Although frequencies of mitochondrial DNA (mtDNA) haplogroups in the different European populations are rather homogenous, there are a few European populations or linguistic isolates that show different mtDNA haplogroup distributions; examples are the Saami and Ladin speakers from the eastern Italian Alps.

MtDNA sequence diversity was analysed from subjects from two villages in Veneto. The first, Posina, is situated in the Venetian Alps near Vicenza. The second, Barco di Pravisdomini is a village on the plains near Venice. In spite of their common Veneto dialect, the two group populations have not preserved a genetic homogeneity; particularly, they show differences in T and J haplogroups frequencies. MtDNA diversity in these two groups seems to depend more on their geographic situation.

HLA class I and class II alleles have been studied for the first time in the Turkish-speaking Tuvinian population, which lives in Russia, North of Mongolia and close to the Altai mountains. Comparisons have been done with about 11000 chromosomes from other worldwide populations, and extended haplotypes, genetic distances, neighbor joining dendrograms and correspondence analyses have been calculated. Tuvinians show an admixture of Mongoloid and Caucasoid characters, the latter probably coming from the ancient Kyrgyz background or, less feasibly, more recent Russian Caucasoid admixture. However, Siberian population traits are not found and thus Tuvinians are closer to Central Asian populations. Siberians are more related to Na-Dene and Eskimo American Indians; Amerindians (from nowadays Iberian–America) are not related to any other group, including Pacific Islanders, Siberians or other American Indians. The ‘more than one wave’ model for the peopling of the Americas is supported.

Although molecular genetic evidence continues to accumulate that is consistent with a recent common African ancestry of modern humans, its ability to illuminate regional histories remains incomplete. A set of unique event polymorphisms associated with the non-recombining portion of the Y-chromosome (NRY) addresses this issue by providing evidence concerning successful migrations originating from Africa, which can be interpreted as subsequent colonizations, differentiations and migrations overlaid upon previous population ranges. A total of 205 markers identified by denaturing high performance liquid chromatography (DHPLC), together with 13 taken from the literature, were used to construct a parsimonious genealogy. Ancestral allelic states were deduced from orthologous great ape sequences. A total of 131 unique haplotypes were defined which trace the microevolutionary trajectory of global modern human genetic diversification. The genealogy provides a detailed phylogeographic portrait of contemporary global population structure that is emblematic of human origins, divergence and population history that is consistent with climatic, paleoanthropological and other genetic knowledge.

A sample of mitochondrial DNA (mtDNA) from the southeastern African population of Mozambique has been shown to have affinities with populations both to its north and south. From the north came sequences that may have been involved in the Bantu expansion (from western, through eastern, to southern Africa), such as members of haplogroups L3b, L3e1a and a subset of L1a. The dating of the major component of Mozambican mtDNAs, the subset L2a of haplogroup L2, displayed an age range compatible with the Bantu expansion. The southern influence was traced by the presence of sequence types from haplogroup L1d, a probable relict of Khoisan-speaking populations that inhabited the region prior to their displacement by the Bantu-speaking incomers. Within historical times, the forced displacement of Mozambicans as part of the slave trade, mainly documented as being to the Americas, generated a differential input of eastern African sequences into the mtDNA pools of the Americas and of Europe, as testified to by the greater number of sequence matches between Mozambique and the Americas, compared to those between Mozambique and Europe.

In Danes we replicated the 3′APOB–VNTR gene/longevity association study previously carried out in Italians, by which the Small alleles (less than 35 repeats) had been identified as frailty alleles for longevity. In Danes, neither genotype nor allele frequencies differed between centenarians and 20–64-year-old subjects. However, when Danish and Italian data were compared, a significant difference (p = 0.0004) was found between the frequencies of Small alleles in youths, which disappeared in centenarians (p = 0.290). Furthermore, the demographic-genetic approach revealed in Danes a significant gene–sex interaction relevant to Long alleles (more than 37 repeats). The different findings in Denmark and Italy suggest that gene/longevity associations are population-specific, and heavily affected by the population-specific genetic and environmental history.

In order to investigate the origin of the Eastern Slavs, mitochondrial DNA (mtDNA) sequence variation was examined in Russians and Ukrainians by hypervariable segment I (HVS I) sequencing and restriction analysis of the haplogroup-specific sites. No significant differences were found for Russians and Ukrainians when compared to other Europeans – in fact, they fall within the range of gene diversity seen throughout Europe and exhibit the unimodal pattern of pairwise sequence differences. Moreover, HVS I sequences in the Russians and Ukrainians are similar or identical to those found in eastern and western European populations. Despite the small genetic distances between Europeans, phylogenetic analysis reveals a considerable heterogeneity of Eastern Slavonic populations – they do not cluster together onto a phylogenetic tree. Analysis of distribution of rare HVS I types shared between populations of Eastern Slavs and other West Eurasians has shown that Russians share rare haplotypes mainly with Germans and Finno–Ugric populations. Of these, subhaplogroup H1 sequence types, which are defined by different combinations of nucleotides 16192T, 16294T, 16304C, 16311C and 16320T, are found predominantly in common between Russians and German-speaking populations. The data obtained allow us to conclude that the Slavonic migrations in early Middle Ages from their putative homeland in central Europe to the east of Europe were accompanied mostly by the same mtDNA types characteristic for the pre-Slavonic populations of eastern Europe.

The mtDNA haplogroup L3e, which is identified by the restriction site +2349 MboI within the Afro-Eurasian superhaplogroup L3 (−3592 HpaI), is omnipresent in Africa but virtually absent in Eurasia (except for neighbouring areas with limited genetic exchange). L3e was hitherto poorly characterised in terms of HVS-I motifs, as the ancestral HVS-I type of L3e cannot be distinguished from the putative HVS-I ancestor of the entire L3 (differing from the CRS by a transition at np 16223). An MboI screening at np 2349 of a large number of Brazilian and Caribbean mtDNAs (encompassing numerous mtDNAs of African ancestry), now reveals that L3e is subdivided into four principal clades, each characterised by a single mutation in HVS-I, with additional support coming from HVS-II and partial RFLP analysis. The apparently oldest of these clades (transition at np 16327) occurs mainly in central Africa and was probably carried to southern Africa with the Bantu expansion(s). The most frequent clade (transition at np 16320) testifies to a pronounced expansion event in the mid-Holocene and seems to be prominent in many Bantu groups from all of Africa. In contrast, one clade (transition at np 16264) is essentially restricted to Atlantic western Africa (including Cabo Verde). We propose a tentative L3e phylogeny that is based on 197 HVS-I sequences. We conclude that haplogroup L3e originated in central or eastern Africa about 46,000 (±14,000) years ago, and was a hitchhiker of much later dispersal and local expansion events, with the rise of food production and iron smelting. Enforced migration of African slaves to the Americas translocated L3e mitochondria, the descendants of which in Brazil and the Caribbean still reflect their different regional African ancestries.

The frequency of Wilson's disease in many populations is thought to be about one in 40000 persons, based on case and autopsy studies. Although the Wilson's disease gene has been identified, there is such a large number of mutations already known that it is not currently feasible to determine disease gene frequency by mutation analysis of a population. We have used a novel approach to obtain an estimate of the number of cases of Wilson's disease expected at birth in the US Caucasian population. We used data from four studies to determine that approximately one-third of Wilson's disease mutations in US Caucasian Wilson's disease patients are due to His→Gln at the 1069 position. We then determined the frequency of this mutation in random DNA samples from 2601 US Caucasian newborns to be 0·285%. Multiplying by three gives an expected Wilson's disease heterozygote frequency of 0·855% and an allele frequency of 0·428%, or 0·00428. These data translate into a Wilson's disease frequency of about one in 55000 births. The 95% confidence interval is rather broad, ranging from about one in 18000 to one in 700000 births, but will be reduced as more data are added.

A cohort study of 1425 persons with Down's syndrome (DS), and of their parents (447 mothers, 435 fathers) and siblings (1176), was set up to investigate death rates from various causes and cancer incidence patterns. In individuals with DS the all-cause death rate was six times that of the national population (SMR = 622: 95% CI 559–693), the excess being attributable to many different causes. These included: leukaemia (SMR = 1304: 95% CI 651–2334); diabetes mellitus (SMR = 982: 95% CI 267–2515); Alzheimer's disease (SMR = 22028: 95% CI 7137–51326); epilepsy (SMR = 1727: 95% CI 744–3403); and congenital anomalies (SMR = 4987: 95% CI 4175–5955). The overall survival showed marked improvements for successive birth cohorts, particularly at young ages. For mothers and fathers of persons with DS, all-cause death rates were 20% lower than national rates and there were no significant excesses from any specific cause. For siblings, all-cause death rates were similar to national rates; the only condition with a significantly raised mortality ratio was colo-rectal cancer (SMR = 793: 95% CI 216–2031), but this may well be a chance finding.

Six Y-chromosome linked microsatellites were typed in a sample of 135 unrelated males representing three different ethnic groups: Arabs, Berbers and Blacks of Jerba Island (Tunisia). Analysis of variation at the six Y chromosome STRs showed significant differences in allele distributions between the Black group and the two other Islander groups. The Black group revealed the highest level of genetic diversity as compared to Arabs and Berbers, while the latter group was the most homogenous. Allele frequencies obtained for the three islander groups analysed were compared to data available for some European, Mediterranean and African populations. Principal-coordinate analyses showed genetic differentiation between the three geographically closed groups of Jerba. The absence of the YAP insertion marker and the position of Arabs and Jerban Blacks near the European cluster would suggest their relative ‘admixture’ with European populations.

Linkage analysis and mouse model knockout studies indicate that loci/genes mapping in different chromosome 1 regions are good candidates for nonsyndromic orofacial cleft (OFC) malformation. On this basis, three different regions of the chromosome 1 have been analysed, by linkage analysis, in 38 families with nonsyndromic OFC. Positive scores were obtained by pairwise analysis and a non-parametric linkage approach for the 1p36 region, with markers close to the MTHFR locus. Additional results allowed us to exclude the presence of an OFC susceptibility gene in the 1q21 and 1q32-42·3 regions.

Susceptibility to coeliac disease has a strong genetic component. The HLA associations have been well described but it is clear that other genes outside this region must also be involved in disease development. Two previous genome-wide linkage studies using the affected sib pair method produced conflicting results. Our own family based linkage study of 16 highly informative pedigrees identified 17 possibly linked regions, each of which produced a result significant at p < 0.05 or less.

We have now investigated these 17 regions in a larger set of pedigrees using more finely spaced markers. Fifty multiply affected families were studied, comprising the 16 pedigrees from the original genome screen plus 34 new highly informative pedigrees. A total of 128 microsatellite markers were genotyped with an average spacing between markers of 5 cM. Two-point and three-point linkage analysis using classical and model free methods identified five potential susceptibility loci with heterogeneity lod scores > 2.0, at 6p12, 11p11, 17q12, 18q23 and 22q13.3. The most significant was a heterogeneity lod of 2.6 at D11S914 on chromosome 11p11. This marker maps to a position implicated in one of the two previous genome scans and taken together these results provide strong support for the existence of a susceptibility locus in this region.

Seven Y-chromosome STR loci, DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392 and DYS393 have been analysed in population samples of Angolares, Forros and Tongas, three ethnic groups from the African archipelago of São Tomé e Príncipe (Gulf of Guinea). Complete typings were obtained for 103 chromosomes, which belonged to 79 different haplotypes. The mean heterozygosity per locus in the overall São Tomean sample was 0.566, with the highest value found among Forros and the lowest among Angolares. Angolares also showed the lowest level of haplotype diversity. On average, the mean pairwise difference between two random haplotypes from Angolares, Forros and Tongas was 4.69, 6.74 and 6.23 repeats, respectively. The genetic distances were found to be statistically significant between Angolares and Forros or Tongas. In accordance, AMOVA revealed that the percentage of variation attributable to differences among groups was only significant when we distinguished between Angolares and non-Angolares. Globally, these results indicate that, with respect to the pool of male lineages of São Tomé e Príncipe, some genetic sub-structuring does exist, basically determined by the Angolares ethnic group.

Positive crossover interference refers to the phenomenon that the occurrence of a crossover reduces the probability of another crossover in its vicinity. There have been studies reporting the presence of positive interference in humans. Some studies have also found evidence suggesting within and between chromosomal interference heterogeneity on some of the chromosomes. However, there has been no systematic study of interference and interference heterogeneity in the whole human genome, using pedigree data without first inferring crossovers. In this paper, we studied the Chi-square interference model and other models extensively to compare the relative performance of each of these models for accounting for interference and measuring strength of interference. Our results showed that the Chi-square model consistently fitted the data well and provided easily interpretable estimates of interference strength. The Chi-square model was then used to study interference and interference heterogeneity within and between chromosomes. We found strong evidence of positive interference in the whole human genome. Our results also indicated that the level of interference was fairly constant in most parts of the genome, but there was some evidence suggesting that the levels of interference for two of the chromosomes were different from the rest. We also found evidence of within chromosomal interference heterogeneity for several of the chromosomes.

Most approaches to analysing complex genetic disorders are based on an underlying model that assumes that the probability of being affected is mainly due to the effect of a major, single disease locus. Where the penetrance (the conditional probability of being affected) is hypothesised to be influenced by known covariates, methods have been developed to accommodate these covariates appropriately in the analysis. Unexplained variation in the incomplete penetrance is then attributed to either unspecified environmental effects or to other genes of small effect that might act epistatically with the ‘disease gene’. Recently, there have been some proposals to incorporate two (or more) possibly epistatic identified loci as major effects in the analysis. However, the effect of two (or more) major epistatic disease genes on the analysis of data that assumes a single ‘disease gene’, and so ignores any other major gene, does not seem to have been explored. This investigation is undertaken here for triad data consisting of affected singletons and their parents. Following development of a quite general underlying genetic model, a global approach to analysing two marker loci for triad data is developed. This approach is the appropriate one for such data where two, possibly epistatic, loci have been identified a priori. The motivation for the development of this methodology is to evaluate the possible effect a second epistatic disease locus might be having on the results for triad data collected and analysed in different population studies, where the underlying analysis is based on an underlying major, single disease locus model. It is shown that, dependent on the population parameters associated with the other unidentified major disease gene, results concerning the single ‘disease gene’ can vary markedly. So, finding that conclusions differ from study to study may be indicative of the ‘disease gene’ under investigation acting epistatically with other major disease genes.

Mortality and cancer incidence were assessed in a cohort of 1373 patients with numerical sex chromosome abnormalities diagnosed at three cytogenetics centres in Britain during 1959–90, and were compared with expectations from national rates. Four hundred patients with Turner's syndrome were followed, of whom 62 died, with a relative risk (RR) of death of 4.16 (95% confidence interval (CI) 3.22–5.39). Turner's syndrome patients had greatly raised risks of death from diseases of the nervous, cardiovascular, respiratory, digestive and genitourinary systems. One hundred and sixty three deaths occurred among 646 patients with Klinefelter's syndrome with a 47,XXY constitution, giving an RR of 1.63 (1.40–1.91). Mortality in these patients was significantly raised from diabetes and diseases of the cardiovascular, respiratory and digestive systems. There was also significantly increased mortality for patients with X polysomy (RR = 2.11 (1.43–3.02)) and Y polysomy (RR = 1.90 (1.20–2.85)), the former with significantly increased mortality from cardiovascular disease and the latter from respiratory disease. The only significantly raised risks of cancer incidence or mortality in the cohort were for lung cancer and breast cancer in patients with Klinefelter's syndrome with a 47,XXY constitution, and non-Hodgkin's lymphoma in men with more than three sex chromosomes.

We demonstrate the use of Grade-of-membership (GoM) (Manton et al. 1994) for sibpair linkage analysis: GoM was used to map the IDDM11 locus to the region of chromosome 14q24.3 identified by Field et al. (1996). Haplotype groups were constructed from sib pair information on the number of shared alleles. The sample consisted of 578 sibling pairs found in 246 multiplex IDDM families. Both siblings were diabetic in 53% of the pairs (AA). Pair members could share 0, 1 or 2 alleles IBS at each of eight linked marker loci spanning IDDM11. Three model-based groups best represented the data on allele sharing: the groups corresponded to ‘No’, ‘One’ and ‘Two’ shared haplotypes for the region. Group ‘Two’ was larger (37% vs. 25%, p<0.0001) and more homogeneous (p<0.0001) than expected by chance consistent with the IDDM11 locus being a determinant of diabetes in multiplex families. Genetic linkage of IDDM to the region was demonstrated by a 19% increase in the proportion of AA pairs over the haplotype groups: ‘No’, 42%; ‘One’, 49%; ‘Two’, 61%, p = 0.0005, representing a 43% relative increase.

A number of methods have previously been described which carry out linkage analysis considering information for two or more loci simultaneously. Apart from some ad hoc methods such as analysing subsamples, these methods use information regarding linkage at all loci under consideration. However, if the actual genotype-specific effects are known for some loci then it would be preferable to consider the genotypes of these loci directly, rather than the amount of allele-sharing they demonstrate. Here we present an extension to our likelihood-based method of model-free linkage analysis as implemented in the MFLINK program. This allows the incorporation of liability classes. The genotypes of a locus known to affect risk can be used to assign subjects to liability classes prior to carrying out linkage tests at other loci. An example application is presented for genome scan data on Alzheimer's disease with analysis conditional on Apoliprotein E (APOE) genotypes. The results provide support for the existence of additional susceptibility loci linked to D10S1211 and to D12S358.

Single nucleotide polymorphisms (SNPs) are very common throughout the genome and hence are potentially valuable for mapping disease susceptibility loci by detecting association between SNP markers and disease. However as SNPs are biallelic they may have relatively little power in association studies compared with the information that would be obtainable if marker haplotypes were available and could be used efficiently. Modelling the evolutionary events leading to linkage disequilibrium is very complex and many methods that seek to use information from multiple markers simultaneously need to make simplifying assumptions and may only be applicable when marker haplotypes, rather than genotypes, are available for analysis. We explore the properties of a simple application of a standard artificial neural network to this problem. The pattern-recognition properties of the network are used in the hope that marker haplotypes implicit in the genotypes will differ between cases and controls in a way which will lead to the network being able to classify the subjects correctly, according to their marker genotype. This method makes no assumptions at all regarding population history or the marker map, and can be applied to genotypes, as would be available from a simple case-control sample, without any need to determine haplotypes. Through application to data simulated under a very wide range of assumptions we show that such an analysis produces a useful augmentation in power above that which would be achieved by testing each marker individually, in particular when more than one mutation has occurred in a disease gene at different points in evolution. The application of neural networks to such problems shows considerable promise and further work could usefully be directed towards optimising the design and implementation of such networks.

In this work we present results on DYS434, DYS437, DYS438 and DYS439 loci studied in three population samples from North Portugal (N: 69), Macao (N: 59) and Mozambique (N: 64). Gene and haplotype diversity values are presented and compared. Gene diversity values ranged from 0.0290 to 0.0620 for DYS434; 0.0615 to 0.5959 for DYS437; 0.4906 to 0.6424 for DYS438; 0.5873 to 0.7038 for DYS439. The highest average gene diversity was found in Macao and the lowest in Mozambique. Haplotype diversity in North Portugal, Macao and Mozambique was calculated to be 0.925, 0.928 and 0.787, respectively.

Allele and haplotype frequency distributions for all markers were compared between the three populations. At the haplotype level all the differences between pairs of samples were significant. Sequencing analysis was performed for all alleles found in the four loci. Identical flanking sequences were observed with most of the alleles differing only by the repeat number. However, two variations were found in allele 10 of DYS438: one in a Macao sample presenting a TTTTA before the last TTTTC repetition and one in a Portuguese sample showing a base substitution (A/C) at position 7 downstream from the tandem repeat. A base substitution (C/T) at position 3 upstream from the repeat motif was also found in allele 14 of DYS437 in a sample from Mozambique.