Dataset Information

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing.

ABSTRACT: Functional characterization of disease-causing variants at risk loci has been a significant challenge. Here we report a high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) technology to simultaneously screen hundreds to thousands of SNPs for their allele-dependent protein-binding differences. This technology takes advantage of higher retention rate of protein-bound DNA oligos in protein purification column to quantitatively sequence these SNP-containing oligos. We apply this technology to test prostate cancer-risk loci and observe differential allelic protein binding in a significant number of selected SNPs. We also test a unique application of self-transcribing active regulatory region sequencing (STARR-seq) in characterizing allele-dependent transcriptional regulation and provide detailed functional analysis at two risk loci (RGS17 and ASCL2). Together, we introduce a powerful high-throughput pipeline for large-scale screening of functional SNPs at disease risk loci.

SUBMITTER: Zhang P

PROVIDER: S-EPMC5964124 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing.

Zhang Peng P Xia Ji-Han JH Zhu Jing J Gao Ping P Tian Yi-Jun YJ Du Meijun M Guo Yong-Chen YC Suleman Sufyan S Zhang Qin Q Kohli Manish M Tillmans Lori S LS Thibodeau Stephen N SN French Amy J AJ Cerhan James R JR Wang Li-Dong LD Wei Gong-Hong GH Wang Liang L

Nature communications 20180522 1

Functional characterization of disease-causing variants at risk loci has been a significant challenge. Here we report a high-throughput single-nucleotide polymorphisms sequencing (SNPs-seq) technology to simultaneously screen hundreds to thousands of SNPs for their allele-dependent protein-binding differences. This technology takes advantage of higher retention rate of protein-bound DNA oligos in protein purification column to quantitatively sequence these SNP-containing oligos. We apply this te ...[more]

PMID: 29789573

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Project description:Alkaptonuria (AKU) is a rare inborn error of metabolism caused by a defective homogentisate 1,2-dioxygenase (HGD), an enzyme involved in the tyrosine degradation pathway. Loss of HGD function leads to the accumulation of homogentisic acid (HGA) in connective body tissues in a process called ochronosis, which results on the long term in an early-onset and severe osteoarthropathy. HGD's quaternary structure is known to be easily disrupted by missense mutations, which makes them an interesting target for novel treatment strategies that aim to rescue enzyme activity. However, only prediction models are available providing information on a structural basis. Therefore, an E. coli based whole-cell screening was developed to evaluate HGD missense variants in 96-well microtiter plates. The screening principle is based on HGD's ability to convert the oxidation sensitive HGA into maleylacetoacetate. More precisely, catalytic activity could be deduced from pyomelanin absorbance measurements, derived from the auto-oxidation of remaining HGA. Optimized screening conditions comprised several E. coli expression strains, varied expression temperatures and varied substrate concentrations. In addition, plate uniformity, signal variability and spatial uniformity were investigated and optimized. Finally, eight HGD missense variants were generated via site-directed mutagenesis and evaluated with the developed high-throughput screening (HTS) assay. For the HTS assay, quality parameters passed the minimum acceptance criterion for Z' values > 0.4 and single window values > 2. We found that activity percentages versus wildtype HGD were 70.37 ± 3.08% (for M368V), 68.78 ± 6.40% (for E42A), 58.15 ± 1.16% (for A122V), 69.07 ± 2.26% (for Y62C), 35.26 ± 1.90% (for G161R), 35.86 ± 1.14% (for P230S), 23.43 ± 4.63% (for G115R) and 19.57 ± 11.00% (for G361R). To conclude, a robust, simple, and cost-effective HTS system was developed to reliably evaluate and distinguish human HGD missense variants by their HGA consumption ability. This HGA quantification assay may lay the foundation for the development of novel treatment strategies for missense variants in AKU.

Project description:The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 Genomes database provides a critical opportunity for further interpreting disease associations with single nucleotide polymorphisms (SNPs) discovered from genetic association studies. Currently, direct sequencing of candidate genes or regions on a large number of subjects remains both cost- and time-prohibitive.To accelerate the translation from discovery to functional studies, we propose an in silico gene sequencing method (ISS), which predicts phased sequences of intragenic regions, using SNPs. The key underlying idea of our method is to infer diploid sequences (a pair of phased sequences/alleles) at every functional locus utilizing the deep sequencing data from the 1000 Genomes Project and SNP data from the HapMap Project, and to build prediction models using flanking SNPs. Using this method, we have developed a database of prediction models for 611 known genes. Sequence prediction accuracy for these genes is 96.26% on average (ranges 79%-100%). This database of prediction models can be enhanced and scaled up to include new genes as the 1000 Genomes Project sequences additional genes on additional individuals. Applying our predictive model for the KCNJ11 gene to the Wellcome Trust Case Control Consortium (WTCCC) Type 2 diabetes cohort, we demonstrate how the prediction of phased sequences inferred from GWAS SNP genotype data can be used to facilitate interpretation and identify a probable functional mechanism such as protein changes.Prior to the general availability of routine sequencing of all subjects, the ISS method proposed here provides a time- and cost-effective approach to broadening the characterization of disease associated SNPs and regions, and facilitating the prioritization of candidate genes for more detailed functional and mechanistic studies.

Dataset Information

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing.

Publications

High-throughput screening of prostate cancer risk loci by single nucleotide polymorphisms sequencing.

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