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Abstract Detail

Comparative Genomics/Transcriptomics

Jin, JianJun [1], Eaton, Deren [2].

Traversome: complicated organelle genome structure resolution and isomer frequencies estimation.

Organelle genomes provide an indispensable source of the fundamental data for functional, phylogenetic and evolutionary studies, which makes the accurate and intact assembly crucial. For organelle genomes with limited repetitive sequences, the GetOrganelle toolkit has achieved accurate, complete, and rapid assembly based on second-generation sequencing data. However, most plant mitochondrial genomes and some plastid genomes, due to the existence of abundant repetitive sequences, isomers, or subgenomic structures, still lack effective methods for high-quality resolution. Here we proposed a sub-walks binomial distribution model and a likelihood algorithm of this model to estimate genomic isomer frequencies. We implemented this algorithm in a Bayesian framework and developed the tool Traversome, which utilizes the assembly graph (based on the short reads) and its graph alignment (against the long reads), to resolute separable repeats, estimate contig multiplicities, generate candidate genomic isomers, and estimate isomer frequencies. We further demonstrated that Traversome has the potential to overcome the obstacles in front of the high-quality assembly of complicated organelle genomes such as plant mitogenomes, which can facilitate the studies of organelle genome functions, structural evolution and phylogenetics.

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Related Links:

1 - Columbia University, Ecology, Evolution And Environmental Biology, 1200 Amsterdam Ave, 10th Floor, New York, NY, 10027, United States
2 - Columbia University, Ecology, Evolution, And Environmental Biology, 1200 Amsterdam Ave. , Schermerhorn Ext. Office 1007, New York, NY, 10027, United States

genome structure
graph alignment
mitochondrial genome
chloroplast genome
sub-walks binomial model
Bayesian inference.

Presentation Type: Poster
Session: P1, Comparative Genomics/Transcriptomics Posters
Location: Virtual/Virtual
Date: Monday, July 19th, 2021
Time: 5:00 PM(EDT)
Number: P1GT007
Abstract ID:766
Candidate for Awards:None


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