Sequencing

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11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting TINK: A NOVEL EUKARYOTIC EVIDENCE BASED PAN-TRANSCRIPTOME GENERATION PIPELINE Wednesday, 1st June 18:30 La Fonda NM Room (1st floor) Poster (PS‐1a.03) Chandler Roe, Jason Travis, Nathan Hicks, Elizabeth Driebe, David Engelthaler, Paul Keim TGen North While next generation sequencing has become an increasingly easy laboratory procedure, eukaryotic genome annotation is still a challenging bioinformatic task. High‐throughput mRNA sequencing (RNA‐Seq) platforms allow for a variety of applications such as novel transcript and isoform discovery, expression estimate analysis, alternative splicing as well as exploration of non‐model‐organism transcriptomes. However, the required genome assembly and annotation is a complicated and timeconsuming process that requires multiple steps and command line skills. Our pipeline, TINK, generates an evidence based pan‐transcriptome reference to be used for RNA‐Seq analysis. It provides a rapid, all encompassing, one‐time analysis that allows for discovery of unique transcripts. This pipeline combines ab initio gene prediction using the program AUGUSTUS, protein homology prediction utilizing AAT and de novo RNASeq assemblies using both PASA and Trinity. These results are weighted and combined using EvidenceModeler to create individual genome annotations for each sequenced sample and further compiles, clusters and de‐replicates these annotations to create a novel pan‐transcriptome reference. We have used this technique to explore differential expression and identify novel transcripts from the fungal pathogen Cryptococcus gatti. This pathogen has been characterized into four types, I‐IV, within which subgroups exist. In order to capture transcripts unique to one subtype of C. gattii as well as differing expression levels, multiple analyzes would need to be performed using a different reference each time, which is both computationally expensive and time consuming. TINK provided a reference to allow a single analysis on this data, greatly reducing time and resources. 37
11th Annual <strong>Sequencing</strong>, Finishing, and Analysis in the Future Meeting A RAPID, CULTURE-FREE WHOLE GENOME ASSEMBLY APPROACH FOR CHARACTERIZING COMPLEX METAGENOMICS SAMPLES Wednesday, 1st June 18:30 La Fonda NM Room (1st floor) Poster (PS‐1a.04) Paul Havlak 1 , Brandon Rice 1 , Brenden O’Connell 2 , Christopher Troll 1 , Ei Min 1 , Jonathan Stites 1 , Marco Blanchette 1 , Margot Hartley 1 , Nicholas Putnam 1 , Robert Calef 1 , Richard Green 1,2 1 Dovetail Genomics, LLC, 2 University of California‐Santa Cruz High‐throughput sequencing allows genetic analysis of complex microbial communities that inhabit a wide variety of environments. Shotgun sequencing of environmental samples, which often contain microbes that are refractory to culturing in the lab, can reveal the genes and biochemical pathways present within the organisms in a given environment. However, high‐quality de novo assembly of these highly complex datasets is generally considered to be intractable. We have developed a powerful and efficient method for de novo genome assembly of read data from complex metagenomics datasets. Our approach involves efficient generation of connectivity data from these complex DNA samples. Adapting our Chicago Method, a technique that has worked well for de novo genome assembly of single organisms, we perform proximity ligation and sequencing of in vitro assembled chromatin from metagenomic DNA samples. When combined with shotgun sequence data, we are able to generate genome‐scale assemblies of multiple organisms in metagenomics communities sampled directly from the human gut, soil, and stream water. This fast and simple approach enables a more complete understanding of microbial communities than that afforded by standard culturing techniques or shotgun sequencing alone. 38
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Reliable solutions for focused NGS
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Sequencing

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