Genomic organization, expression analysis, and chromosomal localization of the mouse PEX3 gene encoding a peroxisomal assembly protein

The peroxin Pex3p has been identified as an integral peroxisomal membrane protein in yeast where pex3 mutants lack peroxisomal remnant structures. Although not proven in higher organisms, a role of this gene in the early peroxisome biogenesis is suggested, We report here the cDNA cloning and the genomic structure of the mouse PEX3 gene. The 2 kb cDNA encodes a polypeptide of 372 amino acids (42 kDa). The gene spans a region of 30 kb, contains 12 exons and 11 introns and is located on band A of chromosome 10, The putative promoter region exhibits characteristic housekeeping features. PEX3 expression was identified in all tissues analyzed, with the strongest signals in liver and in testis, and could not be induced by fenofibrate. The data presented may be useful for the generation of a mouse model defective in PEX3 in order to clarify the yet unknown functional impact of disturbances in early peroxisomal membrane assembly

Functional promoter analysis using an approach based on an in vitro evolution strategy

In vitro evolution imitates the natural evolution of genes and has been very successfully applied to the modification of coding sequences, but it has not yet been applied to promoter sequences. We propose an alternative method for functional promoter analysis by applying an in vitro evolution scheme consisting of rounds of error-prone PCR, followed by DNA shuffling and selection of mutant promoter activities. We modified the activity in embryogenic sugarcane cells of the promoter region of the Goldfinger isolate of banana streak virus and obtained mutant promoter sequences that showed an average mutation rate of 2.5% after applying one round of error-prone PCR and DNA shuffling. Selection and sequencing of promoter sequences with decreased or unaltered activity allowed us to rapidly map the position of one cis-acting element that influenced promoter activity in embryogenic sugarcane cells and to discover neutral mutations that did not affect promoter Junction. The selective-shotgun approach of this promoter analysis method immediately after the promoter boundaries have been defined by 5' deletion analysis dramatically reduces the labor associated with traditional linker-scanning deletion analysis to reveal the position of functional promoter domains. Furthermore, this method allows the entire promoter to be investigated at once, rather than selected domains or nucleotides, increasing the, prospect of identifying interacting promoter regions

A generalized joint inference approach for citation matching

Citation matching is the problem of extracting bibliographic records from citation lists in technical papers, and merging records that represent the same publication. Generally, there are three types of data- sets in citation matching, i.e., sparse, dense and hybrid types. Typical approaches for citation matching are Joint Segmentation (Jnt-Seg) and Joint Segmentation Entity Resolution (Jnt-Seg-ER). Jnt-Seg method is effective at processing sparse type datasets, but often produces many errors when applied to dense type datasets. On the contrary, Jnt-Seg-ER method is good at dealing with dense type datasets, but insufficient when sparse type datasets are presented. In this paper we propose an alternative joint inference approach&ndash;Generalized Joint Segmentation (Generalized-Jnt-Seg). It can effectively deal with the situation when the dataset type is unknown. Especially, in hybrid type datasets analysis there is often no a priori information for choosing Jnt-Seg method or Jnt-Seg-ER method to process segmentation and entity resolution. Both methods may produce many errors. Fortunately, our method can effectively avoid error of segmentation and produce well field boundaries. Experimental results on both types of citation datasets show that our method outperforms many alternative approaches for citation matching.<br /