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Metagenomic sequencing has the potential to transform microbial detection and characterization, but new tools are needed to improve its sensitivity. Here we present CATCH, a computational method to enhance nucleic acid capture for enrichment of diverse microbial taxa. CATCH designs optimal probe sets, with a specified number of oligonucleotides, that achieve full coverage of, and scale well with, known sequence diversity. We focus on applying CATCH to capture viral genomes in complex metagenomic samples. We design, synthesize, and validate multiple probe sets, including one that targets the whole genomes of the 356 viral species known to infect humans. Capture with these probe sets enriches unique viral content on average 18-fold, allowing us to assemble genomes that could not be recovered without enrichment, and accurately preserves within-sample diversity. We also use these probe sets to recover genomes from the 2018 Lassa fever outbreak in Nigeria and to improve detection of uncharacterized viral infections in human and mosquito samples. The results demonstrate that CATCH enables more sensitive and cost-effective metagenomic sequencing.

An improved understanding of enhancers in mammalian genomes could facilitate the design of new regulatory elements. Melnikov et al. synthesize thousands of ~90 nt enhancer variants, assay their activity in human cells and use the data to rationally optimize synthetic enhancers.

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

available in PMC 2010 November 2., RNA-Seq provides an unbiased way to study a transcriptome, including both coding and noncoding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes., Merkin Family Foundation for Stem Cell Research, Howard Hughes Medical Institute, National Human Genome Research Institute (U.S.), Burroughs Wellcome Fund, Broad Institute

Nat. Biotechnol. 28, 503–510 (2010); published online 02 May 2010; corrected after print 9 July 2010 In the version of this article initially published, the fourth sentence in the Online Methods section “RNA extraction and library preparation,” that read in part “procedure that combines a random priming step with a shearing step8,9, 28 and results in fragments of ∼700 bp in size,” should have read, “procedure that combines fragmentation of mRNA to a peak size of ∼750 nucleotides by heating6 followed by random-primed reverse transcription8.