Sbc174 evolution2014 week3

Mini-summary

• Neo-darwinism/Modern synthesis

• Major transitions in evolution

• Geological timescales

• Geological drivers of evolution

Vulcanism•Local climate change (e.g. thermal vents, hot springs...)

•Global climate change: Emission of gasses & particles.

•New geological barriers (migration...)

•New islands (“Malay archipelago”, Galapagos... Hawaii... )

Deccan traps

Eyjafjallajokull

3. Major geological drivers of evolution

•Tectonic movement (of continental plates)

•Vulcanism

•Climate change

•Meteorites

Conditions on earth change.

Vulcanism

Tectonic movement

Meteorite impact

Climate change?

?

Consequences: • Large scale migrations • Speciation • Mass extinctions • Adaptive radiations

3. Major geological drivers of evolution

1.Major transitions in evolution

2.Geological timescales

3.Major geological drivers of evolution

4.Recent major extinction events

4. Recent major extinction events

Pg

fraction of genera present in each time interval but extinct in

the following interval

KT: K

-Pg

Creta

ceou

s–Pa

leoge

ne

Trias

sic-Ju

rassi

cPerm

ian-T

riass

ic

Late

Dev

onia

n

Ord

ovic

ian–

Silu

rian

Toda

y

•Oxygen levels. • Tetrapods and early amniotes. • Tropical conditions around equatorial landmasses. • Damp forests: tall trees & lush undergrowth: giant club mosses, lycopods, ferns & seed ferns. • Decaying undergrowth forms coal. • Good habitats for terrestrial invertebrates including spiders, millipedes and insects (e.g. giant dragonflies, scorpions).

Pangaea - single supercontinent

Carboniferous/Permian

Dimetrodon (sub-class Synapsida = “mammal-like reptiles”)

Early Permian mammal-like reptiles

Climate change(since Cambrian)

Permian-Triassic Extinction

Sun et al Science 2012

Went extinct: •Up to 96% of marine species & 70% of terrestrial vertebrates •21 terrestrial tetrapod families (63%) • 7 orders of insects

Jurassic/Cretaceous

•Mammal-like reptiles were replaced as dominant land vertebrates by reptiles (dinosaurs).

• Lizards, modern amphibians and early birds appear.

• The conifer- and fern-dominated vegetation of the Late Triassic continued into the Jurassic.

Cretaceous–Paleogene (KT) extinction 66 million years ago

Subsequently, many adaptive radiations to fill newly vacant niches. eg. mammals, fish, many insects

AmmoniteMosasaur

(marine reptile) Non-bird dinosaurs

Most Plant-eating insects

75% of all species became extinct (50% of genera). Including:

http://www.scotese.com/earth.htm)


Evidence for Chixulub impact

Magnetic field near siteCrater : 180km diameter; bolide: 10km.

•Bolide impact at Chixulub. •huge tsunamis •cloud of dust and water vapour, blocking sun. •plants & phytoplankton die (bottom of food chain) --> animals starve

•dramatic climate & temperature changes are difficult (easier for warm-blooded?)

•Additional causes? •Some groups were ALREADY in decline •Additional impacts? •Deccan traps (India) - 30,000 years of volcanic activity (lava/gas release)


Diprotodon, Australia, extinct 40,000 ya

Dodo, Mauritius, extinct since 1662

Ongoing Anthropocene extinction•Hunting •Habitat destruction, modification & fragmentation !

! Passenger Pigeon North America; extinct since 1914.

Glyptodon, Americas, extinct ~12000 years ago

Extinct New Zealand megafauna were not in declinebefore human colonizationMorten Erik Allentofta,b,c,1, Rasmus Hellerd,e, Charlotte L. Oskamb, Eline D. Lorenzena,f, Marie L. Halec,M. Thomas P. Gilberta, Christopher Jacombg, Richard N. Holdawayc,h, and Michael Bunceb,i,1

aCentre for GeoGenetics, Natural History Museum, University of Copenhagen,1350 Copenhagen K, Denmark; bAncient DNA Laboratory, School of Veterinaryand Life Sciences, Murdoch University, Perth, WA 6150, Australia; cSchool of Biological Sciences, University of Canterbury, Christchurch 8140, New Zealand;dDepartment of Biology, University of Copenhagen, DK-2100 Copenhagen Ø, Denmark; eInstituto Gulbenkian de Ciência, 6 P-2780-156 Oeiras, Portugal;fDepartment of Integrative Biology, University of California, Berkeley, CA 94720; gSouthern Pacific Archaeological Research, Department of Anthropologyand Archaeology, University of Otago, Dunedin 9054, New Zealand; hPalaecol Research Ltd., Hornby, Christchurch 8042, New Zealand; and iTrace andEnvironmental DNA Laboratory, Department of Environment and Agriculture, Curtin University, Perth, WA 6102, Australia

Edited by Robert E. Ricklefs, University of Missouri, St. Louis, MO, and approved February 10, 2014 (received for review August 7, 2013)

The extinction of New Zealand’s moa (Aves: Dinornithiformes) fol-lowed the arrival of humans in the late 13th century and was thefinal event of the prehistoric Late Quaternary megafauna extinc-tions. Determining the state of the moa populations in the pre-extinction period is fundamental to understanding the causes ofthe event. We sampled 281 moa individuals and combined radio-carbon dating with ancient DNA analyses to help resolve the ex-tinction debate and gain insights into moa biology. The samples,which were predominantly from the last 4,000 years preceding theextinction, represent four sympatric moa species excavated fromfive adjacent fossil deposits. We characterized the moa assem-blage using mitochondrial DNA and nuclear microsatellite markersdeveloped specifically for moa. Although genetic diversity differedsignificantly among the four species, we found that the millenniapreceding the extinction were characterized by a remarkable de-gree of genetic stability in all species, with no loss of heterozygos-ity and no shifts in allele frequencies over time. The extinction eventitself was too rapid to be manifested in the moa gene pools. Contra-dicting previous claims of a decline in moa before Polynesian settle-ment in New Zealand, our findings indicate that the populationswere large and stable before suddenly disappearing. This interpre-tation is supported by approximate Bayesian computation analyses.Our analyses consolidate the disappearance of moa as the mostrapid, human-facilitated megafauna extinction documentedto date.

The causes of Late Quaternary megafauna extinctions con-tinue to be debated (e.g., refs. 1–3). Climate has been invoked

as a major factor driving demographic shifts over evolutionarytimescales, but it is undeniable that most recent megafauna ex-tinctions occurred in the presence of humans. However, the role ofhumans in the extinction process differs among continents andthe species studied (4), and it has proven difficult to find evidencefor a direct causative link between anthropogenic activity andmegafauna loss.Ancient DNA (aDNA) research has contributed significantly

to the extinction debate. DNA extracted from fossil materialspanning thousands of years can yield insights into the de-mographic histories of extirpated populations and extinct speciesin the period leading up to their loss (5–7). However, mostefforts have involved continental-scale data where the largegeographic distances hamper fine-scale inferences, limiting ourability to determine the causative agents of discrete demographicevents. In contrast, island extinctions offer analytical advantagesnot afforded by studies of widely distributed species. In islandendemics, the absence of gene flow from mainland populationsallows us to disregard the spatial dimension in the geneticanalyses and focus on extinction dynamics through time.New Zealand is central to the megafauna extinction debate.

It was the last major landmass to be colonized by humansand harbored a diverse assemblage of avian megafauna (8–10).Among them were nine species of moa (11): large, wingless ratite

birds ranging in size from the ∼12-kg North Island morph ofEuryapteryx curtus to the ∼250-kg females of the two Dinornisspecies (8). Moa inhabited a variety of habitats across the NewZealand archipelago until their extinction shortly after the ar-rival of Polynesian settlers, estimated at approximately the late13th century (8–10, 12). The abundance of well-preserved ar-chaeological sites containing evidence of large-scale exploitationof moa (e.g., ref. 13) brings the controversy of the role of humansin the extinction event into sharp focus.Early claims of environmental changes or poor adaptive abil-

ities of moa as causes for the extinction (reviewed in ref. 8) havenow been largely replaced by the view that direct or indirecthuman impacts—including hunting, fires, and the introduction ofexotic species—were the primary drivers (14–18). Ecologicalmodeling suggests that such human-mediated extinction couldhave happened within 100 y of Polynesian colonization (10). Incontrast, it has been argued, based on limited mitochondrialDNA (mtDNA) data, that moa populations had already col-lapsed before human arrival, as a consequence of volcaniceruptions or diseases, suggesting that humans were just one ofseveral additive factors responsible for the extinction (19).To address this issue, we investigated the demographic tra-

jectories of four sympatric moa species in the four millennialeading up to their extinction. We genotyped 281 individuals ofDinornis robustus (Dinornithidae), Euryapteryx curtus, Pachyorniselephantopus, and Emeus crassus (all Emeidae) using mtDNA andsix nuclear microsatellite markers developed specifically for moa

Significance

In New Zealand, nine species of moa (large, wingless ratitebirds) went extinct shortly after Polynesian settlement. In thisstudy, we characterize the gene pools of four moa speciesduring the final 4,000 y of their existence and gain new insightsinto moa biology and their population sizes. Our analysesshow that moa populations were large and viable prior tohuman arrival in New Zealand, and their demise thereforerepresents a striking example of human overexploitation ofmegafauna.

Author contributions: M.E.A., M.L.H., R.N.H., and M.B. designed research; M.E.A., C.L.O.,R.N.H., and M.B. performed research; M.L.H., M.T.P.G., and C.J. contributed new reagents/analytic tools; M.E.A., R.H., R.N.H., and M.B. analyzed data; and M.E.A., R.H., E.D.L., R.N.H.,and M.B. wrote the paper.

The authors declare no conflict of interest.

This article is a PNAS Direct Submission.

Data deposition: The sequences reported in this paper have been deposited in theGenBank database [accession nos. KJ533749–KJ533834 (D. robustus), KJ533835–KJ533912(E. crassus), KJ533913–KJ533991 (E. curtus), and KJ533992–KJ534022 (P. elephantopus)].1To whom correspondence may be addressed. E-mail: [email protected] [email protected].

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1314972111/-/DCSupplemental.

4922–4927 | PNAS | April 1, 2014 | vol. 111 | no. 13 www.pnas.org/cgi/doi/10.1073/pnas.1314972111

the Holocene, which seems reasonable from an ecological per-spective. Moa were primarily forest and shrubland dwellers, withsome entering herbfields and the subalpine zone (8, 33), andpollen records from the South Island reflect an establishmentof postglacial shrubland in 14,000–10,000 y B.P., followed bypodocarp forest expansion during approximately 13,600–7,500 yB.P. (34, 35).

Population Size of D. robustus. Our data suggest that D. robustushad an effective population size (Ne) of ∼9,200 individuals whenPolyneisans reached New Zealand. Although the posterior dis-tributions are wide, this is the modal value from the free-modelABC analysis (Table 3), which encompasses both mtDNA and

nuclear microsatellite data and is without any directional re-strictions on simulated growth rate. The conversion of effectivepopulation size to census population size (Nc) is problematic,especially for extinct taxa with limited biological information,and no Ne:Nc ratios have been published for extant ratites.However, our best estimate of Ne:Nc ratio for D. robustus is 0.4(SI Materials and Methods). With an Ne of 9,200, we thereforeestimate a census size of ∼23,000 D. robustus individuals, which isthe same order of magnitude as the 14,100 individuals estimatedfrom ecological modeling (SI Materials and Methods and Data-sets S2 and S3). Such a large population size of a heavy andslowly maturing species (36) suggests a larger, panmictic SouthIsland population, rather than a local enclave isolated in NorthCanterbury. This finding suggests that D. robustus individualscould disperse over long distances and sustain population con-nectivity in a landscape fragmented by rivers, glaciers, andmountain ranges. It seems reasonable to infer that for flightlessbirds, larger body size translates into higher dispersal rates,resulting in larger effective population sizes and higher levels ofgenetic diversity. This hypothesis could also explain why thesmallest species of the region (E. crassus) had the lowest ob-served genetic diversity (Table 2).The fossil record suggests that moa had skewed sex ratios with

an excess of females (8, 37). If the sexes did not contribute evenlyto the effective population size, we would expect a deviationfrom a 1:4 ratio between mtDNA and microsatellite (autosomal)effective population sizes. Indeed, we observe a 1:4 ratio in theABC analysis of D. robustus, suggesting that putative skewed sexratios did not cause differential reproductive success between thesexes. Our result could indicate mating competition amongfemales and accordance with the observation of pronouncedreverse sexual size-dimorphism (38, 39) and hypotheses of fe-male territoriality (37) in moa.

Genetic Diversity in the Moa Community. We found differing levelsof genetic diversity in the four moa species, although eachremained constant through time (Fig. 3 and Table 2). In the fourmillennia preceding extinction, we found only half the geneticdiversity in E. crassus compared to the three other moa species,suggesting either a smaller population size or a previous de-mographic bottleneck. Unlike E. curtus and P. elephantopus,E. crassus was not present in the wetter western and north-western South Island during the Pleistocene (40); the morelimited distribution likely resulted in smaller population sizes. Ifa bottleneck was the cause of lower levels of genetic diversityin E. crassus, it could reflect population isolation in a habitat

0.0

0.2

0.4

0.6

0.8

D. robustusD. robustus

P. elephantopus

E. curtus

E. crassus

10 020Time (kyr)

Time (yr BP)Polynesian

colonization

3040

0100020003000

1.E3

1.E4

1.E5

1.E6A

B

Log

Ne*τ

Exp

ecte

d he

tero

zygo

sity

HE

Fig. 3. Demographic history and genetic diversity. (A) Bayesian skyline plotfor D. robustus (n = 87), where the y axis depicts the effective female pop-ulation size multiplied by generation time. Year zero corresponds to the ageof the youngest sample at 602 B.P. (B) Expected heterozygosity (HE) for sixmicrosatellite loci, measured across time in the four moa species (n = 188).Data points represent the mean age and mean HE (with SE) of the moaindividuals in 1,000-y time bins.

Table 3. ABC analysis

Model Ncur Nanc/Ncur T μ pMarginaldensity

PriorsFree model 500–50,000 0.01–100 100–31,700 10−3–10−5 0.4–0.9 0.31Model selection: decline 500–50,000 1–100 100–31,700 10−3–10−5 0.4–0.9 0.24Model selection: expand 500–50,000 0.01–1 100–31,700 10−3–10−5 0.4–0.9 1.26

PosteriorsFree model 9,200 [900–45,600] 0.90 [0.26–25.84] 1,100 [100–15,900] 5.1e-5 [2.4e-5–1.1e-4] 0.82 [0.75–0.89]Model selection: expand 10,200 [3800–37,900] 0.47 [0.04–1.00] 1,900 [1100–19,500] 4.8e-5 [2.4e-5–9.8e-5] 0.81 [0.72–0.89]

ABC analysis of D. robustusmtDNA and microsatellite data combined. Priors were incorporated on a log scale with a uniform distribution, but here they areshown on a natural scale for clarity. Ncur is “current” population size, representing effective population size at the last sampling point (602 B.P.). Nanc/Ncur isthe size of the “ancient” effective population size at the onset of demographic change relative to Ncur. Numbers are diploid individuals rounded to thenearest 100, converted from haploids as used in ABCtoolbox. T is the time at the onset of the demographic change measured in years relative to the youngestsampling point, rounded to the nearest 100, and converted from generations, as used in ABCtoolbox (generation time assumed to be 10 y for D. robustus). μ isthe microsatellite mutation rate per generation, and p is the shape parameter of the geometric distribution of the General Stepwise Model. Marginaldensities were compared for the two scenarios in the model selection approach, and the Bayes factor support for the expand model was 5.25 (1.26/0.24),indicating substantial support (Jeffreys; ref. 58). Posterior parameter estimates represented by mode values, and 90% HPDs are shown for the two modelswith highest marginal density (free and expand models).

Allentoft et al. PNAS | April 1, 2014 | vol. 111 | no. 13 | 4925

GEN

ETICS

Ongoing Anthropocene extinction•Hunting •Habitat destruction, modification & fragmentation •Pollution/Overexploitation •Spread of invasive species - & new pathogens •Climate change !

Rainforest loss in Sumatra

Margono et al 2012

Summary.

•The history of the earth is divided into geological time periods

• These are defined by characteristic flora and fauna

•Large-scale changes in biodiversity (mass extinctions) were triggered by continental movement and catastrophic events

A. Proximate vs Ultimate?

B. Fossilization & learning from Fossils

Why is X? Why does ?

Two types of answer:

Proximate explanations: mechanisms responsible for the trait.

(generally within the lifetime of an organism)

Ultimate explanations: fitness consequences of the trait.

(generally over many generations)

Some examples

•Why do waxwings migrate South in winter? •Proximate: a mechanism in their brains senses days are getting shorter/colder

•Ultimate: Those migrating South have been better at surviving the winter.

•Why do human babies cry? •Proximate explanations: cold? hunger? wants attention? high level of a stress hormone? neural signal for pain?

•Ultimate: babies that don’t cry when they need help are less likely to survive.

Fossils & Fossilization

1. How fossilization works. Some examples of fossils.

2. Dating fossils.

3. What we can learn from fossils?

y . wurm {@} qmul . ac .uk

Geological context

Three broad classes of rock:

•Sedimentary rocks: formed by particles (mineral or organic) gradually settling out of solution, then compacting to form rock

•Igneous rocks: formed by the cooling of magma

•Metamorphic rocks: modification of existing rocks under high pressure and heat

Fossils: only in sedimentary rocks (deposited on oceanic shorelines, lake beds, flood plains...) !

Weathering or erosion can expose the older layers

Fossilization•Two main types:

•Permineralization

• “Natural cast” process

•Fossilization is rare & only in sediment...

•Ancient material also occurs: • in amber •by mummification • in ice

Fossil formation at Sterkfontein

Limestone deposits were laid down 2.5 billion years ago when the area was a shallow sea. Caves eventually form below the surface. ‘Pot holes’ form between the surface and the caves. Debris, including animals, fall in! Compaction and cementing with water and limestone produces “Breccia”.

Fossil preservation

•Hard part like shells, bones and teeth are usually all that remain

•Soft tissues fossils are rare

Why are fossils rare?•Fossils don’t form often:

•Predators, scavengers, insects consume corpses •Bacteria and fungi decompose remains •Even faster in tropics (acid soil, warm, humid...)

!•Best locations for fossil formation::

•arid deserts, deep water (with low O2)

Recent continental movements...

TETHYS

SEA

LAURASIA

GONDW

ANA

EquatorTriassic 200 Mya

Pangaea - single supercontinent

Why are fossils rare?•Fossils don’t form often:

•Predators, scavengers, insects consume corpses •Bacteria and fungi decompose remains •Even faster in tropics (acid soil, warm, humid...)

!•Best locations for fossil formation:

•arid deserts, deep water (with low O2), cold !

•Fossils can be lost: •mountains: lots of erosion •Metamorphosis and subduction of rocks destroys fossils

!•Most are still buried rather than exposed at the surface

A few examples...

Aquatic reptile; not a dinosaur. But same time (Mesozoic Era).A typical fossil skeleton.

Plesiosaur fossil

Parts of head, and anvil/brush of Akmonistion zangerli, shark

from Carboniferous of Scotland

More typical…

Belemnites •very abundant during Mezosoic

Ammonites

http://www.bbc.co.uk/nature/life/

Ammonite#p00bkt26

http://www.bbc.co.uk/nature/life/Ammonite#p00bkt26

http://www.bbc.co.uk/nature/life/Ammonite%23p00bkt26

Ammonites

AmmoniteNautilus

Feathers, like soft tissue, are rarely preserved. But here imprinted in the rock.

Archaeopteryx - late Jurassic (150Mya)

“Fuzzy Raptor” (a dromaeosaur)

The earliest Eutherian Mammal?Lower Cretaceous of China, 125 Mya

Eomaia scansoria Ji et al., (2002) Nature

416, 816-822 A climbing mammal from a lake shore environment

Leptictidium tobieni Paleogene (Messel Shales, Germany)

Soft tissues + gut contents are preserved

Bipedal (extinct) mammal.

Dinosaur footprint

•At the time, this footprint of a dinosaur pressed into soft mud and became preserved in the now hardened rock. Can inform us on locomotion.

INSECT IN AMBER

• This mosquito was imbedded in tree sap that subsequently hardened into amber, preserving the insect within.

Neanderthal skull from Iraq

(≈50,000 years old) !

Very rarely, DNA can be extracted and

sequenced from such sub-fossils

Some animals get trapped in ice


1. How fossilization happens & some examples.

2. Dating fossils


Dating methods

• Absolute - the item itself is dated !

• Relative - strata above (younger) and below (older) are dated and the item expressed relative to these

Best method depends on context & age.

Principles of radiometric dating

Dating methods

Stratigraphy

As sediment collects, deeper layers are compacted by the ones above until they harden and become rock. Deeper Fossils are older than those above. Thus positions within the rock layers gives fossils a chronological age.

Index (Zone) Fossils

!

!

•Here, Locality 3 has no layer B (wasn’t formed or eroded).

•Index fossils: diagnostic fossil species that help dating new finds

Photo taken by (Luca Galuzzi) * http://www.galuzzi.it

http://commons.wikimedia.org/wiki/User:Lucag

http://www.galuzzi.it/


1. How fossilization happens & some examples.

2. Dating fossils


What can we learn?

Fossils can sometimes directly or indirectly tell us a great deal about the behavior of an organism, or its lifestyle

Fossilized tracks at Laetoli (Tanzania)

Footprints preserved in volcanic ash from: 3 hominids (Australopithecus afarensis) Numerous other mammals

Fossil Ichthyosaur giving birth

•Such special preservations can inform us about the reproductive pattern in this species (live birth) .

Fossil Eggs

Information on development and social/reproductive behavior

Interpreting fossils

•Careful interpretation: helps make sense of fossilized remains

•Analysis of hard parts can tell something about soft anatomy (e.g where muscles are (.e.g muscle scars).

•Geology: --> environment (freshwater/marine/swamp))

• Infer from living organisms & relatives.

Hallucigenia sparsa (Cambrian Period)

From the Burgess Shale (Canada). Example of a soft bodied animal fossil, also very old!

Now re-interpreted as an Onychophoran ("velvet worm")

© BBC - Life in the Undergrowth

…or do they? (discovered fossilised melanosomes)

Colors don’t fossilize...

Fossils - Summary

• Fossils form in sedimentary rock

• Fossilization is a rare process

• Usually, only the hard parts like bone, teeth, exoskeletons and shells are preserved

• Fossils of different ages occur in different strata, and “index fossils” can be used to cross-reference between different geographic locations

•Careful interpretation is required.

DNA & learning from DNA.

DNA in evolution•Species relationships previously based on:

•bone structures •morphologies •development •behavior •ecological niche • ....

1. DNA sequences change

2. Evolutionary relationships 3.Current evolutionary contexts

DNA holds lots of additional information:

1. DNA sequences change

DNA mutations occur all the time. Reasons:

•mistakes in DNA replication or recombination •mutagens (radiation, chemicals) •viruses • transposons

Inherited: only if in germ line.

Not inherited from soma.

Types of mutations•Small: replacement, insertion, deletion. E.g.:

•Big: inversions, duplications, deletions

original: TGCAGATAGAGAGAGAGAGAGAGCAGATnew : TGCAGATAGAGAGAGAGAGCAGAT

Polymerase slippage in satellite

original: GATTACAGATTACAnew : GATTACATATTACAPoint mutation

Mutations are the source of genetic, inheritable variation

What happens to a mutation?•Most point mutations are neutral: no effect.

•Some are very deleterious;

See population genetics lectures & practical

• --> selection eliminates or fixes them

•--> Genetic drift, hitchhiking... (--> elimination or fixation)

Some increase fitness.

Eg. antennapedia (hox gene) mutation:

2. DNA clarifies evolutionary relationships between speciesHuman: GATTACAPeacock: GATTGCA Amoeba: GGCTCCA

Human

Peacock

Amoeba

Linnaeus 1735 classification of animals

Molecular clock•Basic hypothesis: more differences - more time has passed

•Allows relative timing

•Allows “absolute timing”

•But:

• rate of differentiation differs:

• between lineages

•between contexts

• small amounts of data: unreliable

•Differential segregation of alleles (see future lectures)

Time

Gen

etic

chan

ge

Carl Woese in 1977

http://en.wikipedia.org/wiki/Carl_Woese

An issue with sequence phylogenies

•Can be ambiguous if not enough information.

Ambiguities in mutationsancestral sequence species 1. species 2. What happened

•Can be ambiguous if not enough information.

An issue with sequence phylogenies

•Whole genome sequencing is now dirt cheap! No longer a problem! (for establishing relationships in past 200-400 million years...)

•Used to be expensive.

•Mitochondrial gene vs. nuclear gene. Several genes?

This changes everything.454

Illumina Solid...

Any lab can sequence anything!

With enough data...

Artiodactyla

Cetartiodactyla

Cetacea

Cows are more closely related to whales than to

horses

Bat echolocation

Teeling 2002

Echolocation Evolved twice!

Flight

Ancient DNA

Ancient DNA

Hair sequencing

Ancient DNA: below 2km of icecriterion of authenticity obviously dismissesmany putative taxa that are present at lowabundance or have heterogeneous distributions,as is typical of environmental samples (16), butefficiently minimizes the influence of possiblelow-level contamination and misidentificationsdue to DNA damage (17).

Approximately 31% of the sequences fromthe John Evans Glacier silty sample were as-signed to plant taxa that passed the authentica-tion and identification criteria. These belong tothe order Rosales, the family Salicaceae, and thegenus Saxifraga (Table 1). This result is con-sistent with the John Evans Glacier forming nomore than a few thousand years ago in a highArctic environment (18), characterized by lowplant diversity and sparse vegetation cover sim-ilar to that currently surrounding the glacier,which consists mainly of Arctic willow (Salica-ceae), purple saxifrage (Saxifraga), Dryas (Ro-sales), and Arctic poppy (Papaver) (19). Thus,by confirming the expected result, the John EvansGlacier study can be regarded as a positive con-trol, showing that DNA data from silty ice reli-ably record the local ecology.

In contrast to the John Evans Glacier siltysample, the 45% of the Dye 3 DNA sequencesthat could be assigned to taxa reveal a commu-nity very different from that of Greenland today.The taxa identified include trees such as alder(Alnus), spruce (Picea), pine (Pinus), and mem-bers of the yew family (Taxaceae) (Table 1).Their presence indicates a northern boreal for-est ecosystem rather than today’s Arctic environ-ment. The other groups identified, includingAsteraceae, Fabaceae, and Poaceae, are mainly

Table 1. Plant and insect taxa obtained from the JEG and Dye 3 silty icesamples. For each taxon (assigned to order, family, or genus level), thegenetic markers (rbcL, trnL, or COI), the number of clone sequencessupporting the identification, and the probability support (in percentage)

are shown. Sequences have been deposited in GenBank under accessionnumbers EF588917 to EF588969, except for seven sequences less than 50bp in size that are shown below. Their taxon identifications are indicatedby symbols.

Order Marker Clones Support (%) Family Marker Clones Support (%) Genus Marker Clones Support (%)JEG sampleRosales rbcL 3 90–99Malpighiales rbcL

trnL25

99–10099–100

Salicaceae rbcLtrnL

24

99–100100

Saxifragales rbcL 3 92–94 Saxifragaceae rbcL 2 92 Saxifraga rbcL 2 91Dye 3 sampleConiferales rbcL

trnL4427

97–100100

Pinaceae* rbcLtrnL

2025

100100

PiceaPinus†

rbcLtrnL

2017

99–10090–99

Taxaceae‡ rbcLtrnL

232

91–98100

Poales§ rbcLtrnL

6717

99–10097–100

Poaceae§ rbcLtrnL

6713

99–100100

Asterales rbcLtrnL

1827

90–100100

Asteraceae rbcLtrnL

227

91100

Fabales rbcLtrnL

103

99–10099

Fabaceae rbcLtrnL

103

99–10099

Fagales rbcLtrnL

1012

95–99100

Betulaceae rbcLtrnL

811

93–9798–100

Alnus rbcLtrnL

79

91–9598–100

Lepidoptera COI 12 97–99*Env_2, trnL ATCCGGTTCATGAAGACAATGTTTCTTCTCCTAAGATAGGAAGGG. Env_3, trnL ATCCGGTTCATGAAGACAATGTTTCTTCTCCTAATATAGGAAGGG. Env_4, trnL ATCCGGTTCATGAGGACAATGTTTCTTCTCCTAATA-TAGGAAGGG. †Env_5, trnL CCCTTCCTATCTTAGGAGAAGAAACATTGTCTTCATGAACCGGAT. Env_6, trnL TTTCCTATCTTAGGAGAAGAAACATTGTCTTCATGAACCGGAT. ‡Env_1, trnL ATCCGTATTATAG-GAACAATAATTTTATTTTCTAGAAAAGG. §Env_7, trnL CTTTTCCTTTGTATTCTAGTTCGAGAATCCCTTCTCAAAACACGGAT.

Fig. 1. Sample location and core schematics. (A) Map showing the locations of the Dye 3 (65°11'N,45°50'W) and GRIP (72°34'N, 37°37'W) drilling sites and the Kap København Formation (82°22'N,W21°14'W) in Greenland as well as the John Evans Glacier (JEG) (79°49'N, 74°30'W) on EllesmereIsland (Canada). The inset shows the ratio of D– to L–aspartic acid, a measure of the extent of proteindegradation; more highly degraded samples (above the line) failed to yield amplifiable DNA. (B)Schematic drawing of ice core/icecap cross section, with depth [recorded in meters below thesurface (m.b.s.)] indicating the depth of the cores and the positions of the Dye 3, GRIP, and JEGsamples analyzed for DNA, DNA/amino acid racemization/luminescence (underlined), and 10Be/36Cl(italic). The control GRIP samples are not shown. The lengths (in meters) of the silty sections arealso shown.

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criterion of authenticity obviously dismissesmany putative taxa that are present at lowabundance or have heterogeneous distributions,as is typical of environmental samples (16), butefficiently minimizes the influence of possiblelow-level contamination and misidentificationsdue to DNA damage (17).

Approximately 31% of the sequences fromthe John Evans Glacier silty sample were as-signed to plant taxa that passed the authentica-tion and identification criteria. These belong tothe order Rosales, the family Salicaceae, and thegenus Saxifraga (Table 1). This result is con-sistent with the John Evans Glacier forming nomore than a few thousand years ago in a highArctic environment (18), characterized by lowplant diversity and sparse vegetation cover sim-ilar to that currently surrounding the glacier,which consists mainly of Arctic willow (Salica-ceae), purple saxifrage (Saxifraga), Dryas (Ro-sales), and Arctic poppy (Papaver) (19). Thus,by confirming the expected result, the John EvansGlacier study can be regarded as a positive con-trol, showing that DNA data from silty ice reli-ably record the local ecology.

In contrast to the John Evans Glacier siltysample, the 45% of the Dye 3 DNA sequencesthat could be assigned to taxa reveal a commu-nity very different from that of Greenland today.The taxa identified include trees such as alder(Alnus), spruce (Picea), pine (Pinus), and mem-bers of the yew family (Taxaceae) (Table 1).Their presence indicates a northern boreal for-est ecosystem rather than today’s Arctic environ-ment. The other groups identified, includingAsteraceae, Fabaceae, and Poaceae, are mainly

Table 1. Plant and insect taxa obtained from the JEG and Dye 3 silty icesamples. For each taxon (assigned to order, family, or genus level), thegenetic markers (rbcL, trnL, or COI), the number of clone sequencessupporting the identification, and the probability support (in percentage)

are shown. Sequences have been deposited in GenBank under accessionnumbers EF588917 to EF588969, except for seven sequences less than 50bp in size that are shown below. Their taxon identifications are indicatedby symbols.

Order Marker Clones Support (%) Family Marker Clones Support (%) Genus Marker Clones Support (%)JEG sampleRosales rbcL 3 90–99Malpighiales rbcL

trnL25

99–10099–100

Salicaceae rbcLtrnL

24

99–100100

Saxifragales rbcL 3 92–94 Saxifragaceae rbcL 2 92 Saxifraga rbcL 2 91Dye 3 sampleConiferales rbcL

trnL4427

97–100100

Pinaceae* rbcLtrnL

2025

100100

PiceaPinus†

rbcLtrnL

2017

99–10090–99

Taxaceae‡ rbcLtrnL

232

91–98100

Poales§ rbcLtrnL

6717

99–10097–100

Poaceae§ rbcLtrnL

6713

99–100100

Asterales rbcLtrnL

1827

90–100100

Asteraceae rbcLtrnL

227

91100

Fabales rbcLtrnL

103

99–10099

Fabaceae rbcLtrnL

103

99–10099

Fagales rbcLtrnL

1012

95–99100

Betulaceae rbcLtrnL

811

93–9798–100

Alnus rbcLtrnL

79

91–9598–100

Lepidoptera COI 12 97–99*Env_2, trnL ATCCGGTTCATGAAGACAATGTTTCTTCTCCTAAGATAGGAAGGG. Env_3, trnL ATCCGGTTCATGAAGACAATGTTTCTTCTCCTAATATAGGAAGGG. Env_4, trnL ATCCGGTTCATGAGGACAATGTTTCTTCTCCTAATA-TAGGAAGGG. †Env_5, trnL CCCTTCCTATCTTAGGAGAAGAAACATTGTCTTCATGAACCGGAT. Env_6, trnL TTTCCTATCTTAGGAGAAGAAACATTGTCTTCATGAACCGGAT. ‡Env_1, trnL ATCCGTATTATAG-GAACAATAATTTTATTTTCTAGAAAAGG. §Env_7, trnL CTTTTCCTTTGTATTCTAGTTCGAGAATCCCTTCTCAAAACACGGAT.

Fig. 1. Sample location and core schematics. (A) Map showing the locations of the Dye 3 (65°11'N,45°50'W) and GRIP (72°34'N, 37°37'W) drilling sites and the Kap København Formation (82°22'N,W21°14'W) in Greenland as well as the John Evans Glacier (JEG) (79°49'N, 74°30'W) on EllesmereIsland (Canada). The inset shows the ratio of D– to L–aspartic acid, a measure of the extent of proteindegradation; more highly degraded samples (above the line) failed to yield amplifiable DNA. (B)Schematic drawing of ice core/icecap cross section, with depth [recorded in meters below thesurface (m.b.s.)] indicating the depth of the cores and the positions of the Dye 3, GRIP, and JEGsamples analyzed for DNA, DNA/amino acid racemization/luminescence (underlined), and 10Be/36Cl(italic). The control GRIP samples are not shown. The lengths (in meters) of the silty sections arealso shown.

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23. L. Mehl, B. R. Hacker, G. Hirth, P. B. Kelemen,J. Geophys. Res. 108, 10.1029/2002JB002233(2003).

24. B. R. Jicha, D. W. Scholl, B. S. Singer, G. M. Yogodzinski,S. M. Kay, Geology 34, 661 (2006).

25. C.-T. Lee, X. Cheng, U. Horodyskyj, Contrib. Min. Petrol.151, 222 (2006).

26. P. B. Kelemen, K. Hanghøj, A. R. Greene, in The Crust,

R. L. Rudnick, Ed. (Elsevier-Pergamon, Oxford, 2003),vol. 3, pp. 593–659.

27. T. V. Gerya, D. A. Yuen, Earth Planet. Sci. Lett. 212, 47(2003).

28. We thank M. Long, E. Kneller, and C. Conrad forconversations that motivated this work. Funding wasprovided by NSF grants EAR-9910899, EAR-0125919, andEAR-0509882.

Supporting Online Materialwww.sciencemag.org/cgi/content/full/317/5834/108/DC1SOM TextFigs. S1 and S2References

13 February 2007; accepted 9 May 200710.1126/science.1141269

Ancient Biomolecules fromDeep Ice Cores Reveal a ForestedSouthern GreenlandEske Willerslev,1* Enrico Cappellini,2 Wouter Boomsma,3 Rasmus Nielsen,4Martin B. Hebsgaard,1 Tina B. Brand,1 Michael Hofreiter,5 Michael Bunce,6,7Hendrik N. Poinar,7 Dorthe Dahl-Jensen,8 Sigfus Johnsen,8 Jørgen Peder Steffensen,8Ole Bennike,9 Jean-Luc Schwenninger,10 Roger Nathan,10 Simon Armitage,11Cees-Jan de Hoog,12 Vasily Alfimov,13 Marcus Christl,13 Juerg Beer,14 Raimund Muscheler,15Joel Barker,16 Martin Sharp,16 Kirsty E. H. Penkman,2 James Haile,17 Pierre Taberlet,18M. Thomas P. Gilbert,1 Antonella Casoli,19 Elisa Campani,19 Matthew J. Collins2

It is difficult to obtain fossil data from the 10% of Earth’s terrestrial surface that is covered by thickglaciers and ice sheets, and hence, knowledge of the paleoenvironments of these regions hasremained limited. We show that DNA and amino acids from buried organisms can be recoveredfrom the basal sections of deep ice cores, enabling reconstructions of past flora and fauna. Weshow that high-altitude southern Greenland, currently lying below more than 2 kilometers of ice,was inhabited by a diverse array of conifer trees and insects within the past million years. Theresults provide direct evidence in support of a forested southern Greenland and suggest that manydeep ice cores may contain genetic records of paleoenvironments in their basal sections.

The environmental histories of high-latituderegions such as Greenland and Antarcticaare poorly understood because much of

the fossil evidence is hidden below kilometer-thick ice sheets (1–3). We test the idea that thebasal sections of deep ice cores can act asarchives for ancient biomolecules.

The samples studied come from the basalimpurity-rich (silty) ice sections of the 2-km-long Dye 3 core from south-central Greenland(4), the 3-km-long Greenland Ice Core Project(GRIP) core from the summit of the Greenlandice sheet (5), and the Late Holocene John EvansGlacier on Ellesmere Island, Nunavut, northernCanada (Fig. 1). The last-mentioned sample wasincluded as a control to test for potential exoticDNA because the glacier has recently overriddena land surface with a known vegetation cover(6). As an additional test for long-distanceatmospheric dispersal of DNA, we includedfive control samples of debris-free Holoceneand Pleistocene ice taken just above the basalsilty samples from the Dye 3 and GRIP icecores (Fig. 1B). Finally, our analyses includedsediment samples from the Kap KøbenhavnFormation from the northernmost part ofGreenland, dated to 2.4 million years beforethe present (Ma yr B.P.) (1, 2).

The silty ice yielded only a few pollen grainsand no macrofossils (7). However, the Dye 3and John Evans Glacier silty ice samples showedlow levels of amino acid racemization (Fig. 1A,inset), indicating good organic matter preserva-tion (8). Therefore, after previous success withpermafrost and cave sediments (9–11), we at-tempted to amplify ancient DNA from the ice.This was done following strict criteria to secureauthenticity (12–14), including covering the sur-

face of the frozen cores with plasmid DNA tocontrol for potential contamination that mayhave entered the interior of the samples throughcracks or during the sampling procedure (7).Polymerase chain reaction (PCR) products ofthe plasmid DNA were obtained only from ex-tracts of the outer ice scrapings but not from theinterior, confirming that sample contaminationhad not penetrated the cores.

Using PCR, we could reproducibly amplifyshort amplicons [59 to 120 base pairs (bp)] ofthe chloroplast DNA (cpDNA) rbcL gene andtrnL intron from ~50 g of the interior ice meltsfrom the Dye 3 and the John Evans Glacier siltysamples. From Dye 3, we also obtained 97-bpamplicons of invertebrate cytochrome oxidasesubunit I (COI) mitochondrial DNA (mtDNA).Attempts to reproducibly amplify DNA fromthe GRIP silty ice and from the Kap KøbenhavnFormation sediments were not successful. Theseresults are consistent with the amino acid race-mization data demonstrating superior preser-vation of biomolecules in the Dye 3 and JohnEvans Glacier silty samples, which is likelybecause these samples are colder (Dye 3) oryounger (John Evans Glacier) than the GRIPsample (Fig. 1A, inset). We also failed to amplifyDNA from the five control samples of Holoceneand Pleistocene ice taken just above the siltysamples from the Dye 3 and GRIP ice cores(volumes: 100 g to 4 kg; Fig. 1B) (7). None ofthe samples studied yielded putative sequencesof vertebrate mtDNA.

A previous study has shown that simple com-parisons of short DNA sequences to GenBanksequences by means of the Basic Local Align-ment Search Tool (BLAST) make misidentifica-tion likely (15). Therefore, we assigned theobtained sequences to the taxonomic levels oforder, family, or genus using a new rigorousstatistical approach (7). In brief, this Bayesianmethod calculates the probability that each se-quence belongs to a particular clade by consid-ering its position in a phylogenetic tree based onsimilar GenBank sequences. In the calculationof these probabilities, uncertainties regarding phy-logeny, models of evolution, and missing dataare taken into account. Sequences with >90%posterior probability of membership to a taxo-nomic group were assigned to that group. Addi-tionally, a given plant taxon was only consideredgenuine if sequences assigned to that taxon werefound to be reproducibly obtained in separateanalyses (by independent laboratories for theDye 3 sample and within the laboratory for theJohn Evans Glacier control sample). This strict

1Centre for Ancient Genetics, University of Copenhagen,Denmark. 2BioArch, Departments of Biology and Archaeology,University of York, UK. 3Bioinformatics Centre, University ofCopenhagen, Denmark. 4Centre for Comparative Genomics,University of Copenhagen, Denmark. 5Max Planck Institute forEvolutionary Anthropology, Germany. 6Murdoch UniversityAncient DNA Research Laboratory, Murdoch University,Australia. 7McMaster Ancient DNA Center, McMaster Uni-versity, Canada. 8Ice and Climate, University of Copenhagen,Denmark. 9Geological Survey of Denmark and Greenland,Denmark. 10Research Laboratory for Archaeology and theHistory of Art, University of Oxford, UK. 11Department ofGeography, Royal Holloway, University of London, UK.12Department of Earth Sciences, University of Oxford, UK.13Paul Scherrer Institut (PSI)/Eidgenössische TechnischeHochschule (ETH) Laboratory for Ion Beam Physics, Institutefor Particle Physics, ETH Zurich, Switzerland. 14Swiss FederalInstitute of Aquatic Science and Technology (EAWAG),Switzerland. 15GeoBiosphere Science Center, Lund Univer-sity, Sweden. 16Department of Earth and AtmosphericSciences, University of Alberta, Canada. 17Ancient Biomole-cules Centre, Oxford University, UK. 18Laboratoire d'EcologieAlpine, CNRS Unité Mixte de Recherche 5553, UniversitéJoseph Fourier, Boîte Postale 53, 38041 Grenoble Cedex 9,France. 19Dipartimento di Chimica Generale e Inorganica,Università di Parma, Italy.

*To whom correspondence should be addressed. E-mail:[email protected]

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Willerslev 2007

SprucePine

BirchLegumes

Butterflies

Daisies/SunflowerGrasses

Consensus with fossil record?

Molecular evolution analysis: •Earliest placental mammals (ie. eutherians)•body mass >1kg; lifespan >25years

Genomic Evidence for Large, Long-Lived Ancestors toPlacental MammalsJ. Romiguier,1 V. Ranwez,1,2 E.J.P. Douzery,1 and N. Galtier*,1

1CNRS, Universite Montpellier 2, UMR 5554, ISEM, Montpellier, France2Montpellier SupAgro, UMR 1334, AGAP, Montpellier, France

*Corresponding author: E-mail: [email protected].

Associate editor: Naruya Saitou

Abstract

It is widely assumed that our mammalian ancestors, which lived in the Cretaceous era, were tiny animals that survived massiveasteroid impacts in shelters and evolved into modern forms after dinosaurs went extinct, 65 Ma. The small size of most Mesozoicmammalian fossils essentially supports this view. Paleontology, however, is not conclusive regarding the ancestry of extantmammals, because Cretaceous and Paleocene fossils are not easily linked to modern lineages. Here, we use full-genome data toestimate the longevity and body mass of early placental mammals. Analyzing 36 fully sequenced mammalian genomes, wereconstruct two aspects of the ancestral genome dynamics, namely GC-content evolution and nonsynonymous over synonym-ous rate ratio. Linking these molecular evolutionary processes to life-history traits in modern species, we estimate that earlyplacental mammals had a life span above 25 years and a body mass above 1 kg. This is similar to current primates, cetartiodactyls,or carnivores, but markedly different from mice or shrews, challenging the dominant view about mammalian origin andevolution. Our results imply that long-lived mammals existed in the Cretaceous era and were the most successful in evolution,opening new perspectives about the conditions for survival to the Cretaceous–Tertiary crisis.

Key words: phylogeny, GC-content, dN/dS ratio, GC-biased gene conversion, placentalia, fossils.

IntroductionIt is commonly assumed that early mammals were small crea-tures that only evolved into a variety of forms and sizes afterthe massive extinction of large reptiles, at the Cretaceous/Tertiary (KT) boundary, 65 Ma (Dawkins 2004; Feldhameret al. 2007). This scenario is consistent with theoretical con-siderations: Cope’s rule (Alroy 1998) states that current livinglineages generally descend from small ancestors, because largeforms have a short-term advantage but tend to be moreprone to extinction in the long run. The hypothesis of asmall ancestral size is also largely supported by the fossilrecord: most of the Cretaceous mammals are smaller thana few inches, whereas post-KT deposits include numerouslarge mammals (Luo 2007; Smith et al. 2010).

Paleontology, however, is not conclusive regarding the an-cestry of extant mammals due to the difficulty of linkingCretaceous and Paleocene fossils to modern lineages(Archibald et al. 2001; Asher et al. 2005). Genomic data pro-vide an attractive opportunity to characterize the ancestralfeatures of extant species: genome dynamics is imprinted byspecies life-history traits (Nikolaev et al. 2007; Nabholz et al.2008; Romiguier et al. 2010), and ancestral genome characterscan be reconstructed by phylogenetic methods (Galtier et al.1999; Blanchette et al. 2004; Boussau et al. 2009; Lartillot andPoujol 2011). If molecular evolution can be traced back to thelast common ancestor of extant placentals, then we couldpotentially learn about its macroscopic characteristics, eventhough this ancestor is not physically observable becausemissing from the fossil record.

In mammals, two genomic variables are known to correlatewith species life-history traits. First, species longevity and bodymass influence the ratio of nonsynonymous (= amino acidchanging, dN) to synonymous (dS) nucleotide substitutionrates. It has been shown that large and long-lived speciesdisplay a higher dN/dS ratio, on average, than small andshort-lived ones, presumably because of the smaller averagepopulation sizes, and hence the less effective purifying selec-tion, in long-lived animals (Nikolaev et al. 2007). Second, largespecies tend to show a lower GC3 (percentage of G and C atthe third position of codons) than small species. This effect issupposed to be caused by GC-biased gene conversion (Duretand Galtier 2009), a mechanism by which a biased DNA-repair process favors G and C alleles during meiotic recom-bination. Because short-lived species experience a higher rateof meiosis per time unit, their genome shows a faster diver-gence in gene GC3 and an increase in average GC3 (Romiguieret al. 2010).

Here, we quantify the influence of species longevity ongene coding sequence evolutionary dynamics (dN/dS ratioand GC3 divergence) in modern placental mammals. Thenwe reconstruct ancestral gene sequences using nonhomoge-neous phylogenetic models and estimate the dN/dS and GC3dynamics in the deepest branches of the mammalian tree. Onthe basis of the existing correlation between genomic pro-cesses and traits, we estimate the maximal life span of earlyplacental mammals. Our analysis suggests that the ancestorsof living placentals had a longevity and body mass similar tocurrent primates, cetartiodactyls, or carnivores but differed

Article

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Mol. Biol. Evol. 30(1):5–13 doi:10.1093/molbev/mss211 Advance Access publication September 4, 2012 5

at UniversitÃ

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ownloaded from

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ie. very different from “mouse-like”

Eomaia scansoria

What common ancestor of placental mammals radiated after K-T (Cretaceous-Palogene) extinction?

3. DNA sequence clarifies current relationships

Three-spined stickleback Gasterosteus aculeatus

Bill Cresko et al; David Kingsley et al

Example 1.

Independent colonization events

less than 10,000 years ago

in Saltwater:

in Freshwater:

conservative (and unbiased) nature with which SNPs are calledusing our methodology (see Methods), and additional sequencingof these samples may increase the number of SNPs identified.Furthermore, in agreement with the hypothesis that freshwaterpopulations in this region have been derived post-glacially fromoceanic populations [49,55,65,79], global genetic diversity mea-sures are increased only slightly when combining pairs ofpopulations whether they are both oceanic, both freshwater, orone of each (Table 2).

Our data support the hypothesis that oceanic sticklebackpopulations have few barriers to dispersal, relatively large amountsof gene flow, and little population genetic subdivision[55,57,59,60,103,104]. Rabbit Slough and Resurrection Bay, thetwo oceanic populations in our study, are the most geographicallydistant from one another (.1000 km as the fish swims). Despitethis distance, the oceanic populations show the least amount ofdifferentiation between them (FST = 0.0076; Table 2). In contrast,higher values of FST were observed in pairwise comparisonsamong freshwater populations and between freshwater andoceanic populations (0.05–0.15), which is generally interpretedas low to moderate amounts of population structuring (Table 2).

The freshwater populations, despite their younger age, are moredivergent both from the oceanic ancestral populations and fromeach other, consistent with our supposition that they representindependent colonizations from the ancestral oceanic population.These results are remarkably similar to results obtained previouslyfrom some of these same populations using a small number ofmicrosatellite and mtDNA markers [55]. This combination oflarge amounts of genetic variation and overall low-to-moderatedifferentiation between populations, coupled with recent and rapidphenotypic evolution in the freshwater populations, presents anideal situation for identifying genomic regions that have respondedto various kinds of natural selection.

Patterns of genetic diversity distributed across thegenome

To assess genome-wide patterns we examined mean nucleotidediversity (p) and heterozygosity (H) using a Gaussian kernelsmoothing function across each linkage group (Figure 4 and FigureS1). Although the overall mean diversity and heterozygosity valuesare 0.00336 and 0.00187, respectively, values vary widely acrossthe genome. Nucleotide diversity within genomic regions rangesfrom 0.0003 to over 0.01, whereas heterozygosity values rangefrom 0.0001 to 0.0083. This variation in diversity across thegenome provides important clues to the evolutionary processesthat are maintaining genetic diversity. For example, whileexpected (p) and observed (H) heterozygosity largely correspond,they differ at a few genomic regions (e.g., on Linkage Group XI).Genomic regions that exhibit significantly (p,1025) low levels ofdiversity and heterozygosity (e.g. on LG II and V, Figure 4and Figure S1) may be the result of low mutation rate,low recombination rate, purifying or positive selection that isconsistent across populations, or some combination of factors[9,36,105–107].

In contrast, other genomic regions, such as those on LG III andXIII (Figure 4), show very high levels of both diversity andheterozygosity. The most striking such region, found near the endof LG III, corresponds precisely with a region of reduceddifferentiation among populations (Figure 5). This suggests thepresence of balancing selection maintaining a common pool ofgenetic variation at this genomic region within and amongpopulations. To further investigate the pattern of increased geneticvariation on LG III, we delineated a region from 14.8 to 16.1 Mb(Figure 5; see Methods). Within the corresponding 1.3-Mb interval inthe published stickleback genome are several candidate targets ofbalancing selection, namely genes implicated in the first line ofdefense against pathogens [108]: ZEB1 (ENSGACG00000017648),and two adjacent APOL genes (ENSGACG00000017778, EN-SGACG00000017779). Supporting the importance of this region inimmune response, there are also orthologs of several inflammationpathway genes: LTB4R (ENSGACG00000017812), SHARPIN(ENSGACG00000017834), and CEBPD (ENSGACG00000017927)[109–111]. The region of significantly elevated nucleotide diversityon LG XIII (18.1–19.1 Mb) also contains candidate targets ofbalancing selection including a TRIM14 (ENSGACG00000014283)and three TRIM35 genes (ENSGACG00000014250, ENSG-ACG00000014251, ENSGACG00000014403). Many members ofthis large gene family have been implicated in innate immuneresponse (reviewed in [112]), and one gene, TRIM5alpha, bears thesignature of balancing selection in primates [113]. The sticklebackTRIM cluster on LG XIII provides a second example of balancingselection acting at a TRIM locus.

Evidence for balancing selection on Major HistoCompatibility(MHC) loci is somewhat weaker. An MHC Class II gene(ENSGACG00000017967) falls nearly 580 kb outside the interval

Figure 1. Location of oceanic and freshwater populationsexamined. Threespine stickleback were sampled from three freshwa-ter (Bear Paw Lake [BP], Boot Lake [BL], Mud Lake [ML]) and two oceanic(Rabbit Slough [RS], Resurrection Bay [RB]) populations in south centralAlaska, USA (see inset). The three freshwater populations occur indifferent drainages and are separated by barriers to dispersal, andprevious evidence supports the hypothesis that they representindependent colonization events from ancestral oceanic populations[49].doi:10.1371/journal.pgen.1000862.g001

Population Genomics in Stickleback

PLoS Genetics | www.plosgenetics.org 3 February 2010 | Volume 6 | Issue 2 | e1000862

F

S

F

F

S

S = Saltwater

F = Freshwater

Bill Cresko et al;

Different amounts of armor plating

RAD = Restriction-site Associated DNA sequencing

each locus sequenced 5–10 times per fish.

Bill Cresko et al;

conservative (and unbiased) nature with which SNPs are calledusing our methodology (see Methods), and additional sequencingof these samples may increase the number of SNPs identified.Furthermore, in agreement with the hypothesis that freshwaterpopulations in this region have been derived post-glacially fromoceanic populations [49,55,65,79], global genetic diversity mea-sures are increased only slightly when combining pairs ofpopulations whether they are both oceanic, both freshwater, orone of each (Table 2).

Our data support the hypothesis that oceanic sticklebackpopulations have few barriers to dispersal, relatively large amountsof gene flow, and little population genetic subdivision[55,57,59,60,103,104]. Rabbit Slough and Resurrection Bay, thetwo oceanic populations in our study, are the most geographicallydistant from one another (.1000 km as the fish swims). Despitethis distance, the oceanic populations show the least amount ofdifferentiation between them (FST = 0.0076; Table 2). In contrast,higher values of FST were observed in pairwise comparisonsamong freshwater populations and between freshwater andoceanic populations (0.05–0.15), which is generally interpretedas low to moderate amounts of population structuring (Table 2).

The freshwater populations, despite their younger age, are moredivergent both from the oceanic ancestral populations and fromeach other, consistent with our supposition that they representindependent colonizations from the ancestral oceanic population.These results are remarkably similar to results obtained previouslyfrom some of these same populations using a small number ofmicrosatellite and mtDNA markers [55]. This combination oflarge amounts of genetic variation and overall low-to-moderatedifferentiation between populations, coupled with recent and rapidphenotypic evolution in the freshwater populations, presents anideal situation for identifying genomic regions that have respondedto various kinds of natural selection.

Patterns of genetic diversity distributed across thegenome

To assess genome-wide patterns we examined mean nucleotidediversity (p) and heterozygosity (H) using a Gaussian kernelsmoothing function across each linkage group (Figure 4 and FigureS1). Although the overall mean diversity and heterozygosity valuesare 0.00336 and 0.00187, respectively, values vary widely acrossthe genome. Nucleotide diversity within genomic regions rangesfrom 0.0003 to over 0.01, whereas heterozygosity values rangefrom 0.0001 to 0.0083. This variation in diversity across thegenome provides important clues to the evolutionary processesthat are maintaining genetic diversity. For example, whileexpected (p) and observed (H) heterozygosity largely correspond,they differ at a few genomic regions (e.g., on Linkage Group XI).Genomic regions that exhibit significantly (p,1025) low levels ofdiversity and heterozygosity (e.g. on LG II and V, Figure 4and Figure S1) may be the result of low mutation rate,low recombination rate, purifying or positive selection that isconsistent across populations, or some combination of factors[9,36,105–107].

In contrast, other genomic regions, such as those on LG III andXIII (Figure 4), show very high levels of both diversity andheterozygosity. The most striking such region, found near the endof LG III, corresponds precisely with a region of reduceddifferentiation among populations (Figure 5). This suggests thepresence of balancing selection maintaining a common pool ofgenetic variation at this genomic region within and amongpopulations. To further investigate the pattern of increased geneticvariation on LG III, we delineated a region from 14.8 to 16.1 Mb(Figure 5; see Methods). Within the corresponding 1.3-Mb interval inthe published stickleback genome are several candidate targets ofbalancing selection, namely genes implicated in the first line ofdefense against pathogens [108]: ZEB1 (ENSGACG00000017648),and two adjacent APOL genes (ENSGACG00000017778, EN-SGACG00000017779). Supporting the importance of this region inimmune response, there are also orthologs of several inflammationpathway genes: LTB4R (ENSGACG00000017812), SHARPIN(ENSGACG00000017834), and CEBPD (ENSGACG00000017927)[109–111]. The region of significantly elevated nucleotide diversityon LG XIII (18.1–19.1 Mb) also contains candidate targets ofbalancing selection including a TRIM14 (ENSGACG00000014283)and three TRIM35 genes (ENSGACG00000014250, ENSG-ACG00000014251, ENSGACG00000014403). Many members ofthis large gene family have been implicated in innate immuneresponse (reviewed in [112]), and one gene, TRIM5alpha, bears thesignature of balancing selection in primates [113]. The sticklebackTRIM cluster on LG XIII provides a second example of balancingselection acting at a TRIM locus.

Evidence for balancing selection on Major HistoCompatibility(MHC) loci is somewhat weaker. An MHC Class II gene(ENSGACG00000017967) falls nearly 580 kb outside the interval

Figure 1. Location of oceanic and freshwater populationsexamined. Threespine stickleback were sampled from three freshwa-ter (Bear Paw Lake [BP], Boot Lake [BL], Mud Lake [ML]) and two oceanic(Rabbit Slough [RS], Resurrection Bay [RB]) populations in south centralAlaska, USA (see inset). The three freshwater populations occur indifferent drainages and are separated by barriers to dispersal, andprevious evidence supports the hypothesis that they representindependent colonization events from ancestral oceanic populations[49].doi:10.1371/journal.pgen.1000862.g001



F

S

F

F

S

S = Saltwater

F = Freshwater

20 fish per population

45,789 loci genotyped

Differentiation between populations (FST)

Saltwater vs. Saltwater

Figure 6. Genome-wide differentiation among populations. FST across the genome, with colored bars indicating significantly elevated(p#1025, blue; p#1027, red) and reduced (p#1025, green) values. Vertical gray shading indicates boundaries of the linkage groups and unassembledscaffolds, and gold shading indicates the nine peaks of substantial population differentiation discussed in the text. (A) FST between the two oceanicpopulations (RS and RB; note that no regions of FST are significantly elevated or reduced). (B,C,D) Differentiation of each single freshwater populationfrom the two oceanic populations, shown as the mean of the two pairwise comparisons (with RS and RB): (B) BP, (C) BL, (D) ML. Colored bars in eachplot represent regions where both pairwise comparisons exceeded the corresponding significance threshold. (E) Overall population differentiationbetween the oceanic and freshwater populations. (F) Differentiation among the three freshwater populations (BP, BL, ML).doi:10.1371/journal.pgen.1000862.g006



Freshwater vs.

Freshwater




Freshwater vs. Saltwater




FST bewteen 2 populations: 0 = populations have same alleles in similar frequencies 1 = populations have completely different alleles

Bill Cresko et al; David Kingsley et al

Nine identified regions• Identified regions include:

• 31 that likely to affect morphology or osmoregulation • some previously identified via crosses; most new

• E.g. EDA gene.

• “rare” recessive allele (found in 1-5% of ocean individuals)• the “rare” allele went to fixation in all freshwater

populations (ie. all individuals homozygous for the rare allele)

Example 2: Little fire ant Wasmannia DNA identifies family relationships

Fournier et al 2005

Normally, * males (haploid) carry only maternal DNA * workers and new queens (all diploid) carry DNA from their father and their mother

reproduction (that is, by ameiotic parthenogenesis). In 33 of the 34nests, all queens (n ¼ 135) and gynes (n ¼ 9) cohabiting in the samenest shared an identical genotype at each of the 11 loci (Table 1 andFig. 1). The single exception was nest B-12, in which queens differedat 1 of the 11 loci: four queens were heterozygous at Waur-2164and the remaining three queens were homozygous for one of thetwo alleles. This variation probably reflects a mutation or recombi-nation event in one queen followed by clonal reproduction withinthe nest. The history of this genetic change could be reconstructedfrom the genotypes of queens collected in neighbouring nests (Figs 1and 2). Nine queens from two neighbouring nests (B-11 and B-13)had the same genotype as the four heterozygous queens for locusWaur-2164, indicating that the mutation or recombination eventprobably was from a heterozygote to a homozygote queen. The threehomozygote queens from nest B-12 had a unique genotype in thepopulation, which further supports this interpretation.A comparison between nests supports the view of restricted female

gene flow, with budding being the main mode of colony formation.Within three of the five sites of collection (A, C and D) all queens hadthe same genotype at the 11 loci (Fig. 2). In one of the two other sites(B), all queens from 8 of the 17 nests also had an identical genotype,whereas in the other site (E) the queen genotypes were different in thethree nests sampled. Taken together, these data indicate that queensbelonging to the same lineage of clonally produced individualsfrequently head closely located nests. Moreover, genetic differen-tiation between sites was very strong, with a single occurrence ofgenotypes shared between sites (the eight queens of nest E-3 hadgenotypes identical to the most common genotype found at site B),showing that gene flow by females is extremely restricted.In stark contrast to reproductive females, the genotypic analyses

revealed that workers are produced by normal sexual reproduction(Table 1). Over all 31 queenright nests, each of the 248 genotypedworkers had, at seven or more loci, one allele that was absent inqueens of their nest. Moreover, the 232 workers from the 29 nests inwhich the sperm in the queen’s spermathecae was successfullyobtained had all genotypes consistent with those expected undersexual reproduction between the two parental genomes.The genetic analyses of the sperm collected in the queens’

Table 1 | Genotypes of queens (Q), their mates (M) and workers (w) in one nest (E-3) at each of the 11 microsatellite loci

Individual Waur-225 Waur-275 Waur-418 Waur-566 Waur-680 Waur-716 Waur-730 Waur-1166 Waur-2164 Waur-3176 Waur-1gam

QueensQ-1 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-2 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-3 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-4 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-5 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-6 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-7 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-8 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298MalesM-1 269 107 118 265 187 192 214 95 320 244 282M-2 269 107 118 265 187 192 214 95 320 244 282M-3 269 107 118 265 187 192 214 95 320 244 282M-4 269 107 118 265 187 192 214 95 320 244 282M-5 269 107 118 265 187 192 214 95 320 244 282M-6 269 107 118 265 187 192 214 95 320 244 282M-7 269 107 118 265 187 192 214 95 320 244 282M-8 269 107 118 265 187 192 214 95 320 244 282Workersw-1 223 269 115 107 112 118 263 265 171 187 198 192 160 214 95 95 306 320 230 244 298 282w-2 225 269 115 107 100 118 263 265 171 187 184 192 158 214 95 95 298 320 230 244 288 282w-3 223 269 105 107 112 118 263 265 171 187 198 192 160 214 97 95 298 320 230 244 298 282w-4 225 269 115 107 100 118 263 265 171 187 184 192 158 214 97 95 306 320 230 244 288 282w-5 223 269 105 107 100 118 263 265 171 187 198 192 158 214 97 95 306 320 230 244 298 282w-6 225 269 115 107 112 118 263 265 171 187 184 192 160 214 97 95 306 320 230 244 288 282w-7 223 269 105 107 100 118 263 265 171 187 184 192 158 214 97 95 306 320 230 244 298 282w-8 225 269 115 107 112 118 263 265 171 187 184 192 158 214 97 95 298 320 230 244 288 282

The identities of mates were determined by the sperm collected in the queen’s spermathecae. Queens and males’ genotypes illustrate their clonal production, whereas workers’ genotypes areconsistent with normal sexual reproduction. Paternal alleles are in italics.

Figure 2 | Neighbour-joining dendrogram of the genetic (allele-shared)distances between queens (Q), gynes (G) and male sperms (M) collectedover all the five sites (A–E). The collection number of each nest is givenwith the letter of the site (see Fig. 1 for details). The number of individualssharing the same genotype (n) is given for all nests.

NATURE|Vol 435|30 June 2005 LETTERS

1231© 2005 Nature Publishing Group

reproduction (that is, by ameiotic parthenogenesis). In 33 of the 34nests, all queens (n ¼ 135) and gynes (n ¼ 9) cohabiting in the samenest shared an identical genotype at each of the 11 loci (Table 1 andFig. 1). The single exception was nest B-12, in which queens differedat 1 of the 11 loci: four queens were heterozygous at Waur-2164and the remaining three queens were homozygous for one of thetwo alleles. This variation probably reflects a mutation or recombi-nation event in one queen followed by clonal reproduction withinthe nest. The history of this genetic change could be reconstructedfrom the genotypes of queens collected in neighbouring nests (Figs 1and 2). Nine queens from two neighbouring nests (B-11 and B-13)had the same genotype as the four heterozygous queens for locusWaur-2164, indicating that the mutation or recombination eventprobably was from a heterozygote to a homozygote queen. The threehomozygote queens from nest B-12 had a unique genotype in thepopulation, which further supports this interpretation.A comparison between nests supports the view of restricted female

gene flow, with budding being the main mode of colony formation.Within three of the five sites of collection (A, C and D) all queens hadthe same genotype at the 11 loci (Fig. 2). In one of the two other sites(B), all queens from 8 of the 17 nests also had an identical genotype,whereas in the other site (E) the queen genotypes were different in thethree nests sampled. Taken together, these data indicate that queensbelonging to the same lineage of clonally produced individualsfrequently head closely located nests. Moreover, genetic differen-tiation between sites was very strong, with a single occurrence ofgenotypes shared between sites (the eight queens of nest E-3 hadgenotypes identical to the most common genotype found at site B),showing that gene flow by females is extremely restricted.In stark contrast to reproductive females, the genotypic analyses

revealed that workers are produced by normal sexual reproduction(Table 1). Over all 31 queenright nests, each of the 248 genotypedworkers had, at seven or more loci, one allele that was absent inqueens of their nest. Moreover, the 232 workers from the 29 nests inwhich the sperm in the queen’s spermathecae was successfullyobtained had all genotypes consistent with those expected undersexual reproduction between the two parental genomes.The genetic analyses of the sperm collected in the queens’

Table 1 | Genotypes of queens (Q), their mates (M) and workers (w) in one nest (E-3) at each of the 11 microsatellite loci

Individual Waur-225 Waur-275 Waur-418 Waur-566 Waur-680 Waur-716 Waur-730 Waur-1166 Waur-2164 Waur-3176 Waur-1gam

QueensQ-1 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-2 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-3 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-4 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-5 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-6 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-7 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298Q-8 223 225 105 115 100 112 263 263 171 171 184 198 158 160 95 97 298 306 230 230 288 298MalesM-1 269 107 118 265 187 192 214 95 320 244 282M-2 269 107 118 265 187 192 214 95 320 244 282M-3 269 107 118 265 187 192 214 95 320 244 282M-4 269 107 118 265 187 192 214 95 320 244 282M-5 269 107 118 265 187 192 214 95 320 244 282M-6 269 107 118 265 187 192 214 95 320 244 282M-7 269 107 118 265 187 192 214 95 320 244 282M-8 269 107 118 265 187 192 214 95 320 244 282Workersw-1 223 269 115 107 112 118 263 265 171 187 198 192 160 214 95 95 306 320 230 244 298 282w-2 225 269 115 107 100 118 263 265 171 187 184 192 158 214 95 95 298 320 230 244 288 282w-3 223 269 105 107 112 118 263 265 171 187 198 192 160 214 97 95 298 320 230 244 298 282w-4 225 269 115 107 100 118 263 265 171 187 184 192 158 214 97 95 306 320 230 244 288 282w-5 223 269 105 107 100 118 263 265 171 187 198 192 158 214 97 95 306 320 230 244 298 282w-6 225 269 115 107 112 118 263 265 171 187 184 192 160 214 97 95 306 320 230 244 288 282w-7 223 269 105 107 100 118 263 265 171 187 184 192 158 214 97 95 306 320 230 244 298 282w-8 225 269 115 107 112 118 263 265 171 187 184 192 158 214 97 95 298 320 230 244 288 282

The identities of mates were determined by the sperm collected in the queen’s spermathecae. Queens and males’ genotypes illustrate their clonal production, whereas workers’ genotypes areconsistent with normal sexual reproduction. Paternal alleles are in italics.

Figure 2 | Neighbour-joining dendrogram of the genetic (allele-shared)distances between queens (Q), gynes (G) and male sperms (M) collectedover all the five sites (A–E). The collection number of each nest is givenwith the letter of the site (see Fig. 1 for details). The number of individualssharing the same genotype (n) is given for all nests.

NATURE|Vol 435|30 June 2005 LETTERS

1231© 2005 Nature Publishing Group

mate with their brothers inside the nest, and yet maintainheterozygosity in the queen and worker castes over anunlimited number of generations.

Surprisingly, the heterozygosity level of new queens iscompletely independent of the genealogical link betweenthe mother queen and her mate in this species, as thereis no mixing of the paternal and maternal lineages. Bycontrast, the level of worker heterozygosity depends onthe genetic similarity between the maternal and paternallineages, because workers are sexually produced. Butsince all queens and all males in our study populationhad the same genotype, queens were no more geneticallysimilar to their brothers than to any other male in thepopulation, and the level of worker heterozygosity wastherefore not affected by whether queens mated withtheir brothers or other males.

The particular reproductive system of P. longicornisprobably provides an important pre-adaptation allowingthis species to colonize new habitats. Paratrechina longicornisis arguably the most broadly dispersed of all ant species,distributed widely across the Old World and New Worldin both the Northern Hemisphere and Southern Hemi-sphere [25]. The multiple introductions of this specieshave probably been accompanied by repeated reductionsin population size during the founding stages of new popu-lations. However, the complete separation of the maternaland paternal genomes allows such founding events tooccur without any cost associated with inbreeding (i.e.mating between related individuals) in workers. Whateverthe population size, a high level of heterozygosity can bemaintained in workers as a result of the very stark geneticdifferences between the paternal and maternal lineages.Population bottlenecks only affect the allelic diversity atthe population level, without decreasing observed hetero-zygosity of queens and workers. In the studied population,there was actually no genotypic diversity within either thematernal or paternal clonal lineages, yet the observed het-erozygosity in workers was extremely high (across the 12microsatellite loci, observed heterozygosity was close to 1;electronic supplementary material, table S1).

Recent studies have reported similar reproductivestrategies involving clonal reproduction of both sexes in

two other ant species: Wasmannia auropunctata and Vollen-hovia emeryi [21,22]. On the basis of the results of ourstudy, it is likely that the mating system of these speciesalso translates into reduced effects of bottlenecks andsib mating on the level of heterozygosity of females. Inter-estingly, W. auropunctata is also an invasive ant, and recentstudies have shown that introduced populations oftenderive from a single queen introduction [30] and arecharacterized by the presence of a single queen and asingle male genotype. The presence of a single queenand a single male genotype in our P. longicornis populationis also compatible with the population being initiated bya single mated queen.

Interestingly, our study shows that P. longicornis queenslay male eggs that inherit no maternal genes. There are atleast two potential mechanisms that could lead to a malebeing clonally produced by his father. First, the maternalgenome could be eliminated after the egg was fertilized[21]. Indeed, other examples of selective elimination ofone parental genome have been reported in species suchas the parasitoid wasp Nasonia vitripennis [31,32] andthe waterfrog hybridogenetic species complex Rana escu-lenta [33,34], and as probable in some ants of the genusFormica [35,36]. In these cases, however, it is always thepaternal genome that is eliminated and not the maternalone. The alternative possibility is that females sometimeslay anucleated eggs that develop into haploid males whenfertilized [37]. Unfortunately, it is not possible to knowwhich eggs will give rise to males and females, and it willthus be very difficult to discriminate between these twopotential mechanisms.

In conclusion, this study demonstrates that P. longicor-nis uses an unusual mode of reproduction acting as apre-adaptation for situations where inbreeding and bottle-necking occur. Even if populations are initiated by a singlefemale, the clonal reproduction of both males and queensensures a high level of observed heterozyosity of workerswhen the founding queen and her mate have differentalleles. Moreover, this unusual system of reproductionmaintains similar levels of observed heterozygosity forqueens and for workers even if matings occur between sib-lings over several generations. This may be an importantfactor explaining why this species has been so successfulin invading new habitats.

We thank Sasithorn Hasin and Mingkwan Nipitwattanaphonfor collecting material in Thailand, Vicky Menetrey for hercontribution to lab work, and three anonymous reviewersfor their useful comments. This work was supported by anEMBO fellowship (M.P.), United States National ScienceFoundation grant DEB no. 0640690 (M.A.D.G.) and theSwiss National Science Foundation (L.K.).

REFERENCES1 Charlesworth, D. & Willlis, J. 2009 The genetics of

inbreeding depression. Nat. Rev. Genet. 10, 783–796.(doi:10.1038/nrg2664)

2 Whiting, P. W. 1939 Sex determination and reproductiveeconomy in Habrobracon. Genetics 24, 110–111.

3 Whiting, P. W. 1943 Multiple alleles in complementarysex determination of Habrobracon. Genetics 28, 365–382.

4 Butcher, R. D. J., Whitfield, W. G. F. & Hubbard, S. F. 2000Single-locus complementary sex determination in Diadegmachrysostictos (Gmelin) (Hymenoptera: Ichneumonidae).J. Hered. 91, 104–111. (doi:10.1093/jhered/91.2.104)

gynes workers males

queen mate

Figure 2. Clonal reproduction in queens and males. Thefigure summarizes the reproduction system of P. longicornisin the study population. Maternal (light) and paternal(dark) chromosomes are displayed. Contribution to thegenome of the offspring is indicated by arrows (dashedarrow represents the mother laying haploid eggs with noactual contribution to the genome).

2680 M. Pearcy et al. Sib mating without inbreeding

Proc. R. Soc. B (2011)

on January 21, 2013rspb.royalsocietypublishing.orgDownloaded from

Here: * workers carry DNA

from mother & father * new queens are 100%

clones of their mother * new males are 100%

clones of their father

Example 3: Species-interactions via DNA sequencingCurrent Biology Vol 22 No 8

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Screening mammal biodiversity using DNA from leechesIda Bærholm Schnell1,2,†, Philip Francis Thomsen2,†, Nicholas Wilkinson3, Morten Rasmussen2, Lars R.D. Jensen1, Eske Willerslev2, Mads F. Bertelsen1, and M. Thomas P. Gilbert2,*

With nearly one quarter of mammalian species threatened, an accurate description of their distribution and conservation status is needed [1]. For rare, shy or cryptic species, existing monitoring methods are often prohibitively expensive or unreliable. The problem is particularly acute in tropical forests, where a disproportionate number of species are listed by IUCN as ‘data deficient’ [2], due to the difficulty of monitoring with conventional approaches. This presents serious obstacles to conservation management. We, here, describe a new screening tool, the analysis of mammalian DNA extracted from haematophagous leeches. By demonstrating that PCR amplifiable mammalian blood DNA survives for at least four months post feeding in haematophagous Hirudo spp. leeches, we hypothesise that most wild caught adult leeches will contain DNA traces of their last blood meal. We subsequently demonstrate the efficacy of the method, by testing it in situ using terrestrial Haemadipsa spp. leeches caught in a tropical Vietnamese rainforest setting, and identify cryptic, rare and newly discovered mammalian species. We propose that DNA from leeches represents a quick, cost-effective and standardised way to obtain basic data on mammalian biodiversity and species occupancy, facilitating efficient use of limited conservation resources.

An emerging tool for assessing mammalian biodiversity is the profiling of DNA extracted from micropredators. In addition to ticks and mosquitoes [2], haematophagous leeches represent promising candidates as, following feeding, they store concentrated blood for several months [3]. Furthermore, several studies have demonstrated that

Correspondences in the medical leech (Hirudo medicinalis) viruses remain detectable in the blood meal for up to 27 weeks, indicating viral nucleic acid survival [4,5]. To examine whether PCR amplifiable mammalian DNA persists in ingested blood, we fed 26 medical leeches (Hirudo spp.) freshly drawn goat (Capra hircus) blood (Supplemental information) then sequentially killed them over 141 days. Following extraction of total DNA, a goat-specific quantitative PCR assay demonstrated mitochondrial DNA (mtDNA) survival in all leeches, thus persistence of goat DNA, for at least 4 months (Figure 1A; Supplemental information).

We subsequently applied the method to monitor terrestrial mammal biodiversity in a challenging environment. Haemadipsa spp. leeches were collected in a densely forested biotope in the Central Annamite region of Vietnam (Figure 1B; Supplemental information), in which five new mammal species have recently been discovered. Despite the interest these discoveries have generated, including adoption of the saola (Pseudoryx nghetinhensis) as a regional flagship species by the World Wildlife Fund, all attempts to develop standardised survey and monitoring techniques for these species have failed.

Remarkably, 21 out of 25 leeches tested yielded mammalian mtDNA sequences, representing six species spanning three orders — Artiodactyla, Carnivora and Lagomorpha (Figure 1B; Supplemental information). We deliberately chose PCR assays that are unable to PCR amplify human DNA in order to prevent false positives derived from human contamination of the leeches at time of sampling (Supplemental information). Therefore, it is possible that human DNA is present in the four samples that failed to yield an amplicon; thus, the value is a conservative estimate of the blood-meal-derived mammalian DNA prevalence in the leeches. Although multiple clones were sequenced per amplicon, no leech yielded sequences from more than one species, suggesting that rapid decline in blood meal DNA concentration over time (Supplemental information) will render DNA levels derived from a new feeding to be greatly higher than those from previous feedings. Two of the detected species have been recently described, the Truong Son muntjac (Muntiacus truongsonensis, one leech) and

foundation for modern studies of how and why sexual dimorphisms arose and evolved; with the advent of new technologies the near future will certainly provide deeper insights into the molecular basis of these processes.

Further readingBull, J.J. (1983). Evolution of Sex Determining

Mechanisms. (Menlo Park, California: Benjamin Cummings Publishing Company, Inc.)

Darwin, C. (1871). The Descent of Man and Selection in Relation to Sex. (London: John Murray.)

Dewing, P., Shi, T., Horvath, S., and Vilain, E. (2003). Sexually dimorphic gene expression in mouse brain precedes gonadal differentiation. Mol. Brain. Res. 118, 82–90.

Graves, J.A.M. (2008). Weird animal genomes and the evolution of vertebrate sex and sex chromosomes. Annu. Rev. Genet. 42, 565–586.

Herpin, A., and Schartl, M. (2011). Dmrt1 genes at the crossroads: a widespread and central class of sexual development factors in fish. FEBS J. 278, 1010–1019.

Hodgkin, J. (2002). Exploring the envelope: systematic alteration in the sex-determination system of the nematode Caenorhabditis elegans. Genetics 162, 767–780.

Hosken, D.J., and House, C.M. (2011). Sexual selection. Curr. Biol. 21, R62–R65.

Matson, C.K., Murphy, M.W., Sarver, A.L., Griswold, M.D., Bardwell, V.J., and Zarkower, D. (2011). DMRT1 prevents female reprogramming in the postnatal mammalian testis. Nature 476, 101–104.

Matson, C.K., and Zarkower, D. (2012). Sex and the singular DM domain: insights into sexual regulation, avolution and plasticity. Nat. Rev. Genet. 13, 163–174.

Quinn, A.E., Georges, A., Sarre, S.D., Guarino, F., Ezaz, T., and Graves, J.A.M. (2007). Temperature sex reversal implies sex gene dosage in a reptile. Science 316, 411.

Robinett, C.C., Vaughan, A.G., Knapp, J.M., and Baker, B.S. (2010). Sex and the single cell. II. There is a time and place for sex. PLoS Biol. 8, e1000365.

Sekido, R., and Lovell-Badge, R. (2009). Sex determination and SRY: down to a wink and a nudge. Trends Genet. 25, 19–29.

Tanaka, K., Barmina, O., Sanders, L.E., Arbeitman, M.N., and Kopp, A. (2011). Evolution of sex-specific traits through changes in HOX-dependent doublesex expression. PLoS Biol. 9, e1001131.

Uhlenhaut, N.H., Jakob, S., Anlag, K., Eisenberger, T., Sekido, R., Kress, J., Treier, A.-C., Klugmann, C., Klasen, C., Holter, N.I., et al. (2009). Somatic sex reprogramming of adult ovaries to testes by FOXL2 ablation. Cell 139, 1130–1142.

Veitia, R.A. (2010). FOXL2 versus SOX9: a lifelong ‘‘battle of the sexes’’. Bioessays 32, 375–380.

Williams, T.M., and Carroll, S.B. (2009). Genetic and molecular insights into the development and evolution of sexual dimorphism. Nat. Rev. Genet. 10, 797–804.

Williams, T.M., Selegue, J.E., Werner, T., Gompel, N., Kopp, A., and Carroll, S.B. (2008). The regulation and evolution of a genetic switch controlling sexually dimorphic traits in Drosophila. Cell 134, 610–623.

Zhao, D., McBride, D., Nandi, S., McQueen, H.A., McGrew, M.J., Hocking, P.M., Lewis, P.D., Sang, H.M., and Clinton, M. (2010). Somatic sex identity is cell autonomous in the chicken. Nature 464, 237–242.

Department of Genetics, Cell Biology, and Development, University of Minnesota, Minneapolis, MN 55455, USA. E-mail: [email protected]

MagazineR263

Annamite striped rabbit (Nesolagus timminsi, four leeches). Although IUCN lists both as ‘data deficient’, future data are expected to confirm their threatened status. Six leeches contained small-toothed ferret-badger (Melogale moschata) DNA, a cryptic species impossible to discriminate from related M. personata without handling. Three contained serow (Capricornis maritimus) DNA, a near-threatened species in decline. Lastly cow (Bos taurus) and pig (Sus scrofa) DNA were observed in two and five leeches, respectively. Pigs are the most common large terrestrial mammal in the area and cows are used to transport timber.

Terrestrial Haemadipsidae leeches are ideal for this method, due to their diverse prey base and readiness to attack humans, making them easy to collect. Haemadipsids abound in the humid forests of Southeast Asia, which have one of the most poorly described and most threatened mammal faunas in the world [1], and are present in Madagascar, South Asia and Australia. Elsewhere, as the Hirudo data show, aquatic leeches

Figure 1. Monitoring mammals with leeches.(A) Survival of mtDNA in goat blood ingested by Hirudo medicinalis over time, relative to freshly drawn sample (100%, ca. 2.4E+09 mtDNA copies/gram blood). Mitochondrial DNA remained detectable in all fed leeches, with a minimum observed level at 1.6E+04 mtDNA/gram blood ingested. The line shows a simple exponential decay model, p < 0.001, R2 = 0.43 (Supplemental information). (B) Vietnamese field site location and examples of mammals identified in Hae-madipsa spp. leeches. From left to right: Annamite striped rabbit, small-toothed ferret-badger, Truong Son munjtac (coat coloration and markings remain unknown), serow. Pictures do not reflect true size proportions. See also Supplemental information.

may prove useful. Aside from leech dietary revelations, the method has potential to revolutionise mammal detection surveys in tropical habitats. Throughout tropical Asia, mammal populations are severely depleted by hunting, remaining individuals are wary of humans, and habitats are frequently dense, rugged and humid, making detection of many species challenging. For example, although N. timminsi has been suspected in the survey area since its description in 1996, and over 2000 nights of camera trapping have been performed, this is the first confirmed record. Also, although Melogale have been detected using camera traps, the two species cannot be distinguished by sight; thus, our result is the first confirmed M. moschata for Bach Ma National Park. Similarly, the M. truongsonensis observation is the first confirmed record from the Saola Nature Reserve.

The potential for leeches in mammal surveys goes beyond making simple ad hoc records. Datasets of presence records can be used for inductive modelling of geographic range or for

estimating total occupancy across a landscape [6,7], information central to conservation. Unlike camera trapping and dung-searches, leech data collection is simple, inexpensive and can be conducted by untrained personnel. Furthermore, the laboratory methods can easily be undertaken using simple approaches. Much work is required to fully explore the potential of biodiversity monitoring of mammals (and other vertebrates), including a better understanding of leech feeding and dispersal behavior. However, our results demonstrate that profiling DNA extracted from haematophagous terrestrial leeches is a quick, cost-effective, and standardised way to obtain basic data on the species occupancy of known mammals.

Supplemental InformationSupplemental Information includes experimental procedures and two tables and can be found with this article online at doi:10.1016/j.cub.2012.02.058.

AcknowledgementsWe thank Tina Brand and Sam Turvey for assistance, Lucy Molleson for illustrations, and the Danish National Research Foundation for funding.

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2. Townzen, J.S., Brower, A.V.Z., and Judd, D.D. (2008). Identification of mosquito bloodmeals using mitochondrial cytochrome oxidase subunit I and cytochrome b gene sequences. Med. Vet. Entomol. 22, 386–393.

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1Copenhagen Zoo, Frederiksberg, 2000, Denmark. 2Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Copenhagen, 1350, Denmark. 3Department of Geography, University of Cambridge, Cambridge, CB2 3EN, UK. †These authors contributed equally *E-mail: [email protected]

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