Focussing reduced representation CpG sequencing through judicious restriction enzyme choice

ABSTRACTBackgroundDNA methylation in CpG context is fundamental to the epigenetic regulation of gene expression in high eukaryotes. Disorganization of methylation status is implicated in many diseases, cellular differentiation, imprinting, and other biological processes. Techniques that enrich for biologically relevant genomic regions with high CpG content are desired, since, depending on the size of an organism’s methylome, the depth of sequencing required to cover all CpGs can be prohibitively expensive. Currently, restriction enzyme based reduced representation bisulfite sequencing and its modified protocols are widely used to study methylation differences. Recently, Agilent Technologies and Roche NimbleGen have ventured to both reduce sequencing costs and capture CpGs of known biological relevance by marketing in-solution custom-capture hybridization platforms. We aimed to evaluate the similarities and differences of these three methods considering each targets approximately 10-13% of the human methylome.ResultsOverall, the regions covered per platform were as expected: targeted capture based methods covered >95% of their designed regions whereas the restriction enzyme-based method covered >70% of the expected fragments. While the total number of CpG loci shared by all methods was low, ~30% of any platform, the methylation levels of CpGs common across platforms were concordant. Annotation of CpG loci with genomic features revealed roughly the same proportions of feature annotations across the three platforms. Targeted capture methods encompass similar amounts of annotations with the restriction enzyme based method covering fewer promoters (~9%) and shores (~8%) and more unannotated loci (7-14%).ConclusionsAlthough all methods are largely consistent in terms of covered CpG loci and cover similar proportions of annotated CpG loci, the restriction based enrichment results in more unannotated regions and the commercially available capture methods result in less off-target regions. Quality of DNA is very important for restriction based enrichment and starting material can be low. Conversely, quality of the starting material is less important for capture methods, and at least twice the amount of starting material is required. Pricing is marginally less for restriction based enrichment, and number of samples to be prepared is not restricted to the number of samples a kit supports. The one advantage of capture libraries is the ability to custom design areas of interest. The choice of the technique should be decided by the number of samples, the quality and quantity of DNA available and the biological areas of interest since comparable data are obtained from all platforms.

Download Full-text

DNA methylation estimation using methylation-sensitive restriction enzyme bisulfite sequencing (MREBS)

10.1101/217208 ◽

2017 ◽

Cited By ~ 2

Author(s):

Giancarlo Bonora ◽

Liudmilla Rubbi ◽

Marco Morselli ◽

Constantinos Chronis ◽

Kathrin Plath ◽

...

Keyword(s):

Dna Methylation ◽

Restriction Enzyme ◽

Large Scale ◽

Bisulfite Sequencing ◽

Multiple Regression Model ◽

Reduced Representation ◽

A Genome ◽

Genome Bisulfite Sequencing ◽

Methylation Sensitive Restriction Enzyme ◽

Wide Scale

ABSTRACTWhole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) are widely used for measuring DNA methylation levels on a genome-wide scale(1). Both methods have limitations: WGBS is expensive and prohibitive for most large-scale projects; RRBS only interrogates 6-12% of the CpGs in the human genome(16,19). Here, we introduce methylation-sensitive restriction enzyme bisulfite sequencing (MREBS) which has the reduced sequencing requirements of RRBS, but significantly expands the coverage of CpG sites in the genome. We built a multiple regression model that combines the two features of MREBS: the bisulfite conversion ratios of single cytosines (as in WGBS and RRBS) as well as the number of reads that cover each locus (as in MRE-seq(12)). This combined approach allowed us to estimate differential methylation across 60% of the genome using read count data alone, and where counts were sufficiently high in both samples (about 1.5% of the genome), our estimates were significantly improved by the single CpG conversion information. We show that differential DNA methylation values based on MREBS data correlate well with those based on WGBS and RRBS. This newly developed technique combines the sequencing cost of RRBS and DNA methylation estimates on a portion of the genome similar to WGBS, making it ideal for large-scale projects of mammalian genomes.

Download Full-text

In silico analysis identifies novel restriction enzyme combinations that expand reduced representation bisulfite sequencing CpG coverage

BMC Research Notes ◽

10.1186/1756-0500-7-534 ◽

2014 ◽

Vol 7 (1) ◽

Cited By ~ 10

Author(s):

Daniel B Martinez-Arguelles ◽

Sunghoon Lee ◽

Vassilios Papadopoulos

Keyword(s):

Restriction Enzyme ◽

In Silico ◽

Bisulfite Sequencing ◽

In Silico Analysis ◽

Reduced Representation ◽

Reduced Representation Bisulfite Sequencing ◽

Silico Analysis

Download Full-text

Would an RRS by any other name sound as RAD?

10.1101/283085 ◽

2018 ◽

Author(s):

Erin O Campbell ◽

Bryan M T Brunet ◽

Julian R Dupuis ◽

Felix A H Sperling

Keyword(s):

Literature Review ◽

Restriction Enzyme ◽

Restriction Enzymes ◽

Shotgun Sequencing ◽

Sequencing Technology ◽

Reduced Representation ◽

Minor Elements ◽

Scientific Innovation ◽

A Genome ◽

Unique Method

ABSTRACTSampling markers throughout a genome with restriction enzymes emerged in the 2000s as reduced representation shotgun sequencing (RRS). Rapid advances in sequencing technology have since spurred modifications of RRS, giving rise to many derivatives with unique names, such as RADseq. But naming conventions have often been more creative than consistent, with unclear criteria for recognition as a unique method resulting in a proliferation of names characterized by ambiguity. We conducted a literature review to assess methodological and etymological relationships among 36 restriction enzyme-based methods, as well as rates of correct referencing of commonly-used methods. We identify several instances of methodological convergence or misattribution in the literature, and note that many published derivatives have modified only minor elements of parent protocols. We urge greater restraint in naming derivative methods, to strike a better balance between clarity, recognition of scientific innovation, and correct attribution.

Download Full-text

Comprehensive evaluation of SNP identification with the Restriction Enzyme-based Reduced Representation Library (RRL) method

BMC Genomics ◽

10.1186/1471-2164-13-77 ◽

2012 ◽

Vol 13 (1) ◽

pp. 77 ◽

Cited By ~ 7

Author(s):

Ye Du ◽

Hui Jiang ◽

Ying Chen ◽

Cong Li ◽

Meiru Zhao ◽

...

Keyword(s):

Restriction Enzyme ◽

Comprehensive Evaluation ◽

Reduced Representation ◽

Reduced Representation Library

Download Full-text

Predicting genome sizes and restriction enzyme recognition-sequence probabilities across the eukaryotic tree of life

10.1101/007781 ◽

2014 ◽

Author(s):

Santiago Herrera ◽

Paula H. Reyes-Herrera ◽

Timothy M. Shank

Keyword(s):

Restriction Enzyme ◽

High Throughput Sequencing ◽

Sequence Data ◽

Restriction Enzymes ◽

Tree Of Life ◽

Design Element ◽

Recognition Sequence ◽

Reduced Representation ◽

Common Strategy ◽

Taxonomic Groups

High-throughput sequencing of reduced representation libraries obtained through digestion with restriction enzymes ? generically known as restriction-site associated DNA sequencing (RAD-seq) ? is a common strategy to generate genome-wide genotypic and sequence data from eukaryotes. A critical design element of any RAD-seq study is a knowledge of the approximate number of genetic markers that can be obtained for a taxon using different restriction enzymes, as this number determines the scope of a project, and ultimately defines its success. This number can only be directly determined if a reference genome sequence is available, or it can be estimated if the genome size and restriction recognition sequence probabilities are known. However, both scenarios are uncommon for non-model species. Here, we performed systematic in silico surveys of recognition sequences, for diverse and commonly used type II restriction enzymes across the eukaryotic tree of life. Our observations reveal that recognition-sequence frequencies for a given restriction enzyme are strikingly variable among broad eukaryotic taxonomic groups, being largely determined by phylogenetic relatedness. We demonstrate that genome sizes can be predicted from cleavage frequency data obtained with restriction enzymes targeting ?neutral? elements. Models based on genomic compositions are also effective tools to accurately calculate probabilities of recognition sequences across taxa, and can be applied to species for which reduced-representation data is available (including transcriptomes and ?neutral? RAD-seq datasets). The analytical pipeline developed in this study, PredRAD (https://github.com/phrh/PredRAD), and the resulting databases constitute valuable resources that will help guide the design of any study using RAD-seq or related methods.

Download Full-text

A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

10.1101/694133 ◽

2019 ◽

Author(s):

Melanie K. Hess ◽

Suzanne J. Rowe ◽

Tracey C. Van Stijn ◽

Hannah M. Henry ◽

Sharon M. Hickey ◽

...

Keyword(s):

Microbial Community ◽

Correspondence Analysis ◽

High Throughput ◽

Restriction Enzyme ◽

Low Cost ◽

Methane Emissions ◽

Phenotypic Correlation ◽

Reduced Representation ◽

Freeze Dried ◽

Reduced Representation Sequencing

AbstractMicrobial community profiles have been associated with a variety of traits, including methane emissions in livestock, however, these profiles can be difficult and expensive to obtain for thousands of samples. The objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n=236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to sequencing. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of host genetics, laboratory and analytical method, and the genetic and phenotypic correlations with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach via a correspondence analysis, with estimates for repeatability of 0.62±0.06, heritability 0.31±0.29, and genetic and phenotypic correlation with methane emissions of 0.88±0.25 and 0.64±0.05 respectively for the first component of correspondence analysis. The reference-free approach assigned 62.0±5.7% of reads to common 65 bp tags, much higher than the reference-based approach of 6.8±1.8% of reads assigned. Sensitivity studies suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, therefore the current work of 118 samples/lane and future proposed 384 samples/lane are well within that threshold. Our approach is now being used to investigate host factors affecting the rumen and its association with a variety of production and environmental traits. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Download Full-text