Novel Sequence Discovery by Subtractive Genomics.

Subtractive genomics can be used in any research where the goal is to identify the sequence of a gene, protein, or general region that is embedded in a larger genomic context. Subtractive genomics enables a researcher to isolate a target sequence of interest (T) by comprehensive sequencing and subtracting out known genetic elements (reference, R). The method can be used to identify novel sequences such as mitochondria, chloroplasts, viruses, or germline restricted chromosomes, and is particularly useful when T cannot be easily isolated from R. Beginning with the comprehensive genomic data (R + T), the method uses Basic Local Alignment Search Tool (BLAST) against a reference sequence, or sequences, to remove the matching known sequences (R), leaving behind the target (T). For subtraction to work best, R should be a relatively complete draft that is missing T. Since sequences remaining after subtraction are tested through quantitative Polymerase Chain Reaction (qPCR), R does not need to be complete for the method to work. Here we link computational steps with experimental steps into a cycle that can be iterated as needed, sequentially removing multiple reference sequences and refining the search for T. The advantage of subtractive genomics is that a completely novel target sequence can be identified even in cases in which physical purification is difficult, impossible, or expensive. A drawback of the method is finding a suitable reference for subtraction and obtaining T-positive and negative samples for qPCR testing. We describe our implementation of the method in the identification of the first gene from the germline-restricted chromosome of zebra finch. In that case computational filtering involved three references (R), sequentially removed over three cycles: an incomplete genomic assembly, raw genomic data, and transcriptomic data.