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What will ultimately have the bigger impact on future molecular diagnostics and drug development?

Transcriptomics – Epigenetics, DNA/RNA editing, alternative splicing, microRNA regulation (79%, 99 Votes)

Genomics – Genotype, GWAS, mutations / SNP, indels, copy number variation (21%, 26 Votes)

Total Voters: 125

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Eastern Diamondback Rattlesnake (Conus bullatus)
Protozoan Parasite (Plasmodium falciparum)
Périgord Black Truffle (Tuber melanosporum)
Migratory Locust (Locusta migratoria)
Mosquito (Anopheles funestus)
Milkweed Bug (Oncopeltus fasciatus)
Greenhouse Whitefly (Trialeurodes vaporariorum)
Pigeon Pea (Cajanus Cajan)
Buckwheat (Fagopyrum)
Mungbean (Vigna radiata)
Copepod (Tigriopus californicus)
Freshwater Planarian (Schmidtea mediterranea)
Black Cohosh (Actaea racemosa)
Sweet Potato (Ipomoea batatas)

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Animal toxins represent a valuable source of pharmacologically active macromolecules, a unique system for studying molecular adaptation, and a powerful framework for examining structure-function relationships in proteins. Snake venoms in particular represent a tremendous opportunity to study a large, integrated system of proteins that contribute to a single, well-defined, ecologically critical phenotypic trait. As these proteins and peptides are produced in dedicated glands, transcriptome sequencing has proven to be an effective approach to identifying the expressed toxin genes.

Researchers at Florida State University set out to study molecular evolutionary patterns in all of the genes that contribute to a single, defined, evolutionarily critical phenotype, the ability to produce venom. So they generated a venom-gland transcriptome for the Eastern Diamondback Rattlesnake (Crotalus adamanteus) using Roche 454 sequencing technology.

They identified 40 unique toxin transcripts, 30 of which have full-length coding sequences, and 10 have only partial coding sequences. They found toxins from 11 previously described families of snake-venom toxins and have discovered two putative, previously undescribed toxin classes. The most diverse and highly expressed toxin classes are the serine proteinases, metalloproteinases, and C-type lectins. The serine proteinases are the most abundant class, accounting for 35% of the toxin sequencing reads.

Rokyta DR, Wray KP, Lemmon AR, Lemmon EM, Caudle SB. (2011) A high-throughput venom-gland transcriptome for the Eastern Diamondback Rattlesnake (Crotalus adamanteus) and evidence for pervasive positive selection across toxin classes. Toxicon [Epub ahead of print]. [abstract]

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from Genetic Engineering News- Third-Generation Sequencing Debuts
by Vicki Glaser

Helicos BioSciences

In Helicos’ tSMS technology, labeled nucleotides are mixed with nucleic-acid templates immobilized on a flow cell. Detection of the fluorescent signals emitted as a result of each base addition is performed in the HeliScope™ Genetic Analysis System. The Helicos system can sequence 105–180 megabases/hour with average read lengths of 33–36 bases from templates ranging in length from 25 to 5,000 bases.

It will enable a range of applications including chromatin profiling by direct sequencing of immunoprecipitated DNA, direct RNA sequencing, small RNA quantitation, digital gene expression, copy number variation assessment, and epigenetic analysis.

For direct RNA sequencing, the system can produce 300–400 million aligned reads/run with an average read length of 34 nucleotides (range 25–55) and a <5% per nucleotide error rate. Dr. Milos presented qualitative and quantitative data from RNA studies using tSMS to map the 3´ ends of RNA transcripts from yeast and human liver cells, producing a high-resolution map of 3´ polyadenylation sites. Another project under way is using direct RNA sequencing to study a pool of micro-RNAs and generate miRNA count distribution. Early results suggest that the technique yields greater quantitative accuracy than conventional cDNA-based methods.

Pacific BioSciences

In Pacific BioSciences SMRT™ sequencing technology, sequencing takes place on SMRT cells, each of which contains thousands of zero-mode waveguides (ZMWs). Each ZMW represents a hole tens of nanometers in diameter in a metal film that has been deposited on a silicon dioxide substrate.

The PacBio system generates both DNA sequence and epigenomic information directly from the real-time sequencing of genomic DNA. Single-molecule sensitivity enables faster results and longer read lengths.

Within about two years, the company plans to offer an application that will enable direct RNA sequencing in real time on the SMRT system without the need to convert RNA to cDNA. This application will provide insights into the epigenetics of RNA. An example was presented at the AGBT conference in which RNA sequencing using SMRT technology could distinguish pseudo-uridine from its native analog.

(read the full article…)

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The 12th annual Advances in Genome Biology and Technology (AGBT) meeting will be held in Marco Island, Florida, from February 2-5, 2011. The AGBT meeting has become the most complete scientific forum for acquiring information about the latest advances in DNA (and RNA) sequencing technologies and their myriad applications.

Thursday, February 3rd (Morning)

9:45 a.m. – 10:15 a.m.
David Craig, TGen, “Integrative Analysis of Whole-Genome and Transcriptome Sequence Data for Identification of Treatment Options for Metastatic Triple Negative Breast Cancer”

10:15 a.m. – 10:45 a.m.
Andy Mungall, BC Cancer Agency, “Analyses of Approximately Two Hundred Acute Myeloid Leukemia Messenger and MicroRNA Transcriptomes”

7:50 p.m. – 8:10 p.m.
Obi Griffith, Lawrence Berkeley National Lab., “Transcriptome and Exome Sequencing of Breast Cancer Cell Lines to Identify Molecular Predictors of Response to Anti-Cancer Compounds”

Thursday, February 3rd (Evening)

7:30 p.m. – 7:50 p.m.
Scott Kuersten, Epicentre Biotechnologies, LLC, “Analysis of RNA 5′ End Modifications by RNA-seq”

7:50 p.m. – 8:10 p.m.
Kai Lao, Life Technologies, “Tracing the Derivation of Embryonic Stem Cells From the Inner Cell Mass by Single Cell RNA-Seq Analysis”

8:30 p.m. – 8:50 p.m.
Brian Haas, Broad Institute of MIT and Harvard, “Transcriptome Without a Genome: de novo Reconstruction of Transcriptomes Using RNA-Seq Data”

8:50 p.m. – 9:10 p.m.
Inanc Birol, BC Cancer Agency, “De novo Assembly of Transcriptome Sequencing Data Identifies Chimeric Transcription in Healthy Mouse Tissue”

9:10 p.m. – 9:30 p.m.
Christopher Mason, Weill Cornell Medical College, “SeQC: Expansion and Refinement of the Human Genome by Ultra-Deep RNA Sequencing”

Friday, February 4th (Afternoon & Evening)

8:20 p.m. – 8:40 p.m.
Praveen Cherukuri, NHGRI, “Massively Parallel Sequencing of Exomes and Transcriptomes in ClinSeq Participants”

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Bed bugs (Cimex lectularius) are blood-feeding insects poised to become one of the major pests in households throughout the United States. Resistance of C. lectularius to insecticides/pesticides is one factor thought to be involved in its sudden resurgence. Despite its high-impact status, scant knowledge exists at the genomic level for C. lectularius.

Researchers at Ohio State University used 454 pyrosequencing to study the C. lectularius transcriptome in order to identify potential genes involved in pesticide resistance.

KEGG analysis of the C. lectularius sequences revealed putative members of several detoxification pathways involved in pesticide resistance. Lamprin domains, Protein Kinase domains, Protein Tyrosine Kinase domains and cytochrome P450 domains were among the top Pfam domains predicted for the C. lectularius sequences. An initial assessment of putative defense genes, including a cytochrome P450 and a glutathione-S-transferase (GST), revealed high transcript levels for the cytochrome P450 (CYP9) in pesticide-exposed versus pesticide-susceptible C. lectularius populations.

Bai X, Mamidala P, Rajarapu SP, Jones SC, Mittapalli O (2011) Transcriptomics of the Bed Bug (Cimex lectularius). PLoS ONE 6(1): e16336. [article]

RNA-Seq Insights into the Active Genome

Part of the X-Gen Congress and Expo
March 14-18 San Diego, CA

Transcriptomics underpins many fields of biological science. While RNA-Seq is perhaps the most complex NGS application, the determination of expression levels of specific genes, differential splicing, and allele-specific expression of transcripts addresses many biological-related issues. These range from basic cellular function to the understanding of biological vents that govern the development and progression of disease. NGS is transforming our understanding of transcriptomes and giving new biological insights into the “active genome.”

(download the final agenda… )

Day 1 – Wed, March 16th

Plenary Keynote Session:
The Personal Impact of Sequencing from Patient to Population

It Takes a Village
Hugh Rienhoff, M.D., Director, MyDaughtersDNA.org

Data-Driven Personalized Medicine
Atul Butte, M.D., Ph.D., Assistant Professor, Pediatrics, Medicine, Computer Science, Stanford University, Lucille Packard Children’s Hospital

Clinical Significance of Indigenous Genome Sequencing
Vanessa Hayes, Ph.D., Professor, Human Genomics, J. Craig Venter Institute

Luncheon Presentation Sponsored by: Agilent Technologies

Transcriptomes

RNA-Seq in Solving Real World Biological Problems
Erik Flemington, Ph.D., Professor, Pathology, Tulane Health Sciences Center; Professor, Cancer Research, Program Leader, Cancer Genetics program, Tulane Cancer Center

Integrating Short, Long, and Paired-End Sequencing to Study Dynamic Transcriptomes During Neural Differentiation of Human Embryonic Stem Cells
Jiaqian Wu, Ph.D., Postdoctoral Research Fellow, Genetics, Stanford University School of Medicine

Scaffolding a Caenorhabditis nematode Genome with RNA-Seq
Ali Mortazavi, Ph.D., California Institute of Technology (invited)

The Transcriptome of the Human Pathogen Trypanosoma brucei at Single-Nucleotide Resolution
Christian Tschudi, Ph.D., Associate Professor, Epidemiology of Microbial Diseases, Yale University

Widespread and Unexpected Effects of RDR2 Mutation on the Expression of Transposons, Genes and 24 NT Small RNAs
Yi Jia, Ph.D., Postdoctoral Associate, Department of Plant Breeding and Genetics, Cornell University Read more

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Here is an excellent tutorial posted on the SEQanswers web forum by Matt Young.

Guide to analyzing RNA-seq data – BioinfWiki.pdf

Guide to analyzing RNA-seq data – BioinfWiki – Update 21-01-2011.pdf

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NEUMA (Normalization by Expected Uniquely Mappable Area) is a novel, efficient and intuitive approach of estimating mRNA abundances from the whole transcriptome shotgun sequencing (RNA-Seq) data. NEUMA, is based on effective length normalization using uniquely mappable areas of gene and mRNA isoform models. Using the known transcriptome sequence model such as RefSeq, NEUMA pre-computes the numbers of all possible gene-wise and isoform-wise informative reads: the former being sequences mapped to all mRNA isoforms of a single gene exclusively and the latter uniquely mapped to a single mRNA isoform. The results are used to estimate the effective length of genes and transcripts, taking experimental distributions of fragment size into consideration. Quantitative RT-PCR based on 27 randomly selected genes in two human cell lines and computer simulation experiments demonstrated superior accuracy of NEUMA over other recently developed methods. NEUMA covers a large proportion of genes and mRNA isoforms and offers a measure of consistency (‘consistency coefficient’) for each gene between an independently measured gene-wise level and the sum of the isoform levels. NEUMA is applicable to both paired-end and single-end RNA-Seq data. We propose that NEUMA could make a standard method in quantifying gene transcript levels from RNA-Seq data.

NEUMA is available at: http://neuma.kobic.re.kr/

Lee S, Seo CH, Lim B, Yang JO, Oh J, Kim M, Lee S, Lee B, Kang C, Lee S. (2011) Accurate quantification of transcriptome from RNA-Seq data by effective length normalization. Nucleic Acids Res 39(2), e9. [abstract]

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from Nature Biotechnology

Two methods for de novo transcriptome assembly of short reads were published this year from Lior Pachter and colleagues¹ and from Aviv Regev and colleagues². The transcriptome can be analyzed by sequencing cDNA reverse transcribed from RNA (RNA-Seq), but mapping and assembling the resulting reads are challenging owing to the complexities introduced by RNA splicing. The two methods are the first that robustly assemble full-length transcripts, including alternative splicing isoforms. In contrast to previous approaches, these two methods first map reads to the genome using software that takes possible splice junctions into account, thereby making assembly more manageable. Then, they apply graph-based algorithms to determine^{1, 2} and quantify¹ the most likely splice isoforms. The algorithms were applied to mammalian transcriptomes to follow global patterns of splicing during a developmental time course¹ and to identify novel, spliced, long, noncoding RNAs that had not been annotated by existing methods².

Read the full review³

1. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. (2010) Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28(5), 511-15. [abstract]
2. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A. (2010) Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol (5), 503-10. [abstract]
3. Mak HC. (2011) Next-generation sequence analysis. Nature Biotechnology 29, 45-46. [article]

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Tisserant E, Da Silva C, Kohler A, Morin E, Wincker P, Martin F. (2011) Deep RNA sequencing improved the structural annotation of the Tuber melanosporum transcriptome. New Phytol 189(3), 883-91. [abstract]

Mizrachi E, Hefer CA, Ranik M, Joubert F, Myburg AA. (2010) De novo assembled expressed gene catalog of a fast-growing Eucalyptus tree produced by Illumina mRNA-Seq. BMC Genomics 11, 681. [abstract]

Coleman SJ, Zeng Z, Wang K, Luo S, Khrebtukova I, Mienaltowski MJ, Schroth GP, Liu J, MacLeod JN. (2010) Structural annotation of equine protein-coding genes determined by mRNA sequencing. Anim Genet 41(Suppl 2), 121-30. [abstract]

Martin J, Zhu W, Passalacqua KD, Bergman N, Borodovsky M. (2010) Bacillus anthracis genome organization in light of whole transcriptome sequencing. BMC Bioinformatics 11(Suppl 3), S10. [abstract]

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• RNA-SeqDatasetsImprovingGenomeAnnotationinPlants Animals Bacteria|RNA-SeqBlog

Illumina Acquires Epicentre Biotechnologies, Leading Provider of Nucleic Acid Sample Preparation Reagents and Specialty Enzymes
Combination Enhances Illumina’s Sample Preparation and Enzyme Portfolio

1/11/11 07:30 PM  SAN DIEGO–(BUSINESS WIRE)–Illumina, Inc. (NASDAQ:ILMN) today announced that it has acquired Epicentre Biotechnologies, a leading provider of nucleic acid sample preparation reagents and specialty enzymes used in sequencing and microarray applications. A key component of the acquisition is direct access to Epicentre’s proprietary Nextera™ technology for next-generation sequencing library preparation, which greatly simplifies genetic analysis workflows and reduces time from sample preparation to answer. (read the entire release… )

Illumina Announces MiSeq™ Personal Sequencing System
Delivers Next-Generation Sequencing to Individual Researchers

1/11/11 07:20 PM  SAN DIEGO–(BUSINESS WIRE)–Illumina, Inc. (NASDAQ:ILMN) today announced MiSeq™, a low-cost personal sequencing system that provides individual researchers a platform with rapid turnaround time, unmatched accuracy, and radically improved ease of use. Leveraging the company’s TruSeq™ sequencing chemistry, the system’s revolutionary workflow offers the flexibility to go from purified DNA to analyzed data in as few as eight hours, or to generate in excess of 1 gigabase per run in slightly over a day. Expected to be priced under $125,000 with individual run prices ranging from $400-$750, MiSeq will be the most affordable next-generation sequencing (NGS) platform available. (read the entire release… )

Life Technologies Makes DNA Sequencing More Accessible to Laboratories of All Sizes Around the World
New Innovations Lower Costs and Simplify Workflows

1/11/11 07:30 AM  CARLSBAD, Calif.–(BUSINESS WIRE)–Life Technologies Corporation (NASDAQ: LIFE) today announced a series of new product innovations across the company’s DNA sequencing portfolio. To date, most sequencing technologies have primarily addressed the needs of researchers in the highest throughput laboratories, limiting widespread accessibility of these powerful next-generation sequencing technologies. As a pioneer of DNA sequencing, Life Technologies continues to enable researchers in any size laboratory to access applications that meet their specific technical and financial research requirements. As a result of these innovations, researchers now have greater flexibility from their sequencing platforms, a more simplified sample preparation, increased data throughput and expedited data analysis. (read the entire release… )

Biologist- RNA seq – NIH – Bethesda, Maryland
Kelly Scientific Resources (Bethesda, MD)
…you must have: 1. Bachelor degree with 3+ years experience in Genome Technology, RNA Seq , and validation. 2. OR Master degree with 1+ year experience…
Science Careers (11/08/10)

Bioinformatics Scientist
Illumina (Hayward, CA)
…and develop bioinformatics tools for analyzing sequencing data from different assays including: RNA – Seq , miRNA profiling and discovery, ChiP- Seq and DNA…
Illumina (01/07/11)

Stanford Postdoctoral Fellow
Stanford Univeristy (Stanford,CA)
… a postdoctoral fellow position open for investigation of role of epigenetics and pluripotent stem cell biology. The ideal candidate should be a recent PhD graduate with solid background in DNA-seq, RNA-seq, CHiP, and other molecular biology skills…
Nature Jobs (1/6/11)

Research Scientist
Lockheed Martin (MD)
…bioinformatics tools for whole genome sequencing analysis, variant detection (SNPs and indels), ChIP- Seq , RNA – Seq , etc. .Proficiency in the use of UNIX/Linux…
Lockheed Martin (01/05/11)

Bioinformatics Systems Engineer II* (Center for Human Genetics)
Vanderbilt University (Nashville, TN)
…assist with analysis of high-throughput sequencing datasets derived from whole genome re-sequencing, RNA – seq , ChlP- seq , and custom DNA capture projects. The…
iHireJobNetwork (01/03/11)

Scientist – Translational Medicine, Sequencing
Sanofi-Aventis (Cambridge, MA)
…to address scientific questions. Scienfic questions will include somatic mutation detection, RNA – seq , copy number variation assessment, working with FFPE tissue,…
CareerBuilder.com (12/31/10)

PhD or Postdoc: Genomic regulatory control and variation in Drosophila
University of Leuven (Belgium)
…will use fly genetics, combined with high-throughput technologies such as RNA-Seq and ChIP-Seq to measure gene expression and transcription factor binding on a genomic scale…
Nature Jobs (12/28/10)

DNA Sequencing and Computational Biology Core Facility Director
National Institutes of Health (Bethesda, MD)
… will participate in analyzing large-scale data sets consisting of a wide spectrum of sequencing applications, including but not limited to chromatin immunoprecipitation sequencing (ChIP-Seq), RNA-seq, targeted and whole-genome DNA sequencing, microRNA sequencing…
Nature Jobs (12/22/10)

Postdoctoral Fellow In Epigenetics
New York University School of Medicine (Tuxedo, NY)
Posted: December 20, 2010
…will use genomic approaches such as ChIP-Seq, RNA-Seq and microarrays, in addition to conventional molecular biological and biochemical techniques to undertake projects related to epigenetics and functional genomics, in collaboration with bioinformaticians…
Nature Jobs (12/20/10)

Research Scientists I & II (Bioinformatics/Systems Biology)
Henry M. Jackson Foundation (Frederick, MD)
…involving bio informatics (eg, algorithms for next-generation sequencing, metagenomics, and RNA – Seq and systems biology (eg, signaling, protein, and metabolic…
ScienceCareers.com (12/15/10)

Research Specialist
Howard Hughes Medical Institute (Philadelphia, PA)
…the lab uses DNA microarray technology and high throughput sequencing (RNA-Seq) to measure the expression levels of genes in a cell…
Monster (11/19/10)

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• SEQanswers – RNA Sequencing

  • TopHat extremely low paired mapping rate. PLS HELP! May 22, 2013
    Hey guys, I have some problems with my paried-end RNA seq analysis on Galaxy. As you can see in the bam flagstat output, my tophat alignment rate is... […]
    Felix.Lee
  • Identifying small RNA sequence within whole genome sequence May 21, 2013
    Hi all, I want to know if there are any useful bioinformatic tool to find small RNA sequence within a whole bacteria genome. Thank you in... […]
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  • standard of clean data May 21, 2013
    Hi all I recently got my prokaryotes RNA-seq data report back. the standard filter steps of the raw data set by our local sequencing center is as... […]
    Pengfei Liu
  • Problem with cummeRbund diffData() May 20, 2013
    Hi all, I'm running Tophat/cufflinks/cuffdiff for differential gene expression and analysis with cummeRbund (v 2.0.0). I'm having an issue with... […]
    Enrique Zudaire
  • How to increase rowsize in heatmap? May 16, 2013
    Hi, I am a complete newbie to all things cummeRbund and am currently fighting with generating readable heatmaps. When I use ... […]
    Mags
  • novoalign mapping May 15, 2013
    Hi, I want to use novoalign to map reads - allowing up to 15 mismatches for 100 bp paired-end reads I am new to novoalign(went through the... […]
    abh

• Biostar – RNA-Seq

  • Why am I getting so many unmapped reads in STAR, classified as "too short"?
    I am currently using STAR to map several Hi-SEQ mRNA runs. I'm having trouble getting a decent amount of reads to map, but I don't really understand why. I'm hoping you can shed some light :) In the final log, only about 50% (or less) of the reads map to the reference. I'm using a GTF in addition to the genome. The unmapped bin that most […]
  • What are the best practices for SNP identification in RNA seq transcriptome data
    I have 20 RICE RNA seq tranascriptome data hiseq 2000 platform paired end reads. I aligned fasta reads with BWA and remove PCR duplicates with PICARD. Later I call SNP with samtools using various parameters. I would like to clarify what parameters should I used while alinging to reference rice genome for looking SNP location 100 bp upstream and 250 bp downst […]
  • How do TopHat options -g , --supress-hits, and Bowtie options interplay?
    Hi, I am currently using TopHat2 to map RNA-seq runs. I think there have been some changes pertaining the -g option. Does anyone know how it works now? I used to think that setting -g would look for n alignments for a given read, report them [if top-scoring] and discard those reads that had more than g [top scoring] alignments. Now, the description sounds mo […]
  • What happened to -k in TopHat for multiple-mapping reads?
    Selecting -g n in tophat does not discard reads mapping more than n, but instead only reports n alignments for those out all all their TOP scoring alignments. I think there used to be an option -k that would allow one to discard reads that topped x alignments -- whatever happened to that? I only see -g in the tophat 2 manual, no reporting options like before […]
  • Does tophat use the library-type information for mapping, or just for the XS flag?
    When I specify library-type to TopHat, i.e., first-strand, second-strand, unstranded, TopHat appends a value + or - to the XS:A flag, which is useful for subsequent analyses, such as annotation. However, does this information actually influence the "mappability" of reads, or is this unaffected? My thinking is that the information would be considere […]
  • Purpose of Y-shaped adapters in Illumina Sequencing?
    Hi all, Y adapters different sequences to be annealed to the 5' and 3' ends of each molecule in a library. The arms of the Y are unique, and the middle part, connected to the DNA fragment, is complementary. What are the advantages of this? My take of this over having fully-complementary adapters (ADAPTER1 - - - - - ADAPTER1) is that: -Upon primer a […]