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Advances in Genome Biology and Technology (AGBT) General Meeting is certainly one of the main Next Generation Sequencing events of the year which brings together the latest advances in technology, software, applications, data resources and public policy. AGBT consists of multiple scientific sessions, industry workshops and networking events allowing sharing of experience and the latest ideas in the field of sequencing.

As a bronze sponsor of AGBT 2018 we are pleased to give a talk in a main program of the conference, present a poster and have a suite for hosting various events.

Check the location of our suite “Escambia” on the plan.

Lexogen events and presentations

Workshop at Lexogen Suite – Escambia

SLAMseq and QuantSeq: Efficient Gene Expression Profiling, Now Also Time-Resolved!

Tuesday, February 13, 5:15 – 7:15 PM – Dinner reception and workshop.

Time-resolved gene expression profiling with Lexogen’s QuantSeq and SLAMseq kits

Lukas Paul, Senior Manager of Scientific Affairs, Lexogen, Austria

Tuesday, February 13, 5:45 – 6:00 PM @ Lexogen suite – Escambia

Lexogen’s family of QuantSeq kits is based on a highly efficient workflow for the generation of tag-profiling RNA-Seq libraries. One read per fragment is created, and reads mapped to annotated genes are simply counted without need for mRNA length dependent calculations. QuantSeq’s robustness (the input can be as low as 100 pg total RNA and from degraded sources such as FFPE samples), cost efficiency (starting from USD 19.80 per sample), and high multiplexing properties (only 3 M reads are needed per transcriptome and 4×96 barcodes are available) make it the ideal choice for gene expression evaluations. QuantSeq is also the perfect RNA-Seq library preparation for the SLAMseq method, published recently and already available in kit format from Lexogen. SLAMseq delivers transcriptome-wide RNA synthesis and degradation rates, and the higher number of library preparations associated with sampling at multiple time-points and in replicate is efficiently managed by the QuantSeq workflow.

SLAMseq, a new method to detect RNA synthesis and decay rates transcriptome-wide

Stefan L. Ameres, Group Leader, Institute of Molecular Biotechnology (IMBA), Austria

Tuesday, February 13, 6:00 – 6:15 PM @ Lexogen suite – Escambia

Currently available RNA sequencing methods provide only a snapshot of cellular RNA populations but obscure any information on the dynamics of RNA biogenesis and turnover. We have developed thiol-linked alkylation for the metabolic sequencing of RNA (SLAMseq), a sequencing approach that identifies RNA that has been metabolically labeled with 4-thiouridine in living cells from high-throughput sequencing data. I will discuss how SLAMseq can be used to study transcriptional and post-transcriptional gene regulation and present ongoing efforts that illustrate the compatibility of SLAMseq with various available RNA-Seq methods, including mRNA 3´ end sequencing (QuantSeq), small RNA sequencing, and full-length transcriptome sequencing.

SLAMdunk – a pipeline for analyzing SLAMseq data in established and emerging applications

Tobias Neumann, Bioinformatician, Research Institute of Molecular Pathology (IMP), Austria

Tuesday, February 13, 6:15 – 6:30 PM @ Lexogen suite – Escambia

Thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAMseq) enables the direct quantification of 4-thiouridine (4sU) labeled mRNAs within the total mRNA pool by detecting thymine-to-cytosine (T>C) conversions during reverse transcription wherever 4sU is incorporated. Inherently increased mismatch rates due to these T>C conversions, increased false-positive rates due to Single-Nucleotide-Polymorphisms (SNPs), and the lower complexity of 3’ UTR regions targeted by the QuantSeq protocol pose major challenges for accurately and robustly quantifying T>C conversions in SLAMseq datasets. We present SLAMdunk, an application of DUNK (see poster Neumann T. et al: “Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets”) to SLAMseq datasets. SLAMdunk enable researchers to analyze SLAMseq data from raw reads to fully normalized T>C conversion quantifications without expert bioinformatics knowledge and is complemented by comprehensive visualization and summary statistics. As one key application, we have established SLAMseq as an approach for monitoring direct transcriptional responses to targeted cell perturbations such as treatment with small-molecule inhibitors or rapid protein degradation through the AID/auxin systems. Applying SLAMseq/SLAMdunk to quantify changes in newly synthesized mRNAs within the first hour following acute protein inhibition or degradation enables the unambiguous identification of direct transcriptional targets, independent of variable mRNA turnover rates and prior to the onset of conceivable secondary effects. Together, our studies establish SLAMseq/SLAMdunk as a simple, robust and highly scalable method for probing direct transcriptional functions of defined genes or small-molecule inhibitors, with broad applicability in molecular biology research and drug development, which will be discussed.

QuantSeq gene expression profiling for tumor/immune analysis in mice and man

Anne-M. Krogsdam, Assistant Professor, Innsbruck Medical University, Austria

Tuesday, February 13, 6:30 – 6:45 PM @ Lexogen suite – Escambia

Three years ago, when we first tested the Lexogen 3’-RNA QuantSeq library method, we expected to have to go through a tedious implementation phase, as was the case with various other available RNA-seq methods. This however, was not the case!

Since then we have applied the Lexogen 3’-RNA QuantSeq method for various RNA expression profiling studies, including pathway analysis and determination of neo-antigen expression and expression of immune checkpoint regulators in tumors and tumor infiltrating lymphocytes.

To be able to extend our tumor expression profiling studies to larger cohorts of human patient samples we have further applied a slightly modified version of the Lexogen 3’-RNA QuantSeq method, which allows us to include even severely degraded RNA, extracted from Formalin-Fixed Paraffin-Embedded (FFPE) tumor archives.

Generally, more than half of RNA samples extracted from FFPE tumors are degraded to a point where they are no longer amenable to RNA-seq. With the modified method we are able to include previously discarded samples, giving access to a much broader spectrum of tumor samples.

Poster session – Poster #204

Estimating pre-PCR fragment numbers from post-PCR frequencies of unique molecular identifiers

Michael Moldaschl, Andreas Tuerk

Wednesday,  February 14, 4:45 – 6:10 PM

PCR amplification ensures sufficient input material in RNA-Seq sequencing. However, efficiency variations in PCR also introduce bias in subsequent gene and isoform quantification. Unique molecular identifiers (UMIs) can identify PCR duplicates. Hence, the number of pre-PCR fragment copies is often estimated as the number of distinct UMIs (UMI counting).
Here, we investigate computational methods for estimating pre-PCR fragment copies if the numbers of UMIs is too small for UMI counting or if UMIs are not uniformly distributed. We study two types of methods. The first is a correction to UMI counting, the second can be summarized as duplication model estimates (DME). For DMEs the post-PCR counts for each UMI are modelled by distributions parameterized by the number of pre-PCR copies and the duplication efficiency. Parameters are estimated simultaneously for all UMIs by maximum likelihood optimization. For duplication models with Poisson and binomial process we give closed form solutions.
We perform experiments on synthetic data from duplication models with Poisson, binomial and branching process and efficiencies between 0.5 and 0.9. Data were generated for 64 and 256 UMIs with even and biased distribution, pre-PCR fragment numbers range from 10 to 10k. Simple UMI counting fails in most cases. Corrected UMI counting leads to improved results but fails to converge once most UMIs have been seen. DMEs, in contrast, yield bias free results for all pre-PCR abundances with variance in most cases significantly smaller than that of the other methods. For Poisson or binomial duplication models the closed form solutions provide a fast algorithm. For duplication models with branching process DMEs with multi-component mixtures for the post-PCR UMI counts give the best performance amongst all duplication models and methods. Since a branching process is the most accurate description of PCR amplification we expect DMEs to perform well on real RNA-Seq data.

Plenary session

SLAMseq: Thiol-linked alkylation for the metabolic sequencing of RNA

Stefan L. Ameres, Group Leader, Institute of Molecular Biotechnology (IMBA), Austria

Thursday,  February 15, 11:35 – 11:50 AM

Gene expression profiling by high-throughput sequencing reveals qualitative and quantitative changes in RNA species at steady-state but obscures the intracellular dynamics of RNA transcription, processing and decay. We developed thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAMseq), an orthogonal chemistry-based epitranscriptome-sequencing technology that uncovers 4-thiouridine (s4U)-incorporation in RNA species at single-nucleotide resolution and absolute stoichiometry. In combination with established metabolic RNA labeling protocols and coupled to standard, high-throughput RNA sequencing methods, SLAMseq provides rapid access to RNA expression dynamics. We show that SLAMseq reports the functional RNA polymerase II-dependent transcriptional output, enables the systematic evaluation of post-transcriptional gene regulatory signatures, and provides quantitative evidence for microRNA-directed target mRNA decay. Chemical nucleotide-analog-derivatization provides an accessible, cost-effective, and scalable method for the rapid and transcriptome-wide analysis of gene expression dynamics in living cells.

Social Events

Tuesday, 13 February, 2018


Join us for the celebration of opening a new dimension in RNA-Seq. Participate in a SLAM dunk tournament and get a chance to win a portable speaker from one of the top brands.

9:30 PM – SLAM dunk tournament and Austrian schnapps testing.

11:30 PM – Prize drawing and winner announcement.

Wednesday, 14 February, 2018

Join us for the RNA and space inspired party. Discover Lexogen’s portfolio of tools to Explore the transcriptomes in your Research projects.

9:30 PM – “Mission RNA” party with cocktails and Star Wars VR experience.

Meet our team at AGBT!

Stop by our suite or contact us via email for any questions. Our AGBT team is looking forward to meeting you!


 Alexander Seitz
CEO and Founder

Dalia Daujotyte
Head of Business Development

Lukas Paul
Senior Manager of Scientific Affairs

Jekaterina Aleksejeva
Marketing Manager


Andreas Tuerk
Head of Bioinformatics

Birgit Steinmetz
Product Manager

Jeff Hudson
North American Sales Manager

Kristy Ramsey
Technical Sales Manager – West Coast



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