An optimized, broadly applicable piggyBac transposon induction system.

The piggyBac (PB) transposon has been used in a number of biological applications. The insertion of PB transposons into the genome can disrupt genes or regulatory regions, impacting cellular function, so for many experiments it is important that PB transposition is tightly controlled. Here, we systematically characterize three methods for the post-translational control of the PB transposon in four cell lines. We investigated fusions of the PB transposase with ERT2 and two degradation domains (FKBP-DD, DHFR-DD), in multiple orientations, and determined (i) the fold-induction achieved, (ii) the absolute transposition efficiency of the activated construct and (iii) the effects of two inducer molecules on cellular transcription and function. We found that the FKBP-DD confers the PB transposase with a higher transposition activity and better dynamic range than can be achieved with the other systems. In addition, we found that the FKBP-DD regulates transposon activity in a reversible and dose-dependent manner. Finally, we showed that Shld1, the chemical inducer of FKBP-DD, does not interfere with stem cell differentiation, whereas tamoxifen has significant effects. We believe the FKBP-based PB transposon induction will be useful for transposon-mediated genome engineering, insertional mutagenesis and the genome-wide mapping of transcription factor binding.

Exploring Quantitative Yeast Phenomics with Single-Cell Analysis of DNA Damage Foci.

A significant challenge of functional genomics is to develop methods for genome-scale acquisition and analysis of cell biological data. Here, we present an integrated method that combines genome-wide genetic perturbation of Saccharomyces cerevisiae with high-content screening to facilitate the genetic description of sub-cellular structures and compartment morphology. As proof of principle, we used a Rad52-GFP marker to examine DNA damage foci in ∼20 million single cells from ∼5,000 different mutant backgrounds in the context of selected genetic or chemical perturbations. Phenotypes were classified using a machine learning-based automated image analysis pipeline. 345 mutants were identified that had elevated numbers of DNA damage foci, almost half of which were identified only in sensitized backgrounds. Subsequent analysis of Vid22, a protein implicated in the DNA damage response, revealed that it acts together with the Sgs1 helicase at sites of DNA damage and preferentially binds G-quadruplex regions of the genome. This approach is extensible to numerous other cell biological markers and experimental systems.

Origin and consequences of the relationship between protein mean and variance.

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝µ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝µ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome.

Global gene deletion analysis exploring yeast filamentous growth.

The dimorphic switch from a single-cell budding yeast to a filamentous form enables Saccharomyces cerevisiae to forage for nutrients and the opportunistic pathogen Candida albicans to invade human tissues and evade the immune system. We constructed a genome-wide set of targeted deletion alleles and introduced them into a filamentous S. cerevisiae strain, Σ1278b. We identified genes involved in morphologically distinct forms of filamentation: haploid invasive growth, biofilm formation, and diploid pseudohyphal growth. Unique genes appear to underlie each program, but we also found core genes with general roles in filamentous growth, including MFG1 (YDL233w), whose product binds two morphogenetic transcription factors, Flo8 and Mss11, and functions as a critical transcriptional regulator of filamentous growth in both S. cerevisiae and C. albicans.

"Calling cards" for DNA-binding proteins in mammalian cells.

The ability to chronicle transcription-factor binding events throughout the development of an organism would facilitate mapping of transcriptional networks that control cell-fate decisions. We describe a method for permanently recording protein-DNA interactions in mammalian cells. We endow transcription factors with the ability to deposit a transposon into the genome near to where they bind. The transposon becomes a "calling card" that the transcription factor leaves behind to record its visit to the genome. The locations of the calling cards can be determined by massively parallel DNA sequencing. We show that the transcription factor SP1 fused to the piggyBac transposase directs insertion of the piggyBac transposon near SP1 binding sites. The locations of transposon insertions are highly reproducible and agree with sites of SP1-binding determined by ChIP-seq. Genes bound by SP1 are more likely to be expressed in the HCT116 cell line we used, and SP1-bound CpG islands show a strong preference to be unmethylated. This method has the potential to trace transcription-factor binding throughout cellular and organismal development in a way that has heretofore not been possible.

Retrotransposon profiling of RNA polymerase III initiation sites.

Although retroviruses are relatively promiscuous in choice of integration sites, retrotransposons can display marked integration specificity. In yeast and slime mold, some retrotransposons are associated with tRNA genes (tDNAs). In the Saccharomyces cerevisiae genome, the long terminal repeat retrotransposon Ty3 is found at RNA polymerase III (Pol III) transcription start sites of tDNAs. Ty1, 2, and 4 elements also cluster in the upstream regions of these genes. To determine the extent to which other Pol III-transcribed genes serve as genomic targets for Ty3, a set of 10,000 Ty3 genomic retrotranspositions were mapped using high-throughput DNA sequencing. Integrations occurred at all known tDNAs, two tDNA relics (iYGR033c and ZOD1), and six non-tDNA, Pol III-transcribed types of genes (RDN5, SNR6, SNR52, RPR1, RNA170, and SCR1). Previous work in vitro demonstrated that the Pol III transcription factor (TF) IIIB is important for Ty3 targeting. However, seven loci that bind the TFIIIB loader, TFIIIC, were not targeted, underscoring the unexplained absence of TFIIIB at those sites. Ty3 integrations also occurred in two open reading frames not previously associated with Pol III transcription, suggesting the existence of a small number of additional sites in the yeast genome that interact with Pol III transcription complexes.

Calling Cards enable multiplexed identification of the genomic targets of DNA-binding proteins.

Transcription factors direct gene expression, so there is much interest in mapping their genome-wide binding locations. Current methods do not allow for the multiplexed analysis of TF binding, and this limits their throughput. We describe a novel method for determining the genomic target genes of multiple transcription factors simultaneously. DNA-binding proteins are endowed with the ability to direct transposon insertions into the genome near to where they bind. The transposon becomes a "Calling Card" marking the visit of the DNA-binding protein to that location. A unique sequence "barcode" in the transposon matches it to the DNA-binding protein that directed its insertion. The sequences of the DNA flanking the transposon (which reveal where in the genome the transposon landed) and the barcode within the transposon (which identifies the TF that put it there) are determined by massively parallel DNA sequencing. To demonstrate the method's feasibility, we determined the genomic targets of eight transcription factors in a single experiment. The Calling Card method promises to significantly reduce the cost and labor needed to determine the genomic targets of many transcription factors in different environmental conditions and genetic backgrounds.

Bisulfite Patch PCR enables multiplexed sequencing of promoter methylation across cancer samples.

Aberrant DNA methylation frequently occurs at gene promoters during cancer progression. It is important to identify these loci because they are often misregulated and drive tumorigenesis. Bisulfite sequencing is the most direct and highest resolution assay for identifying aberrant promoter methylation. Recently, genomic capture methods have been combined with next-generation sequencing to enable genome-scale surveys of methylation in individual samples. However, it is challenging to validate candidate loci identified by these approaches because an efficient method to bisulfite sequence more than 50 differentially methylated loci across a large number of samples does not exist. To address this problem, we developed Bisulfite Patch PCR, which enables highly multiplexed bisulfite PCR and sequencing across many samples. Using this method, we successfully amplified 100% of 94 targeted gene promoters simultaneously in the same reaction. By incorporating sample-specific DNA barcodes into the amplicons, we analyzed 48 samples in a single run of the 454 Life Sciences (Roche) FLX sequencer. The method requires small amounts of starting DNA (250 ng) and does not require a shotgun library construction. The method was highly specific; 90% of sequencing reads aligned to targeted loci. The targeted promoters were from genes that are frequently mutated in breast and colon cancer, and the samples included breast and colon tumor and adjacent normal tissue. This approach allowed us to identify nine gene promoters that exhibit tumor-specific DNA methylation defects that occur frequently in colon and breast cancer. We also analyzed single nucleotide polymorphisms to observe DNA methylation that accumulated on specific alleles during tumor development. This method is broadly applicable for studying DNA methylation across large numbers of patient samples using next-generation sequencing.

Nested Patch PCR enables highly multiplexed mutation discovery in candidate genes.

Medical resequencing of candidate genes in individual patient samples is becoming increasingly important in the clinic and in clinical research. Medical resequencing requires the amplification and sequencing of many candidate genes in many patient samples. Here we introduce Nested Patch PCR, a novel method for highly multiplexed PCR that is very specific, can sensitively detect SNPs and mutations, and is easy to implement. This is the first method that couples multiplex PCR with sample-specific DNA barcodes and next-generation sequencing to enable highly multiplex mutation discovery in candidate genes for multiple samples in parallel. In our pilot study, we amplified exons from colon cancer and matched normal human genomic DNA. From each sample, we successfully amplified 96% (90 of 94) targeted exons from across the genome, totaling 21.6 kbp of sequence. Ninety percent of all sequencing reads were from targeted exons, demonstrating that Nested Patch PCR is highly specific. We found that the abundance of reads per exon was reproducible across samples. We reliably detected germline SNPs and discovered a colon tumor specific nonsense mutation in APC, a gene causally implicated in colorectal cancer. With Nested Patch PCR, candidate gene mutation discovery across multiple individual patient samples can now utilize the power of second-generation sequencing.

A sensitive procedure to detect alternatively spliced mRNA in pooled-tissue samples.

One important goal of genomics is to explore the extent of alternative splicing in the transcriptome and generate a comprehensive catalog of splice forms. New computational and experimental approaches have led to an increase in the number of predicted alternatively spliced transcripts; however, validation of these predictions has not kept pace. In this work, we systematically explore different methods for the validation of cassette exons predicted by computational methods or tiling microarrays. Our goal was to find a procedure that is cost effective, sensitive and specific. We examined three ways of priming the reverse transcription (RT) reaction-poly-dT priming, random priming and pooled exon-specific priming. We also examined two strategies for PCR amplification-flanking PCR, which uses primers that hybridize to the constitutive exons flanking the predicted exon, and a semi-nested PCR with a primer that targets the predicted exon. We found that the combination of RT using a pool of gene-specific primers followed by semi-nested PCR resulted in a significant increase in sensitivity over the most commonly used methodology (97% of the test set was detected versus 14%). Our method was also highly specific-no false positives were detected using a test set of true negatives. Finally, we demonstrate that this method is able to detect alternative exons with a high sensitivity from whole-organism RNA, allowing all tissues to be sampled in a single experiment. The protocol developed here is an accurate and cost-effective way to validate predictions of alternative splicing.

Calling cards for DNA-binding proteins.

Identifying genomic targets of transcription factors is fundamental for understanding transcriptional regulatory networks. Current technology enables identification of all targets of a single transcription factor, but there is no realistic way to achieve the converse: identification of all proteins that bind to a promoter of interest. We have developed a method that promises to fill this void. It employs the yeast retrotransposon Ty5, whose integrase interacts with the Sir4 protein. A DNA-binding protein fused to Sir4 directs insertion of Ty5 into the genome near where it binds; the Ty5 becomes a "calling card" the DNA-binding protein leaves behind in the genome. We constructed customized calling cards for seven transcription factors of yeast by including in each Ty5 a unique DNA sequence that serves as a "molecular bar code." Ty5 transposition was induced in a population of yeast cells, each expressing a different transcription factor-Sir4 fusion and its matched, bar-coded Ty5, and the calling cards deposited into selected regions of the genome were identified, revealing the transcription factors that visited that region of the genome. In each region we analyzed, we found calling cards for only the proteins known to bind there: In the GAL1-10 promoter we found only calling cards for Gal4; in the HIS4 promoter we found only Gcn4 calling cards; in the PHO5 promoter we found only Pho4 and Pho2 calling cards. We discuss how Ty5 calling cards might be implemented for mapping all targets of all transcription factors in a single experiment.

Non-EST-based prediction of novel alternatively spliced cassette exons with cell signaling function in Caenorhabditis elegans and human.

To better understand the complex role that alternative splicing plays in intracellular signaling, it is important to catalog the numerous splice variants involved in signal transduction. Therefore, we developed PASE (Prediction of Alternative Signaling Exons), a computational tool to identify novel alternative cassette exons that code for kinase phosphorylation or signaling protein-binding sites. We first applied PASE to the Caenorhabditis elegans genome. In this organism, our algorithm had an overall specificity of > or =76.4%, including 33 novel cassette exons that we experimentally verified. We then used PASE to analyze the human genome and made 804 predictions, of which 308 were found as alternative exons in the transcript database. We experimentally tested 384 of the remaining unobserved predictions and discovered 26 novel human exons for a total specificity of > or =41.5% in human. By using a test set of known alternatively spliced signaling exons, we determined that the sensitivity of PASE is approximately 70%. GO term analysis revealed that our exon predictions were found in the introns of known signal transduction genes more often than expected by chance, indicating PASE enriches for splice variants that function in signaling pathways. Overall, PASE was able to uncover 59 novel alternative cassette exons in C. elegans and humans through a genome-wide ab initio prediction method that enriches for exons involved in signaling.