Negative feedback buffers effects of regulatory variants.

Mechanisms conferring robustness against regulatory variants have been controversial. Previous studies suggested widespread buffering of RNA misexpression on protein levels during translation. We do not find evidence that translational buffering is common. Instead, we find extensive buffering at the level of RNA expression, exerted through negative feedback regulation acting in trans, which reduces the effect of regulatory variants on gene expression. Our approach is based on a novel experimental design in which allelic differential expression in a yeast hybrid strain is compared to allelic differential expression in a pool of its spores. Allelic differential expression in the hybrid is due to cis-regulatory differences only. Instead, in the pool of spores allelic differential expression is not only due to cis-regulatory differences but also due to local trans effects that include negative feedback. We found that buffering through such local trans regulation is widespread, typically compensating for about 15% of cis-regulatory effects on individual genes. Negative feedback is stronger not only for essential genes, indicating its functional relevance, but also for genes with low to middle levels of expression, for which tight regulation matters most. We suggest that negative feedback is one mechanism of Waddington's canalization, facilitating the accumulation of genetic variants that might give selective advantage in different environments.

Alternative polyadenylation diversifies post-transcriptional regulation by selective RNA-protein interactions.

Recent research has uncovered extensive variability in the boundaries of transcript isoforms, yet the functional consequences of this variation remain largely unexplored. Here, we systematically discriminate between the molecular phenotypes of overlapping coding and non-coding transcriptional events from each genic locus using a novel genome-wide, nucleotide-resolution technique to quantify the half-lives of 3' transcript isoforms in yeast. Our results reveal widespread differences in stability among isoforms for hundreds of genes in a single condition, and that variation of even a single nucleotide in the 3' untranslated region (UTR) can affect transcript stability. While previous instances of negative associations between 3' UTR length and transcript stability have been reported, here, we find that shorter isoforms are not necessarily more stable. We demonstrate the role of RNA-protein interactions in conditioning isoform-specific stability, showing that PUF3 binds and destabilizes specific polyadenylation isoforms. Our findings indicate that although the functional elements of a gene are encoded in DNA sequence, the selective incorporation of these elements into RNA through transcript boundary variation allows a single gene to have diverse functional consequences.

An efficient method for genome-wide polyadenylation site mapping and RNA quantification.

The use of alternative poly(A) sites is common and affects the post-transcriptional fate of mRNA, including its stability, subcellular localization and translation. Here, we present a method to identify poly(A) sites in a genome-wide and strand-specific manner. This method, termed 3'T-fill, initially fills in the poly(A) stretch with unlabeled dTTPs, allowing sequencing to start directly after the poly(A) tail into the 3'-untranslated regions (UTR). Our comparative analysis demonstrates that it outperforms existing protocols in quality and throughput and accurately quantifies RNA levels as only one read is produced from each transcript. We use this method to characterize the diversity of polyadenylation in Saccharomyces cerevisiae, showing that alternative RNA molecules are present even in a genetically identical cell population. Finally, we observe that overlap of convergent 3'-UTRs is frequent but sharply limited by coding regions, suggesting factors that restrict compression of the yeast genome.

Genotyping 1000 yeast strains by next-generation sequencing.

BACKGROUND: The throughput of next-generation sequencing machines has increased dramatically over the last few years; yet the cost and time for library preparation have not changed proportionally, thus representing the main bottleneck for sequencing large numbers of samples. Here we present an economical, high-throughput library preparation method for the Illumina platform, comprising a 96-well based method for DNA isolation for yeast cells, a low-cost DNA shearing alternative, and adapter ligation using heat inactivation of enzymes instead of bead cleanups. RESULTS: Up to 384 whole-genome libraries can be prepared from yeast cells in one week using this method, for less than 15 euros per sample. We demonstrate the robustness of this protocol by sequencing over 1000 yeast genomes at ~30x coverage. The sequence information from 768 yeast segregants derived from two divergent S. cerevisiae strains was used to generate a meiotic recombination map at unprecedented resolution. Comparisons to other datasets indicate a high conservation of recombination at a chromosome-wide scale, but differences at the local scale. Additionally, we detected a high degree of aneuploidy (3.6%) by examining the sequencing coverage in these segregants. Differences in allele frequency allowed us to attribute instances of aneuploidy to gains of chromosomes during meiosis or mitosis, both of which showed a strong tendency to missegregate specific chromosomes. CONCLUSIONS: Here we present a high throughput workflow to sequence genomes of large number of yeast strains at a low price. We have used this workflow to obtain recombination and aneuploidy data from hundreds of segregants, which can serve as a foundation for future studies of linkage, recombination, and chromosomal aberrations in yeast and higher eukaryotes.

Common clonal origin of conventional T cells and induced regulatory T cells in breast cancer patients.

Regulatory CD4+ T cells (Treg) prevent tumor clearance by conventional T cells (Tconv) comprising a major obstacle of cancer immune-surveillance. Hitherto, the mechanisms of Treg repertoire formation in human cancers remain largely unclear. Here, we analyze Treg clonal origin in breast cancer patients using T-Cell Receptor and single-cell transcriptome sequencing. While Treg in peripheral blood and breast tumors are clonally distinct, Tconv clones, including tumor-antigen reactive effectors (Teff), are detected in both compartments. Tumor-infiltrating CD4+ cells accumulate into distinct transcriptome clusters, including early activated Tconv, uncommitted Teff, Th1 Teff, suppressive Treg and pro-tumorigenic Treg. Trajectory analysis suggests early activated Tconv differentiation either into Th1 Teff or into suppressive and pro-tumorigenic Treg. Importantly, Tconv, activated Tconv and Treg share highly-expanded clones contributing up to 65% of intratumoral Treg. Here we show that Treg in human breast cancer may considerably stem from antigen-experienced Tconv converting into secondary induced Treg through intratumoral activation.

Is there still a need for candidate gene approaches in the era of genome-wide association studies?

Most genetic variants associated with complex diseases in humans are believed to have a small impact on risk. With traditional candidate gene/pathway approaches several associations with disease risk could be identified. However, now that genome-wide association studies are feasible, the question arises if there is still a need for these approaches. By using HapMap data, we evaluated to which extent commercially available microarrays cover, through linkage disequilibrium, all currently known genes and biological processes in different populations. Furthermore, we estimated the power to detect an association with any specific SNP. Our study shows that coverage of individual genes and pathways by current commercial genotyping platforms is satisfactory for the vast majority of RefSeq gene regions. However, depending on the gene or the population, there may still be a need for candidate gene approaches, especially when looking at polymorphisms with low allele frequencies.

Interleukin promoter polymorphisms and prognosis in colorectal cancer.

There is strong evidence that cancer-associated inflammation promotes tumor growth and progression. This is especially true for colorectal cancer (CRC). Interleukins (ILs) are important modulators for inflammation. We examined whether promoter polymorphisms in key IL genes (IL4, IL4R, IL6, IL8 and IL10) are associated with the risk or clinical outcome of CRC. Five single-nucleotide polymorphisms (SNPs) were analyzed in genomic DNA from a cohort including 308 Swedish incident cases of CRC with data on Dukes' stage and up to 16 years of follow-up and 585 healthy controls. The selected SNPs have previously been shown to be functional and/or associated with cancer. None of the analyzed SNPs associated with the risk of CRC. When stratifying by tumor stage, significantly more patients carrying at least one G allele of IL10-1082 had tumors with Dukes' stages A + B than with stages C + D (P(trend) = 0.035 for genotype distribution). Analyzing associations with overall survival time, we found the rare T allele of IL4-590 to be related to a longer survival [CT versus CC Cox proportional hazard ratio 0.69, 95% confidence intervals 0.46-1.03, TT versus CC 0.32 (0.10-1.03)]. For IL6-174, the CG genotype was associated with a longer survival when compared with the CC genotype [0.64 (0.40-1.01)]. The present study was particularly suitable for survival analysis because all patients were sampled before the diagnosis of CRC. Our results suggest that the SNPs IL4-590 and IL6-174 may be useful markers for CRC prognosis. The predicted biological effect of these SNPs in relation to promotion of cancer progression is consistent with the observed increased survival time.

Polymorphisms of genes coding for ghrelin and its receptor in relation to anthropometry, circulating levels of IGF-I and IGFBP-3, and breast cancer risk: a case-control study nested within the European Prospective Investigation into Cancer and Nutrition (EPIC).

Ghrelin, an endogenous ligand for the growth hormone secretagogue receptor, has two major functions: the stimulation of the growth hormone production and the stimulation of food intake. Accumulating evidence also suggests a role of ghrelin in cancer development. We conducted a case-control study on 1359 breast cancer cases and 2389 matched controls, nested within the European Prospective Investigation into Cancer and Nutrition, to examine the association of common genetic variants in the genes coding for ghrelin (GHRL) and its receptor (GHSR) with anthropometric measures, circulating insulin growth factor I (IGF-I) and insulin-like growth factor-binding protein 3 and breast cancer risk. Pair-wise tagging was used to select the 15 polymorphisms that represent the majority of common genetic variants across the GHRL and GHSR genes. A significant increase in breast cancer risk was observed in carriers of the GHRL rs171407-G allele (odds ratio: 1.2; 95% confidence interval: 1.0-1.4; P = 0.02). The GHRL single-nucleotide polymorphism rs375577 was associated with a 5% increase in IGF-I levels (P = 0.01). A number of GHRL and GHSR polymorphisms were associated with body mass index (BMI) and height (P between <0.01 and 0.04). The false-positive report probability (FPRP) approach suggests that these results are noteworthy (FPRP < 0.20). The results presented here add to a growing body of evidence that GHRL variations are associated with BMI. Furthermore, we have observed evidence for association of GHRL polymorphisms with circulating IGF-I levels and with breast cancer risk. These associations, however, might also be due to chance findings and further large studies are needed to confirm our results.

The single nucleotide polymorphism IVS1+309 in mouse double minute 2 does not affect risk of familial breast cancer.

The mouse double minute 2 (MDM2) oncoprotein promotes cell survival and cell cycle progression by inhibiting the p53 tumor suppressor protein. Further, MDM2 overexpression can inhibit DNA double-strand break repair in a p53-independent manner. Recently, it was shown that a single nucleotide polymorphism (SNP) in the MDM2 promoter was associated with an accelerated tumor formation in individuals with a p53 mutation. The present case-control study investigated the association of this SNP (IVS1+309) with the risk and the age of onset of familial breast cancer in patients with unknown p53 mutation status. Data from 549 women affected by familial breast cancer and 1,065 healthy controls were analyzed. The cases did not carry BRCA1/2 mutations. Cases and controls showed a similar genotype distribution and the SNP did not seem to modify the age of onset of familial breast cancer. The data were also examined taking into account the presence of any additional cancer after breast cancer and the family history of cases; however, no association was found. These results suggest that the SNP IVS1+309 alone affects neither the risk nor the age of onset of heritable breast cancer.

AAVvector-mediated in vivo reprogramming into pluripotency.

In vivo reprogramming of somatic cells into induced pluripotent stem cells (iPSC) holds vast potential for basic research and regenerative medicine. However, it remains hampered by a need for vectors to express reprogramming factors (Oct-3/4, Klf4, Sox2, c-Myc; OKSM) in selected organs. Here, we report OKSM delivery vectors based on pseudotyped Adeno-associated virus (AAV). Using the AAV-DJ capsid, we could robustly reprogram mouse embryonic fibroblasts with low vector doses. Swapping to AAV8 permitted to efficiently reprogram somatic cells in adult mice by intravenous vector delivery, evidenced by hepatic or extra-hepatic teratomas and iPSC in the blood. Notably, we accomplished full in vivo reprogramming without c-Myc. Most iPSC generated in vitro or in vivo showed transcriptionally silent, intronic or intergenic vector integration, likely reflecting the increased host genome accessibility during reprogramming. Our approach crucially advances in vivo reprogramming technology, and concurrently facilitates investigations into the mechanisms and consequences of AAV persistence.

MDM2 SNP309 and cancer risk: a combined analysis.

A paper by Bond et al. reported that a single-nucleotide polymorphism (SNP) in the intronic promoter region of the mouse double minute 2 (MDM2) gene (called SNP309) can significantly change the expression of MDM2 and thereby suppress the p53 pathway. Furthermore, it was shown that SNP309 accelerates tumor formation in Li-Fraumeni patients. This initial report aroused the attention of many researchers, which investigated the role of SNP309 for the risk and the onset of cancer in different tissues. To provide a more robust estimate of the effect of this polymorphism on cancer risk, we combined the available genotype data for breast, colorectal and lung cancers. For breast cancer, we combined the data from 11 studies including 5737 cases and 6703 controls. For colorectal cancer, we combined the data from five studies with 1620 cases and 886 controls. For lung cancer, we performed a fixed-effect meta-analysis from seven studies including 4276 cases and 5318 controls. Our results suggest that the SNP309 variant does not have an impact on the risk of breast [odds ratio (OR) = 0.97, 95% confidence interval (CI) = 0.87-1.08] or colorectal cancers (OR = 0.97, 95% CI = 0.76-1.25). However, the combined estimate of the ORs for lung cancer revealed an increased risk for GG versus TT (OR = 1.27, 95% CI = 1.12-1.44). The data show that SNP309 alone has little or no effect on the risk of common cancers, but it might modify the time of tumor onset and prognosis.

Allelotyping of pooled DNA with 250 K SNP microarrays.

BACKGROUND: Genotyping technologies for whole genome association studies are now available. To perform such studies to an affordable price, pooled DNA can be used. Recent studies have shown that GeneChip Human Mapping 10 K and 50 K arrays are suitable for the estimation of the allele frequency in pooled DNA. In the present study, we tested the accuracy of the 250 K Nsp array, which is part of the 500 K array set representing 500,568 SNPs. Furthermore, we compared different algorithms to estimate allele frequencies of pooled DNA. RESULTS: We could confirm that the polynomial based probe specific correction (PPC) was the most accurate method for allele frequency estimation. However, a simple k-correction, using the relative allele signal (RAS) of heterozygous individuals, performed only slightly worse and provided results for more SNPs. Using four replicates of the 250 K array and the k-correction using heterozygous RAS values, we obtained results for 104.141 SNPs. The correlation between estimated and real allele frequency was 0.983 and the average error was 0.046, which was comparable to the results obtained with the 10 K array. Furthermore, we could show how the estimation accuracy depended on the SNP type (average error for A/T SNPs: 0.043 and for G/C SNPs: 0.052). CONCLUSION: The combination of DNA pooling and analysis of single nucleotide polymorphisms (SNPs) on high density microarrays is a promising tool for whole genome association studies.

GENE-IS: Time-Efficient and Accurate Analysis of Viral Integration Events in Large-Scale Gene Therapy Data.

Integration site profiling and clonality analysis of viral vector distribution in gene therapy is a key factor to monitor the fate of gene-corrected cells, assess the risk of malignant transformation, and establish vector biosafety. We developed the Genome Integration Site Analysis Pipeline (GENE-IS) for highly time-efficient and accurate detection of next-generation sequencing (NGS)-based viral vector integration sites (ISs) in gene therapy data. It is the first available tool with dual analysis mode that allows IS analysis both in data generated by PCR-based methods, such as linear amplification method PCR (LAM-PCR), and by rapidly evolving targeted sequencing (e.g., Agilent SureSelect) technologies. GENE-IS makes use of trimming strategies, customized reference genome, and soft-clipped information with sequential filtering steps to provide annotated IS with clonality information. It is a scalable, robust, precise, and reliable tool for large-scale pre-clinical and clinical data analysis that provides users complete flexibility and control over analysis with a broad range of configurable parameters. GENE-IS is available at https://github.com/G100DKFZ/gene-is.

Genome-Wide Identification of Alternative Polyadenylation Events Using 3'T-Fill.

Due to the increasing appreciation of the impact of alternative polyadenylation on cellular biology, our straightforward, scalable method is of interest to any researcher studying eukaryotic transcription. In addition to high quality gene expression measurements, it precisely maps poly(A) sites and thereby permits the distinction between differential 3'UTR isoforms. As sequencing through long homopolymer stretches is not possible on the Illumina platform, we developed a method that fills up the poly(A) stretch with dTTPs before the sequencing reaction starts.

Determination of allele frequency in pooled DNA: comparison of three PCR-based methods.

Determination of allele frequency in pooled DNA samples is a powerful and efficient tool for large-scale association studies. In this study, we tested and compared three PCR-based methods for accuracy, reproducibility, cost, and convenience. The methods compared were: (i) real-time PCR with allele-specific primers, (ii) real-time PCR with allele-specific TaqMan probes, and (iii) quantitative sequencing. Allele frequencies of three single nucleotide polymorphisms in three different genes were estimated from pooled DNA. The pools were made of genomic DNA samples from 96 cases with basal cell carcinoma of the skin and 96 healthy controls with known genotypes. In this study, the allele frequency estimation made by real-time PCR with allele-specific primers had the smallest median deviation (MD) from the real allele frequency with 1.12% (absolute percentage points) and was also the cheapest method. However; this method required the most time for optimization and showed the highest variation between replicates (SD = 6.47%). Quantitative sequencing, the simplest method, was found to have intermediate accuracies (MD = 1.44%, SD = 4.2%). Real-time PCR with TaqMan probes, a convenient but very expensive method, had an MD of 1.47% and the lowest variation between replicates (SD = 3.18%).

Candidate genetic modifiers for breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers.

BACKGROUND: BRCA1 and BRCA2 mutation carriers are at substantially increased risk for developing breast and ovarian cancer. The incomplete penetrance coupled with the variable age at diagnosis in carriers of the same mutation suggests the existence of genetic and nongenetic modifying factors. In this study, we evaluated the putative role of variants in many candidate modifier genes. METHODS: Genotyping data from 15,252 BRCA1 and 8,211 BRCA2 mutation carriers, for known variants (n = 3,248) located within or around 445 candidate genes, were available through the iCOGS custom-designed array. Breast and ovarian cancer association analysis was performed within a retrospective cohort approach. RESULTS: The observed P values of association ranged between 0.005 and 1.000. None of the variants was significantly associated with breast or ovarian cancer risk in either BRCA1 or BRCA2 mutation carriers, after multiple testing adjustments. CONCLUSION: There is little evidence that any of the evaluated candidate variants act as modifiers of breast and/or ovarian cancer risk in BRCA1 or BRCA2 mutation carriers. IMPACT: Genome-wide association studies have been more successful at identifying genetic modifiers of BRCA1/2 penetrance than candidate gene studies.

Quantitative real-time polymerase chain reaction: methodical analysis and mathematical model.

Real-time polymerase chain reaction was established for 16 genes using the LightCycler system to evaluate gene expression in human hepatocytes. During the experiments a large set of data has been obtained. These data have now been evaluated with respect to template stability, accuracy of melting curve analysis, and reproducibility. In addition, the statistical evaluation of the efficiencies of all 16 polymerase chain reactions led to a new mathematical model. To examine template stability, the degradation of mRNA and cDNA was determined at different temperatures. Surprisingly, cDNA, which was obtained by first-strand synthesis, appeared to degrade significantly faster than the respective mRNA. Melting curve analysis is a fast and sensitive method to check for polymerase chain reaction specificity. However, we show that two transcription variants of the glutathione S-transferase 1 gene, with over 100 bp length difference, could not be distinguished by this method. Furthermore, an equation was set up describing the correlation between polymerase chain reaction efficiency and crossing point. This equation can be used to estimate the number of template molecules without having a standard of known concentration. Finally, experimental reproducibility of the real-time polymerase chain reaction was defined.

Induced mutations in yeast cell populations adapting to an unforeseen challenge.

The modern evolutionary synthesis assumes that mutations occur at random, independently of the environment in which they confer an advantage. However, there are indications that cells facing challenging conditions can adapt rapidly, utilizing processes beyond selection of pre-existing genetic variation. Here, we show that a strong regulatory challenge can induce mutations in many independent yeast cells, in the absence of general mutagenesis. Whole genome sequencing of cell lineages reveals a repertoire of independent mutations within a single lineage that arose only after the cells were exposed to the challenging environment, while other cells in the same lineage adapted without any mutation in their genomes. Thus, our experiments uncovered multiple alternative routes for heritable adaptation that were all induced in the same lineage during a short time period. Our results demonstrate the existence of adaptation mechanisms beyond random mutation, suggesting a tight connection between physiological and genetic processes.

An evaluation of high-throughput approaches to QTL mapping in Saccharomyces cerevisiae.

Dissecting the molecular basis of quantitative traits is a significant challenge and is essential for understanding complex diseases. Even in model organisms, precisely determining causative genes and their interactions has remained elusive, due in part to difficulty in narrowing intervals to single genes and in detecting epistasis or linked quantitative trait loci. These difficulties are exacerbated by limitations in experimental design, such as low numbers of analyzed individuals or of polymorphisms between parental genomes. We address these challenges by applying three independent high-throughput approaches for QTL mapping to map the genetic variants underlying 11 phenotypes in two genetically distant Saccharomyces cerevisiae strains, namely (1) individual analysis of >700 meiotic segregants, (2) bulk segregant analysis, and (3) reciprocal hemizygosity scanning, a new genome-wide method that we developed. We reveal differences in the performance of each approach and, by combining them, identify eight polymorphic genes that affect eight different phenotypes: colony shape, flocculation, growth on two nonfermentable carbon sources, and resistance to two drugs, salt, and high temperature. Our results demonstrate the power of individual segregant analysis to dissect QTL and address the underestimated contribution of interactions between variants. We also reveal confounding factors like mutations and aneuploidy in pooled approaches, providing valuable lessons for future designs of complex trait mapping studies.

Genome-wide polyadenylation site mapping.

Alternative polyadenylation site usage gives rise to variation in 3' ends of transcripts in diverse organisms ranging from yeast to human. Accurate mapping of polyadenylation sites of transcripts is of major biological importance, since the length of the 3'UTR can have a strong influence on transcript stability, localization, and translation. However, reads generated using total mRNA sequencing mostly lack the very 3' end of transcripts. Here, we present a method that allows simultaneous analysis of alternative 3' ends and transcriptome dynamics at high throughput. By using transcripts produced in vitro, the high precision of end mapping during the protocol can be controlled. This method is illustrated here for budding yeast. However, this method can be applied to any natural or artificially polyadenylated RNA.