No description available.

No description available.

No description available.

No description available.

No description available.

The aim of this project was to clone the gene encoding the catalytic subunit of the rat DNA replication enzyme, DNA polymerase alpha. A strategy was adopted in which cDNA clones expressing the catalytic subunit sequences would be identified using anti-DNA polymerase antibodies. DNA polymerase alpha was partially purified from regenerating rat liver and exponentially growing rat Y3 myeloma cells. The catalytic subunit was identified as a 170-180kD polypeptide by activity gel analysis of partially purified Y3 cell fractions. The catalytic subunit was found to be susceptible to degradation but without loss of polymerase activity. Glycerol gradient analysis indicated a two stage degradation of DNA polymerase in vivo. Sera were collected from mice immunised with partially purified DNA polymerase alpha from regenerated rat liver. These sera cross-reacted with Western-blotted Y3 cell fractions; removed polymerase activity from solution in plate binding assays and bound alpha polymerase activity (140-180kD) on an immuno-adsorption column cDNA was synthesised using size selected mRNA from exponentially growing Y3 cells and cloned into the expression vectors pUC8 and ?gtll, both of which utilise the lac Z gene to express cloned DNA sequences. Immunoscreening of the ?gtll library was frustrated by non-specific binding of the serum. This non-specific binding was overcome by pre-adsorbing the serum against a lysate of E. coli JM 83. Screening of the pUC8 library revealled 27 out of 2.25x104 colonies which bound pre-adsorbed anti-DNA polymerase alpha serum.

The aim of the project was to determine the sequence of the gene encoding glucose-6-phosphate dehydrogenase (G6PDH) in the industrially used, but genetically little explored yeast Candida utilis. In the first strategy, a C. utilis DNA library was constructed in the expression vector phage lambda gt11, and was screened immunologically with antiserum raised against C. utilis G6PDH. The second strategy involved construction of libraries in the plasmid vector pTZ18R and screening with a mixed oligonucleotide probe. Two methods were developed that allow DNA, of appropriate quality for the construction of DNA libraries, to be prepared from C. utilis cells. Both involve centrifugation of C. utilis lysates through caesium trifluoroacetate gradients. A rabbit antiserum was raised against a commercial preparation of C. utilis G6PDH. It reacted with Western blotted C. utilis G6PDH, and non-specific binding of the antiserum to Western blotted E. coli protein was reduced by treatment with an E. coli extract. Antiserum pretreated in this way was used for immunological screening. Sequence information was determined for the inserts of 7 phage identified during immunological screening. None of the insert sequences was considered to contain part of the C. utilis G6PDH coding sequence. One putative positive colony was identified during the screening of the pTZ18R libraries. Sequence determination showed the insert to contain a region complementary to 16 bases in one of the 17-base long probe oligonucleotides. This insert was considered not to contain part of the C. utilis G6PDH coding sequence. Time did not permit further work which, using the methods developed, should now permit determination of the C. utilis G6PDH gene sequence.

Gene set enrichment analysis aims to discover sets of genes, such as biological pathways or protein complexes, which may show moderate but coordinated differentiation across experimental conditions. The existing gene set enrichment approaches utilize single gene statistic as a measure of differentiation for individual genes. These approaches do not utilize any inter-gene correlations, but it has been known that genes in a pathway often interact with each other. Motivated by the need for taking gene dependence into account, we propose a novel gene set enrichment algorithm, where the gene-gene correlation is addressed via a gene-pair representation strategy. Relying on an appropriately defined gene pair statistic, the gene set statistic is formulated using a competitive null hypothesis. Extensive simulation studies show that our proposed approach can correctly control the type I error (false positive rate), and retain good statistical power for detecting true differential expression. The new method is also applied to analyze several gene expression datasets. / October 2016

No description available.

No description available.