What can a molecular clock provide an estimate of?

What can a molecular clock provide an estimate of?
Chris Limb

It doesn't tick, it doesn't have hands, and it doesn't tell you what time of day it is. But a molecular clock does tell time—on an epoch scale. The molecular clock, explains Blair Hedges, is a tool used to calculate the timing of evolutionary events.

Instead of measuring seconds, minutes and hours, says Hedges, Penn State professor of biology, the molecular clock measures the number of changes, or mutations, which accumulate in the gene sequences of different species over time. Evolutionary biologists can use this information to deduce how species evolve, and to fix the date when two species diverged on the evolutionary timeline. "Unlike a wristwatch, which measures time from regular changes (ticks), a molecular clock measures time from random changes (mutations) in DNA," Hedges notes.

The concept of a molecular clock was first put forward in 1962 by chemist Linus Pauling and biologist Emile Zuckerkandl, and is based on the observation that genetic mutations, although random, occur at a relatively constant rate. Thus, the theory goes, the number of differences between any two gene sequences increases over time. As Hedges explains, this thinking led to the idea that the number of mutations in a given stretch of DNA could be used as a measure of time.

But before any clock can work, it has to be calibrated, he adds. Setting a molecular clock "begins with a known, like the fossil record," for a specific species. Then, once the rate of mutation is determined, calculating the time of divergence of that species becomes relatively easy. "If the rate is 5 mutations every million years, and you count 25 mutations in your DNA sequence, then your sequences diverged 5 million years ago."

"A nice aspect of molecular clocks is that different genes evolve at different rates, which gives us flexibility to date events throughout the history of life" Hedges points out. Broadly speaking, the evolution of important genes occurs more slowly than that of genes with less vital functions. More rapidly changing genes are used to date more recent evolutionary events, and slower evolving genes are used to map more ancient divergences, he explains.

"The molecular clock is useful for obtaining evolutionary information when you have little or no fossil record," says Hedges. "For example, fungi, which are soft and squishy, don't make fossils well. But we can take the rate of change of genes from vertebrates or plants, which have a decent fossil record, and apply it to the unknown group."

The molecular clock can also be used for putting a series of evolutionary events into chronological order. This is done by comparing sequences from different species to determine when they last shared a common ancestor, in effect drawing the family tree. "It's often difficult to do find common ancestors between species using fossils, no matter what the organism," says Hedges.

Though the molecular clock is still regarded as somewhat controversial, says Hedges, it is gaining acceptance as our understanding of genome sequences improves. "As more researchers opt to use the technique," he concludes, "the molecular clock is itself evolving into a more accurate timepiece."

S. Blair Hedges, Ph.D., is professor of biology in the Eberly College of Science, .

The use of molecular clocks to track evolution includes both ribosomal RNA sequences for deep relationships and mitochondrial DNA for recent divergences.

From: Molecular Biology (Third Edition), 2019

You read and hear it all the time—“this is an ancient, million-year-old species,” or, “this animal has been around for hundreds of thousands of years.” But, how do scientists really know how old these species are? It’s not like they can use a time machine to see—not yet, at least. But the molecular clock can help make some estimates.

It’s not magic. It’s not even just a random guess. It’s actually just a basic math problem. Scientists make a few measurements and plug the numbers into an equation to get an estimate of a species’ age. This technique is called the molecular clock, and it was thought up by scientists Linus Pauling and Emile Zuckerkandl in 1962.

What can a molecular clock provide an estimate of?

How does the molecular clock work?

Measuring the age of a species with the molecular clock technique requires just two simple things: an estimate of the number of genetic mutations between a species and its closest relative and the average genetic mutation rate (i.e., how many mutations show up in a population in a specified time frame, such as 5 mutations per year).

To show how this works, let’s take a simple hypothetical example. Let’s pretend that we’re taxonomists—biologists who study how organisms are related to each other. We’re given the job of trying to figure out how different turkeys are related to each other, and there are two species—the Ocellated Turkey (Meleagris ocellata) and the Wild Turkey (Meleagris gallopavo).

Let’s say we analyze the DNA of the two species and find that there are 5,000 mutations that are different between them. We also know the mutation rate: the species will show 1,000 new mutations every million years, or 0.001 mutation/year. If we divide the number of mutations by the mutation rate (5,000 mutations ÷ 0.001 mutation/year), we find out that these two turkey species are about 5 million years old. Ta da!

This approach doesn’t come without limitations, though. You need to assume that the genes mutate at the same rate. If the genes go through periods where they change very quickly and then don’t change at all, then it’s like having a yardstick with random ticks on it. You can’t use it to measure distance (or time) any more.

Because of this limitation (and others), there is actually a lot of science and math that goes on behind the scenes of a lot of these calculations. But at its essence, it’s just measuring the passage of time by using the mutation rate as a yardstick.

What can a molecular clock provide an estimate of?

How do scientists use the molecular clock?

The molecular clock basically measures the amount of time since two species have diverged from each other. Obviously, this would be really useful information for someone who is putting together a family tree for related species (called a phylogenetic tree), but scientists can use this information for more than just planning really epic family reunions.

Phylogenetic trees help us make sense of the world. We can see which species are related and how closely, and we can use this information for conservation measures. For example, some scientists have proposed bringing back wooly mammoths (Mammuthus primigenius) with the help of elephants. Indian elephants (Elephas maximus) are the closest living species to the wooly mammoth, having split from each other about 7 million years ago. By using similar, non-endangered species in conservation efforts for things like raising offspring, the chances of success are greatly increased.

Believe it or not, molecular clocks are also useful in forensics and epidemiology! Scientists have successfully used the molecular clock method to prove that one person infected another person with a disease, such as the case of this Spanish anesthetist who infected hundreds of patients with hepatitis C. Scientists also use the molecular clock technique to track evolving pathogens like the Zika virus or Mycobacterium tuberculosis.

The molecular clock – don’t leave home without it!

The molecular clock has proved to be an invaluable tool in an evolutionary biologist’s toolkit. Without it, we wouldn’t have a complete picture about the natural history of our world. For many organisms that don’t fossilize well, like jellyfish or bacteria, it’s the only technique that scientists can use to date the species.

Technique to deduce the time in prehistory when two or more life forms diverged

The molecular clock is a figurative term for a technique that uses the mutation rate of biomolecules to deduce the time in prehistory when two or more life forms diverged. The biomolecular data used for such calculations are usually nucleotide sequences for DNA, RNA, or amino acid sequences for proteins. The benchmarks for determining the mutation rate are often fossil or archaeological dates. The molecular clock was first tested in 1962 on the hemoglobin protein variants of various animals, and is commonly used in molecular evolution to estimate times of speciation or radiation. It is sometimes called a gene clock or an evolutionary clock.

Early discovery and genetic equidistance

The notion of the existence of a so-called "molecular clock" was first attributed to Émile Zuckerkandl and Linus Pauling who, in 1962, noticed that the number of amino acid differences in hemoglobin between different lineages changes roughly linearly with time, as estimated from fossil evidence.[1] They generalized this observation to assert that the rate of evolutionary change of any specified protein was approximately constant over time and over different lineages (known as the molecular clock hypothesis).

The genetic equidistance phenomenon was first noted in 1963 by Emanuel Margoliash, who wrote: "It appears that the number of residue differences between cytochrome c of any two species is mostly conditioned by the time elapsed since the lines of evolution leading to these two species originally diverged. If this is correct, the cytochrome c of all mammals should be equally different from the cytochrome c of all birds. Since fish diverges from the main stem of vertebrate evolution earlier than either birds or mammals, the cytochrome c of both mammals and birds should be equally different from the cytochrome c of fish. Similarly, all vertebrate cytochrome c should be equally different from the yeast protein."[2] For example, the difference between the cytochrome c of a carp and a frog, turtle, chicken, rabbit, and horse is a very constant 13% to 14%. Similarly, the difference between the cytochrome c of a bacterium and yeast, wheat, moth, tuna, pigeon, and horse ranges from 64% to 69%. Together with the work of Emile Zuckerkandl and Linus Pauling, the genetic equidistance result directly led to the formal postulation of the molecular clock hypothesis in the early 1960s.[3]

Similarly, Vincent Sarich and Allan Wilson in 1967 demonstrated that molecular differences among modern Primates in albumin proteins showed that approximately constant rates of change had occurred in all the lineages they assessed.[4] The basic logic of their analysis involved recognizing that if one species lineage had evolved more quickly than a sister species lineage since their common ancestor, then the molecular differences between an outgroup (more distantly related) species and the faster-evolving species should be larger (since more molecular changes would have accumulated on that lineage) than the molecular differences between the outgroup species and the slower-evolving species. This method is known as the relative rate test. Sarich and Wilson's paper reported, for example, that human (Homo sapiens) and chimpanzee (Pan troglodytes) albumin immunological cross-reactions suggested they were about equally different from Ceboidea (New World Monkey) species (within experimental error). This meant that they had both accumulated approximately equal changes in albumin since their shared common ancestor. This pattern was also found for all the primate comparisons they tested. When calibrated with the few well-documented fossil branch points (such as no Primate fossils of modern aspect found before the K-T boundary), this led Sarich and Wilson to argue that the human-chimp divergence probably occurred only ~4–6 million years ago.[5]

Relationship with neutral theory

The observation of a clock-like rate of molecular change was originally purely phenomenological. Later, the work of Motoo Kimura[6] developed the neutral theory of molecular evolution, which predicted a molecular clock. Let there be N individuals, and to keep this calculation simple, let the individuals be haploid (i.e. have one copy of each gene). Let the rate of neutral mutations (i.e. mutations with no effect on fitness) in a new individual be μ {\displaystyle \mu }

What can a molecular clock provide an estimate of?
. The probability that this new mutation will become fixed in the population is then 1/N, since each copy of the gene is as good as any other. Every generation, each individual can have new mutations, so there are μ {\displaystyle \mu } N new neutral mutations in the population as a whole. That means that each generation, μ {\displaystyle \mu } new neutral mutations will become fixed. If most changes seen during molecular evolution are neutral, then fixations in a population will accumulate at a clock-rate that is equal to the rate of neutral mutations in an individual.

Calibration

The molecular clock alone can only say that one time period is twice as long as another: it cannot assign concrete dates. For viral phylogenetics and ancient DNA studies—two areas of evolutionary biology where it is possible to sample sequences over an evolutionary timescale—the dates of the intermediate samples can be used to more precisely calibrate the molecular clock. However, most phylogenies require that the molecular clock be calibrated against independent evidence about dates, such as the fossil record.[7] There are two general methods for calibrating the molecular clock using fossil data: node calibration and tip calibration.[8]

Node calibration

Sometimes referred to as node dating, node calibration is a method for phylogeny calibration that is done by placing fossil constraints at nodes. A node calibration fossil is the oldest discovered representative of that clade, which is used to constrain its minimum age. Due to the fragmentary nature of the fossil record, the true most recent common ancestor of a clade will likely never be found.[8] In order to account for this in node calibration analyses, a maximum clade age must be estimated. Determining the maximum clade age is challenging because it relies on negative evidence—the absence of older fossils in that clade. There are a number of methods for deriving the maximum clade age using birth-death models, fossil stratigraphic distribution analyses, or taphonomic controls.[9] Alternatively, instead of a maximum and a minimum, a prior probability of the divergence time can be established and used to calibrate the clock. There are several prior probability distributions including normal, lognormal, exponential, gamma, uniform, etc.) that can be used to express the probability of the true age of divergence relative to the age of the fossil;[10] however, there are very few methods for estimating the shape and parameters of the probability distribution empirically.[11] The placement of calibration nodes on the tree informs the placement of the unconstrained nodes, giving divergence date estimates across the phylogeny. Historical methods of clock calibration could only make use of a single fossil constraint (non-parametric rate smoothing),[12] while modern analyses (BEAST[10] and r8s[13]) allow for the use of multiple fossils to calibrate the molecular clock. Simulation studies have shown that increasing the number of fossil constraints increases the accuracy of divergence time estimation.[14]

Tip calibration

Sometimes referred to as tip dating, tip calibration is a method of molecular clock calibration in which fossils are treated as taxa and placed on the tips of the tree. This is achieved by creating a matrix that includes a molecular dataset for the extant taxa along with a morphological dataset for both the extinct and the extant taxa.[9] Unlike node calibration, this method reconstructs the tree topology and places the fossils simultaneously. Molecular and morphological models work together simultaneously, allowing morphology to inform the placement of fossils.[8] Tip calibration makes use of all relevant fossil taxa during clock calibration, rather than relying on only the oldest fossil of each clade. This method does not rely on the interpretation of negative evidence to infer maximum clade ages.[9]

Expansion calibration

Demographic changes in populations can be detected as fluctuations in historical coalescent effective population size from a sample of extant genetic variation in the population using coalescent theory.[15][16][17] Ancient population expansions that are well documented and dated in the geological record can be used to calibrate a rate of molecular evolution in a manner similar to node calibration. However, instead of calibrating from the known age of a node, expansion calibration uses a two-epoch model of constant population size followed by population growth, with the time of transition between epochs being the parameter of interest for calibration.[18][19] Expansion calibration works at shorter, intraspecific timescales in comparison to node calibration, because expansions can only be detected after the most recent common ancestor of the species in question. Expansion dating has been used to show that molecular clock rates can be inflated at short timescales[18] (< 1 MY) due to incomplete fixation of alleles, as discussed below[20][21]

Total evidence dating

This approach to tip calibration goes a step further by simultaneously estimating fossil placement, topology, and the evolutionary timescale. In this method, the age of a fossil can inform its phylogenetic position in addition to morphology. By allowing all aspects of tree reconstruction to occur simultaneously, the risk of biased results is decreased.[8] This approach has been improved upon by pairing it with different models. One current method of molecular clock calibration is total evidence dating paired with the fossilized birth-death (FBD) model and a model of morphological evolution.[22] The FBD model is novel in that it allows for "sampled ancestors", which are fossil taxa that are the direct ancestor of a living taxon or lineage. This allows fossils to be placed on a branch above an extant organism, rather than being confined to the tips.[23]

Methods

Bayesian methods can provide more appropriate estimates of divergence times, especially if large datasets—such as those yielded by phylogenomics—are employed.[24]

Non-constant rate of molecular clock

Sometimes only a single divergence date can be estimated from fossils, with all other dates inferred from that. Other sets of species have abundant fossils available, allowing the hypothesis of constant divergence rates to be tested. DNA sequences experiencing low levels of negative selection showed divergence rates of 0.7–0.8% per Myr in bacteria, mammals, invertebrates, and plants.[25] In the same study, genomic regions experiencing very high negative or purifying selection (encoding rRNA) were considerably slower (1% per 50 Myr).

In addition to such variation in rate with genomic position, since the early 1990s variation among taxa has proven fertile ground for research too,[26] even over comparatively short periods of evolutionary time (for example mockingbirds[27]). Tube-nosed seabirds have molecular clocks that on average run at half speed of many other birds,[28] possibly due to long generation times, and many turtles have a molecular clock running at one-eighth the speed it does in small mammals, or even slower.[29] Effects of small population size are also likely to confound molecular clock analyses. Researchers such as Francisco J. Ayala have more fundamentally challenged the molecular clock hypothesis.[30][31][32] According to Ayala's 1999 study, five factors combine to limit the application of molecular clock models:

  • Changing generation times (If the rate of new mutations depends at least partly on the number of generations rather than the number of years)
  • Population size (Genetic drift is stronger in small populations, and so more mutations are effectively neutral)
  • Species-specific differences (due to differing metabolism, ecology, evolutionary history, ...)
  • Change in function of the protein studied (can be avoided in closely related species by utilizing non-coding DNA sequences or emphasizing silent mutations)
  • Changes in the intensity of natural selection.

What can a molecular clock provide an estimate of?

Woody bamboos (tribes Arundinarieae and Bambuseae) have long generation times and lower mutation rates, as expressed by short branches in the phylogenetic tree, than the fast-evolving herbaceous bamboos (Olyreae).

Molecular clock users have developed workaround solutions using a number of statistical approaches including maximum likelihood techniques and later Bayesian modeling. In particular, models that take into account rate variation across lineages have been proposed in order to obtain better estimates of divergence times. These models are called relaxed molecular clocks[33] because they represent an intermediate position between the 'strict' molecular clock hypothesis and Joseph Felsenstein's many-rates model[34] and are made possible through MCMC techniques that explore a weighted range of tree topologies and simultaneously estimate parameters of the chosen substitution model. It must be remembered that divergence dates inferred using a molecular clock are based on statistical inference and not on direct evidence.

The molecular clock runs into particular challenges at very short and very long timescales. At long timescales, the problem is saturation. When enough time has passed, many sites have undergone more than one change, but it is impossible to detect more than one. This means that the observed number of changes is no longer linear with time, but instead flattens out. Even at intermediate genetic distances, with phylogenetic data still sufficient to estimate topology, signal for the overall scale of the tree can be weak under complex likelihood models, leading to highly uncertain molecular clock estimates.[35]

At very short time scales, many differences between samples do not represent fixation of different sequences in the different populations. Instead, they represent alternative alleles that were both present as part of a polymorphism in the common ancestor. The inclusion of differences that have not yet become fixed leads to a potentially dramatic inflation of the apparent rate of the molecular clock at very short timescales.[21][36]

Uses

The molecular clock technique is an important tool in molecular systematics, the use of molecular genetics information to determine the correct scientific classification of organisms or to study variation in selective forces. Knowledge of approximately constant rate of molecular evolution in particular sets of lineages also facilitates estimation of the dates of phylogenetic events, including those not documented by fossils, such as the divergences between living taxa. In these cases—especially over long stretches of time—the limitations of the molecular clock hypothesis (above) must be considered; such estimates may be off by 50% or more.

See also

  • Charles Darwin
  • Gene orders
  • Human mitochondrial molecular clock
  • Mitochondrial Eve and Y-chromosomal Adam
  • Models of DNA evolution
  • Molecular evolution
  • Neutral theory of molecular evolution

References

  1. ^ Zuckerkandl E, Pauling (1962). "Molecular disease, evolution, and genic heterogeneity". In Kasha, M., Pullman, B (eds.). Horizons in Biochemistry. Academic Press, New York. pp. 189–225.
  2. ^ Margoliash E (October 1963). "Primary Structure and Evolution of Cytochrome C". Proceedings of the National Academy of Sciences of the United States of America. 50 (4): 672–679. Bibcode:1963PNAS...50..672M. doi:10.1073/pnas.50.4.672. PMC 221244. PMID 14077496.
  3. ^ Kumar S (August 2005). "Molecular clocks: four decades of evolution". Nature Reviews. Genetics. 6 (8): 654–662. doi:10.1038/nrg1659. PMID 16136655. S2CID 14261833.
  4. ^ Sarich VM, Wilson AC (July 1967). "Rates of albumin evolution in primates". Proceedings of the National Academy of Sciences of the United States of America. 58 (1): 142–148. Bibcode:1967PNAS...58..142S. doi:10.1073/pnas.58.1.142. PMC 335609. PMID 4962458.
  5. ^ Sarich VM, Wilson AC (December 1967). "Immunological time scale for hominid evolution". Science. 158 (3805): 1200–1203. Bibcode:1967Sci...158.1200S. doi:10.1126/science.158.3805.1200. JSTOR 1722843. PMID 4964406. S2CID 7349579.
  6. ^ Kimura M (February 1968). "Evolutionary rate at the molecular level". Nature. 217 (5129): 624–626. Bibcode:1968Natur.217..624K. doi:10.1038/217624a0. PMID 5637732. S2CID 4161261.
  7. ^ Benton MJ, Donoghue PC (January 2007). "Paleontological evidence to date the tree of life". Molecular Biology and Evolution. 24 (1): 26–53. doi:10.1093/molbev/msl150. PMID 17047029.
  8. ^ a b c d Donoghue PC, Yang Z (July 2016). "The evolution of methods for establishing evolutionary timescales". Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences. 371 (1699): 20160020. doi:10.1098/rstb.2016.0020. PMC 4920342. PMID 27325838.
  9. ^ a b c O'Reilly JE, Dos Reis M, Donoghue PC (November 2015). "Dating Tips for Divergence-Time Estimation". Trends in Genetics. 31 (11): 637–650. doi:10.1016/j.tig.2015.08.001. hdl:1983/ba7bbcf4-1d51-4b74-a800-9948edb3bbe6. PMID 26439502.
  10. ^ a b Drummond AJ, Suchard MA, Xie D, Rambaut A (August 2012). "Bayesian phylogenetics with BEAUti and the BEAST 1.7". Molecular Biology and Evolution. 29 (8): 1969–1973. doi:10.1093/molbev/mss075. PMC 3408070. PMID 22367748.
  11. ^ Claramunt S, Cracraft J (December 2015). "A new time tree reveals Earth history's imprint on the evolution of modern birds". Science Advances. 1 (11): e1501005. Bibcode:2015SciA....1E1005C. doi:10.1126/sciadv.1501005. PMC 4730849. PMID 26824065.
  12. ^ Sanderson M (1997). "A nonparametric approach to estimating divergence times in the absence of rate constancy" (PDF). Molecular Biology and Evolution. 14 (12): 1218–1231. doi:10.1093/oxfordjournals.molbev.a025731. S2CID 17647010. Archived from the original (PDF) on 21 April 2017.
  13. ^ Sanderson MJ (January 2003). "r8s: inferring absolute rates of molecular evolution and divergence times in the absence of a molecular clock". Bioinformatics. 19 (2): 301–302. doi:10.1093/bioinformatics/19.2.301. PMID 12538260.
  14. ^ Zheng Y, Wiens JJ (April 2015). "Do missing data influence the accuracy of divergence-time estimation with BEAST?". Molecular Phylogenetics and Evolution. 85 (1): 41–49. doi:10.1016/j.ympev.2015.02.002. PMID 25681677.
  15. ^ Rogers AR, Harpending H (May 1992). "Population growth makes waves in the distribution of pairwise genetic differences". Molecular Biology and Evolution. 9 (3): 552–569. doi:10.1093/oxfordjournals.molbev.a040727. PMID 1316531.
  16. ^ Shapiro B, Drummond AJ, Rambaut A, Wilson MC, Matheus PE, Sher AV, et al. (November 2004). "Rise and fall of the Beringian steppe bison". Science. 306 (5701): 1561–1565. Bibcode:2004Sci...306.1561S. doi:10.1126/science.1101074. PMID 15567864. S2CID 27134675.
  17. ^ Li H, Durbin R (July 2011). "Inference of human population history from individual whole-genome sequences". Nature. 475 (7357): 493–496. doi:10.1038/nature10231. PMC 3154645. PMID 21753753.
  18. ^ a b Crandall ED, Sbrocco EJ, Deboer TS, Barber PH, Carpenter KE (February 2012). "Expansion dating: calibrating molecular clocks in marine species from expansions onto the Sunda Shelf Following the Last Glacial Maximum". Molecular Biology and Evolution. 29 (2): 707–719. doi:10.1093/molbev/msr227. PMID 21926069.
  19. ^ Hoareau TB (May 2016). "Late Glacial Demographic Expansion Motivates a Clock Overhaul for Population Genetics". Systematic Biology. 65 (3): 449–464. doi:10.1093/sysbio/syv120. PMID 26683588.
  20. ^ Ho SY, Tong KJ, Foster CS, Ritchie AM, Lo N, Crisp MD (September 2015). "Biogeographic calibrations for the molecular clock". Biology Letters. 11 (9): 20150194. doi:10.1098/rsbl.2015.0194. PMC 4614420. PMID 26333662.
  21. ^ a b Ho SY, Phillips MJ, Cooper A, Drummond AJ (July 2005). "Time dependency of molecular rate estimates and systematic overestimation of recent divergence times". Molecular Biology and Evolution. 22 (7): 1561–1568. doi:10.1093/molbev/msi145. PMID 15814826.
  22. ^ Heath TA, Huelsenbeck JP, Stadler T (July 2014). "The fossilized birth-death process for coherent calibration of divergence-time estimates". Proceedings of the National Academy of Sciences of the United States of America. 111 (29): E2957–E2966. arXiv:1310.2968. Bibcode:2014PNAS..111E2957H. doi:10.1073/pnas.1319091111. PMC 4115571. PMID 25009181.
  23. ^ Gavryushkina A, Heath TA, Ksepka DT, Stadler T, Welch D, Drummond AJ (January 2017). "Bayesian Total-Evidence Dating Reveals the Recent Crown Radiation of Penguins". Systematic Biology. 66 (1): 57–73. arXiv:1506.04797. doi:10.1093/sysbio/syw060. PMC 5410945. PMID 28173531.
  24. ^ dos Reis M, Inoue J, Hasegawa M, Asher RJ, Donoghue PC, Yang Z (September 2012). "Phylogenomic datasets provide both precision and accuracy in estimating the timescale of placental mammal phylogeny". Proceedings. Biological Sciences. 279 (1742): 3491–3500. doi:10.1098/rspb.2012.0683. PMC 3396900. PMID 22628470.
  25. ^ Ochman H, Wilson AC (1987). "Evolution in bacteria: evidence for a universal substitution rate in cellular genomes". Journal of Molecular Evolution. 26 (1–2): 74–86. Bibcode:1987JMolE..26...74O. doi:10.1007/BF02111283. PMID 3125340. S2CID 8260277.
  26. ^ Douzery EJ, Delsuc F, Stanhope MJ, Huchon D (2003). "Local molecular clocks in three nuclear genes: divergence times for rodents and other mammals and incompatibility among fossil calibrations". Journal of Molecular Evolution. 57 (Suppl 1): S201–S213. Bibcode:2003JMolE..57S.201D. CiteSeerX 10.1.1.535.897. doi:10.1007/s00239-003-0028-x. PMID 15008417. S2CID 23887665.
  27. ^ Hunt JS, Bermingham E, Ricklefs RE (2001). "Molecular systematics and biogeography of Antillean thrashers, tremblers, and mockingbirds (Aves: Mimidae)". Auk. 118 (1): 35–55. doi:10.1642/0004-8038(2001)118[0035:MSABOA]2.0.CO;2. ISSN 0004-8038. S2CID 51797284.
  28. ^ Rheindt, F. E. & Austin, J. (2005). "Major analytical and conceptual shortcomings in a recent taxonomic revision of the Procellariiformes – A reply to Penhallurick and Wink (2004)" (PDF). Emu. 105 (2): 181–186. doi:10.1071/MU04039. S2CID 20390465.
  29. ^ Avise JC, Bowen BW, Lamb T, Meylan AB, Bermingham E (May 1992). "Mitochondrial DNA evolution at a turtle's pace: evidence for low genetic variability and reduced microevolutionary rate in the Testudines". Molecular Biology and Evolution. 9 (3): 457–473. doi:10.1093/oxfordjournals.molbev.a040735. PMID 1584014.
  30. ^ Ayala FJ (January 1999). "Molecular clock mirages". BioEssays. 21 (1): 71–75. doi:10.1002/(SICI)1521-1878(199901)21:1<71::AID-BIES9>3.0.CO;2-B. PMID 10070256. Archived from the original on 16 December 2012.
  31. ^ Schwartz, J. H. & Maresca, B. (2006). "Do Molecular Clocks Run at All? A Critique of Molecular Systematics". Biological Theory. 1 (4): 357–371. CiteSeerX 10.1.1.534.4502. doi:10.1162/biot.2006.1.4.357. S2CID 28166727.
    • "No Missing Link? Evolutionary Changes Occur Suddenly, Professor Says". ScienceDaily (Press release). 12 February 2007.
  32. ^ Pascual-García A, Arenas M, Bastolla U (November 2019). "The Molecular Clock in the Evolution of Protein Structures". Systematic Biology. 68 (6): 987–1002. doi:10.1093/sysbio/syz022. PMID 31111152.
  33. ^ Drummond AJ, Ho SY, Phillips MJ, Rambaut A (May 2006). "Relaxed phylogenetics and dating with confidence". PLOS Biology. 4 (5): e88. doi:10.1371/journal.pbio.0040088. PMC 1395354. PMID 16683862.
  34. ^ Felsenstein J (2001). "Taking variation of evolutionary rates between sites into account in inferring phylogenies". Journal of Molecular Evolution. 53 (4–5): 447–455. Bibcode:2001JMolE..53..447F. doi:10.1007/s002390010234. PMID 11675604. S2CID 9791493.
  35. ^ Marshall, D. C., et al. 2016. Inflation of molecular clock rates and dates: molecular phylogenetics, biogeography, and diversification of a global cicada radiation from Australasia (Hemiptera: Cicadidae: Cicadettini). Systematic Biology 65(1):16–34.
  36. ^ Peterson GI, Masel J (November 2009). "Quantitative prediction of molecular clock and ka/ks at short timescales". Molecular Biology and Evolution. 26 (11): 2595–2603. doi:10.1093/molbev/msp175. PMC 2912466. PMID 19661199.

Further reading

  • Ho, S.Y.W., ed. (2020). The Molecular Evolutionary Clock: Theory and Practice. Springer, Cham. doi:10.1007/978-3-030-60181-2. ISBN 978-3-030-60180-5. S2CID 231672167.
  • Kumar S (August 2005). "Molecular clocks: four decades of evolution". Nature Reviews. Genetics. 6 (8): 654–662. doi:10.1038/nrg1659. PMID 16136655. S2CID 14261833.
  • Morgan GJ (1998). "Emile Zuckerkandl, Linus Pauling, and the molecular evolutionary clock, 1959-1965". Journal of the History of Biology. 31 (2): 155–178. doi:10.1023/A:1004394418084. PMID 11620303. S2CID 5660841.
  • Zuckerkandl E, Pauling LB (1965). "Evolutionary divergence and convergence in proteins". In Bryson V, Vogel HJ (eds.). Evolving Genes and Proteins. Academic Press, New York. pp. 97–166.
  • Allan Wilson and the molecular clock
  • Molecular clock explanation of the molecular equidistance phenomenon
  • Date-a-Clade service for the molecular tree of life

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