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We describe Trans-ABySS, a de novo short-read transcriptome assembly and analysis pipeline that addresses variation in local read densities by assembling read substrings with varying stringencies and then merging the resulting contigs before analysis. Analyzing 7.4 gigabases of 50-base-pair paired-end Illumina reads from an adult mouse liver poly(A) RNA library, we identified known, new and alternative structures in expressed transcripts, and achieved high sensitivity and specificity relative to reference-based assembly methods.

MicroRNAs are key regulators of gene expression in diverse biological processes and their importance in embryonic stem cells is indisputable. New 'next-generation' technologies such as Illumina massively parallel sequencing offer vast improvements, in both scale and sensitivity, to microRNA profiling studies. We describe a detailed procedure for the preparation of small RNA libraries for Illumina sequencing. We further comment on approaches for analyzing the resultant sequence data for measuring microRNA abundance.

We describe the details of a serial analysis of gene expression (SAGE) library construction and analysis platform that has enabled the generation of >298 high-quality SAGE libraries and >30 million SAGE tags primarily from sub-microgram amounts of total RNA purified from samples acquired by microdissection. Several RNA isolation methods were used to handle the diversity of samples processed, and various measures were applied to minimize ditag PCR carryover contamination. Modifications in the SAGE protocol resulted in improved cloning and DNA sequencing efficiencies. Bioinformatic measures to automatically assess DNA sequencing results were implemented to analyze the integrity of ditag structure, linker or cross-species ditag contamination, and yield of high-quality tags per sequence read. Our analysis of singleton tag errors resulted in a method for correcting such errors to statistically determine tag accuracy. From the libraries generated, we produced an essentially complete mapping of reliable 21-base-pair tags to the mouse reference genome sequence for a meta-library of ∼5 million tags. Our analyses led us to reject the commonly held notion that duplicate ditags are artifacts. Rather than the usual practice of discarding such tags, we conclude that they should be retained to avoid introducing bias into the results and thereby maintain the quantitative nature of the data, which is a major theoretical advantage of SAGE as a tool for global transcriptional profiling.

As part of the effort to sequence the genome ofRattus norvegicus, we constructed a physical map comprised of fingerprinted bacterial artificial chromosome (BAC) clones from the CHORI-230 BAC library. These BAC clones provide ∼13-fold redundant coverage of the genome and have been assembled into 376 fingerprint contigs. A yeast artificial chromosome (YAC) map was also constructed and aligned with the BAC map via fingerprinted BAC and P1 artificial chromosome clones (PACs) sharing interspersed repetitive sequence markers with the YAC-based physical map. We have annotated 95% of the fingerprint map clones in contigs with coordinates on the version 3.1 rat genome sequence assembly, using BAC-end sequences and in silico mapping methods. These coordinates have allowed anchoring 358 of the 376 fingerprint map contigs onto the sequence assembly. Of these, 324 contigs are anchored to rat genome sequences localized to chromosomes, and 34 contigs are anchored to unlocalized portions of the rat sequence assembly. The remaining 18 contigs, containing 54 clones, still require placement. The fingerprint map is a high-resolution integrative data resource that provides genome-ordered associations among BAC, YAC, and PAC clones and the assembled sequence of the rat genome.

A physical map of a genome is an essential guide for navigation, allowing the location of any gene or other landmark in the chromosomal DNA. We have constructed a physical map of the mouse genome that contains 296 contigs of overlapping bacterial clones and 16,992 unique markers. The mouse contigs were aligned to the human genome sequence on the basis of 51,486 homology matches, thus enabling use of the conserved synteny (correspondence between chromosome blocks) of the two genomes to accelerate construction of the mouse map. The map provides a framework for assembly of whole-genome shotgun sequence data, and a tile path of clones for generation of the reference sequence. Definition of the human-mouse alignment at this level of resolution enables identification of a mouse clone that corresponds to almost any position in the human genome. The human sequence may be used to facilitate construction of other mammalian genome maps using the same strategy.