Elliott H. Margulies

We have developed a novel approach for using massively parallel short-read sequencing to generate fast and inexpensive de novo genomic assemblies comparable to those generated by capillary-based methods. The ultrashort (Drosophila melanogaster genome. We subsequently demonstrate the accuracy of our assembly method with meaningful comparisons against the current available D. melanogaster reference genome (dm3). The ease of assembly and accuracy for comparative genomics suggest that our approach will scale to future mammalian genome-sequencing efforts, saving both time and money without sacrificing quality.

The identification of evolutionarily constrained sequences is an unbiased approach for finding functional sequences in genomes. However, their identification is strongly affected by upstream analyses. Genomes are sequenced to different levels of finishing, which affects downstream comparative analyses. Before genomic sequences can be aligned, segments of homologous collinearity must be identified. Errors at this stage can have a dramatic effect on the identification of constrained sequences. Base-pair sequence-alignment programs differentially handle the complexities of evolution, such as insertions/deletions and duplications. In addition, new approaches to identify regions of alignment uncertainty can be used. Current approaches that utilize evolutionary sequence constraint focus on regions that are deeply constrained. Newer approaches combined with sequences from more species can now be pursued to identify weakly and/or lineage-specific constrained sequences. The amount of detectable constrained sequence depends on the phylogenetic scope being pursued as well as the resolution and intensity of the desired detectable constraint. Large collaborative projects such as ENCODE are shedding light on the correlation between sequence constraint and sequence function. Additional methods are also available for determining the biological significance of constrained sequences.

An international, peer-reviewed genome sciences journal featuring outstanding original research that offers novel insights into the biology of all organisms

Background: Although genes play a key role in many complex diseases, the specific genes involved in most complex diseases remain largely unidentified. Their discovery will hinge on the identification of key sequence variants that are conclusively associated with disease. While much attention has been focused on variants in protein-coding DNA, variants in noncoding regions may also play many important roles in complex disease by altering gene regulation. Since the vast majority of noncoding genomic sequence is of unknown function, this increases the challenge of identifying "functional" variants that cause disease. However, evolutionary conservation can be used as a guide to indicate regions of noncoding or coding DNA that are likely to have biological function, and thus may be more likely to harbor SNP variants with functional consequences. To help bias marker selection in favor of such variants, we devised a process that prioritizes annotated SNPs for genotyping studies based on their location within Multi-species Conserved Sequences (MCSs) and used this process to select SNPs in a region of linkage to a complex disease. This allowed us to evaluate the utility of the chosen SNPs for further association studies. Previously, a region of chromosome 1q43 was linked to Multiple Sclerosis (MS) in a genome-wide screen. We chose annotated SNPs in the region based on location within MCSs (termed MCS-SNPs). We then obtained genotypes for 478 MCS-SNPs in 989 individuals from MS families. Results: Analysis of our MCS-SNP genotypes from the 1q43 region and comparison to HapMap data confirmed that annotated SNPs in MCS regions are frequently polymorphic and show subtle signatures of selective pressure, consistent with previous reports of genome-wide variation in conserved regions. We also present an online tool that allows MCS data to be directly exported to the UCSC genome browser so that MCS-SNPs can be easily identified within genomic regions of interest. Conclusion: Our results showed that MCS can easily be used to prioritize markers for follow-up and candidate gene association studies. We believe that this novel approach demonstrates a paradigm for expediting the search for genes contributing to complex diseases.

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization.