Open annotation offers a democratic solution to genome sequencing.
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Human chromosome 2 is unique to the human lineage in being the product of a head-to-head fusion of two intermediate-sized ancestral chromosomes. Chromosome 4 has received attention primarily related to the search for the Huntington's disease gene, but also for genes associated with Wolf-Hirschhorn syndrome, polycystic kidney disease and a form of muscular dystrophy. Here we present approximately 237 million base pairs of sequence for chromosome 2, and 186 million base pairs for chromosome 4, representing more than 99.6% of their euchromatic sequences. Our initial analyses have identified 1,346 protein-coding genes and 1,239 pseudogenes on chromosome 2, and 796 protein-coding genes and 778 pseudogenes on chromosome 4. Extensive analyses confirm the underlying construction of the sequence, and expand our understanding of the structure and evolution of mammalian chromosomes, including gene deserts, segmental duplications and highly variant regions.
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The rapid accumulation of microarray data translates into a need for methods to effectively integrate data generated with different platforms. Here we introduce an approach, 2(nd)-order expression analysis, that addresses this challenge by first extracting expression patterns as meta-information from each data set (1(st)-order expression analysis) and then analyzing them across multiple data sets. Using yeast as a model system, we demonstrate two distinct advantages of our approach: we can identify genes of the same function yet without coexpression patterns and we can elucidate the cooperativities between transcription factors for regulatory network reconstruction by overcoming a key obstacle, namely the quantification of activities of transcription factors. Experiments reported in the literature and performed in our lab support a significant number of our predictions.
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