Comparative genomic sequencing analysis of a region in human chromosome 11p15.3, mouse chromosome 7 and analysis of the novel STK33, Stk33 gene

The comparative genomic sequence analysis of a region in human chromosome 11p15.3 and its homologous segment in mouse chromosome 7 between ST5 and LMO1 genes has been performed. 158,201 bases were sequenced in the mouse and compared with the syntenic region in human, partially available in the public databases. The analysed region exhibits the typical eukaryotic genomic structure and compared with the close neighbouring regions, strikingly reflexes the mosaic pattern distribution of (G+C) and repeats content despites its relative short size. Within this region the novel gene STK33 was discovered (Stk33 in the mouse), that codes for a serine/threonine kinase. The finding of this gene constitutes an excellent example of the strength of the comparative sequencing approach. Poor gene-predictions in the mouse genomic sequence were corrected and improved by the comparison with the unordered data from the human genomic sequence publicly available. Phylogenetical analysis suggests that STK33 belongs to the calcium/calmodulin-dependent protein kinases group and seems to be a novelty in the chordate lineage. The gene, as a whole, seems to evolve under purifying selection whereas some regions appear to be under strong positive selection. Both human and mouse versions of serine/threonine kinase 33, consists of seventeen exons highly conserved in the coding regions, particularly in those coding for the core protein kinase domain. Also the exon/intron structure in the coding regions of the gene is conserved between human and mouse. The existence and functionality of the gene is supported by the presence of entries in the EST databases and was in vivo fully confirmed by isolating specific transcripts from human uterus total RNA and from several mouse tissues. Strong evidence for alternative splicing was found, which may result in tissue-specific starting points of transcription and in some extent, different protein N-termini. RT-PCR and hybridisation experiments suggest that STK33/Stk33 is differentially expressed in a few tissues and in relative low levels. STK33 has been shown to be reproducibly down-regulated in tumor tissues, particularly in ovarian tumors. RNA in-situ hybridisation experiments using mouse Stk33-specific probes showed expression in dividing cells from lung and germinal epithelium and possibly also in macrophages from kidney and lungs. Preliminary experimentation with antibodies designed in this work, performed in parallel to the preparation of this manuscript, seems to confirm this expression pattern. The fact that the chromosomal region 11p15 in which STK33 is located may be associated with several human diseases including tumor development, suggest further investigation is necessary to establish the role of STK33 in human health.

On the car sequencing problem: analysis and solution methods

This work deals with the car sequencing (CS) problem, a combinatorial optimization problem for sequencing mixed-model assembly lines. The aim is to find a production sequence for different variants of a common base product, such that work overload of the respective line operators is avoided or minimized. The variants are distinguished by certain options (e.g., sun roof yes/no) and, therefore, require different processing times at the stations of the line. CS introduces a so-called sequencing rule H:N for each option, which restricts the occurrence of this option to at most H in any N consecutive variants. It seeks for a sequence that leads to no or a minimum number of sequencing rule violations. In this work, CS’ suitability for workload-oriented sequencing is analyzed. Therefore, its solution quality is compared in experiments to the related mixed-model sequencing problem. A new sequencing rule generation approach as well as a new lower bound for the problem are presented. Different exact and heuristic solution methods for CS are developed and their efficiency is shown in experiments. Furthermore, CS is adjusted and applied to a resequencing problem with pull-off tables.