We have developed an accurate, yet inexpensive and high-throughput, method for determining the allele frequency of biallelic polymorphisms in pools of DNA samples. The assay combines kinetic (real-time quantitative) PCR with allele-specific amplification and requires no post-PCR processing. The relative amounts of each allele in a sample are quantified. This is performed by dividing equal aliquots of the pooled DNA between two separate PCR reactions, each of which contains a primer pair specific to one or the other allelic SNP variant. For pools with equal amounts of the two alleles, the two amplifications should reach a detectable level of fluorescence at the same cycle number. For pools that contain unequal ratios of the two alleles, the difference in cycle number between the two amplification reactions can be used to calculate the relative allele amounts. We demonstrate the accuracy and reliability of the assay on samples with known predetermined SNP allele frequencies from 5% to 95%, including pools of both human and mouse DNAs using eight different SNPs altogether. The accuracy of measuring known allele frequencies is very high, with the strength of correlation between measured and known frequencies having an r 2 = 0.997. The loss of sensitivity as a result of measurement error is typically minimal, compared with that due to sampling error alone, for population samples up to 1000. We believe that by providing a means for SNP genotyping up to thousands of samples simultaneously, inexpensively, and reproducibly, this method is a powerful strategy for detecting meaningful polymorphic differences in candidate gene association studies and genome-wide linkage disequilibrium scans.

Spt6 is a conserved transcription factor that associates with RNA polymerase II (pol II) during elongation. Spt6 is essential for viability in Saccharomyces cerevisiae and regulates chromatin structure during pol II transcription. Here we present evidence that mutations that impair Spt6, a second elongation factor, Spt4, and pol II can affect 3-end formation at GAL10. Additional analysis suggests that Spt6 is required for cotranscriptional association of the factor Ctr9, a member of the Paf1 complex, with GAL10 and GAL7, and that Ctr9 association with chromatin 3 of GAL10 is regulated by the GAL10 polyadenylation signal. Overall, these results provide new evidence for a connection between the transcription elongation factor Spt6 and 3-end formation in vivo.Many factors are believed to contribute to pol II 1 transcription elongation and to mRNA processing, based on either physical association with pol II, cotranscriptional association with transcribed DNA, or association with the nascent RNA (1-4). In Saccharomyces cerevisiae, these include factors involved in mRNA capping, splicing, termination, and export. They also include the highly conserved and mostly essential elongation factors, the Spt4/Spt5 complex, Spt6, and the Spt16/Pob3 complex. Additionally, the Paf1 complex (comprising Paf1, Ctr9, Rtf1, Leo1, and Cdc73), Isw1, Iws1, the Set1 complex, Set2, and Chd1 have also been implicated as part of the pol II elongation complex (5-16).Previous work has shown that Spt6 is broadly utilized in pol II transcription (17,18), and data from several laboratories implicates Spt6 as a pol II elongation factor (16, 18 -20). Spt6 has been shown to interact with histones and is involved in the organization of chromatin structure over transcribed regions (21-23). Spt6 has also been implicated in RNA processing, because Drosophila Spt6 is associated with the nuclear exosome (24). Additional roles for Spt6 in the transcription cycle probably also exist.The Paf1 complex is a multisubunit complex that associates with pol II and localizes to transcribed regions (14,16,(25)(26)(27)(28)(29). Although all of the roles of the Paf1 complex remain to be elucidated, recently, some complex members have been shown to be required for cotranscriptional ubiquitylation of histone H2B at position 123 (H2B Lys-123) and methylation of histone H3 lysines at positions 4 (Lys 4 ), 36 (Lys 36 ), and 79 (Lys 79 ) (30 -34). Thus, the Paf1 complex appears to coordinate histone modifications with transcription. Mutations in genes encoding Paf1 complex members also exhibit a wide spectrum of genetic interactions with mutations in elongation factor genes such as SPT4, SPT5, SPT16, and POB3 (14,35,36).As pol II goes through the cycle of transcription initiation, elongation, and termination, it is presented with different tasks. Many of these tasks are coordinated through the phosphorylation of the largest subunit of pol II on its conserved C-terminal domain, which in yeast consists of 26 repeats of consensus Tyr 1 -Ser 2 -Pro 3 -Thr 4 -Ser 5 -Pro 6 -Ser 7 ...

In the current era of functional genomics, it is remarkable that the intracellular range of transcript abundance is largely unknown. For the yeast Saccharomyces cerevisiae, hybridization-based complexity analysis and SAGE analysis showed that the majority of yeast mRNAs are present at one or fewer copies per cell; however, neither method provides an accurate estimate of the full range of low abundance transcripts. Here we examine the range of intracellular transcript abundance in yeast using kinetically monitored, reverse transcriptase-initiated PCR (kRT-PCR). Steady-state transcript levels encoded by all 65 genes on the left arm of chromosome III and 185 transcription factor genes are quantitated. Abundant transcripts encoded by glycolytic genes, previously quantitated by kRT-PCR, are present at a few hundred copies per cell whereas genes encoding physiologically important transcription factors are expressed at levels as low as one-thousandth transcript per cell. Of the genes assessed, only the silent mating type loci, HML and HMR, are transcriptionally silent. The results show that transcript abundance in yeast varies over six orders of magnitude. Finally, kRT-PCR, cDNA microarray, and high density oligonucleotide array assays are compared for their ability to detect and quantitate the complete yeast transcriptome.Measurements of the intracellular range of transcript abundance relied initially on hybridization-based complexity analysis and more recently on SAGE 1 analysis. For the yeast Saccharomyces cerevisiae, hybridization-based complexity analysis (1) and SAGE analysis (2) showed that 75% of poly(A) mRNA is encoded by only 20% of yeast genes. SAGE analysis also showed that 75% of yeast genes are expressed at 1 or fewer copies per cell (2). Because of technical limitations, neither method provides an accurate estimate of the range of low abundance transcripts encoded by the majority of yeast genes.We previously demonstrated the accuracy, sensitivity, and reliability of kRT-PCR for quantitating mRNA levels in complex mixtures of total cellular RNA over a wide range of relative transcript abundance (3-5). In contrast to second order hybridization-based complexity analysis or SAGE analysis, where signal to noise decreases exponentially with decreasing transcript abundance, signal to noise is constant for kRT-PCR; only the PCR cycle number where product accumulation is detected varies with transcript abundance. For highly expressed yeast metabolic genes, mRNA levels determined by kRT-PCR are in good agreement (within 2-fold) with those made by Northern blotting, enzyme activity measurements, and SAGE (5). For highly repressed genes, fold repression measured by kRT-PCR versus enzyme activity are within 2-fold down to transcript levels of 0.01 copy per cell (5). Here we employ kRT-PCR to assess the full range of transcript abundance in yeast using selected subsets of the yeast transcriptome and total cellular RNA isolated from early log phase cultures of strain BY4742 (derived from strain S288C) grown in YPD medi...

(20), and probably the other affected glycolytic genes (7). * Corresponding author.We report here the identification of three distinct DNAbinding proteins that interact specifically with sequences within the 5'-flanking regions of the ENO] and EN02 genes. The binding sites for these factors were mapped and found to correlate with essential regions of UAS elements identified from deletion mapping analysis (9, 10).

There are two enolase genes, ENO] and EN02, per haploid yeast genome. Expression of the ENO] gene is quantitatively similar in cells grown on glucose or gluconeogenic carbon sources. In contrast, EN02 expression is induced more than 20-fold in cells grown on glucose as the carbon source. cis-Acting regulatory sequences were mapped within the 5'-flanking region of the constitutively expressed yeast enolase gene ENO]. A complex positive regulatory region was located 445 base pairs (bp) upstream from the transcriptional initiation site which was required for ENO] expression in cells grown on glycolytic or gluconeogenic carbon sources. A negative regulatory region was located 160 bp upstream from the transcriptional initiation site. Sequences required for the function of this negative regulatory element were mapped to a 38-bp region. Deletion of all or a portion of these latter sequences permitted glucose-dependent induction of ENO] expression that was quantitatively similar to that of the glucose-inducible EN02 gene. The negative regulatory element therefore prevents glucose-dependent induction of the ENO] gene. Hybrid 5'-flanking regions were constructed which contained the upstream regulatory sequences of one enolase gene fused at a site upstream from the TATAAA box in the other enolase gene. Analysis of the expression of enolase genes containing these hybrid 5'-flanking region showed that the positive regulatory regions of ENO] and EN02 were functionally similar, as were the regions extending from the TATAAA boxes to the initiation codons. Based on these studies, we conclude that the negative regulatory element plays the critical role in maintaining the constitutive expression of the ENO] structural gene in cells grown on glucose or gluconeogenic carbon sources.Enolase is one of the most abundant enzymes in Saccharomyces cerevisiae. There are two yeast enolase structural genes, designated ENO] and EN02, which encode polypeptides differing in 20 of 436 amino acid residues (3). The two genes are expressed differentially in vegetative cells grown on glycolytic or gluconeogenic carbon sources. The steady-state concentrations of the ENOJ-encoded mRNA and polypeptide are similar in cells grown on the two carbon sources, whereas the intracellular concentrations of the ENO2-encoded mRNA and polypeptide are more than 20-fold higher in cells grown on glucose than on glycerol plus lactate (9). We showed previously that transcription of the ENO2 gene is regulated by upstream activation sequences located approximately 460 base pairs (bp) upstream from the transcription initiation site (2). Genetic analysis further showed that sequences within this regulatory region mediate the observed glucose-dependent induction of transcription of ENO2 (2).Having located the cis-acting sequences which regulate transcription of the ENO2 structural gene, we were interested to determine how transcription of the constitutively expressed ENO] structural gene is regulated. Of particular interest is the issue of coordinate regulation of transcri...