The authors have declared that no competing interests exist.
Conceived and designed the experiments: SW SE JM. Performed the experiments: SW. Analyzed the data: SW JM CO. Contributed reagents/materials/analysis tools: WW FZ JY XN JS. Wrote the paper: SW CO.
The timing of the origin and diversification of rodents remains controversial, due to conflicting results from molecular clocks and paleontological data. The fossil record tends to support an early Cenozoic origin of crown-group rodents. In contrast, most molecular studies place the origin and initial diversification of crown-Rodentia deep in the Cretaceous, although some molecular analyses have recovered estimated divergence times that are more compatible with the fossil record. Here we attempt to resolve this conflict by carrying out a molecular clock investigation based on a nine-gene sequence dataset and a novel set of seven fossil constraints, including two new rodent records (the earliest known representatives of Cardiocraniinae and Dipodinae). Our results indicate that rodents originated around 61.7–62.4 Ma, shortly after the Cretaceous/Paleogene (K/Pg) boundary, and diversified at the intraordinal level around 57.7–58.9 Ma. These estimates are broadly consistent with the paleontological record, but challenge previous molecular studies that place the origin and early diversification of rodents in the Cretaceous. This study demonstrates that, with reliable fossil constraints, the incompatibility between paleontological and molecular estimates of rodent divergence times can be eliminated using currently available tools and genetic markers. Similar conflicts between molecular and paleontological evidence bedevil attempts to establish the origination times of other placental groups. The example of the present study suggests that more reliable fossil calibration points may represent the key to resolving these controversies.
Molecular clocks and fossil record are the two major approaches to date evolutionary divergence times, which are crucial for using the Tree of Life to understand evolutionary processes and mechanisms. In the case of major divergences among groups of placental mammals, the general tendency has been for paleontological studies to suggest that these events took place in the Paleocene, while molecular ones place them deep in the Cretaceous
Molecular clocks attempt to pinpoint divergence events whereas the fossil record alone can yield minimum estimates given by the first known fossil occurrence for a given group
We use the fossils noted above to create seven fossil calibrations with a nine-gene sequence dataset to re-evaluate the timing of rodent origin and diversification. For taxon sampling, we included major lineage across rodents, and sampled comprehensively within Dipodoidea to include all six subfamilies, an approach we referred to as “bottom-up” taxon sampling (i.e. building up an analytic model from a foundation of many individual data samples, versus the “top-down” approach of inferring an analytic model from relatively few data points). This sampling approach allowed us to accurately incorporate these new calibration points based on Chinese dipodoid fossils that are comparatively recent in geological time. Our analysis implements a relaxed molecular clock model using Bayesian and maximum likelihood approaches. Our results suggest that rodents originated and diversified after the K/Pg boundary at the beginning of the Cenozoic, a finding consistent with patterns found in the fossil record.
The BEAST
We inferred a time-calibrated phylogenetic tree for 41 mammal species focusing on the superfamily Dipodoidea (jerboas and relatives) for which we sampled 18 species, representing all six subfamilies. Nine unlinked nuclear genes were used to construct the tree using Bayesian
The Bayesian posterior probability and the maximum likelihood bootstrap values for each of the nodes are provided from the left to the right of the slash, respectively. Support scores are not shown for nodes that receive a full support of both posterior probability and bootstrap value.
Fossil constraints are indicated by circle A to G on the corresponding nodes:
Nodes | Description of Nodes | Bayesian estimates | Foss. Cons. Exp. Dist. | Likelihood estimates | Uniform constraint | ||||
ESS | Mean | offset | 95% cre. int. | Mini. | Maxi. | ||||
1 | Marsupialia-Placentalia | 165.3 (160–175.7) | 8861 | 3.9 | 124.6 | 160–190 | - | 160 | 160 |
2 | Base of Boreoeutheria | 69.8 (58.6–81.9) | 257 | - | - | - | 69.71 | - | - |
3 | Perissodactyla-Carnivora | 56.5 (44.2–69.5) | 691 | 2.5 | 62.3 | 62.36–71.52 | 60.7 | - | - |
4 | Caniformia-Feliformia | 41.6 (38–48.4) | 1992 | 6.5 | 38 | 38–61.98 | 42.55 | 38 | 61.7 |
5 | Primates-Glires | 65.2 (55–75.4) | 254 | - | - | - | 65.35 | - | - |
6 | Hominoidea-Lemuroidea | 55.6 (40.4–70) | 697 | - | - | - | 57.86 | - | - |
7 | Lagomorpha-Rodentia | 61.7 (52.8–71) | 251 | - | - | - | 62.37 | - | - |
8 | Ochotonidae-Leporidae | 34.6 (18.8–50.7) | 386 | - | - | - | 38.11 | - | - |
9 | Base of Rodentia | 57.7 (50.1–66) | 245 | - | - | - | 58.89 | - | - |
10 | Base of Hystricomorpha | 50.2 (41.6–58.7) | 445 | - | - | - | 52.32 | - | - |
11 | Hystricidae-Caviomorpha | 36.9 (31.6–43) | 1095 | - | - | - | 35.19 | - | - |
12 |
|
29.8 (28.5–32.2) | 4214 | 2.3 | 28.5 | 28.56–36.98 | 28.5 | 28.5 | 37 |
13 |
|
24.6 (17.6–30) | 876 | - | - | - | 25.52 | - | - |
14 | Myodonta-Sciuromorpha | 55.6 (48.4–63.2) | 251 | - | - | - | 56.98 | - | - |
15 | Base of Sciuromorpha | 25.4 (11.9–38.6) | 245 | - | - | - | 35.87 | - | - |
16 |
|
17.8 (7.3–29.9) | 228 | - | - | - | 27.54 | - | - |
17 | Myodonta-Castorimorpha | 52.9 (46.5–59.9) | 268 | - | - | - | 54.57 | - | - |
18 | Base of Castorimorpha | 45.5 (33.9–55.3) | 408 | - | - | - | 49.96 | - | - |
19 | Heteromyidae-Geomyidae | 20.6 (9.9–32.2) | 453 | - | - | - | 22.31 | - | - |
20 | Muroidea-Dipodoidea | 45.4 (43–49.4) | 539 | 3 | 43 | 43.08–54.07 | 46.08 | 43 | 54 |
21 | Cricetidae-Muridae | 23.4 (14.7–32.2) | 561 | - | - | - | 20.93 | - | - |
22 | Mouse-Rat | 9.5 (7.3–12.9) | 1206 | 1.4 | 7.3 | 7.335–12.46 | 10.96 | 7.3 | 12.2 |
24 | Base of Dipodoidea | 32.4 (25.2–39.7) | 515 | - | - | - | 28.85 | - | - |
25 | Zapodidae-Dipodidae | 25.3 (19.1–31.7) | 528 | - | - | - | 22.47 | - | - |
26 |
|
5.7 (1.9–10.1) | 1063 | - | - | - | 3.5 | - | - |
27 | Base of Dipodidae | 18.3 (13.9–22.8) | 664 | - | - | - | 16.15 | - | - |
28 |
|
10.2 (9–12.4) | 4295 | 1.1 | 9 | 9.028–13.06 | 11.27 | 9 | 13 |
29 | Euchoreutinae-Allactaginae | 14.1 (11.2–17.3) | 693 | - | - | - | 12.24 | - | - |
30 | Dipodinae-Allactaginae | 12.4 (10.5–14.9) | 747 | 0.7 | 10.5 | 10.52–13.08 | 11.29 | 10.5 | 13 |
31 | Base of Allactaginae | 7.7 (5.4–9.9) | 562 | - | - | - | 4.53 | - | - |
37 | Base of Dipodinae | 7.5 (5–9.8) | 627 | - | - | - | 4.25 | - | - |
Values in parentheses are the 95% credibility intervals. - indicates that the corresponding node was not present in the corresponding analyses. Abbreviations: Foss. Cons. Exp. Dist., fossil constraints set as exponential distribution; ESS, effective sample size; Cre. Int., credibility interval; Mini, minimum; Maxi, Maximum.
We estimate that the divergence between rodents and lagomorphs occurred about 61.7 Ma (Bayesian, Bayesian credibility interval (BCI) 52.8–71) or 62.4 Ma (likelihood). The basal divergence of rodents was estimated to be 57.7 Ma (Bayesian, BCI 50.1–66) or 58.9 Ma (likelihood). These estimates are roughly consistent with recent interpretations of the early gliran fossil record. The oldest known Glires,
We tested for the Node Density Effect (NDE)
Although the confidence intervals attached to our Bayesian estimates are relatively wide, as is often the cases for studies like this one that employ a limited number of genes
We tested the sensitivity of applying different fossil constraints for their impact on the estimated times of divergence within rodents.
Compared with the estimated dates using all constraints, omitting constraint D for the divergence between Dipodoidea and Muroidea has limited impact on the estimated times for all nodes. The estimated date of 44 Ma (BCI 33.9–54.9) for Dipodoidea-Muroidea divergence is close to 45.4 Ma (BCI 43–49.3) when this fossil constraint was employed (
Nodes | Description of Nodes | Bayesian (unit: Ma) | Likelihood (unit: Ma) | ||||
124.6 root | No cons. D | No cons. E, F, G | No cons. C, D, F, G | 180 root | No cons. E, F, G | ||
1 | Marsupialia-Placentalia | 127.8 (124.6–134) | 165.1 (160–175.1) | 165.6 (160–176.8) | 165.9 (160–177.6) | – | – |
2 | Base of Boereoeutheria | 68.1 (58–79.3) | 68.1 (54.6–83.3) | 77.4 (62.2–94.9) | 84.3 (57.6–116.5) | 72.9 | 69.71 |
3 | Perissodactyla-Carnivora | 55.5 (43.6–67.7) | 55.9 (43–69.7) | 61.1 (45.4–78.6) | 64.2 (44.2–88.3) | 63.11 | 60.70 |
4 | Caniformia-Feliformia | 41.4 (38–47.9) | 41.4 (38–47.8) | 41.9 (38–49.3) | 42.4 (38–50.8) | 44.07 | 42.55 |
5 | Primates-Glires | 63.8 (55.2–73.7) | 63.6 (51.4–78.1) | 72.4 (58.3–88) | 79 (53.2–108.6) | 68.03 | 65.35 |
6 | Hominoidea-Lemuroidea | 54.2 (39.5–68.1) | 54.6 (37.8–71.1) | 62.1 (43.5–81.3) | 66.4 (41–95.7) | 60.08 | 57.86 |
7 | Lagomorpha-Rodentia | 60.5 (52.5–69.4) | 60.2 (48.7–73.4) | 68.4 (55.6–82.6) | 74.7 (50.6–103) | 64.81 | 62.37 |
8 | Ochotonidae-Leporidae | 34 (18.5–50.2) | 34.2 (17.3–50) | 38.9 (20.3–57.5) | 41.5 (19.7–64.6) | 39.43 | 38.11 |
9 | Base of Rodentia | 56.7 (49.8–64.5) | 56.2 (45.3–68.1) | 63.7 (52–76.5) | 69.7 (46.5–96.1) | 61.06 | 58.89 |
10 | Base of Hystricomorpha | 49.6 (42.1–57.7) | 49.1 (39.7–59.5) | 54.8 (44–66.8) | 58.9 (39.1–83.9) | 54.00 | 52.32 |
11 | Hystricidae-Caviomorpha | 36.87 (31.5–42.4) | 36.6 (31.1–42.8) | 38.7 (32–46.2) | 38.8 (22.3–56.3) | 35.52 | 35.19 |
12 |
|
29.8 (28.5–32.2) | 29.8 (28.5–32.3) | 30 (28.5–32.9) | 28.5 (15.9–43) | 28.50 | 28.50 |
13 |
|
24.7 (17.9–30.1) | 24.8 (18.2–30.3) | 24.9 (18.6–30.1) | 23.5 (11.8–36.5) | 25.48 | 25.52 |
14 | Myodonta-Sciuromorpha | 54.7 (48.3–62) | 54.1 (43.4–65.7) | 61.3 (50.4–73.8) | 67.3 (45.6–91.9) | 59.06 | 56.98 |
15 | Base of Sciuromorpha | 25.3 (12.8–38.6) | 25.7 (12.8–39.9) | 29.8 (15.8–45.6) | 32.3 (14.4–53.5) | 37.12 | 35.87 |
16 |
|
17.8 (6.7–30.6) | 18.2 (7.1–31.4) | 21.3 (9.2–35.6) | 23 (8.2–40.9) | 28.48 | 27.54 |
17 | Myodonta-Castorimorpha | 52.2 (46.2–58.7) | 51.5 (41.1–63.1) | 58.4 (47.9–70) | 64.3 (44–88.6) | 56.55 | 54.57 |
18 | Base of Castorimorpha | 45.2 (34.8–54.5) | 44.6 (32.1–56.9) | 50.7 (37.9–63.6) | 55.4 (35.8–78.1) | 51.75 | 49.96 |
19 | Heteromyidae-Geomyidae | 20.3 (9.7–30.8) | 20 (9.2–31.6) | 23.6 (11.9–36.4) | 25.3 (10.8–40.7) | 23.11 | 22.31 |
20 | Muroidea-Dipodoidea | 45 (43–48.5) | 44 (33.9–54.9) | 49.2 (43–57.6) | 55.8 (37.3–77.1) | 47.73 | 46.08 |
21 | Cricetidae-Muridae | 23.1 (14.1–31.9) | 23.2 (14.6–33) | 29.3 (19.4–39.6) | 28.4 (15.3–43.5) | 21.67 | 20.93 |
22 | Mouse-Rat | 9.5 (7.3–13) | 9.5 (7.3–12.9) | 16.1 (7.8–24.5) | 10.3 (7.3–14.4) | 11.35 | 10.96 |
24 | Base of Dipodoidea | 32.2 (24.8–39.3) | 31.6 (22.9–40.8) | 37.9 (29.6–46.8) | 42.7 (27.9–60.7) | 29.88 | 28.85 |
25 | Zapodidae-Dipodidae | 25.1 (18.7–31.8) | 24.6 (17.9–31.9) | 31.4 (23.5–39.2) | 35.2 (22.1–50.3) | 23.27 | 22.47 |
26 |
|
5.6 (1.9–9.9) | 5.5 (2–9.9) | 6.7 (2.4–11.8) | 7.4 (2.1–14) | 3.63 | 3.50 |
27 | Base of Dipodidae | 18 (13.8–22.4) | 17.9 (13.6–22.7) | 25 (18.4–32.1) | 28 (17.2–40.1) | 16.72 | 16.15 |
28 |
|
10.2 (9–12.3) | 10.2 (9–12.3) | 15.8 (8.2–23.9) | 17.5 (7.9–28.4) | 11.67 | 11.27 |
29 | Euchoreutinae-Allactaginae | 13.9 (11.2–16.8) | 13.9 (11.1–17.1) | 20.7 (14.9–27.1) | 23.1 (14.3–33.3) | 12.67 | 12.24 |
30 | Dipodinae-Allactaginae | 12.2 (10.5–14.5) | 12.3 (10.5–14.8) | 19.1 (13.7–25.2) | 21.2 (13–30.8) | 11.69 | 11.29 |
31 | Base of Allactaginae | 7.5 (5.4–9.8) | 7.6 (5.3–10) | 10.3 (6.7–14.3) | 11.4 (6.6–17.3) | 4.69 | 4.53 |
37 | Base of Dipodinae | 7.5 (5.2–9.8) | 7.4 (5.1–9.8) | 10.4 (6.4–14.5) | 11.5 (6.1–17.5) | 4.40 | 4.25 |
Values in parentheses are the 95% Bayesian credibility intervals. - indicates that the corresponding node was not present in the corresponding analyses. Abbreviation: cons., constraint.
The above analyses demonstrate that changes of the age of non-rodent constraints have limited impact on the estimated divergence times of nodes in the rodent tree. By contrast, removal of all three recent rodent constraints results in dramatic increase of ages for other nodes, reverting to the older divergence times estimated by earlier studies. Moreover, these results indicate that the use of a single mouse-rat constraint for the divergence time estimates for rodents can result in overestimates for all nodes in Glires.
When constaints on tip rodent nodes E, F and G were relaxed, the estimated dates for all nodes change little (
Three hypotheses have been proposed to characterize the evolutionary radiation of placental mammals: the Explosive Model puts the origin of placental orders and their intraordinal diversification shortly after the K/Pg boundary, whereas the Short Fuse Model places the origin of placental orders and intraordinal diversification in the Cretaceous, and the Long Fuse Model posits Cretaceous origins of placental orders but intraordinal diversification after the K/Pg boundary. Paleontological evidence favors the Explosive Model, suggesting that the origin and diversification of placental mammals occurred following the K/Pg extinction event that wiped out the non-avian dinosaurs and opened up many ecological niches. By contrast, recent molecular studies support either the Short Fuse or the Long Fuse Models, which suggests that continental breakup in the Late Cretaceous contributed to the origin and/or diversification of placental mammals, rather than the opening of ecological niches by differential extinction among groups. For rodents, most previous molecular studies consistently support a Short Fuse Model for them, making rodents one of the oldest placental orders which originated and diversified in the Cretaceous
Recent phylogenetic studies, based on extensive sampling of fossil mammals, have placed all Cretaceous eutherians outside the placental crown groups
Our study is methodologically similar to others that employed the relaxed molecular clock and multiple fossil calibration points
The major difference between the fossil constraints used in this study and those used by Huchon et al. (2007)
Our results show that reconciliation between estimates of divergence times based on molecular clock and paleontological data is possible with standard tools and genetic markers, at least for the Rodentia, the most speciose of all mammalian orders. Achieving this consistency requires a reasonable number of reliable fossil calibration points supported by a well-constrained paleontological and stratigraphic record. The consistency between our results and the paleontological record suggests that similar controversies regarding the origin and diversification of other major biological groups, including the post-K/Pg diversification of various orders of modern mammals and birds
This study includes 33 rodent species across major rodent lineages and eight outgroup taxa. The taxa examined and their classification are provided in
Genomic DNA was prepared from either muscle or liver tissue samples using DNeasy Tissue Kit (Qiagen, inc). PCR reactions were undertaken in 25-µL volumes with the following conditions: 94°C (5–10 min); 35 cycles of 94°C (45 s); 55°C (45 s); 72°C (40–60 s); 72°C (5–10 min). Sequence data were collected on ABI 3730 DNA Analyzers for both directions subsequent to Big Dye chemistry. The primers for both PCR and sequencing reactions are identified in
DNA sequences were aligned using Kalign as implemented in the program eBioX (
Phylogenetic trees were constructed using maximum likelihood and Bayesian criteria. The Akaike information criterion was used to determine the best substitution models of sequence evolution based on the results from MODELTEST 3.07
Bayesian inference of phylogeny was performed with the program MrBayes 3.1.2
The levels of molecular rate heterogeneity for the concatenated dataset and for each of the loci were examined in the program BEAST 1.5.4
We employed two approaches to estimates divergence times of each node: a Bayesian method as implemented in the program BEAST 1.5.4, and a penalized likelihood method in the program r8s 1.71
Bayesian analyses of molecular dating were estimated for the combined dataset with the substitution models for each gene partition. The relaxed molecular clock model was chosen for all BEAST analyses
The program r8s
We applied seven fossil age constraints for the molecular dating analyses in this study. Minimum age constraints were based on the earliest known fossil record of a member of one of the divergent lineages. Where possible, the maximum age constraints are based on the age of the youngest well-sampled horizon that does not contain any members of the divergent lineages, in a stratigraphic sequence in which members of these lineages subsequently appear. When a stratigraphic sequence suitable for setting a particular upper bound by this method was not available, the age of the oldest member of the stem lineage leading up to the divergence was used as the upper bound. For the program BEAST, these calibration points were set as soft constraints with upper and lower bounds that allow for a 2.5% chance of lying beyond each user-input bound. The r8s program only allows the fossil calibrations to be set as a hard bound. Fossil constraints are as follows (
we assigned a minimum age of 160 Ma and a maximum age of 190 Ma for the divergence between marsupials and placentals, based on the earliest known placental mammal
We assigned a minimum age of 38 Ma and a maximum age of 61.7 Ma for the divergence between caniforms and feliforms, based on the oldest known crown carnivoran
We assigned a minimum age of 28.5 Ma and a maximum age of 37 Ma for the divergence between
The earliest muroid is
We assigned a minimum age of 7.3 Ma and a maximum age of 12.2 Ma for the divergence between mice and rats, based on the occurence of the earliest known mouse
We assigned a minimum age of 9 Ma for the divergence between the two cardiocraniine genera
We assigned a minimum age of 10.5 Ma for the divergence between the two dipodoid subfamilies Dipodinae and Allactaginae, based on the occurence of the earliest known dental fossils of Dipodinae from the middle bed of the Dingshanyanchi Formation, Xinjiang, China (
We set a maximum age of 13 Ma for the divergence between Dipodinae and Allactaginae and the divergence between
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Results of the test of molecular rate heterogeneity. The ucld.stdev parameters for each locus and the concatenated, partitioned data-set estimated by BEAST. Abbreviations: 95% C. I. = 95% Confidence Interval; ESS = Effective Sample Size.
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List of taxon sampling for this study. Abbreviations: MVZ = Museum of Vertebrate Zoology, University of California, Berkeley; MCZ = Museum of Comparative Zoology, Harvard University; AMNH = American Museum of Natural History; NMNH = National Museum of Natural History, Smithsonian Institution.
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Characteristics of genes included show the AIC weights supporting the best model for each entry.
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Primer.
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List of GenBank accession numbers.
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Comparisons of divergence times for major nodes estimated using BEAST with full taxa and with a tree that is free of NDE by reducing taxon sampling in the subfamilies Dipodinae and Allactaginae. Values in parentheses are the 95% Bayesian credibility intervals. Note that these two analyses produced similar estimates of divergence times for major nodes. Statistical test shows that there is no significant difference between these two time estimates (t-test, p-value = 0.954).
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We are grateful to D. Kramerov of the Russian Academy of Sciences, and A. Shahin of the Minia University of Egypt for donating DNA and tissue samples. We would like to thank F. Jenkins, L. Flynn and C. Sullivan for comments. We thank the Museum of Comparative Zoology (MCZ), Harvard University, the Museum of Vertebrate Zoology, University of California at Berkeley, the American Museum of Natural History, New York, and the National Museum of Natural History, Smithsonian Institution for the loan of tissues.