Multiple Advantageous Amino Acid Variants in the NAT2 Gene in Human Populations

Background: Genetic variation at NAT2 has been long recognized as the cause of differential ability to metabolize a wide variety of drugs of therapeutic use. Here, we explore the pattern of genetic variation in 12 human populations that significantly extend the geographic range and resolution of previous surveys, to test the hypothesis that different dietary regimens and lifestyles may explain inter-population differences in NAT2 variation. Methodology/Principal Findings: The entire coding region was resequenced in 98 subjects and six polymorphic positions were genotyped in 150 additional subjects. A single previously undescribed variant was found (34T>C; 12Y>H). Several aspects of the data do not fit the expectations of a neutral model, as assessed by coalescent simulations. Tajima's D is positive in all populations, indicating an excess of intermediate alleles. The level of between-population differentiation is low, and is mainly accounted for by the proportion of fast vs. slow acetylators. However, haplotype frequencies significantly differ across groups of populations with different subsistence. Conclusions/Significance: Data on the structure of haplotypes and their frequencies are compatible with a model in which slow-causing variants were present in widely dispersed populations before major shifts to pastoralism and/or agriculture. In this model, slow-causing mutations gained a selective advantage in populations shifting from hunting-gathering to pastoralism/agriculture. We suggest the diminished dietary availability of folates resulting from the nutritional shift, as the possible cause of the fitness increase associated to haplotypes carrying mutations that reduce enzymatic activity. © 2008 Luca et al

Enlarging the gene-geography of Europe and the Mediterranean area to STR loci of common forensic use: longitudinal and latitudinal frequency gradients

Background: Tetranucleotide Short Tandem Repeats (STRs) for human identification and common use in forensic cases have recently been used to address the population genetics of the North-Eastern Mediterranean area. However, to gain confidence in the inferences made using STRs, this kind of analysis should be challenged with changes in three main aspects of the data, i.e. the sizes of the samples, their distance across space and the genetic background from which they are drawn.Aim: To test the resilience of the gradients previously detected in the North-Eastern Mediterranean to the enlargement of the surveyed area and population set, using revised data.Subjects and methods: STR genotype profiles were obtained from a publicly available database (PopAffilietor databank) and a dataset was assembled including >7000 subjects from the Arabian Peninsula to Scandinavia, genotyped at eight loci. Spatial principal component analysis (sPCA) was applied and the frequency maps of the nine alleles which contributed most strongly to sPC1 were examined in detail.Results: By far the greatest part of diversity was summarised by a single spatial principal component (sPC1), oriented along a SouthEast-to-NorthWest axis. The alleles with the top 5% squared loadings were TH01(9.3), D19S433(14), TH01(6), D19S433(15.2), FGA(20), FGA(24), D3S1358(14), FGA(21) and D2S1338(19). These results confirm a clinal pattern over the whole range for at least four loci (TH01, D19S433, FGA, D3S1358).Conclusions: Four of the eight STR loci (or even alleles) considered here can reproducibly capture continental arrangements of diversity. This would, in principle, allow for the exploitation of forensic data to clarify important aspects in the formation of local gene pools.Italian Ministry of Justice [CUP E81J10001270005

DNA repair gene variants are associated with an increased risk of myelodysplastic syndromes in a Czech population

Abstract Background Interactions between genetic variants and risk factors in myelodysplastic syndromes are poorly understood. In this case–control study, we analyzed 1 421 single nucleotide polymorphisms in 408 genes involved in cancer-related pathways in 198 patients and 292 controls. Methods The Illumina SNP Cancer Panel was used for genotyping of samples. The chi-squared, p-values, odds ratios and upper and lower limits of the 95% confidence interval were calculated for all the SNPs that passed the quality control filtering. Results Gene-based analysis showed nine candidate single nucleotide polymorphisms significantly associated with the disease susceptibility (q-value . Four of these polymorphisms were located in oxidative damage/DNA repair genes (LIG1, RAD52, MSH3 and GPX3), which may play important roles in the pathobiology of myelodysplastic syndromes. Two of nine candidate polymorphisms were located in transmembrane transporters (ABCB1 and SLC4A2), contributing to individual variability in drug responses and patient prognoses. Moreover, the variations in the ROS1 and STK6 genes were associated with the overall survival of patients. Conclusions Our association study identified genetic variants in Czech population that may serve as potential markers for myelodysplastic syndromes.</p

Loci and alleles with the strongest impact on the SpatialPCA eigenvalues 1 and 2.

<p>Loci and alleles with the strongest impact on the SpatialPCA eigenvalues 1 and 2.</p

Maps of: A) scores for the 41 locations in sPC1 obtained on the full dataset with adegenet; B) scores in sPC2 obtained as in A; C) posterior assignment probabilities of the 41 locations to either of two clusters obtained on the reduced dataset derived from sPC1 with Geneland; D) posterior assignment probabilities of the 41 locations to either of two clusters obtained on the reduced dataset derived from sPC2 with Geneland.

<p>In A and B white and black squares represent negative and positive scores, respectively, with square size proportional to the absolute value (inset in panel A). In each of panels C and D shades of grey indicate probabilities of assignment to one of two mutually exclusive clusters from 0 (dark grey) to 1 (white). Color versions of panels C and D are reported in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0167065#pone.0167065.s007" target="_blank">S7 Fig</a>.</p

Representation of effective migration surfaces as obtained with EEMS on the reduced datasets derived from sPC 1 (A) and sPC2 (B).

<p>The coloured area covers only the user-defined polygon. The grid used by the program is shown in grey. Note that only 34 sampled demes appear (black dots, with size proportional to the n. of individuals), assigned to a grid vertex and not necessarily coinciding exactly with the original sampling location. Pooled locations were (numbered as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0167065#pone.0167065.s011" target="_blank">S1 Table</a>): 6+7, 9+10, 13+14+15+16, 25+26, 30+32. Note the different colour scales between the two maps. In both maps brown belts correspond to low migration values, i.e. barriers to gene flow.</p