FGF4 Independent Derivation of Trophoblast Stem Cells from the Common Vole

The derivation of stable multipotent trophoblast stem (TS) cell lines from preimplantation, and early postimplantation mouse embryos has been reported previously. FGF4, and its receptor FGFR2, have been identified as embryonic signaling factors responsible for the maintenance of the undifferentiated state of multipotent TS cells. Here we report the derivation of stable TS-like cell lines from the vole M. rossiaemeridionalis, in the absence of FGF4 and heparin. Vole TS-like cells are similar to murine TS cells with respect to their morphology, transcription factor gene expression and differentiation in vitro into derivatives of the trophectoderm lineage, and with respect to their ability to invade and erode host tissues, forming haemorrhagic tumours after subcutaneous injection into nude mice. Moreover, vole TS-like cells carry an inactive paternal X chromosome, indicating that they have undergone imprinted X inactivation, which is characteristic of the trophoblast lineage. Our results indicate that an alternative signaling pathway may be responsible for the establishment and stable proliferation of vole TS-like cells

On the origin of the H1N1 (A/USSR/90/77) influenza virus

The influenza virus H1N1 (the A/USSR/90/77 strain) that reappeared in 1977 after the H1N1 influenza viruses had disappeared from the human population, is compared with the A/FM/1/47 and the A/FW/1/50 influenza viruses by the method of oligonucleotide mapping of individual segments of the viral RNAs. Seven genes of the A/USSR/90/77 virus appear to be very similar to the corresponding genes of the A/FW/1/50 virus, whereas the gene coding for the M protein displays considerable homology to the corresponding gene of the A/FM/1/47 virus. The data demonstrate that the A/USSR/90/77 strain is a recombinant virus

Detection of regulatory SNPs in human genome using ChIP-seq ENCODE data.

A vast amount of SNPs derived from genome-wide association studies are represented by non-coding ones, therefore exacerbating the need for effective identification of regulatory SNPs (rSNPs) among them. However, this task remains challenging since the regulatory part of the human genome is annotated much poorly as opposed to coding regions. Here we describe an approach aggregating the whole set of ENCODE ChIP-seq data in order to search for rSNPs, and provide the experimental evidence of its efficiency. Its algorithm is based on the assumption that the enrichment of a genomic region with transcription factor binding loci (ChIP-seq peaks) indicates its regulatory function, and thereby SNPs located in this region are more likely to influence transcription regulation. To ensure that the approach preferably selects functionally meaningful SNPs, we performed enrichment analysis of several human SNP datasets associated with phenotypic manifestations. It was shown that all samples are significantly enriched with SNPs falling into the regions of multiple ChIP-seq peaks as compared with the randomly selected SNPs. For experimental verification, 40 SNPs falling into overlapping regions of at least 7 TF binding loci were selected from OMIM. The effect of SNPs on the binding of the DNA fragments containing them to the nuclear proteins from four human cell lines (HepG2, HeLaS3, HCT-116, and K562) has been tested by EMSA. A radical change in the binding pattern has been observed for 29 SNPs, besides, 6 more SNPs also demonstrated less pronounced changes. Taken together, the results demonstrate the effective way to search for potential rSNPs with the aid of ChIP-seq data provided by ENCODE project

Summary of the experimental testing of putative rSNPs selected from S_omim.

<p>1- no influence, 2- influence of SNP on the band intensity, 3- influence of SNP on the band mobility.</p

enrichment of S_gwas sample and its high-confidence derivatives, S_pV, S_OR and S_int, as well as S_r sample with putative rSNPs as a function of cut-off number of overlapping TF binding loci (<i>i</i>) for defining OTFRs.

<p>500 bootstrap iterations were performed for each point. The resulting standard deviations and confidence intervals are shown by error bars and colour-filled areas,respectively. The subsamples of S_gwas were generated with filtering of SNPs by P-value <1 e–7 (S_pV), OR>3 and <0.3 (S_OR), and by both criteria (S_int). S_gwas sample was extracted from NHGRI GWAS catalog.</p

A variety of SNP effects on binding of the corresponding oligonucleotides to nuclear proteins from K562 cells.

<p>rs79734816:C>T (<i>A</i>), rs2071002:A>C (<i>B</i>), and rs74393987:C>T (<i>C</i>) change the number and intensity of bands, while rs75996864:G>T (<i>D</i>) affect only band intensity, and 7961894:C>T (<i>E</i>) do not have any. Changes in the binding of allelic variants with the nuclear proteins are indicated by arrows.</p

The used approach to genome-wide selection of rSNPs.

<p>Computational analysis was applied to identify the SNPs in the most likely regulatory regions of the human genome and predict rSNPs for experimental verification.</p