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How deep is deep enough for RNA-Seq profiling of bacterial transcriptomes?
Haas Brian J,Chin Melissa,Nusbaum Chad,Birren Bruce W
BMC Genomics , 2012, DOI: 10.1186/1471-2164-13-734

Abstract: Background High-throughput sequencing of cDNA libraries (RNA-Seq) has proven to be a highly effective approach for studying bacterial transcriptomes. A central challenge in designing RNA-Seq-based experiments is estimating a priori the number of reads per sample needed to detect and quantify thousands of individual transcripts with a large dynamic range of abundance. Results We have conducted a systematic examination of how changes in the number of RNA-Seq reads per sample influences both profiling of a single bacterial transcriptome and the comparison of gene expression among samples. Our findings suggest that the number of reads typically produced in a single lane of the Illumina HiSeq sequencer far exceeds the number needed to saturate the annotated transcriptomes of diverse bacteria growing in monoculture. Moreover, as sequencing depth increases, so too does the detection of cDNAs that likely correspond to spurious transcripts or genomic DNA contamination. Finally, even when dozens of barcoded individual cDNA libraries are sequenced in a single lane, the vast majority of transcripts in each sample can be detected and numerous genes differentially expressed between samples can be identified. Conclusions Our analysis provides a guide for the many researchers seeking to determine the appropriate sequencing depth for RNA-Seq-based studies of diverse bacterial species.

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High-Resolution Description of Antibody Heavy-Chain Repertoires in Humans
Ramy Arnaout, William Lee, Patrick Cahill, Tracey Honan, Todd Sparrow, Michael Weiand, Chad Nusbaum, Klaus Rajewsky, Sergei B. Koralov
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0022365

Abstract: Antibodies' protective, pathological, and therapeutic properties result from their considerable diversity. This diversity is almost limitless in potential, but actual diversity is still poorly understood. Here we use deep sequencing to characterize the diversity of the heavy-chain CDR3 region, the most important contributor to antibody binding specificity, and the constituent V, D, and J segments that comprise it. We find that, during the stepwise D-J and then V-DJ recombination events, the choice of D and J segments exert some bias on each other; however, we find the choice of the V segment is essentially independent of both. V, D, and J segments are utilized with different frequencies, resulting in a highly skewed representation of VDJ combinations in the repertoire. Nevertheless, the pattern of segment usage was almost identical between two different individuals. The pattern of V, D, and J segment usage and recombination was insufficient to explain overlap that was observed between the two individuals' CDR3 repertoires. Finally, we find that while there are a near-infinite number of heavy-chain CDR3s in principle, there are about 3–9 million in the blood of an adult human being.

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Closing gaps in the human genome using sequencing by synthesis
Manuel Garber, Michael C Zody, Harindra M Arachchi, Aaron Berlin, Sante Gnerre, Lisa M Green, Niall Lennon, Chad Nusbaum
Genome Biology , 2009, DOI: 10.1186/gb-2009-10-6-r60

Abstract: The finished sequence of human chromosome 15 contained nine sequence gaps at the time of publication [1]. Six of these gaps were flanked by segmental duplications, and recent work showed that one of these gaps could be closed by resolving assembly issues in segmental duplications [2]. A similar process has recently been undertaken genome-wide [3]. Three of the chromosome 15 gaps occur in regions of unique sequence with no evidence of copy number variation. Alignment of these regions to the publicly released Celera whole-genome shotgun assembly suggested gap sizes of 12, 10 and 9 kb [4], all substantially smaller than previous estimates [1]. No additional gap sequence was assembled in the more deeply covered HuRef assembly [5]. Further, flanks for two of these gaps could be aligned to scaffolds in the Rhesus macaque genome (rheMac2 assembly [6]), which provided size estimates similar to those from Celera. No clones spanned the orthologous regions in the chimpanzee genome assembly.Using both the NCBI build 36 and Celera assemblies we designed six primer pairs anchored in unique sequences that tiled the three gaps (for two of the three we used Celera contigs inside the build 36 gap to design primers; Table S1 in Additional data file 1). We amplified these regions via PCR from human genomic DNA (Coriell NA15510; see Materials and methods). End sequences of the PCR products matched the gap-flanking sequences, and product sizes on agarose gels closely matched the expected product sizes based on the gap sizing in the Celera assembly (Figure S1 in Additional data file 1). We then attempted to clone the PCR products directly, but sequencing of these showed that we were unsuccessful in obtaining clones that contained the desired product. Next, we produced and assembled small insert (average length 500 bp) 'shatter' libraries from the PCR products [7]. This approach of breaking difficult regions into much smaller fragments has been used with great success to resolve sequences

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Correction: Closing gaps in the human genome using sequencing by synthesis
Manuel Garber, Michael C Zody, Harindra C Arachchi, Aaron Berlin, Sante Gnerre, Lisa M Green, Niall Lennon, Chad Nusbaum
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-4-403

Abstract:

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Strand-specific RNA sequencing reveals extensive regulated long antisense transcripts that are conserved across yeast species
Moran Yassour, Jenna Pfiffner, Joshua Z Levin, Xian Adiconis, Andreas Gnirke, Chad Nusbaum, Dawn-Anne Thompson, Nir Friedman, Aviv Regev
Genome Biology , 2010, DOI: 10.1186/gb-2010-11-8-r87

Abstract: Here, we use strand-specific RNA sequencing to study anti-sense transcription in Saccharomyces cerevisiae. We detect 1,103 putative antisense transcripts expressed in mid-log phase growth, ranging from 39 short transcripts covering only the 3' UTR of sense genes to 145 long transcripts covering the entire sense open reading frame. Many of these antisense transcripts overlap sense genes that are repressed in mid-log phase and are important in stationary phase, stress response, or meiosis. We validate the differential regulation of 67 antisense transcripts and their sense targets in relevant conditions, including nutrient limitation and environmental stresses. Moreover, we show that several antisense transcripts and, in some cases, their differential expression have been conserved across five species of yeast spanning 150 million years of evolution. Divergence in the regulation of antisense transcripts to two respiratory genes coincides with the evolution of respiro-fermentation.Our work provides support for a global and conserved role for antisense transcription in yeast gene regulation.Antisense transcription plays an important role in gene regulation from bacteria to humans. While the role of antisense transcripts is increasingly studied in metazoans [1], less is known about its relevance for gene regulation in the yeast Saccharomyces cerevisiae, a key model for eukaryotic gene regulation. Recent genomic studies using tiling microarrays showed evidence of stable antisense transcription in S. cerevisiae [2,3] and Schizosaccharomyces pombe [4,5].It is unclear how broad the role of antisense transcription is and what key functional processes in yeast it affects. A few functional antisense transcripts have been implicated in the control of several key genes, including the meiosis regulator gene IME4 [6], the phosphate metabolism gene PHO84 [7], the galactose metabolism gene GAL10 [8], and the inositol phosphate biosynthetic gene KCS1 [9]. In contrast, genome-scale anal

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Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts
Joshua Z Levin, Michael F Berger, Xian Adiconis, Peter Rogov, Alexandre Melnikov, Timothy Fennell, Chad Nusbaum, Levi A Garraway, Andreas Gnirke
Genome Biology , 2009, DOI: 10.1186/gb-2009-10-10-r115

Abstract: In recent years, a technologic revolution has shifted DNA sequencing from traditional Sanger methods to "next-generation" sequencing (see review [1]). Applying these new sequencing methods to cDNA libraries, termed RNA-Seq, generates a wealth of information beyond that obtained from sequencing genomic DNA (see review [2]). RNA-Seq provides insights at multiple levels into the transcription of the genome as it yields sequence, splicing, and expression-level information leading to the identification of novel transcripts [3,4] and sequence alterations. For research into somatic mutations in cancer (for example, The Cancer Genome Atlas [5-7]), this method has the advantage of enriching for changes in coding sequences, which are more likely to affect function, compared with sequencing genomic DNA. Chromosomal rearrangements, including translocations, are an important class of mutations in cancer [8]. Although chromosomal rearrangements can be detected by next-generation sequencing of genomic DNA [9,10], RNA-Seq is a powerful tool to identify those rearrangements that lead to chimeric transcripts and are more likely to have functional consequences in cancer [3,11].Despite these advantages of RNA-Seq, the complexity of the transcriptome and the wide dynamic range of expression levels render whole-transcriptome sequencing an expensive proposition, particularly at the depth required to call mutations and identify structural rearrangements or aberrant splice forms in low-abundance mRNAs. Mortazavi and colleagues [12] reported that 40 million reads were required to provide onefold coverage of a transcriptome, whereas the calling genotypes with high confidence may require coverage levels of at least fivefold to 20-fold [13]. This magnitude of coverage invariably results in vast oversampling of abundant transcripts, which adversely affects the efficiency and overall power of the approach.Cost and efficiency considerations have prompted the emergence of methods that allow "target

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Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries
Daniel Aird, Michael G Ross, Wei-Sheng Chen, Maxwell Danielsson, Timothy Fennell, Carsten Russ, David B Jaffe, Chad Nusbaum, Andreas Gnirke
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-2-r18

Abstract: The Illumina sequencing platform [1], like other massively parallel sequencing platforms [2,3], continues to produce ever-increasing amounts of data, yet suffers from under-representation and reduced quality at loci with extreme base compositions that are recalcitrant to the technology [1,4-6]. Uneven coverage due to base composition necessitates sequencing to excessively high mean coverage for de novo genome assembly [7] and for sensitive polymorphism discovery [8,9]. Although loci with extreme base composition constitute only a small fraction of the human genome, they include biologically and medically relevant re-sequencing targets. For example, 104 of the first 136 coding bases of the retinoblastoma tumor suppressor gene RB1 are G or C.Traditional Sanger sequencing has long been known to suffer from problems related to the base composition of sequencing templates. GC-rich stretches led to compression artifacts. Polymerase slippage in poly(A) runs and AT dinucleotide repeats caused mixed sequencing ladders and poor read quality. Processes upstream of the actual sequencing, such as cloning, introduced bias against inverted repeats, extreme base-compositions or genes not tolerated by the bacterial cloning host. Gaps due to unclonable sequences had to be recovered and finished by PCR [10], or, in some cases, by resorting to alternative hosts [11]. Cloning bias hindered efforts to sequence the AT-rich genomes of Dictyostelium [12] and Plasmodium [13] and excluded the GC-rich first exons of about 10% of protein-coding genes in the dog (K Lindblad-Toh, personal communication) from an otherwise high-quality reference genome assembly [14].New genome sequencing technologies [1-3,15-17] no longer rely on cloning in a microbial host. Instead of ligating DNA fragments to cloning vectors, the three major platforms currently on the market (454, Illumina and SOLiD) involve ligation of DNA fragments to special adapters for clonal amplification in vitro rather than in vivo. Due t

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RNA-Seq methods for imperfect samples: development, evaluation and applications
Xian Adiconis, Lin Fan, David DeLuca, Andrey Sivachenko, Nathalie Pochet, Aaron Berlin, Sarah Young, Gad Getz, Aviv Regev, Chad Nusbaum, Andreas Gnirke, Joshua Z Levin
Genome Biology , 2011, DOI: 10.1186/gb-2011-12-s1-p1

Abstract: RNA-Seq methods that start from total RNA and do not require the oligo(dT) purification of mRNA will be valuable for such challenging samples. Such methods use alternative approaches to reduce the fraction of sequencing reads derived from rRNA. We will present results from multiple approaches, including the use of not-so-random (NSR) primers for cDNA synthesis, low-C0t hybridization with a duplex-specific nuclease for light normalization and NuGEN’s Ovation RNA-Seq kit. We demonstrated that these three methods successfully reduce the fraction of rRNA to less than 13%, even when starting from degraded RNA. We compared the performance between these methods and with ‘gold standard’ RNA-Seq data (derived from samples with large quantities of high-quality RNA), using quantitative criteria that evaluate effectiveness for genome annotation, transcript discovery and expression profiling. The application of these methods to samples that contain degraded RNA and/or very low input amounts of RNA will also be presented.

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Massively Parallel Sequencing of Human Urinary Exosome/Microvesicle RNA Reveals a Predominance of Non-Coding RNA
Kevin C. Miranda, Daniel T. Bond, Joshua Z. Levin, Xian Adiconis, Andrey Sivachenko, Carsten Russ, Dennis Brown, Chad Nusbaum, Leileata M. Russo
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0096094

Abstract: Intact RNA from exosomes/microvesicles (collectively referred to as microvesicles) has sparked much interest as potential biomarkers for the non-invasive analysis of disease. Here we use the Illumina Genome Analyzer to determine the comprehensive array of nucleic acid reads present in urinary microvesicles. Extraneous nucleic acids were digested using RNase and DNase treatment and the microvesicle inner nucleic acid cargo was analyzed with and without DNase digestion to examine both DNA and RNA sequences contained in microvesicles. Results revealed that a substantial proportion (~87%) of reads aligned to ribosomal RNA. Of the non-ribosomal RNA sequences, ~60% aligned to non-coding RNA and repeat sequences including LINE, SINE, satellite repeats, and RNA repeats (tRNA, snRNA, scRNA and srpRNA). The remaining ~40% of non-ribosomal RNA reads aligned to protein coding genes and splice sites encompassing approximately 13,500 of the known 21,892 protein coding genes of the human genome. Analysis of protein coding genes specific to the renal and genitourinary tract revealed that complete segments of the renal nephron and collecting duct as well as genes indicative of the bladder and prostate could be identified. This study reveals that the entire genitourinary system may be mapped using microvesicle transcript analysis and that the majority of non-ribosomal RNA sequences contained in microvesicles is potentially functional non-coding RNA, which play an emerging role in cell regulation.

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