Name: detection of rare genomic variants from pooled sequencing using splinter
Uploaded: 2012-06-23T14:00:00
Duration: 14 min 6 s
Description: Watch this Scientific Journal Video about Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER at JoVE.com

This work was supported by the Children's Discovery Institute grant MC-II-2006-1 (RDM and TED), the NIH Epigenetics Roadmap grant [1R01DA025744-01 and 3R01DA025744-02S1] (RDM and FLMV), U01AG023746 (SC), the Saigh Foundation (FLMV and TED), 1K08CA140720-01A1 and Alex's Lemonade Stand "A" Award support (TED). We thank the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. The Center is partially supported by NCI Cancer Center Support Grant #P30 CA91842 to the Siteman Cancer Center and by ICTS/CTSA Grant# UL1RR024992 from the NationalCenter for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. This publication is solely the responsibility of the authors and does not necessarily represent the official view of NCRR or NIH.

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	<li>Vallania, F. L. M., Druley, T. E., Ramos, E., Wang, J., Borecki, I., Province, M., Mitra, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+discovery+of+rare+insertions+and+deletions+in+large+cohorts.">High-throughput discovery of rare insertions and deletions in large cohorts.</a> Genome Research. 20, 1391-1397 (2010).</li><li>Shendure, J., Mitra, R., Varma, C., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advanced+Sequencing+Technologies:+Methods+and+Goals.">Advanced Sequencing Technologies: Methods and Goals.</a> Nature Reviews of Genetics. 5, 335-344 (2004).</li><li>The 1000 Genomes Project Consortium. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+map+of+human+genome+variation+from+population-scale+sequencing.">A map of human genome variation from population-scale sequencing.</a> Nature. 467, 1061-1073 (2010).</li><li>Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Finding+the+missing+heritability+of+complex+diseases.">Finding the missing heritability of complex diseases.</a> Nature. 461, 747-753 (2009).</li><li>Reich, D. E., Lander, E. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+allelic+spectrum+of+human+disease.">On the allelic spectrum of human disease.</a> Trends Genet. 17, 502-510 (2001).</li><li>Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., Hobbs, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+rare+alleles+contribute+to+low+plasma+levels+of+HDL+cholesterol.">Multiple rare alleles contribute to low plasma levels of HDL cholesterol.</a> Science. 305, 869-872 (2004).</li><li>Ji, W., Foo, J. N., O'Roak, B. J., Zhao, H., Larson, M. G., Simon, D. B., Newton-Cheh, C., State, M. W., Levy, D., Lifton, R. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rare+independent+mutations+in+renal+salt+handling+genes+contribute+to+blood+pressure+variation.">Rare independent mutations in renal salt handling genes contribute to blood pressure variation.</a> Nat. Genet. 40, 592-599 (2008).</li><li>Ahituv, N., Kavaslar, N., Schackwitz, W., Ustaszewska, A., Martin, J., Hebert, S., Doelle, H., Ersoy, B., Kryukov, G., Schmidt, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Medical+sequencing+at+the+extremes+of+human+body+mass.">Medical sequencing at the extremes of human body mass.</a> Am. J. Hum. Genet. 80, 779-791 (2007).</li><li>Druley, T. E., Vallania, F. L., Wegner, D. J., Varley, K. E., Knowles, O. L., Bonds, J. A., Robison, S. W., Doniger, S. W., Hamvas, A., Cole, F. S., Fay, J. C., Mitra, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+rare+allelic+variants+from+pooled+genomic+DNA.">Quantification of rare allelic variants from pooled genomic DNA.</a> Nat. Methods. 6, 263-265 (2009).</li><li>Mitra, R. D., Butty, V., Shendure, J., Housman, D., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+Genotyping+and+Haplotyping+with+Polymerase+Colonies.">Digital Genotyping and Haplotyping with Polymerase Colonies.</a> Proc. Natl. Acad. Sci. 100, 5926-5931 (2003).</li></ol>

No conflicts of interest declared.

There is increasing evidence that the incidence and therapeutic response of common, complex phenotypes and diseases such as obesity8, hypercholesterolemia4, hypertension7 and others may be moderated by personal profiles of rare variation. Identifying the genes and pathways where these variants aggregate in affected populations will have profound diagnostic and therapeutic implications, but analyzing affected individuals separately can be time and cost prohibitive. Population-based analysis offers a more efficient method for surveying genetic variation at multiple loci.
We present a novel pooled-DNA sequencing protocol paired with the SPLINTER software package designed to identify this type of genetic variation across populations. We demonstrate the accuracy of this method in identifying and quantifying minor alleles within a large pooled population of 947 individuals, including rare variants that were called de novo from the pooled sequencing and validated by individual pyrosequencing. Our strategy mainly differs from other protocols by the incorporation of a positive and a negative control within every experiment. This allows SPLINTER to achieve much higher accuracy and power compared to other approaches1. The optimal coverage of 25-fold per allele is fixed independently of the size of the pool, making the analysis of large pools feasible as this requirement only scales linearly with the pool size. Our approach is very flexible and can be applied to any phenotype of interest but also to samples that are naturally heterogeneous, such as mixed cell populations and tumor biopsies. Given the ever-increasing interest in pooled sequencing from large target regions such as the exome or genome, our library prep and SPLINTER analysis is compatible with custom-capture and whole-exome sequencing, but the alignment utility in the SPLINTER package was not designed for large references sequences. Therefore, we have successfully utilized the dynamic programming aligner, Novoalign, for genome-wide alignments followed by variant calling from the pooled sample (Ramos et al., submitted). Thus, our pooled sequencing strategy can scale successfully to larger pools with increasing amounts of target sequence.

<table border="1">
<tbody>
 <tr>
 <td>Reagent Name</td>
 <td>Company</td>
 <td>Catalogue Number</td>
 <td>Section</td>
 </tr>
 <tr>
 <td>PfuUltra High-Fidelity</td>
 <td>Agilent</td>
 <td>600384</td>
 <td>1.4</td>
 </tr>
 <tr>
 <td>Betaine</td>
 <td>SIGMA</td>
 <td>B2629</td>
 <td>1.4</td>
 </tr>
 <tr>
 <td>M13mp18 ssDNA vector</td>
 <td>NEB</td>
 <td>N4040S</td>
 <td>1.5</td>
 </tr>
 <tr>
 <td>pGEM-T Easy</td>
 <td>Promega</td>
 <td>A1360</td>
 <td>1.5</td>
 </tr>
 <tr>
 <td>T4 Polynucleotide Kinase</td>
 <td>NEB</td>
 <td>M0201S</td>
 <td>2.2</td>
 </tr>
 <tr>
 <td>T4 Ligase</td>
 <td>NEB</td>
 <td>M0202S</td>
 <td>2.2</td>
 </tr>
 <tr>
 <td>Polyethylene Glycol 8000 MW</td>
 <td>SIGMA</td>
 <td>P5413</td>
 <td>2.2</td>
 </tr>
 <tr>
 <td>Bioruptor sonicator</td>
 <td>Diagenode</td>
 <td>UCD-200-TS</td>
 <td>2.3</td>
 </tr>
 </tbody>
</table>

detection of rare genomic variants from pooled sequencing using splinter

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators.
To address this need, we have developed a pooled sequencing approach1,9 and a novel software package1 for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (<a href="http://www.ibridgenetwork.org/wustl/splinter" target="_blank">http://www.ibridgenetwork.org/wustl/splinter</a>). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.

Watch this Scientific Journal Video about Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER at JoVE.com

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Pooled DNA sequencing is a fast and cost-effective strategy to detect rare variants associated with complex phenotypes in large cohorts. Here we describe the computational analysis of pooled, next-generation sequencing of 32 cancer-related genes using the SPLINTER software package. This method is scalable, and applicable to any phenotype of interest.

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any ...

detection-rare-genomic-variants-from-pooled-sequencing-using

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Biology

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The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with nutrient and energy flow within terrestrial ecosystems. Cultivation-independent environmental genomic, also known as metagenomic, approaches promise unprecedented access to this genetic information with respect to pathway reconstruction and functional screening for high value therapeutic and biomass conversion processes. However, the soil microbiome still remains a challenge largely due to the difficulty in obtaining high molecular weight DNA of sufficient quality for large insert library production. Here we introduce a protocol for extracting high molecular weight, microbial community genomic DNA from soils and sediments. The quality of isolated genomic DNA is ideal for constructing large insert environmental genomic libraries for downstream sequencing and screening applications. 
The procedure starts with cell lysis. Cell walls and membranes of microbes are lysed by both mechanical (grinding) and chemical forces (&beta;-mercaptoethanol). Genomic DNA is then isolated using extraction buffer, chloroform-isoamyl alcohol and isopropyl alcohol. The buffers employed for the lysis and extraction steps include guanidine isothiocyanate and hexadecyltrimethylammonium bromide (CTAB) to preserve the integrity of the high molecular weight genomic DNA. Depending on your downstream application, the isolated genomic DNA can be further purified using cesium chloride (CsCl) gradient ultracentrifugation, which reduces impurities including humic acids. The first procedure, extraction, takes approximately 8 hours, excluding DNA quantification step. The CsCl gradient ultracentrifugation, is a two days process. During the entire procedure, genomic DNA should be treated gently to prevent shearing, avoid severe vortexing, and repetitive harsh pipetting.

A methodology to isolate high molecular weight and high quality genomic DNA from soil microbial community is described.

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with ...

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We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

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5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene expression, maintenance of genome integrity, parental imprinting, X-chromosome inactivation, regulation of development, aging, and cancer1. Recently, the presence of an oxidized 5-mC, 5-hydroxymethylcytosine (5-hmC), was discovered in mammalian cells, in particular in embryonic stem (ES) cells and neuronal cells2-4. 5-hmC is generated by oxidation of 5-mC catalyzed by TET family iron (II)/&alpha;-ketoglutarate-dependent dioxygenases2, 3. 5-hmC is proposed to be involved in the maintenance of embryonic stem (mES) cell, normal hematopoiesis and malignancies, and zygote development2, 5-10. To better understand the function of 5-hmC, a reliable and straightforward sequencing system is essential. Traditional bisulfite sequencing cannot distinguish 5-hmC from 5-mC11. To unravel the biology of 5-hmC, we have developed a highly efficient and selective chemical approach to label and capture 5-hmC, taking advantage of a bacteriophage enzyme that adds a glucose moiety to 5-hmC specifically12.
Here we describe a straightforward two-step procedure for selective chemical labeling of 5-hmC. In the first labeling step, 5-hmC in genomic DNA is labeled with a 6-azide-glucose catalyzed by &beta;-GT, a glucosyltransferase from T4 bacteriophage, in a way that transfers the 6-azide-glucose to 5-hmC from the modified cofactor, UDP-6-N3-Glc (6-N3UDPG). In the second step, biotinylation, a disulfide biotin linker is attached to the azide group by click chemistry. Both steps are highly specific and efficient, leading to complete labeling regardless of the abundance of 5-hmC in genomic regions and giving extremely low background. Following biotinylation of 5-hmC, the 5-hmC-containing DNA fragments are then selectively captured using streptavidin beads in a density-independent manner. The resulting 5-hmC-enriched DNA fragments could be used for downstream analyses, including next-generation sequencing.
Our selective labeling and capture protocol confers high sensitivity, applicable to any source of genomic DNA with variable/diverse 5-hmC abundances. Although the main purpose of this protocol is its downstream application (i.e., next-generation sequencing to map out the 5-hmC distribution in genome), it is compatible with single-molecule, real-time SMRT (DNA) sequencing, which is capable of delivering single-base resolution sequencing of 5-hmC.

Described is a two-step labeling process using &beta;-glucosyltransferase (&beta;-GT) to transfer an azide-glucose to 5-hmC, followed by click chemistry to transfer a biotin linker for easy and density-independent enrichment. This efficient and specific labeling method enables enrichment of 5-hmC with extremely low background and high-throughput epigenomic mapping via next-generation sequencing.

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene ...

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

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Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a diagnostic service laboratory.

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its ...

Isolating Potentiated Hsp104 Variants Using Yeast Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic lateral sclerosis, and &#945;-synuclein, implicated in Parkinson&#8217;s disease, are toxic and form cytoplasmic aggregates in yeast. These features recapitulate protein pathologies observed in patients with these disorders. Thus, yeast are an ideal platform for isolating toxicity suppressors from libraries of protein variants. We are interested in applying protein disaggregases to eliminate misfolded toxic protein conformers. Specifically, we are engineering Hsp104, a hexameric AAA+ protein from yeast that is uniquely capable of solubilizing both disordered aggregates and amyloid and returning the proteins to their native conformations. While Hsp104 is highly conserved in eukaryotes and eubacteria, it has no known metazoan homologue. Hsp104 has only limited ability to eliminate disordered aggregates and amyloid fibers implicated in human disease. Thus, we aim to engineer Hsp104 variants to reverse the protein misfolding implicated in neurodegenerative disorders. We have developed methods to screen large libraries of Hsp104 variants for suppression of proteotoxicity in yeast. As yeast are prone to spontaneous nonspecific suppression of toxicity, a two-step screening process has been developed to eliminate false positives. Using these methods, we have identified a series of potentiated Hsp104 variants that potently suppress the toxicity and aggregation of TDP-43, FUS, and &#945;-synuclein. Here, we describe this optimized protocol, which could be adapted to screen libraries constructed using any protein backbone for suppression of toxicity of any protein that is toxic in yeast.

Yeast proteinopathy models are valuable tools to assess the toxicity and aggregation of proteins implicated in disease. Here, we present methods for screening Hsp104 variant libraries for toxicity suppressors. This protocol could be adapted to screen any protein library for toxicity suppressors of any protein that is toxic in yeast.

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic ...

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TRAP-rc, Translating Ribosome Affinity Purification from Rare Cell Populations of Drosophila Embryos

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Measuring levels of mRNAs in the process of translation in individual cells provides information on the proteins involved in cellular functions at a given ...

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

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We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

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Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

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RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

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Here we provide a detailed, step-by-step protocol for CRISPR/Cas9-based genome engineering of primary human B cells for gene knockout (KO) and knock-in (KI) to study biological functions of genes in B cells and the development of B-cell therapeutics.