Deep sequencing refers to sequencing a genomic region multiple times, sometimes hundreds or even thousands of times. This next-generation sequencing (NGS) approach allows researchers to detect rare clonal types, cells, or microbes comprising as little as 1% of the original sample.
Deep sequencing is useful for studies in oncology, microbial genomics, and other research involving analysis of rare cell populations. For example, deep sequencing is required to identify mutations within tumors, because normal cell contamination is common in cancer samples, and the tumors themselves likely contain multiple sub-clones of cancer cells.
The need for deep sequencing depends on a number of factors. For example, in cancer research, the required sequencing depth increases for low purity tumors, highly polyclonal tumors, and applications that require high sensitivity (identifying low frequency clones). Cancer sequencing depth typically ranges from 80× to up to thousands-fold coverage.
Tumors usually consist of a mixture of normal and tumor tissue. A tumor that contains 50% normal tissue would require double the sequencing depth to detect the tumor mutations with the same confidence as a 100% pure tumor sample.
Advanced tumors are frequently polyclonal. The more clonal types that are present, the deeper the sequencing needs to be to represent each clonal type properly.
Clones representing 1% of the original tumor have the potential to become the predominant clone during drug-resistant relapse. A 1% clone will only be represented once in 100× coverage, assuming the tumor contains no normal tissue.
Deep coverage across the 15 genes most commonly mutated in solid tumors to detect rare variants.
Cost-effective targeted deep sequencing for low-throughput labs.
*i.e. the probability of detecting a mutation at a given allele frequency or abundance level of a tumor clone