s.kumar@asu.edu.

Although it is well established that cis-acting regulatory variation contributes to morphological evolution between species, few concrete examples of polymorphism affecting developmental patterning within species have been demonstrated. Early embryogenesis in Drosophila is initiated by a gradient of Bicoid morphogen activity that results in differential expression of multiple target genes. In a screen for genetic variation affecting this process, we surveyed 96 wild-type lines of Drosophila melanogaster for polymorphisms in binding sites within 16 Bicoid cis-regulatory response elements. One common polymorphism in the orthodenticle (otd) early head enhancer is associated with a complex series of indels/substitutions that define two distinct haplotypes. The middle region of this enhancer exhibits an unusual pattern of nucleotide diversity that does not easily fit into standard models of selection and demography. Population Gene Expression Maps, generated by extracting binary expression profiles from normalized embryo images, revealed a ventral reduction of otd transcript abundance in one of the haplotypes that was recapitulated in expression of transgenic constructs containing the two alleles. We thus demonstrate that even a process as robust as early developmental patterning is affected by standing genetic variation, intriguingly involving otd, whose morphogenetic function bicoid is thought to have displaced during dipteran evolution.The basic patterning processes of early embryogenesis have been conserved for tens of millions of years in the genus Drosophila. There is nevertheless a constant tension between robustness and flexibility during ontogeny, and this gives rise to a surprising evolutionary lability of detailed features of the patterning process that is observed between genera and species (Peel et al., 2005;Damen, 2007). The fundamental morphogen Bicoid (Bcd), that sets up the gradient of anterior-posterior (A-P) positional information (Ephrussi and St Johnston, 2004) is actually an invention of higher diptera that seems to have taken over a role largely performed by another transcription factor, Orthodenticle (Otd), in more primitive insects (Schroder, 2003;Lynch et al., 2006). One of the target genes of Bicoid, the pair-rule gene even-skipped (eve), initiates NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript segmentation, and expression in the second stripe of eve is controlled by an enhancer that has evolved extensive substitutions despite retaining its overall function between divergent Drosophila species (Ludwig et al., 2005). Even closely related species of Drosophila show alterations in the timing of early pattern formation (Kim et al., 2000). These observations suggest that there is also likely to be functional polymorphism for early embryonic patterning within a species, but the extent and nature of such variation has not been documented.Bicoid protein is distributed in a gradient, and activates transcription of target genes at different positions along the A-P ...

High throughput parallel genomic sequencing (Next Generation Sequencing, NGS) shifts the bottleneck in sequencing processes from experimental data production to computationally intensive informatics-based data analysis. This manuscript introduces a biomedical informatics pipeline (BING) for the analysis of NGS data that offers several novel computational approaches to 1. image alignment, 2. signal correlation, compensation, separation, and pixel-based cluster registration, 3. signal measurement and base calling, 4. quality control and accuracy measurement. These approaches address many of the informatics challenges, including image processing, computational performance, and accuracy. These new algorithms are benchmarked against the Illumina Genome Analysis Pipeline. BING is the one of the first software tools to perform pixel-based analysis of NGS data. When compared to the Illumina informatics tool, BING's pixel-based approach produces a significant increase in the number of sequence reads, while reducing the computational time per experiment and error rate (<2%). This approach has the potential of increasing the density and throughput of NGS technologies.