Mutation frequency

Mutation frequency and mutation rates are highly correlated to each other. Mutation frequencies test are cost effective in laboratories [1] however; these two concepts provide vital information in reference to accounting for the emergence of mutations on any given germ line. [2][3]

There are several test utilized in measuring the chances of mutation frequency and rates occurring in a particular gene pool. Some of the test are as follows:

Mutation frequency and rates provide vital information about how often a mutation may be expressed in a particular genetic group or sex.[6] [7] Yoon et., 2009 suggested that as sperm donors ages increased the sperm mutation frequencies increased. This reveals the positive correlation in how males are most likely to contribute to genetic disorders that reside within X-linked recessive chromosome.[8] There are additional factors affecting mutation frequency and rates involving evolutionary influences. Since, organisms may pass mutations to their offspring incorporating and analyzing the mutation frequency and rates of a particular species may provide a means to adequately comprehend its longevity [9]


References

  1. Araten, D., Golde, D., Zhang, R., Taler, H., Gargiulo, L., Notaro, G., & Luzzatto, L. (2005). A quantitative measurement for the human somatic mutation rate. Cancer Research, (65), 8111-8117.
  2. Peruzzi, B., Araten, D., Notaro, R., & Luzzatto, L. (2009). The use of pig-a as a sentinel gene for the study of the somatic mutation rate and the mutagenic agents in vivo. Mutation Research, (705), 3-10.
  3. Peruzzi, B., Araten, D., Notaro, R., & Luzzatto, L. (2009). The use of pig-a as a sentinel gene for the study of the somatic mutation rate and the mutagenic agents in vivo. Mutation Research, (705), 3-10.described mutation frequency as containing a segment of cells that includes a mutation within particular trait, and the authors defined mutation rates as being chances a innovative alteration will take place in hereditary trait due to cell division.
  4. Clune, J., Misevic, D., Ofria, C., Lenski, R., Elena, S. F., & Sanjuan, R. (2008). Natural selection fails to optimize mutation rates for long-term adaptation on rugged fitness landscapes. Computational Biology, 4(9), 1-8.
  5. Nishant, K., Singh, N., & Alani, E. (2009). Genomic mutation rates: what high-throughput methods can tell us. Bioessays, 31(9), 912-920.
  6. Yoon, S., Qin, J., Glaser, R., Jabs, E., Wexler, N., Sokol, R., Arnheim, N., & Calabrese, P. (2009). The ups and downs of mutation frequencies during aging can account for the apert syndrome paternal age effect. PLos Genetics, 5(7), 1-19.
  7. Yoon, S., Qin, J., Glaser, R., Jabs, E., Wexler, N., Sokol, R., Arnheim, N., & Calabrese, P. (2009). The ups and downs of mutation frequencies during aging can account for the apert syndrome paternal age effect. PLos Genetics, 5(7), 1-19.
  8. http://users.rcn.com./jkimball.ma.ultranet/BiologyPages/M/Mutations.html(http://users.rcn.com./jkimball.ma.ultranet/BiologyPages/M/Mutations.html)
  9. Nishant, K., Singh, N., & Alani, E. (2009). Genomic mutation rates: what high-throughput methods can tell us. Bioessays, 31(9), 912-920.

See also

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