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71.
Spatial organization of protein-RNA interactions in the branch site-3' splice site region during pre-mRNA splicing in yeast 总被引:2,自引:0,他引:2 下载免费PDF全文
A series of efficiently spliced pre-mRNA substrates containing single 4-thiouridine residues were used to monitor RNA-protein interactions involving the branch site-3' splice site-3' exon region during yeast pre-mRNA splicing through cross-linking analysis. Prior to the assembly of the prespliceosome, Mud2p and the branch point bridging protein cross-link to a portion of this region in an ATP-independent fashion. Assembly of the prespliceosome leads to extensive cross-linking of the U2-associated protein Hsh155p to this region. Following the first step of splicing and in a manner independent of Prp16p, the U5 small nuclear ribonucleoprotein particle-associated protein Prp8p also associates extensively with the branch site-3' splice site-3' exon region. The subsequent cross-linking of Prp16p to the lariat intermediate is restricted to the 3' splice site and the adjacent 3' exon sequence. Using modified substrates to either mutationally or chemically block the second step, we found that the association of Prp22p with the lariat intermediate represents an authentic transient intermediate and appears to be restricted to the last eight intron nucleotides. Completion of the second step leads to the cross-linking of an unidentified approximately 80-kDa protein near the branch site sequence, suggesting a potential role for this protein in a later step in intron metabolism. Taken together, these data provide a detailed portrayal of the dynamic associations of proteins with the branch site-3' splice site region during spliceosome assembly and catalysis. 相似文献
72.
Celia MT Greenwood Shuying Sun Justin Veenstra Nancy Hamel Bethany Niell Stephen Gruber William D Foulkes 《BMC genetics》2010,11(1):39
Background
Several founder mutations leading to increased risk of cancer among Ashkenazi Jewish individuals have been identified, and some estimates of the age of the mutations have been published. A variety of different methods have been used previously to estimate the age of the mutations. Here three datasets containing genotype information near known founder mutations are reanalyzed in order to compare three approaches for estimating the age of a mutation. The methods are: (a) the single marker method used by Risch et al., (1995); (b) the intra-allelic coalescent model known as DMLE, and (c) the Goldgar method proposed in Neuhausen et al. (1996), and modified slightly by our group. The three mutations analyzed were MSH2*1906 G->C, APC*I1307K, and BRCA2*6174delT.Results
All methods depend on accurate estimates of inter-marker recombination rates. The modified Goldgar method allows for marker mutation as well as recombination, but requires prior estimates of the possible haplotypes carrying the mutation for each individual. It does not incorporate population growth rates. The DMLE method simultaneously estimates the haplotypes with the mutation age, and builds in the population growth rate. The single marker estimates, however, are more sensitive to the recombination rates and are unstable. Mutation age estimates based on DMLE are 16.8 generations for MSH2 (95% credible interval (13, 23)), 106 generations for I1037K (86-129), and 90 generations for 6174delT (71-114).Conclusions
For recent founder mutations where marker mutations are unlikely to have occurred, both DMLE and the Goldgar method can give good results. Caution is necessary for older mutations, especially if the effective population size may have remained small for a long period of time.73.
Ruoqi Peng Sriram Sridhar Gaurav Tyagi Jonathan E. Phillips Rosario Garrido Paul Harris Lisa Burns Lorena Renteria John Woods Leena Chen John Allard Palanikumar Ravindran Hans Bitter Zhenmin Liang Cory M. Hogaboam Chris Kitson David C. Budd Jay S. Fine Carla MT. Bauer Christopher S. Stevenson 《PloS one》2013,8(4)
The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF), has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease. 相似文献
74.
Functional normalization of 450k methylation array data improves replication in large cancer studies
Jean-Philippe Fortin Aurélie Labbe Mathieu Lemire Brent W Zanke Thomas J Hudson Elana J Fertig Celia MT Greenwood Kasper D Hansen 《Genome biology》2014,15(11)
We propose an extension to quantile normalization that removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using data sets from The Cancer Genome Atlas and a large case–control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.
Electronic supplementary material
The online version of this article (doi:10.1186/s13059-014-0503-2) contains supplementary material, which is available to authorized users. 相似文献75.