A peak alignment algorithm with novel improvements in application to electropherogram analysis.

Alignment of peaks in electropherograms or chromatograms obtained from experimental techniques such capillary electrophoresis remains a significant challenge. Accurate alignment is critical for accurate interpretation of various classes of nucleic acid analysis technologies, including conventional DNA sequencing and new RNA structure probing technologies. An automated alignment algorithm was developed based on dynamic programming to align multiple-peak time-series data both globally and locally. This algorithm relies on a new peak similarity measure and other features such as time penalties, global constraints, and minimum-similarity scores and results in rapid, highly accurate comparisons of complex time-series datasets. As a demonstrative case study, the developed algorithm was applied to analysis of capillary electrophoresis data from a Selective 2'-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) evaluation of RNA secondary structure. The algorithm yielded robust analysis of challenging SHAPE probing data. Experimental results show that the peak alignment algorithm corrects retention time variation efficiently due to the presence of fluorescent tags on fragments and differences in capillaries. The tools can be readily adapted for the analysis other biological datasets in which peak retention times vary.

Human growth hormone 1 (GH1) gene expression: complex haplotype-dependent influence of polymorphic variation in the proximal promoter and locus control region.

The proximal promoter region of the human pituitary expressed growth hormone (GH1) gene is highly polymorphic, containing at least 15 single nucleotide polymorphisms (SNPs). This variation is manifest in 40 different haplotypes, the high diversity being explicable in terms of gene conversion, recurrent mutation, and selection. Functional analysis showed that 12 haplotypes were associated with a significantly reduced level of reporter gene expression whereas 10 haplotypes were associated with a significantly increased level. The former tend to be more prevalent in the general population than the latter (p<0.01), possibly as a consequence of selection. Although individual SNPs contributed to promoter strength in a highly interactive and non-additive fashion, haplotype partitioning was successful in identifying six SNPs as major determinants of GH1 gene expression. The prediction and functional testing of hitherto unobserved super-maximal and sub-minimal promoter haplotypes was then used to test the efficacy of the haplotype partitioning approach. Electrophoretic mobility shift assays demonstrated that five SNP sites exhibit allele-specific protein binding. An association was noted between adult height and the mean in vitro expression value corresponding to an individual's GH1 promoter haplotype combination (p=0.028) although only 3.3% of the variance of adult height was found to be explicable by reference to this parameter. Three additional SNPs, identified within sites I and II of the upstream locus control region (LCR), were ascribed to three distinct LCR haplotypes. A series of LCR-GH1 proximal promoter constructs were used to demonstrate that 1) the LCR enhanced proximal promoter activity by up to 2.8-fold depending upon proximal promoter haplotype, and that 2) the activity of a given proximal promoter haplotype was also differentially enhanced by different LCR haplotypes. The genetic basis of inter-individual differences in GH1 gene expression thus appears to be extremely complex.