Hybrid genome assembly of the northern acorn barnacle, Semibalanus balanoides Rebecca Elyanow, Bianca Brown, Joaquin Nunez, David Rand Brown University, Center for Computational Biology, 115 Waterman st., Providence, RI 02906 III. Methods I. Introduction Assembly of Illumina data with SOAPdenovo VI. Conclusion References V. Genome size estimation VII. Future work Barnacles have long been recognized as good model organisms in the field of population ecology and have been well studied in this context. However, little is known about the genomic structure and evolution of barnacle species. The burgeoning field of ecological genomics aims to merge insights from the fields of ecology and genomics into a unified understanding of how a population has been shaped by its environment, from a cellular level to an ecological level. The goal of this project is to develop the northern acorn barnacle, Semibalanus balanoides, as a robust model for ecological genomics. The first step in achieving this goal is to create a draft genome for S. balanoides, which will provide a reference for any future genomic studies. Assembly Metrics Mapping of Illumina reads BLAST results 1. Estimate allele frequencies of barnacles from different microhabitats (high and low tide) through pool-sequencing. See poster 209 for preliminary work. 2. Identify bacterial species that compose microbiome of S. balanoides in different microhabitats. See poster 397 for preliminary work. 3. Perform transcriptome assembly using RNA-seq data and annotate functional sites on the genome 1305 2232 18455 20986 0 5000 10000 15000 20000 25000 SOAPdenovo dipSPAdes Canu DBG2OLC N50 ASSEMBLY N50 31 98 380 525 0 100 200 300 400 500 600 SOAPdenovo dipSPAdes Canu DBG2OLC GENOME SIZE (MB) ASSEMBLY Genome Size (Mb) 2.43 15.67 56.56 70.83 0 10 20 30 40 50 60 70 80 SOAPdenovo dipSPAdes Canu DBG2OLC PERCENT OF MAPPED READS ASSEMBLY Percentage of Illumina reads mapped to assembly II. What is hybrid genome assembly? Hybrid genome assembly is the process of joining raw sequencing data into long contigs using both short-read and long-read data. • Long-reads are easier to assemble than short reads because they contain long range information and can span repeats Short paired-end read from Illumina sequencing: 2x100bp Long-read from PacBio sequencing: 6,258bp • Short-reads have a much lower error rate than long reads (0.1% vs 10%) • By combining long and short-reads together, we leverage both the long-range information from long-reads and the low error-rate of short reads Assembly of Illumina data with dipSpades Assembly of PacBio data with Canu Hybrid assembly of Illumina and Pacbio data with DBG2OLC IV. Results Raw Illumina paired-end reads SOAPdenovo assembly Raw Illumina paired-end reads Raw PacBio SMRT Cell reads Canu error- correction Raw Illumina paired-end reads DBG2OLC assembly Raw PacBio SMRT Cell reads dipSPAdes assembly Sparc consensus calling Canu trimming Canu assembly • 237 million paired-end 85bp Illumina reads were assembled by dipSPAdes • dipSPAds is designed for diploid, highly polymorphic genomes • dipSPAdes assembles haplocontigs (representing both haplomes) then produces consensus contigs and performs haplotype assembly • 237 million paired-end 85bp Illumina reads were assembled by SOAPdenovo • Contigs longer than 1kb were selected • 3 million PacBio SMRT cell reads with an average length of 6kb were assembled with Canu • The MinHash Alignment Process (MHAP) is used to detect overlapping reads and correct errors • Non-confident regions are removed through trimming • Trimmed reads are assembled with the Celera assembler • 3 million PacBio SMRT cell reads and 237 million Illumina reads were assembled with DBG2OLC • DBG2OLC uses de Bruijn Graph (DBG) to construct contigs from Illumina reads, which are used to correct PacBio reads. Corrected PacBio reads are assembled using an Overlap Layout Consensus (OLC) • Parameter tuning increased the assembly size from 409Mb to 525Mb 0 0.1 0.2 0