VascoElbrecht's video: Blasting HiSeq data in Geneious to find mitochondrial reads Part 4

In this tutorial I will show you how to map your NGS data agains a reference genome to find mitochondrial reads and assemble them to generate a novel mitochondrial genome. However, we accidentally downloaded NGS data from a butterfly, and not a stonefly, giving us a really hard time to assemble the genome and work with the data due tu the high genetic distance to the reference genome. However, this is not to bad, as I show all the tricks and approaches what to do when working with a difficult dataset. You will probably have an easier time as your reference genome will be more closely related. However, the process outlined in this tutorial should work just fine = ) (Check out the follow up video to see the process with the correct NGS dataset) 0:13 Importing reference genomes into Geneious 0:53 Finding the optimal reference genome using ncbi Blast 2:51 Creating a Blast database in geneious including all reference genomes and blasting the SRA reads against it 6:05 Assembling the blast hits against the mitochondrial reference 6:41 Using a part of the draft genome to find the optimal reference genome to map the reads again (The blast search before was not perfect, as it used data of the same Genus, not the actual species of the SRA data) 8:38 Selecting the final reference genome, and run a blast search of the NGS data against it (+ map hits against reference genome) 11:57 Fist draft genome + sequence editing to remove errors 15:06 blasting the NGS reads against several improved draft genomes (adding of new hits to the assembly and sequence editing) 25:11 Mapping additional reads to the assembly to test if gaps in the sequence data are due to low coverage (reads not present in the dataset) or genetic distance of the reference genome (to difficult to map / detect with blast) 28:54 Annotate reliable and unreliable / missing regions in the consensus of the mitogenome assembly (includes data editing) 33:34 Compare our final draft against the other published genomes (Alignment) to see if they code for the same proteins or if there are strong differences (Making a MAFFT alignment) 37:11 Giving up (Wrong data set, of cause it could not work. But lets try again with the right one in the next video!)