Mapping Protein-DNA Interactions Using ChIP-exo and Illumina-Based Sequencing

Chromatin immunoprecipitation (ChIP) provides a means of enriching DNA associated with transcription factors, histone modifications, and indeed any other proteins for which suitably characterized antibodies are available. Over the years, sequence detection has progressed from quantitative real-time PCR and Southern blotting to microarrays (ChIP-chip) and now high-throughput sequencing (ChIP-seq). This progression has vastly increased the sequence coverage and data volumes generated. This in turn has enabled informaticians to predict the identity of multi-protein complexes on DNA based on the overrepresentation of sequence motifs in DNA enriched by ChIP with a single antibody against a single protein. In the course of the development of high-throughput sequencing, little has changed in the ChIP methodology until recently. In the last three years, a number of modifications have been made to the ChIP protocol with the goal of enhancing the sensitivity of the method and further reducing the levels of nonspecific background sequences in ChIPped samples. In this chapter, we provide a brief commentary on these methodological changes and describe a detailed ChIP-exo method able to generate narrower peaks and greater peak coverage from ChIPped material.

Genetic association analyses of non-synonymous single nucleotide polymorphisms in diabetic nephropathy

Aims/hypothesis: Diabetic nephropathy, characterised by persistent proteinuria, hypertension and progressive kidney failure, affects a subset of susceptible individuals with diabetes. It is also a leading cause of end-stage renal disease (ESRD). Non-synonymous (ns) single nucleotide polymorphisms (SNPs) have been reported to contribute to genetic susceptibility in both monogenic disorders and common complex diseases. The objective of this study was to investigate whether nsSNPs are involved in susceptibility to diabetic nephropathy using a case-control design.

Methods: White type 1 diabetic patients with (cases) and without (controls) nephropathy from eight centres in the UK and Ireland were genotyped for a selected subset of nsSNPs using Illumina's GoldenGate BeadArray assay. A ? 2 test for trend, stratified by centre, was used to assess differences in genotype distribution between cases and controls. Genomic control was used to adjust for possible inflation of test statistics, and the False Discovery Rate method was used to account for multiple testing.

Results: We assessed 1,111 nsSNPs for association with diabetic nephropathy in 1,711 individuals with type 1 diabetes (894 cases, 817 controls). A number of SNPs demonstrated a significant difference in genotype distribution between groups before but not after correction for multiple testing. Furthermore, neither subgroup analysis (diabetic nephropathy with ESRD or diabetic nephropathy without ESRD) nor stratification by duration of diabetes revealed any significant differences between groups.

Conclusions/interpretation: The nsSNPs investigated in this study do not appear to contribute significantly to the development of diabetic nephropathy in patients with type 1 diabetes.

Impact of Sample Heterogeneity on Methylation Analysis

The recent emergence of high-throughput arrays for methylation analysis has made the influence of tumor content on the interpretation of methylation levels increasingly pertinent. However, to what degree does tumor content have an influence, and what degree of tumor content makes a specimen acceptable for accurate analysis remains unclear. Taking a systematic approach, we analyzed 98 unselected formalin-fixed and paraffin-embedded gastric tumors and matched normal tissue samples using the Illumina GoldenGate methylation assay. Unsupervised hierarchical clustering showed 2 separate clusters with a significant difference in average tumor content levels. The probes identified to be significantly differentially methylated between the tumors and normals also differed according to the tumor content of the samples included, with the sensitivity of identifying the

Deep sequencing reveals predominant expression of miR-21 amongst the small non-coding RNAs in retinal microvascular endothelial cells

The retinal vascular endothelium is essential for angiogenesis and is involved in maintaining barrier selectivity and vascular tone. The aim of this study was to identify and quantify microRNAs and other small regulatory non-coding RNAs (ncRNAs) which may regulate these crucial functions. Primary bovine retinal microvascular endothelial cells (RMECs) provide a well-characterized in vitro system for studying angiogenesis. RNA extracted from RMECs was used to prepare a small RNA library for deep sequencing (Illumina Genome Analyzer). A total of 6.8 million reads were mapped to 250 known microRNAs in miRBase (release 16). In many cases, the most frequent isomiR differed from the sequence reported in miRBase. In addition, five novel microRNAs, 13 novel bovine orthologs of known human microRNAs and multiple new members of the miR-2284/2285 family were detected. Several similar to 30 nucleotide sno-miRNAs were identified, with the most highly expressed being derived from snoRNA U78. Highly expressed microRNAs previously associated with endothelial cells included miR-126 and miR-378, but the most highly expressed was miR-21, comprising more than one-third of all mapped reads. Inhibition of miR-21 with an LNA inhibitor significantly reduced proliferation, migration, and tube-forming capacity of RMECs. The independence from prior sequence knowledge provided by deep sequencing facilitates analysis of novel microRNAs and other small RNAs. This approach also enables quantitative evaluation of microRNA expression, which has highlighted the predominance of a small number of microRNAs in RMECs. Knockdown of miR-21 suggests a role for this microRNA in regulation of angiogenesis in the retinal microvasculature. J. Cell. Biochem. 113: 20982111, 2012. (C) 2012 Wiley Periodicals, Inc.

Genomewide linkage scan of schizophrenia in a large multicenter pedigree sample using single nucleotide polymorphisms

A genomewide linkage scan was carried out in eight clinical samples of informative schizophrenia families. After all quality control checks, the analysis of 707 European-ancestry families included 1615 affected and 1602 unaffected genotyped individuals, and the analysis of all 807 families included 1900 affected and 1839 unaffected individuals. Multipoint linkage analysis with correction for marker-marker linkage disequilibrium was carried out with 5861 single nucleotide polymorphisms (SNPs; Illumina version 4.0 linkage map). Suggestive evidence for linkage ( European families) was observed on chromosomes 8p21, 8q24.1, 9q34 and 12q24.1 in nonparametric and/or parametric analyses. In a logistic regression allele-sharing analysis of linkage allowing for intersite heterogeneity, genomewide significant evidence for linkage was observed on chromosome 10p12. Significant heterogeneity was also observed on chromosome 22q11.1. Evidence for linkage across family sets and analyses was most consistent on chromosome 8p21, with a one-LOD support interval that does not include the candidate gene NRG1, suggesting that one or more other susceptibility loci might exist in the region. In this era of genomewide association and deep resequencing studies, consensus linkage regions deserve continued attention, given that linkage signals can be produced by many types of genomic variation, including any combination of multiple common or rare SNPs or copy number variants in a region. Molecular Psychiatry (2009) 14, 786-795; doi:10.1038/mp.2009.11; published online 17 February 2009

A genome-wide association study provides evidence for association of chromosome 8p23 (MYP10) and 10q21.1 (MYP15) with high myopia in the French population.

PURPOSE. Myopia is a complex trait affected by both genetic and environmental factors. High myopia is associated with increased risk of sight-threatening eye disorders such as retinal detachment. The purpose of this genome-wide association study was to identify susceptibility genes contributing to high myopia in the French population. METHODS. High myopic cases were genotyped using Affymetrix SNP 6.0 chips and population controls were selected from the GABRIEL French dataset in which samples were genotyped by Illumina Human610 quad array. The association study was conducted using 152,234 single nucleotide polymorphisms that were present on both manufacturers' chips in 192 high myopic cases and 1064 controls to identify associated regions. Imputation was performed on peak regions. RESULTS. Associations were found at known myopia locus MYP10 on chromosome 8p23 and MYP15 on chromosome 10q21.1. Rs189798 (8p23) and rs10825992 (10q21.1) showed the strongest associations in these regions (P=6.32x10-7 and P=2.17x10-5, respectively). The imputed results at 8p23 showed 2 peaks of interest. The first spanned 30kb including rs189798 between MIR4660 and PPP1R3B with the most significant association at rs17155227 (P=1.07x10-10). The second novel peak was 4kb in length, encompassing MIR124-1 and the MSRA gene, with the strongest association at rs55864141 (P=1.30x10-7). The peak of imputed data at 10q21.1 was 70kb in length between ZWINT and MIR3924, with rs3107503 having the lowest P value (P=1.54x10-7). CONCLUSION. We provide evidence for the association of MYP10 at 8p23 and MYP15 at 10p21.1 with high myopia in the French population and refine these regions of association.

The topography of DNA methylation in the non-neoplastic colonic mucosa surrounding colorectal cancers

The degree of gene hypermethylation in non-neoplastic colonic mucosa (NNCM) is a potentially important event in the development of colorectal cancer (CRC), particularly for the subgroup with a CpG island methylator phenotype (CIMP). In this study, we aimed to use an unbiased and high-throughput approach to evaluate the topography of DNA methylation in the non-neoplastic colonic mucosa (NNCM) surrounding colorectal cancer (CRC). A total of 61 tissue samples comprising 53 NNCM and 8 tumor samples were obtained from hemicolectomy specimens of two CRC patients (Cases 1 and 2). NNCM was stripped from the underlying colonic wall and samples taken at varying distances from the tumor. The level of DNA methylation in NNCM and tumor tissues was assessed at 1,505 CpG sites in 807 cancer-related genes using Illumina GoldenGate® methylation arrays. Case 1 tumor showed significantly higher levels of methylation compared to surrounding NNCM samples (P?

Trait directed de novo population transcriptome dissects genetic regulation of a balanced polymorphism in phosphorus nutrition/arsenate tolerance in a wild grass Holcus lanatus

The aim of this study was to characterize the transcriptome of a balanced polymorphism, under the regulation of a single gene, for phosphate fertilizer responsiveness/arsenate toler- ance in wild grass Holcus lanatus genotypes screened from the same habitat.

De novo transcriptome sequencing, RNAseq (RNA sequencing) and single nucleotide poly- morphism (SNP) calling were conducted on RNA extracted from H.lanatus. Roche 454 sequencing data were assembled into c. 22 000 isotigs, and paired-end Illumina reads for phosphorus-starved (P) and phosphorus-treated (P+) genovars of tolerant (T) and nontoler- ant (N) phenotypes were mapped to this reference transcriptome.

Heatmaps of the gene expression data showed strong clustering of each P+/P treated genovar, as well as clustering by N/T phenotype. Statistical analysis identified 87 isotigs to be significantly differentially expressed between N and T phenotypes and 258 between P+ and P treated plants. SNPs and transcript expression that systematically differed between N and T phenotypes had regulatory function, namely proteases, kinases and ribonuclear RNA- binding protein and transposable elements.

A single gene for arsenate tolerance led to distinct phenotype transcriptomes and SNP pro- files, with large differences in upstream post-translational and post-transcriptional regulatory genes rather than in genes directly involved in P nutrition transport and metabolism per se.

Association Study of 167 Candidate Genes for Schizophrenia Selected by a Multi-Domain Evidence-Based Prioritization Algorithm and Neurodevelopmental Hypothesis

Integrating evidence from multiple domains is useful in prioritizing disease candidate genes for subsequent testing. We ranked all known human genes (n = 3819) under linkage peaks in the Irish Study of High-Density Schizophrenia Families using three different evidence domains: 1) a meta-analysis of microarray gene expression results using the Stanley Brain collection, 2) a schizophrenia protein-protein interaction network, and 3) a systematic literature search. Each gene was assigned a domain-specific p-value and ranked after evaluating the evidence within each domain. For comparison to this
ranking process, a large-scale candidate gene hypothesis was also tested by including genes with Gene Ontology terms related to neurodevelopment. Subsequently, genotypes of 3725 SNPs in 167 genes from a custom Illumina iSelect array were used to evaluate the top ranked vs. hypothesis selected genes. Seventy-three genes were both highly ranked and involved in neurodevelopment (category 1) while 42 and 52 genes were exclusive to neurodevelopment (category 2) or highly ranked (category 3), respectively. The most significant associations were observed in genes PRKG1, PRKCE, and CNTN4 but no individual SNPs were significant after correction for multiple testing. Comparison of the approaches showed an excess of significant tests using the hypothesis-driven neurodevelopment category. Random selection of similar sized genes from two independent genome-wide association studies (GWAS) of schizophrenia showed the excess was unlikely by chance. In a further meta-analysis of three GWAS datasets, four candidate SNPs reached nominal significance. Although gene ranking using integrated sources of prior information did not enrich for significant results in the current experiment, gene selection using an a priori hypothesis (neurodevelopment) was superior to random selection. As such, further development of gene ranking strategies using more carefully selected sources of information is warranted.

CNV analysis in a large schizophrenia sample implicates deletions at 16p12.1 and SLC1A1 and duplications at 1p36.33 and CGNL1

Large and rare copy number variants (CNVs) at several loci have been shown to increase risk for schizophrenia. Aiming to discover novel susceptibility CNV loci, we analysed 6,882 cases and 11,255 controls genotyped on Illumina arrays, most of which have not been used for this purpose before. We identified genes enriched for rare exonic CNVs among cases, and then attempted to replicate the findings in an additional 14,568 cases and 15,274 controls. In a combined analysis of all samples, 12 distinct loci were enriched among cases with nominal levels of significance (P500kb), rare CNVs showed a 1.2% excess in cases after excluding known schizophrenia-associated loci, suggesting that additional susceptibility loci exist. However, even larger samples are required for their discovery.

Extremely Complex Populations of Small RNAs in the Mouse Retina and RPE/Choroid

Purpose: MicroRNAs (miRNAs) are small non-coding RNAs of ~18-22 nucleotides in length that regulate gene expression. They are widely expressed in the retina, being both required for its normal development and perturbed in disease. The aim of this study was to apply new high-throughput sequencing techniques to more fully characterise the microRNAs and other small RNAs expressed in the retina and retinal pigment epithelium (RPE)/choroid of the mouse.

Methods: Retina and RPE/choroid were dissected from eyes of 3 month-old C57BL/6J mice. Small RNA libraries were prepared and deep sequencing performed on a Genome Analyzer (Illumina). Reads were annotated by alignment to miRBase, other non-coding RNA databases and the mouse genome.

Results: Annotation of 9 million reads to 320 microRNAs in retina and 340 in RPE/choroid provides the most comprehensive profiling of microRNAs to date. Two novel microRNAs were identified in retina. Members of the sensory organ specific miR-183,-182,-96 cluster were amongst the most highly expressed, retina-enriched microRNAs. Remarkably, microRNA 'isomiRs', which vary slightly in length and are differentially detected by Taqman RT-PCR assays, existed for all the microRNAs identified in both tissues. More variation occurred at the 3' ends, including non-templated additions of T and A. Drosha-independent mirtron microRNAs and other small RNAs derived from snoRNAs were also detected.

Conclusions: Deep sequencing has revealed the complexity of small RNA expression in the mouse retina and RPE/choroid. This knowledge will improve the design and interpretation of future functional studies of the role of microRNAs and other small RNAs in retinal disease.

Using ancestry-informative markers to identify fine structure across 15 populations of European origin

The Wellcome Trust Case Control Consortium 3 anorexia nervosa genome-wide association scan includes 2907 cases from 15 different populations of European origin genotyped on the Illumina 670K chip. We compared methods for identifying population stratification, and suggest list of markers that may help to counter this problem. It is usual to identify population structure in such studies using only common variants with minor allele frequency (MAF) >5%; we find that this may result in highly informative SNPs being discarded, and suggest that instead all SNPs with MAF >1% may be used. We established informative axes of variation identified via principal component analysis and highlight important features of the genetic structure of diverse European-descent populations, some studied for the first time at this scale. Finally, we investigated the substructure within each of these 15 populations and identified SNPs that help capture hidden stratification. This work can provide information regarding the designing and interpretation of association results in the International Consortia. 

Genome-wide association study identifies novel loci associated with resistance to bovine tuberculosis

Tuberculosis (TB) caused by Mycobacterium bovis is a re-emerging disease of livestock that is of major economic importance worldwide, as well as being a zoonotic risk there is significant heritability for host resistance to bovine TB (bTB) in dairy cattle. To identify resistance loci for bTB, we undertook a genome-wide association study in female Holstein-Friesian cattle with 592 cases and 559 age-matched controls from case herds. Cases and controls were categorised into distinct phenotypes: skin test and lesion positive vs skin test negative on multiple occasions, respectively these animals were genotyped with the Illumina BovineHD 700K BeadChip. Genome-wide rapid association using linear and logistic mixed models and regression (GRAMMAR), regional heritability mapping (RHM) and haplotype-sharing analysis identified two novel resistance loci that attained chromosome-wise significance, protein tyrosine phosphatase receptor T (PTPRT; P=4.8 × 10 -7) and myosin IIIB (MYO3B; P=5.4 × 10 -6). We estimated that 21% of the phenotypic variance in TB resistance could be explained by all of the informative single-nucleotide polymorphisms, of which the region encompassing the PTPRT gene accounted for 6.2% of the variance and a further 3.6% was associated with a putative copy number variant in MYO3B the results from this study add to our understanding of variation in host control of infection and suggest that genetic marker-based selection for resistance to bTB has the potential to make a significant contribution to bTB control.

Genomic prediction for tuberculosis resistance in dairy cattle

Background: The increasing prevalence of bovine tuberculosis (bTB) in the UK and the limitations of the currently available diagnostic and control methods require the development of complementary approaches to assist in the sustainable control of the disease. One potential approach is the identification of animals that are genetically more resistant to bTB, to enable breeding of animals with enhanced resistance. This paper focuses on prediction of resistance to bTB. We explore estimation of direct genomic estimated breeding values (DGVs) for bTB resistance in UK dairy cattle, using dense SNP chip data, and test these genomic predictions for situations when disease phenotypes are not available on selection candidates. Methodology/Principal Findings: We estimated DGVs using genomic best linear unbiased prediction methodology, and assessed their predictive accuracies with a cross validation procedure and receiver operator characteristic (ROC) curves. Furthermore, these results were compared with theoretical expectations for prediction accuracy and area-under-the-ROC- curve (AUC). The dataset comprised 1151 Holstein-Friesian cows (bTB cases or controls). All individuals (592 cases and 559 controls) were genotyped for 727,252 loci (Illumina Bead Chip). The estimated observed heritability of bTB resistance was 0.23±0.06 (0.34 on the liability scale) and five-fold cross validation, replicated six times, provided a prediction accuracy of 0.33 (95% C.I.: 0.26, 0.40). ROC curves, and the resulting AUC, gave a probability of 0.58, averaged across six replicates, of correctly classifying cows as diseased or as healthy based on SNP chip genotype alone using these data. Conclusions/Significance: These results provide a first step in the investigation of the potential feasibility of genomic selection for bTB resistance using SNP data. Specifically, they demonstrate that genomic selection is possible, even in populations with no pedigree data and on animals lacking bTB phenotypes. However, a larger training population will be required to improve prediction accuracies. © 2014 Tsairidou et al.

Linking watershed terrain and hydrology to soil chemical properties, microbial communities and impacts on soil organic C in a humid mid-latitude forested watershed

Understanding the response of humid mid-latitude forests to changes in precipitation, temperature, nutrient cycling, and disturbance is critical to improving our predictive understanding of changes in the surface-subsurface energy balance due to climate change. Mechanistic understanding of the effects of long-term and transient moisture conditions are needed to quantify
linkages between changing redox conditions, microbial activity, and soil mineral and nutrient interactions on C cycling and greenhouse gas releases. To illuminate relationships between the soil chemistry, microbial communities and organic C we established transects across hydraulic and topographic gradients in a small watershed with transient moisture conditions. Valley bottoms tend to be more frequently saturated than ridge tops and side slopes which generally are only saturated when shallow storm flow zones are active. Fifty shallow (~36”) soil cores were collected during timeframes representative of low CO2, soil winter conditions and high CO2, soil summer conditions. Cores were subdivided into 240 samples based on pedology and analyses of the geochemical (moisture content, metals, pH, Fe species, N, C, CEC, AEC) and microbial (16S rRNA gene
amplification with Illumina MiSeq sequencing) characteristics were conducted and correlated to watershed terrain and hydrology. To associate microbial metabolic activity with greenhouse gas emissions we installed 17 soil gas probes, collected gas samples for 16 months and analyzed them for CO2 and other fixed and greenhouse gasses. Parallel to the experimental efforts our data is being used to support hydrobiogeochemical process modeling by coupling the Community Land Model (CLM) with a subsurface process model (PFLOTRAN) to simulate processes and interactions from the molecular to watershed scales. Including above ground processes (biogeophysics, hydrology, and vegetation dynamics), CLM provides mechanistic water, energy, and organic matter inputs to the surface/subsurface models, in which coupled biogeochemical reaction
networks are used to improve the representation of below-ground processes. Preliminary results suggest that inclusion of above ground processes from CLM greatly improves the prediction of moisture response and water cycle at the watershed scale.