Short-read DNA Sequencing Research Articles

Short-read DNA Sequencing Yields Microsatellite Markers for Rheum

Identifying and evaluating genetic diversity of culinary rhubarb (Rheum ×rhababarum) cultivars using morphological characteristics is challenging given the existence of synonyms and nomenclatural inconsistencies. Some cultivars with similar names are morphologically different, and seedlings may grow and become associated with the parental name. Morphological traits of one cultivar may vary when measured under different environmental conditions. Molecular markers are consistent for unique genotypes across environments and provide genetic fingerprints to assist in resolving identity issues. Microsatellite repeats, also called simple sequence repeats (SSRs), are commonly used for fingerprinting fruit and nut crops, but only 10 SSRs have previously been reported in rhubarb. The objectives of this study were to use short-read DNA sequences to develop new di-nucleotide-containing SSR markers for rhubarb and to determine if the markers were useful for cultivar identification. A total of 97 new SSR primer pairs were designed from the short-read DNA sequences. The amplification success rate of these SSRs was 77%, whereas polymorphism of those reached 76% in a test panel of four or eight rhubarb individuals. From the 57 potentially polymorphic primer pairs obtained, 25 SSRs were evaluated in 58 Rheum accessions preserved in the U.S. Department of Agriculture, National Plant Germplasm System. The primer pairs generated 314 fragments with an average of 12.6 fragments per pair. The clustering of many accessions in well-supported groups supported previous findings based on amplified fragment length polymorphisms (AFLPs). Cluster analysis, using the proportion of shared allele distance among the 25 SSRs, distinguished each of the 58 accessions including individuals that had similar names or the same name. Accessions that grouped in well-supported clusters previously belonged to similar clusters with high bootstrap support based on AFLP. In summary, our technique of mining short-read sequencing data was successful in identifying 97 di-nucleotide-containing SSR sequences. Of those tested, the 25 most polymorphic and easy-to-score primer pairs proved useful in fingerprinting rhubarb cultivars. We recommend the use of short-read sequencing for the development of SSR markers in the identification of horticultural crops.

Variation block-based genomics method for crop plants.

BackgroundIn contrast with wild species, cultivated crop genomes consist of reshuffled recombination blocks, which occurred by crossing and selection processes. Accordingly, recombination block-based genomics analysis can be an effective approach for the screening of target loci for agricultural traits.ResultsWe propose the variation block method, which is a three-step process for recombination block detection and comparison. The first step is to detect variations by comparing the short-read DNA sequences of the cultivar to the reference genome of the target crop. Next, sequence blocks with variation patterns are examined and defined. The boundaries between the variation-containing sequence blocks are regarded as recombination sites. All the assumed recombination sites in the cultivar set are used to split the genomes, and the resulting sequence regions are termed variation blocks. Finally, the genomes are compared using the variation blocks. The variation block method identified recurring recombination blocks accurately and successfully represented block-level diversities in the publicly available genomes of 31 soybean and 23 rice accessions. The practicality of this approach was demonstrated by the identification of a putative locus determining soybean hilum color.ConclusionsWe suggest that the variation block method is an efficient genomics method for the recombination block-level comparison of crop genomes. We expect that this method will facilitate the development of crop genomics by bringing genomics technologies to the field of crop breeding.

Applications and challenges of next-generation sequencing in Brassica species

Next-generation sequencing (NGS) produces numerous (often millions) short DNA sequence reads, typically varying between 25 and 400 bp in length, at a relatively low cost and in a short time. This revolutionary technology is being increasingly applied in whole-genome, transcriptome, epigenome and small RNA sequencing, molecular marker and gene discovery, comparative and evolutionary genomics, and association studies. The Brassica genus comprises some of the most agro-economically important crops, providing abundant vegetables, condiments, fodder, oil and medicinal products. Many Brassica species have undergone the process of polyploidization, which makes their genomes exceptionally complex and can create difficulties in genomics research. NGS injects new vigor into Brassica research, yet also faces specific challenges in the analysis of complex crop genomes and traits. In this article, we review the advantages and limitations of different NGS technologies and their applications and challenges, using Brassica as an advanced model system for agronomically important, polyploid crops. Specifically, we focus on the use of NGS for genome resequencing, transcriptome sequencing, development of single-nucleotide polymorphism markers, and identification of novel microRNAs and their targets. We present trends and advances in NGS technology in relation to Brassica crop improvement, with wide application for sophisticated genomics research into agronomically important polyploid crops.

Impact of genomic structural variation in Drosophila melanogaster based on population-scale sequencing

Genomic structural variation (SV) is a major determinant for phenotypic variation. Although it has been extensively studied in humans, the nucleotide resolution structure of SVs within the widely used model organism Drosophila remains unknown. We report a highly accurate, densely validated map of unbalanced SVs comprising 8962 deletions and 916 tandem duplications in 39 lines derived from short-read DNA sequencing in a natural population (the “Drosophila melanogaster Genetic Reference Panel,” DGRP). Most SVs (>90%) were inferred at nucleotide resolution, and a large fraction was genotyped across all samples. Comprehensive analyses of SV formation mechanisms using the short-read data revealed an abundance of SVs formed by mobile element and nonhomologous end-joining-mediated rearrangements, and clustering of variants into SV hotspots. We further observed a strong depletion of SVs overlapping genes, which, along with population genetics analyses, suggests that these SVs are often deleterious. We inferred several gene fusion events also highlighting the potential role of SVs in the generation of novel protein products. Expression quantitative trait locus (eQTL) mapping revealed the functional impact of our high-resolution SV map, with quantifiable effects at >100 genic loci. Our map represents a resource for population-level studies of SVs in an important model organism.

Reference-Free Comparative Genomics of 174 Chloroplasts

Direct analysis of unassembled genomic data could greatly increase the power of short read DNA sequencing technologies and allow comparative genomics of organisms without a completed reference available. Here, we compare 174 chloroplasts by analyzing the taxanomic distribution of short kmers across genomes [1]. We then assemble de novo contigs centered on informative variation. The localized de novo contigs can be separated into two major classes: tip = unique to a single genome and group = shared by a subset of genomes. Prior to assembly, we found that ∼18% of the chloroplast was duplicated in the inverted repeat (IR) region across a four-fold difference in genome sizes, from a highly reduced parasitic orchid [2] to a massive algal chloroplast [3], including gnetophytes [4] and cycads [5]. The conservation of this ratio between single copy and duplicated sequence was basal among green plants, independent of photosynthesis and mechanism of genome size change, and different in gymnosperms and lower plants. Major lineages in the angiosperm clade differed in the pattern of shared kmers and de novo contigs. For example, parasitic plants demonstrated an expected accelerated overall rate of evolution, while the hemi-parasitic genomes contained a great deal more novel sequence than holo-parasitic plants, suggesting different mechanisms at different stages of genomic contraction. Additionally, the legumes are diverging more quickly and in different ways than other major families. Small duplicated fragments of the rrn23 genes were deeply conserved among seed plants, including among several species without the IR regions, indicating a crucial functional role of this duplication. Localized de novo assembly of informative kmers greatly reduces the complexity of large comparative analyses by confining the analysis to a small partition of data and genomes relevant to the specific question, allowing direct analysis of next-gen sequence data from previously unstudied genomes and rapid discovery of informative candidate regions.

G-SNPM - A GPU-based SNP mapping tool

G-SNPM - A GPU-based SNP mapping tool

METAGENOMIC TAXONOMIC CLASSIFICATION USING EXTREME LEARNING MACHINES

Next-generation sequencing technologies have allowed researchers to determine the collective genomes of microbial communities co-existing within diverse ecological environments. Varying species abundance, length and complexities within different communities, coupled with discovery of new species makes the problem of taxonomic assignment to short DNA sequence reads extremely challenging. We have developed a new sequence composition-based taxonomic classifier using extreme learning machines referred to as TAC-ELM for metagenomic analysis. TAC-ELM uses the framework of extreme learning machines to quickly and accurately learn the weights for a neural network model. The input features consist of GC content and oligonucleotides. TAC-ELM is evaluated on two metagenomic benchmarks with sequence read lengths reflecting the traditional and current sequencing technologies. Our empirical results indicate the strength of the developed approach, which outperforms state-of-the-art taxonomic classifiers in terms of accuracy and implementation complexity. We also perform experiments that evaluate the pervasive case within metagenome analysis, where a species may not have been previously sequenced or discovered and will not exist in the reference genome databases. TAC-ELM was also combined with BLAST to show improved classification results. Code and Supplementary Results: http://www.cs.gmu.edu/~mlbio/TAC-ELM (BSD License).

Characterization of a biogas-producing microbial community by short-read next generation DNA sequencing

BackgroundRenewable energy production is currently a major issue worldwide. Biogas is a promising renewable energy carrier as the technology of its production combines the elimination of organic waste with the formation of a versatile energy carrier, methane. In consequence of the complexity of the microbial communities and metabolic pathways involved the biotechnology of the microbiological process leading to biogas production is poorly understood. Metagenomic approaches are suitable means of addressing related questions. In the present work a novel high-throughput technique was tested for its benefits in resolving the functional and taxonomical complexity of such microbial consortia.ResultsIt was demonstrated that the extremely parallel SOLiD™ short-read DNA sequencing platform is capable of providing sufficient useful information to decipher the systematic and functional contexts within a biogas-producing community. Although this technology has not been employed to address such problems previously, the data obtained compare well with those from similar high-throughput approaches such as 454-pyrosequencing GS FLX or Titanium. The predominant microbes contributing to the decomposition of organic matter include members of the Eubacteria, class Clostridia, order Clostridiales, family Clostridiaceae. Bacteria belonging in other systematic groups contribute to the diversity of the microbial consortium. Archaea comprise a remarkably small minority in this community, given their crucial role in biogas production. Among the Archaea, the predominant order is the Methanomicrobiales and the most abundant species is Methanoculleus marisnigri. The Methanomicrobiales are hydrogenotrophic methanogens. Besides corroborating earlier findings on the significance of the contribution of the Clostridia to organic substrate decomposition, the results demonstrate the importance of the metabolism of hydrogen within the biogas producing microbial community.ConclusionsBoth microbiological diversity and the regulatory role of the hydrogen metabolism appear to be the driving forces optimizing biogas-producing microbial communities. The findings may allow a rational design of these communities to promote greater efficacy in large-scale practical systems. The composition of an optimal biogas-producing consortium can be determined through the use of this approach, and this systematic methodology allows the design of the optimal microbial community structure for any biogas plant. In this way, metagenomic studies can contribute to significant progress in the efficacy and economic improvement of biogas production.

ColoSeq Provides Comprehensive Lynch and Polyposis Syndrome Mutational Analysis Using Massively Parallel Sequencing

Lynch syndrome (hereditary nonpolyposis colon cancer) and adenomatous polyposis syndromes frequently have overlapping clinical features. Current approaches for molecular genetic testing are often stepwise, taking a best-candidate gene approach with testing of additional genes if initial results are negative. We report a comprehensive assay called ColoSeq that detects all classes of mutations in Lynch and polyposis syndrome genes using targeted capture and massively parallel next-generation sequencing on the Illumina HiSeq2000 instrument. In blinded specimens and colon cancer cell lines with defined mutations, ColoSeq correctly identified 28/28 (100%) pathogenic mutations in MLH1, MSH2, MSH6, PMS2, EPCAM, APC, and MUTYH, including single nucleotide variants (SNVs), small insertions and deletions, and large copy number variants. There was 100% reproducibility of detection mutation between independent runs. The assay correctly identified 222 of 224 heterozygous SNVs (99.4%) in HapMap samples, demonstrating high sensitivity of calling all variants across each captured gene. Average coverage was greater than 320 reads per base pair when the maximum of 96 index samples with barcodes were pooled. In a specificity study of 19 control patients without cancer from different ethnic backgrounds, we did not find any pathogenic mutations but detected two variants of uncertain significance. ColoSeq offers a powerful, cost-effective means of genetic testing for Lynch and polyposis syndromes that eliminates the need for stepwise testing and multiple follow-up clinical visits.

Current state-of-art of sequencing technologies for plant genomics research

A number of next-generation sequencing (NGS) technologies such as Roche/454, Illumina and AB SOLiD have recently become available. These technologies are capable of generating hundreds of thousands or tens of millions of short DNA sequence reads at a relatively low cost. These NGS technologies, now referred as second-generation sequencing (SGS) technologies, are being utilized for de novo sequencing, genome re-sequencing, and whole genome and transcriptome analysis. Now, new generation of sequencers, based on the 'next-next' or third-generation sequencing (TGS) technologies like the Single-Molecule Real-Time (SMRT™) Sequencer, Heliscope™ Single Molecule Sequencer, and the Ion Personal Genome Machine™ are becoming available that are capable of generating longer sequence reads in a shorter time and at even lower costs per instrument run. Ever declining sequencing costs and increased data output and sample throughput for NGS and TGS sequencing technologies enable the plant genomics and breeding community to undertake genotyping-by-sequencing (GBS). Data analysis, storage and management of large-scale second or TGS projects, however, are essential. This article provides an overview of different sequencing technologies with an emphasis on forthcoming TGS technologies and bioinformatics tools required for the latest evolution of DNA sequencing platforms.

Identification of bacteria recovered from animals using the 16S ribosomal RNA gene with pyrosequencing and Sanger sequencing

Bacterial identification using genetic sequencing is fast becoming a confirmatory tool for microbiologists. Its application in veterinary diagnostic laboratories is still growing. In addition to availability of Sanger sequencing, pyrosequencing has recently emerged as a unique method for short-read DNA sequencing for bacterial identifications. Its ease of use makes it possible to diagnose infections rapidly at a low cost even in smaller laboratories. In the current study, pyrosequencing was compared with Sanger sequencing for identification of the bacterial organisms. Fifty-four bacterial isolates spanning 23 different bacterial families encountered in veterinary diagnostic microbiology laboratories were sequenced using 16S ribosomal RNA gene with pyrosequencing and Sanger sequencing. Pyrosequencing was able to identify 80% of isolates to the genus level, and 43% isolates to the species level. Sanger sequencing with approximately 500 bp performed better for both genus (100%) and species (87%) identification. Use of different sequence databases to identify bacteria isolated from animals showed relative importance of public databases compared to a validated commercial library. A time and limited cost comparison between pyrosequencing and genetic sequencing of 500 bp showed pyrosequencing was not only faster but also comparable in cost, making it a viable alternative for use in classifying bacteria isolated from animals.

The Awesome Power of Yeast Evolutionary Genetics: New Genome Sequences and Strain Resources for theSaccharomyces sensu strictoGenus

High-quality, well-annotated genome sequences and standardized laboratory strains fuel experimental and evolutionary research. We present improved genome sequences of three species of Saccharomyces sensu stricto yeasts: S. bayanus var. uvarum (CBS 7001), S. kudriavzevii (IFO 1802T and ZP 591), and S. mikatae (IFO 1815T), and describe their comparison to the genomes of S. cerevisiae and S. paradoxus. The new sequences, derived by assembling millions of short DNA sequence reads together with previously published Sanger shotgun reads, have vastly greater long-range continuity and far fewer gaps than the previously available genome sequences. New gene predictions defined a set of 5261 protein-coding orthologs across the five most commonly studied Saccharomyces yeasts, enabling a re-examination of the tempo and mode of yeast gene evolution and improved inferences of species-specific gains and losses. To facilitate experimental investigations, we generated genetically marked, stable haploid strains for all three of these Saccharomyces species. These nearly complete genome sequences and the collection of genetically marked strains provide a valuable toolset for comparative studies of gene function, metabolism, and evolution, and render Saccharomyces sensu stricto the most experimentally tractable model genus. These resources are freely available and accessible through www.SaccharomycesSensuStricto.org.

Hardware accelerator architecture for simultaneous short-read DNA sequences alignment with enhanced traceback phase

Dynamic programming algorithms are widely used to find the optimal sequence alignment between any two DNA sequences. This manuscript presents a new, flexible and scalable hardware accelerator architecture to speedup the implementation of the frequently used Smith–Waterman algorithm. When integrated with a general purpose processor, the developed accelerator significantly reduces the computation time and memory space requirements of alignment tasks. Such efficiency mainly comes from two innovative techniques that are proposed. First, the usage of the maximum score cell coordinates, gathered during the computation of the alignment scores in the matrix-fill phase, in order to significantly reduce the time and memory requirements of the traceback phase. Second, the exploitation of an additional level of parallelism in order to simultaneously align several query sequences with the same reference sequence, targeting the processing of short-read DNA sequences. The results obtained from the implementation of a complete alignment system based on the new accelerator architecture in a Virtex-4 FPGA showed that the proposed techniques are feasible and the developed accelerator is able to provide speedups as high as 16 for the considered test sequences. Moreover, it was also shown that the proposed approach allows the processing of larger DNA sequences in memory restricted environments.

Next-Generation Sequencing Strategies Enable Routine Detection of Balanced Chromosome Rearrangements for Clinical Diagnostics and Genetic Research

The contribution of balanced chromosomal rearrangements to complex disorders remains unclear because they are not detected routinely by genome-wide microarrays and clinical localization is imprecise. Failure to consider these events bypasses a potentially powerful complement to single nucleotide polymorphism and copy-number association approaches to complex disorders, where much of the heritability remains unexplained. To capitalize on this genetic resource, we have applied optimized sequencing and analysis strategies to test whether these potentially high-impact variants can be mapped at reasonable cost and throughput. By using a whole-genome multiplexing strategy, rearrangement breakpoints could be delineated at a fraction of the cost of standard sequencing. For rearrangements already mapped regionally by karyotyping and fluorescence in situ hybridization, a targeted approach enabled capture and sequencing of multiple breakpoints simultaneously. Importantly, this strategy permitted capture and unique alignment of up to 97% of repeat-masked sequences in the targeted regions. Genome-wide analyses estimate that only 3.7% of bases should be routinely omitted from genomic DNA capture experiments. Illustrating the power of these approaches, the rearrangement breakpoints were rapidly defined to base pair resolution and revealed unexpected sequence complexity, such as co-occurrence of inversion and translocation as an underlying feature of karyotypically balanced alterations. These findings have implications ranging from genome annotation to de novo assemblies and could enable sequencing screens for structural variations at a cost comparable to that of microarrays in standard clinical practice.

Innovative technology for cancer risk analysis

After completion of the Human Genome Project, analysis of genetic and genomic variations in different pathological states became possible. The capillary system based on Sanger methods is still very expensive in terms of time, cost and professionalism required. For this reason, the National Human Genome Institute proposed an 'advanced sequencing technology development' project with the aim of sequencing a genome in 1 day for $1000. Three validated platforms are commercially available and single molecule sequencing methods have been recently introduced, which are not only competitive in time and costs, but display greater accuracy than 'past generation' sequencing. Next generation technology allows, in a single experiment, the identification of copy number variation and large rearrangements, or detection of fusion transcripts analysis thus permitting the evaluation of cancer risk at multiple levels (genomic, transcriptomic, proteomic, epigenetic).

De novo assembled expressed gene catalog of a fast-growing Eucalyptus tree produced by Illumina mRNA-Seq

BackgroundDe novo assembly of transcript sequences produced by short-read DNA sequencing technologies offers a rapid approach to obtain expressed gene catalogs for non-model organisms. A draft genome sequence will be produced in 2010 for a Eucalyptus tree species (E. grandis) representing the most important hardwood fibre crop in the world. Genome annotation of this valuable woody plant and genetic dissection of its superior growth and productivity will be greatly facilitated by the availability of a comprehensive collection of expressed gene sequences from multiple tissues and organs.ResultsWe present an extensive expressed gene catalog for a commercially grown E. grandis × E. urophylla hybrid clone constructed using only Illumina mRNA-Seq technology and de novo assembly. A total of 18,894 transcript-derived contigs, a large proportion of which represent full-length protein coding genes were assembled and annotated. Analysis of assembly quality, length and diversity show that this dataset represent the most comprehensive expressed gene catalog for any Eucalyptus tree. mRNA-Seq analysis furthermore allowed digital expression profiling of all of the assembled transcripts across diverse xylogenic and non-xylogenic tissues, which is invaluable for ascribing putative gene functions.ConclusionsDe novo assembly of Illumina mRNA-Seq reads is an efficient approach for transcriptome sequencing and profiling in Eucalyptus and other non-model organisms. The transcriptome resource (Eucspresso, http://eucspresso.bi.up.ac.za/) generated by this study will be of value for genomic analysis of woody biomass production in Eucalyptus and for comparative genomic analysis of growth and development in woody and herbaceous plants.

BFAST: An Alignment Tool for Large Scale Genome Resequencing

BackgroundThe new generation of massively parallel DNA sequencers, combined with the challenge of whole human genome resequencing, result in the need for rapid and accurate alignment of billions of short DNA sequence reads to a large reference genome. Speed is obviously of great importance, but equally important is maintaining alignment accuracy of short reads, in the 25–100 base range, in the presence of errors and true biological variation.MethodologyWe introduce a new algorithm specifically optimized for this task, as well as a freely available implementation, BFAST, which can align data produced by any of current sequencing platforms, allows for user-customizable levels of speed and accuracy, supports paired end data, and provides for efficient parallel and multi-threaded computation on a computer cluster. The new method is based on creating flexible, efficient whole genome indexes to rapidly map reads to candidate alignment locations, with arbitrary multiple independent indexes allowed to achieve robustness against read errors and sequence variants. The final local alignment uses a Smith-Waterman method, with gaps to support the detection of small indels.ConclusionsWe compare BFAST to a selection of large-scale alignment tools - BLAT, MAQ, SHRiMP, and SOAP - in terms of both speed and accuracy, using simulated and real-world datasets. We show BFAST can achieve substantially greater sensitivity of alignment in the context of errors and true variants, especially insertions and deletions, and minimize false mappings, while maintaining adequate speed compared to other current methods. We show BFAST can align the amount of data needed to fully resequence a human genome, one billion reads, with high sensitivity and accuracy, on a modest computer cluster in less than 24 hours. BFAST is available at http://bfast.sourceforge.net.

Computation of Rank and Select Functions on Hierarchical Binary String and Its Application to Genome Mapping Problems for Short-Read DNA Sequences

Abstract We have developed efficient in-practice algorithms for computing rank and select functions on a binary string, based on a novel data structure, a hierarchical binary string with hierarchical accumulatives. It efficiently stores decomposed information on partial summations over various scales of subregions of a given binary string, so that the required space overhead ratio is only about 3.5% irrespective of the string length. Values of rank and select functions are computed hierarchically in [(log(2)n)/8] iterations, where n is the string length. For example, for an unbiased random binary string of 64 G bits, each value of these functions can be computed in about a microsecond, on average, on a single 3.0-GHz CPU using 8+ GB of memory. We also present their applications to genome mapping problems for large-scale short-read DNA sequence data, especially produced by ultra-high-throughput new-generation DNA sequencers. The algorithms are applied to the binarization of the Burrows-Wheeler transform of the human genome DNA sequence. For the sake of high-speed performance, we adopted a somewhat stringent mapping condition that allows at most a single-base mismatch (either a substitution, insertion, or deletion of a single base) per query sequence. An experimentally implemented program mapped several thousands of sequences per second on a single 3.0-GHz CPU, several times faster than ELAND, a widely used mapping program with the Illumina-Solexa 1G analyser.

IFRD1 Is a Candidate Gene for SMNA on Chromosome 7q22-q23

We have established strong linkage evidence that supports mapping autosomal-dominant sensory/motor neuropathy with ataxia (SMNA) to chromosome 7q22-q32. SMNA is a rare neurological disorder whose phenotype encompasses both the central and the peripheral nervous system. In order to identify a gene responsible for SMNA, we have undertaken a comprehensive genomic evaluation of the region of linkage, including evaluation for repeat expansion and small deletions or duplications, capillary sequencing of candidate genes, and massively parallel sequencing of all coding exons. We excluded repeat expansion and small deletions or duplications as causative, and through microarray-based hybrid capture and massively parallel short-read sequencing, we identified a nonsynonymous variant in the human interferon-related developmental regulator gene 1 (IFRD1) as a disease-causing candidate. Sequence conservation, animal models, and protein structure evaluation support the involvement of IFRD1 in SMNA. Mutation analysis of IFRD1 in additional patients with similar phenotypes is needed for demonstration of causality and further evaluation of its importance in neurological diseases.

Efficient yeast ChIP-Seq using multiplex short-read DNA sequencing

BackgroundShort-read high-throughput DNA sequencing technologies provide new tools to answer biological questions. However, high cost and low throughput limit their widespread use, particularly in organisms with smaller genomes such as S. cerevisiae. Although ChIP-Seq in mammalian cell lines is replacing array-based ChIP-chip as the standard for transcription factor binding studies, ChIP-Seq in yeast is still underutilized compared to ChIP-chip. We developed a multiplex barcoding system that allows simultaneous sequencing and analysis of multiple samples using Illumina's platform. We applied this method to analyze the chromosomal distributions of three yeast DNA binding proteins (Ste12, Cse4 and RNA PolII) and a reference sample (input DNA) in a single experiment and demonstrate its utility for rapid and accurate results at reduced costs.ResultsWe developed a barcoding ChIP-Seq method for the concurrent analysis of transcription factor binding sites in yeast. Our multiplex strategy generated high quality data that was indistinguishable from data obtained with non-barcoded libraries. None of the barcoded adapters induced differences relative to a non-barcoded adapter when applied to the same DNA sample. We used this method to map the binding sites for Cse4, Ste12 and Pol II throughout the yeast genome and we found 148 binding targets for Cse4, 823 targets for Ste12 and 2508 targets for PolII. Cse4 was strongly bound to all yeast centromeres as expected and the remaining non-centromeric targets correspond to highly expressed genes in rich media. The presence of Cse4 non-centromeric binding sites was not reported previously.ConclusionWe designed a multiplex short-read DNA sequencing method to perform efficient ChIP-Seq in yeast and other small genome model organisms. This method produces accurate results with higher throughput and reduced cost. Given constant improvements in high-throughput sequencing technologies, increasing multiplexing will be possible to further decrease costs per sample and to accelerate the completion of large consortium projects such as modENCODE.