cell histological type (p = 0.004). Our results may suggest that NBS1 gene alterations contribute to the development of rare ovarian carcinomas. LOH for 657del5 in tumour tissue may support the hypothesis that the NBS1 gene functions as a tumour suppressor.

The origins and genomic affinities of various tribal populations of India are of considerable contemporary interest. In this study, we have investigated relationships among five tribal groups inhabiting the north-eastern, eastern and sub-Himalayan regions of India. DNA samples have been analysed in respect of 25 polymorphic loci, based on which genetic affinities have been estimated. The interesting findings of this study are (i) the Tibeto-Burman speaking, morphologically Mongoloid, tribal groups of India are not genetically very homogeneous, and (ii) the Tharu, a group inhabiting the sub-Himalayan region, may indeed have undergone considerable admixture as has been postulated by some anthropologists.

Ancient diversity in Sub-Saharan Africa is known to have been re-modulated to a large extent by Bantu migrations in the sub-Sahel region, in two southwards waves of advance through both the west and east coasts. Haplotype matching performed for Y-STR haplotypes in several sub-Saharan populations, both inside and outside the migration path, allowed the confirmation of a putative founder haplotype, and its one-step neighbours, of Bantu origin, and detected an increasing drift towards the south, with a stronger reduction of diversity along the western coast. A mixed frequency distribution for the Bantu haplotype core in South Africa, relative to the western and eastern pools, seems to provide evidence for the intermingling between both Bantu waves in that region. The proportion of male lineages considered as predating the Bantu expansion reached 8.8% in Mozambique. Further influence on sub-Saharan diversity may have occurred during the colonial period; in Mozambique, the European genetic impact in the male component was estimated to be around 5.9%, in significant contrast with the female counterpart where no European lineages were detected.

Ornithine transcarbamylase (OTC, EC 2.1.3.3) deficiency, the most common inborn error of urea cycle, is caused by a vast number of point mutations, deletions and insertions in the respective gene. Furthermore, 12 single nucleotide polymorphisms (SNPs) have been described in the OTC gene, four of them causing an amino acid change. We have studied the frequency of these markers in two populations: Portuguese and Mozambican. No significant differences were observed between populations, except for Lys→Arg in codon 46. Allelic associations between polymorphisms were used to define haplotypic patterns. The three common haplotypes (H1, H2 and H3) show a combined frequency of 95% in Portugal and 87% in Mozambique. One haplotype was found only in Portugal and three are only present in Mozambique, resulting in a higher haplotype diversity. The combined information from the SNPs and the DXS1068 (CA)n repeat was used to outline OTC haplotype phylogeny, which, in conjunction with the population data, allowed us to sketch possible evolutionary pathways, although some haplotypes could have arisen by either repeated mutation or recombination.

Gluten sensitive enteropathy has various manifestations, of which the two major forms are classical coeliac disease (cCD) and dermatitis herpetiformis (DH). In cCD predominantly the small intestine is affected, whereas in DH also the skin is affected showing typical rash and IgA deposits. The symptoms in both forms are dependent on gluten intake. The factors diversifying these two clinical outcomes are unknown. In the present report we evaluated the role of the major genetic susceptibility locus, HLA DQ, in 25 families, in which both forms of the disease, cCD and DH, occurred in siblings. By using the family-based approach it can be assumed that within each family variation in environmental factors is substantially lower than in the standard case-control setting, and also the problems related to population stratification can be avoided. Results from the Finnish family material with 25 discordant and 85 concordant sib pairs, and from additional case-control material comprising 71 unrelated Hungarian DH and 68 cCD patients, together indicated that the HLA DQ locus did not differ between the two major outcomes of gluten sensitive enteropathy. The non-HLA DR;DQ factors are critical for the different clinical manifestations of gluten sensitivity.

Genotyping costs still preclude analysis of a comprehensive SNP map in thousands of individual subjects in the search for disease susceptibility loci. Allele frequency estimation in DNA pools from cases and controls offers a partial solution, but variance in these estimates will result in some loss of statistical power. However, there has been no systematic attempt to quantify the several sources of error in previous studies. We report an analysis of the magnitude of variance components of each experimental stage in DNA pooling studies, and find that a design based on the formation of numerous small pools of approximately 50 individuals is superior to the formation of fewer, larger pools and the replication of any of the experimental stages. We conclude that this approach may retain an effective sample size greater than 68% of the true sample size, whilst offering a 60-fold reduction in DNA usage and a greater than 30-fold saving in cost, compared to individual genotyping. The possibility of combining pooling with informed selection of haplotype tag SNPs is also considered. In this way further savings in efficiency may be possible by using pooled allele frequency estimates to infer haplotype frequencies and hence, allele frequencies at untyped markers.

In this paper we compare the power of the multivariate Haseman–Elston (MHE) test proposed earlier by Amos et al. (1990) and a computationally rapid new version of the multivariate Haseman–Elston test (NMHE) (Elston et al. 2000). We show that the power of NMHE was, for different simulation setups, identical or higher than that of MHE. In the bivariate case, the power of the NMHE method was somewhat less than that of the computationally intensive maximum likelihood variance components method (Amos et al. 2001). We present comparisons of the empirical distributions of the NMHE test to its limiting distributions for a range of numbers of traits. The distribution of the NMHE test appeared to conform satisfactorily to its limiting asymptotic distribution in large samples. Otherwise, empirical critical values for NMHE are somewhat higher than predicted, i.e. the test proposed by Elston et al. (2000) is non-conservative. The use of empirical critical values is therefore recommended for limited sample sizes (less than several hundred families). We also present the results of a linkage analysis performed by the NMHE method on a set of 4 body size-related traits. The method identified meaningful combinations of traits that showed significant linkage on chromosome 2 and suggestive linkage to regions on chromosomes 16 and 17.

Previously, we have presented a data mining-based algorithmic approach to genetic association analysis, Haplotype Pattern Mining. We have now extended the approach with the possibility of analysing quantitative traits and utilising covariates. This is accomplished by using a linear model for measuring association. We present results with the extended version, QHPM, with simulated quantitative trait data. One data set was simulated with the population simulator package Populus, and another was obtained from GAW12. In the former, there were 2–3 underlying susceptibility genes for a trait, each with several ancestral disease mutations, and 1 or 2 environmental components. We show that QHPM is capable of finding the susceptibility loci, even when there is strong allelic heterogeneity and environmental effects in the disease models. The power of finding quantitative trait loci is dependent on the ascertainment scheme of the data: collecting the study subjects from both ends of the quantitative trait distribution is more effective than using unselected individuals or individuals ascertained based on disease status, but QHPM has good power to localize the genes even with unselected individuals. Comparison with quantitative trait TDT (QTDT) showed that QHPM has better localization accuracy when the gene effect is weak.

In this article, we provide an overview of the different statistical procedures that have been developed for linkage mapping of quantitative trait loci. We outline the model assumptions, the data requirements and the underlying tests for linkage for the different methods.