Name: methyl-binding dna capture sequencing for patient tissues
Uploaded: 2016-10-31T12:30:00
Description: Watch this Scientific Journal Video about Methyl-binding DNA capture Sequencing for Patient Tissues at JoVE.com

The work is supported by CPRIT Research Training Award RP140105, as well as partially supported by US National Institutes of Health (NIH) grants R01 GM114142 and by William &#38; Ella Owens Medical Research Foundation.

All tissues are obtained following approval of the Institutional Review Board committee and when all participants consented to both molecular analyses and follow-up studies. The protocols are approved by the Human Studies Committee at University of Texas Health Science Center at San Antonio.
1. Methyl-binding DNA Capture (MBDCap)
<ol>
	<li>Sample collection and DNA isolation
	<ol>
		<li>Collect bulk tumor or normal tissue samples from patient paraffin embedded tissue samples.</li>
		<li>Use a co...

<ol>
	<li>Trimarchi, M. P., Mouangsavanh, M., Huang, T. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cancer+epigenetics:+a+perspective+on+the+role+of+DNA+methylation+in+acquired+endocrine.">Cancer epigenetics: a perspective on the role of DNA methylation in acquired endocrine.</a> Chin. J. Cancer. 30, 749-756 (2011).</li><li>Nair, S. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+methyl-DNA+immunoprecipitation+(MeDIP)+and+methyl-CpG+binding+domain+(MBD)+protein+capture+for+genome-wide+DNA+methylation+analysis+reveal+CpG+sequence+coverage+bias.">Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias.</a> Epigenetics. 6, 34-44 (2011).</li><li>Zuo, T., Tycko, B., Liu, T. M., Lin, J. J., Huang, T. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Methods+in+DNA+methylation+profiling.">Methods in DNA methylation profiling.</a> Epigenomics. 1, 331-345 (2009).</li><li>Clark, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparison+of+the+whole+genome+approach+of+MeDIP-seq+to+the+targeted+approach+of+the+Infinium+HumanMethylation450+BeadChip((R))+for+methylome+profiling.">A comparison of the whole genome approach of MeDIP-seq to the targeted approach of the Infinium HumanMethylation450 BeadChip((R)) for methylome profiling.</a> PLoS One. 7, e50233 (2012).</li><li>Walker, D. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+methylation+profiling:+comparison+of+genome-wide+sequencing+methods+and+the+Infinium+Human+Methylation+450+Bead+Chip.">DNA methylation profiling: comparison of genome-wide sequencing methods and the Infinium Human Methylation 450 Bead Chip.</a> Epigenomics. , 1-16 (2015).</li><li>Huang, Y. W., Huang, T. H., Wang, L. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Profiling+DNA+methylomes+from+microarray+to+genome-scale+sequencing.">Profiling DNA methylomes from microarray to genome-scale sequencing.</a> Technol. Cancer Res. Treat. 9, 139-147 (2010).</li><li>Serre, D., Lee, B. H., Ting, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MBD-isolated+Genome+Sequencing+provides+a+high-throughput+and+comprehensive+survey+of+DNA+methylation+in+the+human+genome.">MBD-isolated Genome Sequencing provides a high-throughput and comprehensive survey of DNA methylation in the human genome.</a> Nucleic Acids Res. 38, 391-399 (2010).</li><li>Brinkman, A. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-genome+DNA+methylation+profiling+using+MethylCap-seq.">Whole-genome DNA methylation profiling using MethylCap-seq.</a> Methods. 52, 232-236 (2010).</li><li>Wang, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LOcating+non-unique+matched+tags+(LONUT)+to+improve+the+detection+of+the+enriched+regions+for+ChIP-seq+data.">LOcating non-unique matched tags (LONUT) to improve the detection of the enriched regions for ChIP-seq data.</a> PLoS One. 8, e67788 (2013).</li><li>Gu, F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CMS:+a+web-based+system+for+visualization+and+analysis+of+genome-wide+methylation+data+of+human+cancers.">CMS: a web-based system for visualization and analysis of genome-wide methylation data of human cancers.</a> PLoS One. 8, e60980 (2013).</li><li>Lan, X., Bonneville, R., Apostolos, J., Wu, W., Jin, V. X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=W-ChIPeaks:+a+comprehensive+web+application+tool+for+processing+ChIP-chip+and+ChIP-seq+data.">W-ChIPeaks: a comprehensive web application tool for processing ChIP-chip and ChIP-seq data.</a> Bioinformatics. 27, 428-430 (2011).</li><li>Jadhav, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+DNA+methylation+analysis+reveals+estrogen-mediated+epigenetic+repression+of+metallothionein-1+gene+cluster+in+breast+cancer.">Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.</a> Clin. Epigenetics. 7, 13 (2015).</li><li>Hsu, Y. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Promoter+hypomethylation+of+EpCAM-regulated+bone+morphogenetic+protein+gene+family+in+recurrent+endometrial+cancer.">Promoter hypomethylation of EpCAM-regulated bone morphogenetic protein gene family in recurrent endometrial cancer.</a> Clin. Cancer Res. 19, 6272-6285 (2013).</li><li>Wang, Y. V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Roles+of+Distal+and+Genic+Methylation+in+the+Development+of+Prostate+Tumorigenesis+Revealed+by+Genome-wide+DNA+Methylation+Analysis.">Roles of Distal and Genic Methylation in the Development of Prostate Tumorigenesis Revealed by Genome-wide DNA Methylation Analysis.</a> Sci. Rep. , (2015).</li><li>Plongthongkum, N., Diep, D. H., Zhang, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+the+profiling+of+DNA+modifications:+cytosine+methylation+and+beyond.">Advances in the profiling of DNA modifications: cytosine methylation and beyond.</a> Nat Rev Gen. 15, 647-661 (2014).</li><li>Riebler, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BayMeth:+improved+DNA+methylation+quantification+for+affinity+capture+sequencing+data+using+a+flexible+Bayesian+approach.">BayMeth: improved DNA methylation quantification for affinity capture sequencing data using a flexible Bayesian approach.</a> Genome Biol. 15, R35 (2014).</li></ol>

The MBDCap-seq technique is an affinity enrichment approach3, considered as a cost effective alternative when investigating cohorts with a large number of patients15. The pipeline presented here describes a comprehensive approach from sample procurement to data analysis and interpretation. One of the most important steps is setting up a PCR amplification procedure to improve the PCR efficiency of the GC enriched regions in the genome as this is where DNA methylation occurs. Also, it is essential to ensure that after seq...

Epigenetic regulation of genes through DNA methylation is one of the essential mechanisms required to determine the cell fate by stable differentiation of different tissue types in the body1. Dysregulation of this process has been known to cause various diseases including cancer2.
This process mainly involves the addition of methyl groups on the cytosine residue in the CpG dinucleotides of DNA3. There are a few different techniques currently used to investigate this mechanism, each having their own advantages as outlined in many studies2-8. Here we will discuss one of these techniques called Methyl-Binding DNA Capture&#160;sequencing (MBDCap-seq), where we use an affinity enrichment technique to identify methylated regions of the DNA. This technique builds upon the methyl-binding ability of the MBD2 protein to enrich for the genomic DNA fragments containing methylated CpG sites. We utilize a commercial methylated DNA enrichment kit for the isolation of these methylated regions. Our laboratory has screened hundreds of patient samples using this technique and here we provide a comprehensive optimized protocol, which can be used to investigate large patient cohorts.
As evident with any next-generation sequencing technology, MBDCap-seq also requires a specific bioinformatics approach in order to accurately quantify the levels of methylation across the samples. There have been many recent studies in an effort to optimize the normalization and analysis process of the sequencing data9,10. In this protocol, we demonstrate one of these methods implementing a unique read recovery approach &#8212; LONUT &#8212; followed by linear normalization of each sample in order to enable unbiased comparisons across large number of patient samples.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Methylminer DNA enrichment Kit</td>
			<td>Invitrogen</td>
			<td>ME10025</td>
			<td></td>
		</tr>
		<tr>
			<td>Dynabeads M-280 Streptavidin</td>
			<td>Invitrogen</td>
			<td>112-05D</td>
			<td></td>
		</tr>
		<tr>
			<td>Bioruptor Plus Sonication Device</td>
			<td>diagenode</td>
			<td>B01020001</td>
			<td></td>
		</tr>
		<tr>
			<td>3M sodium acetate pH 5.2</td>
			<td>Sigma</td>
			<td>S7899</td>
			<td>100ml</td>
		</tr>
		<tr>
			<td>SPRIworks Fragment Library System I</td>
			<td>Beckman Coulter</td>
			<td>A50100</td>
			<td>Fully automated library construction system</td>
		</tr>
		<tr>
			<td>Adapter Primers</td>
			<td>Bioo Scientific</td>
			<td>514104</td>
			<td>PCR primer mix</td>
		</tr>
		<tr>
			<td>Qubit</td>
			<td>Invitrogen</td>
			<td>Q32854</td>
			<td>Fluorometric Quantitation System</td>
		</tr>
		<tr>
			<td>PCR master mix</td>
			<td>KAPA scientific</td>
			<td>KK2621</td>
			<td>PCR master mix</td>
		</tr>
		<tr>
			<td>AMPure XP</td>
			<td>Beckman Coulter</td>
			<td>A63881</td>
			<td>PCR Purification beads</td>
		</tr>
		<tr>
			<td>EB Buffer</td>
			<td>Qiagen</td>
			<td>19086</td>
			<td></td>
		</tr>
		<tr>
			<td>HiSeq 2000 Sequencing System</td>
			<td>Illumina</td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

methyl-binding dna capture sequencing for patient tissues

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable development and differentiation of different tissue types. Dysregulation of this process is often the hallmark of various diseases like cancer. Here, we outline one of the recent sequencing techniques, Methyl-Binding DNA Capture sequencing (MBDCap-seq), used to quantify methylation in various normal and disease tissues for large patient cohorts. We describe a detailed protocol of this affinity enrichment approach along with a bioinformatics pipeline to achieve optimal quantification. This technique has been used to sequence hundreds of patients across various cancer types as a part of the 1,000 methylome project (Cancer Methylome System).

We have used MBDCap-seq to study DNA methylation alterations in a large number of patients from diverse cancer types including breast12, endometrial13, prostate14, and liver cancers among others. Here we demonstrate some information from the breast cancer study published recently12. In this instance, we used the whole genome sequencing approach to identify CpG islands that are differentially methylated in tumor with respect to normal across different genomic regions. The investigation revealed that...

Watch this Scientific Journal Video about Methyl-binding DNA capture Sequencing for Patient Tissues at JoVE.com

Methyl-binding DNA capture Sequencing for Patient Tissues

Here we present a protocol to investigate genome wide DNA methylation in large scale clinical patient screening studies using the Methyl-Binding DNA Capture sequencing (MBDCap-seq or MBD-seq) technology and the subsequent bioinformatics analysis pipeline.

Methylation is one of the essential epigenetic modifications to the DNA, which is responsible for the precise regulation of genes required for stable ...

The overall goal of this technique is to systematically investigate the genome-wide DNA methylation landscape in large patient cohorts. This method can help answer key questions in the epigenetic field, especially with regards to which regions in the DNA methylation landscape get deregulated in patients. The main advantage of this technique is large number of the patient can be investigated in a cost effective manner.This technology can have positive implications into the therapy and diagnosis of the patient because we can investigate existing biomarkers and also identify novel biomarkers. Though this method can provide insight into patient cohort, it can also be applied to other systems such as DNA methylation in cells derived from cultured cell lines from mouse-derived samples. Demonstrating this procedure along with Dr.Ya-Ting Hsu will be Mr.Joseph Liu, a technician in our lab.The sequencing part will be demonstrated by Ms.Dawn Garcia who is a technician in our sequencing core. After isolating genomic DNA from tumor or normal tissue according to the text protocol, add 1.2 micrograms of total genomic DNA to 96 microliters of TE buffer and 24 microliters of 5X bind wash buffer to make a 120 microliter solution. Sonicate the DNA solution for 30 seconds, then allow it to rest for 30 seconds.Repeat the sonication a total of 20 to 25 times. Use a bioanalyzer system with a commercial high-sensitivity DNA kit according to the manufacturer's protocol to run one microliter of sonicated DNA solution to check the size of the fragments. They should be in the range of 150 to 350 base pairs.To carry out single fraction elution, prepare elution buffer by making a one-to-one solution of low-salt buffer and high-salt buffer. Use 200 microliters of the elution buffer to resuspend the methyl-binding DNA or MBD beads and incubate the suspension on a rotating mixer for three minutes. After the incubation, place the tube on the magnetic rack for one minute, then carefully pipette the liquid without touching the tip of the pipette on the beads and transfer it to a clean DNase-free 1.5 milliliter microcentrifuge tube.Store this sample on ice. Repeat the elution for the second sample and collect it in the same tube as the first sample. To each non-captured wash and dilution fraction, add one microliter of glycogen, one-tenth the volume of three molar sodium acetate, pH 5.2, and two sample volumes of 100%ethanol.After mixing the solution well, incubate at negative 80 degrees Celsius for at least two hours. Then centrifuge the reaction at 11, 363 times g and four degrees Celsius for 15 minutes. Carefully discard the supernatant without disturbing the pellet and add 500 microliters of cold 70%ethanol.Spin the tube again before repeating the ethanol wash. Air dry the pellet for five minutes. Then use DNase-free water or buffer to resuspend it.Check that the total amount of DNA is over 20 nanograms according to the text protocol. Then place the DNA on ice or store at negative 20 degrees Celsius until further use. For DNA sequencing library preparation, use a fully automated library construction system and follow the standard protocol supplied by the manufacturer.Select DNA fragments of 200 to 400 base pairs in length for library preparation. After preparing the DNA sequencing library, remove the reaction and use a fluorometric quantitation system to quantify the DNA sequencing library. To set up a PCR amplification reaction, in a PCR tube add 15 microliters of DNA sequencing library, 25 microliters of PCR master mix, two microliters of PCR primer mix, and eight microliters of water.Use the program outlined in the text protocol, making adjustments as necessary based on the recommendations of the PCR mix manufacturer. Carry out enough cycles to produce two to 10 millimolar of library DNA. After cleaning up the PCR reactions, barcode each sample and pull four samples together into one lane of a flow cell.Use the standard 50 base pair single-read protocol of our sequencing. Carry out bioinformatics according to the text protocol. Using MBD cap seek to identify CpG islands across different genomic regions that are differentially methylated in tumor with respect to normal tissue, this study revealed that out of the total CpG islands located in gene promoters, 19.5%showed differential methylation in tumors compared to normal.Similarly, 55.2%of intragenic CpG islands investigated showed differential methylation. Intragenic promoters showed 28.1%And for gene promoters without CpG islands, 1.8%showed differential methylation. This heat map clearly depicts differentially methylated regions across 77 breast tumors, 10 breast normal tissues, and 38 breast cancer cell lines.In this figure, methylation is quantified in two endometrial cancer subgroups, non-recurrent vs. recurrent, in two patients at different CpG sites in the promoter CpG island of the identified target gene SFRP1. Once mastered, this technique can be done in four to five days if it is performed properly.While attempting this procedure, it is important to remember to first test the quality of a genomic DNA being tested. Following this procedure, additional methods like pyrosequencing can be performed in order to answer questions like, which are the exact CpGs in the identified differentially enriched regions that have been altered? After its development, this technique paved the way for researchers in the field of epigenetics to explore DNA methylation in large patient cohorts.After watching this video, you should have a good understanding of how to investigate genome-wide DNA methylation in patient samples using the MBD cap sequencing technique. Keep this in mind, sometimes it can be difficult to catch the high quality of the DNA from such as FFP and DNA samples, so proper assessment of the genomic DNA is always taken when we perform the procedure.

methyl-binding-dna-capture-sequencing-for-patient-tissues

Research

JoVE Journal

Genetics

Purification of High Molecular Weight Genomic DNA from Powdery Mildew for Long-Read Sequencing

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics of these pathogens, in part due to a lack of well-developed genetic and genomic resources. These organisms have large, repetitive genomes, which have made genome sequencing and assembly prohibitively difficult. Here, we describe methods for the collection, extraction, purification and quality control assessment of high molecular weight genomic DNA from one powdery mildew species, Golovinomyces cichoracearum. The protocol described includes mechanical disruption of spores followed by an optimized phenol/chloroform genomic DNA extraction. A typical yield was 7 &#181;g DNA per 150 mg conidia. The genomic DNA that is isolated using this procedure is suitable for long-read sequencing (i.e., &#62; 48.5 kbp). Quality control measures to ensure the size, yield, and purity of the genomic DNA are also described in this method. Sequencing of the genomic DNA of the quality described here will allow for the assembly and comparison of multiple powdery mildew genomes, which in turn will lead to a better understanding and improved control of this agricultural pathogen.

Described here is a method for the extraction, purification, and quality control of genomic DNA from the obligate biotrophic fungal pathogen, powdery mildew, for use in long-read genome sequencing.

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics ...

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic fragments. Organellar genomes also exist in admixtures within a given cell or tissue type (heteroplasmy), and an abundance of subtypes may change throughout development or when under stress (sub-stoichiometric shifting). Next-generation sequencing (NGS) technologies are required to obtain deeper understanding of organellar genome structure and function. Traditional sequencing studies use several methods to obtain organellar DNA: (1) If a large amount of starting tissue is used, it is homogenized and subjected to differential centrifugation and/or gradient purification. (2) If a smaller amount of tissue is used (i.e., if seeds, material, or space is limited), the same process is performed as in (1), followed by whole-genome amplification to obtain sufficient DNA. (3) Bioinformatics analysis can be used to sequence the total genomic DNA and to parse out organellar reads. All these methods have inherent challenges and tradeoffs. In (1), it may be difficult to obtain such a large amount of starting tissue; in (2), whole-genome amplification could introduce a sequencing bias; and in (3), homology between nuclear and organellar genomes could interfere with assembly and analysis. In plants with large nuclear genomes, it is advantageous to enrich for organellar DNA to reduce sequencing costs and sequence complexity for bioinformatics analyses. Here, we compare a traditional differential centrifugation method with a fourth method, an adapted CpG-methyl pulldown approach, to separate the total genomic DNA into nuclear and organellar fractions. Both methods yield sufficient DNA for NGS, DNA that is highly enriched for organellar sequences, albeit at different ratios in mitochondria and chloroplasts. We present the optimization of these methods for wheat leaf tissue and discuss major advantages and disadvantages of each approach in the context of sample input, protocol ease, and downstream application.

The comparison and optimization of two plant organellar DNA enrichment methods are presented: traditional differential centrifugation and fractionation of the total gDNA based on methylation status. We assess the resulting DNA quantity and quality, demonstrate performance in short-read next-generation sequencing, and discuss the potential for use in long-read single-molecule sequencing.

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during cancer development and progression. Despite this, the global epigenetic regulation of lncRNAs and repetitive sequences in cancer has not been well investigated, particularly in chronic lymphocytic leukemia (CLL). This study focuses on a unique approach: the immunoprecipitation-based capture of double-stranded, methylated DNA fragments using methyl-binding domain (MBD) proteins, followed by next-generation sequencing (MBD-seq). CLL patient samples belonging to two prognostic subgroups (5 IGVH mutated samples + 5 IGVH unmutated samples) were used in this study. Analysis revealed 5,800 hypermethylated and 12,570 hypomethylated CLL-specific differentially methylated genes (cllDMGs) compared to normal healthy controls. Importantly, these results identified several CLL-specific, differentially methylated lncRNAs, repetitive elements, and protein-coding genes with potential prognostic value. This work outlines a detailed protocol for an MBD-seq and bioinformatics pipeline developed for the comprehensive analysis of global methylation profiles in highly CpG-rich regions using CLL patient samples. Finally, a protein-coding gene and an lncRNA were validated using pyrosequencing, which is a highly quantitative method to analyze CpG methylation levels to further corroborate the findings from the MBD-seq protocol.

This work describes an optimized methyl-CpG-binding domain (MBD) sequencing protocol and a computational pipeline to identify differentially methylated CpG-rich regions in chronic lymphocytic leukemia (CLL) patients.

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Retrospective MicroRNA Sequencing: Complementary DNA Library Preparation Protocol Using Formalin-fixed Paraffin-embedded RNA Specimens

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of cancer development. By using non-invasive or pre-malignant lesions from patients who later develop invasive disease, gene expression analyses may help identify early molecular alterations that predispose to cancer risk. It has been well described that nucleic acids recovered from FFPE tissues have undergone severe physical damage and chemical modifications, which make their analysis difficult and generally requires adapted assays. MicroRNAs (miRNAs), however, which represent a small class of RNA molecules spanning only up to ~18&#8211;24 nucleotides, have been shown to withstand long-term storage and have been successfully analyzed in FFPE samples. Here we present a 3&#39; barcoded complementary DNA (cDNA) library preparation protocol specifically optimized for the analysis of small RNAs extracted from archived tissues, which was recently demonstrated to be robust and highly reproducible when using archived clinical specimens stored for up to 35 years. This library preparation is well adapted to the multiplex analysis of compromised/degraded material where RNA samples (up to 18) are ligated with individual 3&#39; barcoded adapters and then pooled together for subsequent enzymatic and biochemical preparations prior to analysis. All purifications are performed by polyacrylamide gel electrophoresis (PAGE), which allows size-specific selections and enrichments of barcoded small RNA species. This cDNA library preparation is well adapted to minute RNA inputs, as a pilot polymerase chain reaction (PCR) allows determination of a specific amplification cycle to produce optimal amounts of material for next-generation sequencing (NGS). This approach was optimized for the use of degraded FFPE RNA from specimens archived for up to 35 years and provides highly reproducible NGS data.

Formalin-fixed paraffin-embedded specimens represent a valuable source of molecular biomarkers of human diseases. Here we present a laboratory-based cDNA library preparation protocol, initially designed with fresh frozen RNA, and optimized for the analysis of archived microRNAs from tissues stored up to 35 years.

&#8211;Archived, clinically classified formalin-fixed paraffin-embedded (FFPE) tissues can provide nucleic acids for retrospective molecular studies of ...

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been used to analyze the spectrum of clonal mutations in malignancy. Though far more efficient than traditional Sanger methods, NGS struggles with identifying rare clonal and subclonal mutations due to its high error rate of ~0.5&#8211;2.0%. Thus, standard NGS has a limit of detection for mutations that are &#62;0.02 variant allele fraction (VAF). While the clinical significance for mutations this rare in patients without known disease remains unclear, patients treated for leukemia have significantly improved outcomes when residual disease is &#60;0.0001 by flow cytometry. In order to mitigate this artefactual background of NGS, numerous methods have been developed. Here we describe a method for Error-corrected DNA and RNA Sequencing (ECS), which involves tagging individual molecules with both a 16 bp random index for error-correction and an 8 bp patient-specific index for multiplexing. Our method can detect and track clonal mutations at variant allele fractions (VAFs) two orders of magnitude lower than the detection limit of NGS and as rare as 0.0001 VAF.

Next-generation sequencing (NGS) is a powerful tool for genomic characterization that is limited by the high error rate of the platform (~0.5&#8211;2.0%). We describe our methods of error-corrected sequencing that allow us to obviate the NGS error rate and detect mutations at variant allele fractions as rare as 0.0001.

Conventional next-generation sequencing techniques (NGS) have allowed for immense genomic characterization for over a decade. Specifically, NGS has been ...

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding of the basis of various diseases as well as resistance and/or susceptibility mechanisms. However, FFPE tissues, which represent the most common method for preserving tissue morphology in clinical specimens, are not the best sources for gene expression profiling analysis. The RNA obtained from such samples is often degraded, fragmented, and chemically modified, which leads to suboptimal sequencing libraries. In turn, these generate poor quality sequence data that may not be reliable for gene expression analysis and mutation discovery. In order to make the most of FFPE samples and obtain the best possible data from low quality samples, it is important to take certain precautions while planning experimental design, preparing sequencing libraries, and during data analysis. This includes the use of appropriate metrics for precise sample quality control (QC), identifying the best methods for various steps during the sequencing library generation, and careful library QC. In addition, applying correct software tools and parameters for sequence data analysis is critical in order to identify artifacts in RNA-seq data, filter out contamination and low quality reads, assess uniformity of gene coverage, and measure the reproducibility of gene expression profiles among biological replicates. These steps can ensure high accuracy and reproducibility for profiling of very heterogeneous RNA samples. Here we describe the various steps for sample QC, library preparation and QC, sequencing, and data analysis that can help to increase the amount of useful data obtained from low quality RNA, such as that obtained from FFPE-RNA tissues.

This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

A Comprehensive Approach to Studying the Promoter Interactome in Scarce Cells

An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

Spatiotemporal gene transcription is tightly regulated by distal regulatory elements, such as enhancers and silencers, which rely on physical proximity with their target gene promoters to control transcription. Although these regulatory elements are easy to identify, their target genes are difficult to predict, since most of them are cell-type specific and may be separated by hundreds of kilobases in the linear genome sequence, skipping over other non-target genes. For several years, Promoter Capture Hi-C (PCHi-C) has been the gold standard for the association of distal regulatory elements to their target genes. However, PCHi-C relies on the availability of millions of cells, prohibiting the study of rare cell populations such as those commonly obtained from primary tissues. To overcome this limitation, low input Capture Hi-C (liCHi-C), a cost-effective and customizable method to identify the repertoire of distal regulatory elements controlling each gene of the genome, has been developed. liCHi-C relies on a similar experimental and computational framework as PCHi-C, but by employing minimal tube changes, modifying&#160;the reagent concentration and volumes, and swapping or eliminating steps, it accounts&#160;for minimal material loss during library construction. Collectively, liCHi-C enables the study of gene regulation and spatiotemporal genome organization in the context of developmental biology and cellular function.

Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations  

Gene expression is regulated by interactions of gene promoters with distal regulatory elements. Here, we descirbe how low input Capture Hi-C (liCHi-C) allows the identification of these interactions in rare cell types, which were previously unmeasurable.

Spatiotemporal gene transcription is tightly regulated by distal regulatory elements, such as enhancers and silencers, which rely on physical proximity ...

Library Capture, Biotin Pull-Down, and PCR Amplification Using Scarce Cell DNA Library

Begin by taking 500 to 1000 nanograms of the scarce cell DNA library. Dry the DNA with a vacuum concentrator and resuspended it in 3.4 microliters of nuclease-free water. After adding the blockers, and while on the thermocycler, at 65 degrees Celsius, transfer the hybridization solution with the biotinylated RNA to the blocked library.After closing the tube lid firmly, incubate in the thermocycler overnight at 65 degrees Celsius. Then transfer 50 microliters of T1 Streptavidin beads per sample to a 1.5 milliliter DNA low binding tube and place them on a 1.5 milliliter tube magnet. Once all the beads are stuck to the wall, remove the supernatant leaving the beads behind.Now wash the beads thrice with 200 microliters of the binding buffer from the target enrichment kit and resuspend the beads in 200 microliters of binding buffer. Transfer the sample to the resuspended beads while on the thermocycler and incubate for 30 minutes. After washing the beads with 200 microliters of wash buffer 1, incubate them for 15 minutes, rotating at room temperature.Then wash the beads thrice with 200 microliters of wash buffer 2 heated to 65 degrees Celsius and incubate in a thermo block. Finally, after amplifying the library by PCR, perform a DNA purification using paramagnetic beads by adding 270 microliters of stock beads to the sample and mixing by vortexing. An automated electrophoresis profile from a library, just before capture, provided 49.7 nanograms per microliter of DNA in 20 microliters reaction volume.However, 3.06 nanograms per microliter of DNA is obtained from a high sensitivity automated electrophoresis profile from a finished leachic library.