genetic changes to a population due to mutations become more common in the next generation.
when do genetic changes to a population due to mutations become more common?
the next generation
nonlethal mutations accumulate within the gene pool and increase the amount of genetic variation. the abundance of some genetic changes within the gene pool can be reduced by natural selection, while other "more favorable" mutations may accumulate and result in adaptive changes.
mutation
during the 1980s, curtis harris at the us national cancer institute and bert vogelstein at the johns hopkins oncology center in baltimore had managed to show that different types of cancer had their own unique suite of mutations in p53, which were likely to have been caused by different agents, such as the chemicals in tobacco smoke or ultraviolet light from the sun. with the advent of next-generation sequencing, michael stratton saw the potential for the technology to revolutionize our understanding of the genetic changes inside individual tumors, setting the wellcome sanger institute's huge banks of dna-sequencing machines in motion to read every single letter of dna in a tumor. by 2009, stratton and his team had produced the first whole cancer genome sequences. these were detailed maps showing all the genetic changes and mutations that had occurred within two individual cancers—a melanoma from the skin and a lung tumor. the melanoma and lung cancer genomes were powerful proof that the fingerprints of specific culprits could be seen in cancers with one major cause. these tumors still contained many mutations that could not be explained by ultraviolet light or tobacco smoking. the detective work became a lot more complicated for cancers with complex, multiple or even completely unknown origins. by way of analogy, imagine a forensic scientist dusting for fingerprints at a murder scene. the forensic scientist might strike it lucky and find a set of perfect prints on a windowpane or door handle that match a known killer. however, they are much more likely to uncover a mish-mash of fingerprints belonging to a whole range of folk—from the victim and potential suspects to innocent parties and police investigators—all laid on top of each other on all sorts of surfaces. this is very similar to cancer genomes where multiple mutational patterns are commonly overlaid one over another making the data incomprehensible. fortunately, a phd student of stratton's, ludmil alexandrov came up with a way of mathematically solving the problem. alexandrov demonstrated that mutational patterns from individual mutagens found in a tumor can be distinguished from one another using a mathematical approach called blind source separation. the newly disentangled patterns of mutations were termed mutational signatures. in 2013, alexandrov and stratton published the first computational framework for deciphering mutational signatures from cancer genomics data. subsequently, they applied this framework to more than seven thousand cancer genomes creating the first comprehensive map of mutational signatures in human cancer. currently, more than one hundred mutational signatures have been identified across the repertoire of human cancer.
mutational signatures