SIRT1 Allele Frequencies in Depressed Patients of European Descent in Russia.

Depressive disorder (DD) is a widespread mental disorder. Although DD is to some extent inherited, the genes contributing to the risk of this disorder and its genetic mechanisms remain poorly understood. A recent large-scale genome-wide association Chinese study revealed a strong association between the SIRT1 gene variants and DD. The aim of this study was to analyze the occurrence of heterozygote carriers and search for rare SNP variants of the SIRT1 gene in a cohort of DD patients as compared with a cohort of randomly selected members of the Russian population. The complete coding sequences of the SIRT1 gene from 1024 DNA samples from the general Russian population and from 244 samples from patients with DD were analyzed using targeted sequencing. Four new genetic variants of the SIRT1 were discovered. While no significant differences in the allele frequencies were found between the DD patients and the general population, differences between the frequencies of homozygote carriers of specific alleles and occurrences of heterozygous were found to be significant for rs2236318 (P < 0.0001), and putatively, rs7896005 (P < 0.05), and rs36107781 (P < 0.05). The study found for the first time that two new SNPs (i.e., 10:69665829 and 10:69665971) along with recently reported ones (rs773025707 and rs34701705), are putatively associated with DD. The revealed DD-associated SIRT1 SNPs might confer susceptibility to this disorder in Russian population of European descent.

Computational approaches to study the effects of small genomic variations.

Advances in DNA sequencing technologies have led to an avalanche-like increase in the number of gene sequences deposited in public databases over the last decade as well as the detection of an enormous number of previously unseen nucleotide variants therein. Given the size and complex nature of the genome-wide sequence variation data, as well as the rate of data generation, experimental characterization of the disease association of each of these variations or their effects on protein structure/function would be costly, laborious, time-consuming, and essentially impossible. Thus, in silico methods to predict the functional effects of sequence variations are constantly being developed. In this review, we summarize the major computational approaches and tools that are aimed at the prediction of the functional effect of mutations, and describe the state-of-the-art databases that can be used to obtain information about mutation significance. We also discuss future directions in this highly competitive field.

Limitations on the recombinant plasmid selection by Lac(+)/Lac(-) colony phenotype detection.

Lac(+)/Lac(-) selection of recombinant plasmids based on the insertional inactivation of LacZalpha gene cannot differentiate recombinant clones in some cases. Several fragments of exon 11 of human brca1 gene were cloned in LacZalpha-containing plasmids so that frameshift appeared at the 5(')-end of the fragments tested but these fragments were in frame with the part of LacZalpha situated downstream of the polylinker. All plasmids except one caused blue colonies formation after being transformed in Escherichia coli LacZDeltaM15 cells in spite of the frameshift. The fact may be explained by reinitiation of translation within the mRNA transcribed from the inserted DNA fragments at in-frame AUG, GUG, and UUG. The data demonstrated limitations on the Lac(+)/Lac(-) selection of LacZalpha-based recombinant plasmids.