Construction of a YAC contig covering human chromosome 6p22

A contig covering human chromosome 6p22 that consists of 134 YAC clones aligned based on the presence/absence of 52 DNA markers is presented. This contig overlaps with the 6p23 contig at its telomeric end and with the 6p21.3 contig at its centromeric end. The order of loci within the contig resolves the relative positions of several genetically mapped markers. Among the additional markers used here, there are eight novel PCR assays. The 12 known genes and anonymous ESTs located within the contig establish a first step toward a transcriptional map of this region. The instability of YAC clones observed during this work is also discussed. (C) 1996 Academic Press, Inc

Complete Loss of P/Q Calcium Channel Activity Caused by a CACNA1A Missense Mutation Carried by Patients with Episodic Ataxia Type 2

Familial hemiplegic migraine, episodic ataxia type 2 (EA2), and spinocerebellar ataxia type 6 are allelic disorders of the CACNA1A gene (coding for the α1A subunit of P/Q calcium channels), usually associated with different types of mutations (missense, protein truncating, and expansion, respectively). However, the finding of expansion and missense mutations in patients with EA2 has blurred this genotype-phenotype correlation. We report the first functional analysis of a new missense mutation, associated with an EA2 phenotype—that is, T→C transition of nt 4747 in exon 28, predicted to change a highly conserved phenylalanine residue to a serine at codon 1491, located in the putative transmembrane segment S6 of domain III. Patch-clamp recording in HEK 293 cells, coexpressing the mutagenized human α1A-2 subunit, together with human β4 and α2δ subunits, showed that channel activity was completely abolished, although the mutated protein is expressed in the cell. These results indicate that a complete loss of P/Q channel function is the mechanism underlying EA2, whether due to truncating or to missense mutations

DNA Damage Stress Response and Follicle Activation: Signaling Routes of Mammalian Ovarian Reserve

Chemotherapy regimens and radiotherapy are common strategies to fight cancer. In women, these therapies may cause side effects such as premature ovarian insufficiency (POI) and infertility. Clinical strategies to protect the ovarian reserve from the lethal effect of cancer therapies needs better understanding of the mechanisms underlying iatrogenic loss of follicle reserve. Recent reports demonstrate a critical role for p53 and CHK2 in the oocyte response to different DNA stressors, which are commonly used to treat cancer. Here we review the molecular mechanisms underlying the DNA damage stress response (DDR) and discuss crosstalk between DDR and signaling pathways implicated in primordial follicle activation

Alcohol use disorder and GABAB receptor gene polymorphisms in an Italian sample: haplotype frequencies, linkage disequilibrium and association studies

Background: Alcohol use disorder (AUD) is a complex trait with genetic and environmental influences. Several gene variants have been associated with the risk for AUD, including genes encoding the sub-units of the γ-aminobutyric acid (GABA) receptors. Aim: This study evaluated whether specific single nucleotide polymorphisms (SNPs) in genes encoding GABAB receptor sub-units can be considered as candidates for the risk of AUD. Subjects and methods: Seventy-four AUD subjects and 128 Italian controls were genotyped for 10 SNPs in genes encoding GABA-B1 and GABA-B2 sub-units (GABBR1 and GABBR2). Allele, genotype, and haplotype frequencies were tested for the association with the AUD trait. Results: A significant difference between AUD individuals and controls was observed at genotype level for rs2900512 of GABBR2 gene. The homozygous T/T genotype was not found in the controls, whereas it was over-represented in the AUD individuals. Under the recessive model (T/T vs C/T + C/C) this result was statistically significant, as well as the Odds Ratio for the association with the AUD trait. Conclusions: The results provide preliminary data on the association between GABAB receptor gene variation and risk of AUD. To confirm this finding, studies with larger samples and additional characterisation of the phenotypic AUD trait are required

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

Fst analysis in the main geographic regions.

<p>Fst analysis in the main geographic regions.</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

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

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