Download Ecosystem change and species persistence over time: a genome

ECOGEN - Ecosystem change and species persistence over time: a genome-based
approach
Main goal
Develop high taxonomic resolution ancient environmental DNA methods in order to evaluate how
drivers of change (human, climate, biota) affect species persistence and ecosystem tipping points in
arctic-alpine biomes
Subgoals
1) Improve methods for full genome analyses of environmental DNA
2) Compile palaeo data to plan a balanced design of climatic and human impacts
3) Do full genome analyses of lake cores to obtain information on past presence and abundance
of vascular plant species and key herbivores
4) Identify biotic drivers and disentangle their effects from human land use and climate change
on ecosystem resilience and ecosystem services
5) Estimate species persistence across periods of changes and identify factors causing
extinction
6) Provide methods and knowledge to inform species conservation and ecosystem management
Summary – see announcement
Project tasks
We are seeking a research fellow that will join a cross-disciplinary team (ecology, palaeoecology,
genetics, archaeology, geology, niche modelling) working in two geographical regions (Norway
and the Alps). We will expand our knowledge on past vascular plant and animal diversity and
abundance at a taxonomic depth that has not been possible until now due to methodological
limitations. We expect to disentangle the effects of past human land-use (hunting, husbandry,
burning, agriculture), climate change, and biota on species and ecosystem changes and thereby be
able to answer questions central to our understanding of our biological resources, such as the level
of persistence of species and resilience of ecosystems to environmental drivers, the extinction risk
of species, and the capacity of mountain landscape to buffer against these changes. By identifying
drivers of shifts in ecosystem services through time, we may inform future management.
The successful candidate will work on development of improved technology. The most recent
applications of ancient plant DNA analyses are largely developed by our team (Taberlet et al. 2007,
Sønstebø et al. 2010, Yoccoz et al. 2012, Willerslev et al. 2014). For vascular plants, the 50-100
base pair long P6 loop region of the chloroplast trnL (UAA) intron is used in a PCR based method
(Taberlet et al. 2007), which allows identification of all plant families, most genera (>75%), and
one third of the species (Sønstebø et al. 2010). When applied to modern lake sediments, half of the
species present within 2 m of lakes were detected (Alsos et al. In prep.). Our recent study of an
8500 year old core from Svalbard show that the method detect all except two genera identified in a
macrofossil study from the same lake (Alsos et al. 2015). Overall, 1.2 times more taxa of vascular
plants were identified with ancient DNA than macrofossils, and the number of taxa identified per
sample was 2.7 times higher for the former. Thus, DNA analyses of Holocene lake sediment can
reveal the presence of rare taxa and thereby allow for a better estimation of species persistence (Fig.
1). Further, the method is now resource-efficient and repeatable, and it can be extended to any
group of organisms, given that a DNA reference library and adequate primers are developed . It also
allows for semi-quantitative interpretations based on the number of PCR repeats where taxa are
identified (Pansu et al. 2015). We will do minor optimization of these applications and analyse all
samples for vascular plants and key herbivores.
1
Arabis
alpinazones
seeds
Macrofossil
Saliceae
sedaDNA
Arabis
alpina
sedaDNA
Lithostratigraphic
units
1
4
2
M3
L5
M2
L4
L3
M1
L2
L1
4
25
2
Ranunculaceae
Dryas leaves
Taxon
richness sedaDNA20
0
15
sedaDNA
Age (cal. BP)
10
4
Salix reticulata
Taxon
richnessleaves
Dryas
sedaDNA
2000
3000 4000
5000
6000 7000 8000
5 1000
0
macrofossils
0
12
Sedimentary aDNA zones
4
40
D3
D2
D1
Salix
polaris
leavessedaDNA
Koeniga
islandica
LOI
(% dry weight)
8
Macrofossil
zones
M3
M2
M1
0
Arabis
alpina seeds
Lithostratigraphic
units 41
4
L5
L4
L3
L2
L1
2
Saliceae sedaDNA
25
Arabis alpina sedaDNA 0.2
20
XRF K richness
/ sum
Taxon
4
0.1
sedaDNA
2
Dryas leaves sedaDNA15
Ranunculaceae
10
0
60
Taxon
richness
5
Sand and
coarse silt
4
4
40
macrofossils
0
volume)leaves
Salix(%
reticulata
Dryas
sedaDNA
4
20
0
Koeniga islandica sedaDNA
12
40
Salix polaris leaves
100 150 200 250 300 350 400 450 500 550
1
LOI (%alpina
dry weight)
8 50
Arabis
seeds
0
2
Depth (cm below sediment surface)
Arabis alpina sedaDNA 44
Fig.
2. TaxasedaDNA
detected by macrofossil
(numbers of fragments) and ancient sedimentary DNA (number of PCR repeats where taxa were
Saliceae
0.2
4
discovered).
Koenigia
islandica
was
only
detected by sediment ancient DNA (sedaDNA), whereas Arabis alpina and Dryas
XRF
K
/
sum
Ranunculaceae sedaDNA
0.1 frequent in sedaDNA. Note that while macrofossil indicate scattered occurrence of species through
octopetala, were detected more
2
Dryasancient
leaves
time,
DNA shows more
60
4 clearly that they actually did persist (Alsos et al. 2015 ).
0
Salix
leaves
Sand reticulata
and coarse
silt
4
40
0the P6 loop do however limit the taxonomic information. In addition, as
The
short
fragments of
volume)
Dryas(%
sedaDNA
many sequence errors20
generally
are produced during PCR, it is necessary to use very stringent
40
Salix polaris leaves
12
filtering conditions reducing
the amount of usable data (Coissac et al. 2012). To overcome these
0 50
100 150 200 250 300 350 400 450 500 550
problems,
we
will
do
shotgun
sequencing of the DNA extracts from lake sediments and thus
LOI (% dry weight)
48
Depth (cm
sediment biases
surface)(Jónsson et al. 2013), the
avoiding
specific PCR.4 After being corrected
forbelow
deamination
Saliceae sedaDNA
resulting sequences will be mapped against the new taxonomic reference library composed of whole
0.2
2
plastid
and nuclear
ribosomal DNA (see details in Taberlet et al. 2012). A whole genome
XRF Kleaves
/ genomes
sum
Dryas
0.1
0
reference library is currently
being built using a shotgun approach for the alpine flora of the Alps
4
60
(PhyloAlps,
1500
species)
and
Norway (NorBOL, 2000 species http://www.norbol.org/). The new
Dryas
sedaDNA
Sand and
coarse silt
reference
libraries will40give low coverage for single copy nuclear genes but sufficient coverage for
(% volume)
12 are present in many copies per cell. The new genomic reference library
plastid and rDNA which
20
will
thus
include the
LOI (%
dryalso
weight)
8 classic barcoding markers (CBOL et al. 2009) and the P6 loop. Thus,
50 in 100
150attempt
200 of
250
300 analyses
350 400
450 500
550 samples so
while identification of 4taxa
the only
shotgun
of ancient
sediment
far was strongly limited by data available
in reference
librariessurface)
(Smith et al. 2015), our complete
Depth
(cm below sediment
0.2
reference
libraries may allow 100% resolution at species level for vascular plants and key
XRF K / sum
0.1 our new shotgun applications will also improve the quantitative
herbivores. In addition,
60
interpretation of past flora
and fauna as it avoids the PCR step.
Sand and coarse silt
(% volume)
40
References
20
Alsos I.G., Sjögren P., Edwards M.E., et al. (2015). Sedimentary ancient DNA from Lake Skartjørna, Svalbard: Assessing the
resilience of arctic flora50to Holocene
100 climate
150 change.
200 The
250Holocene.
300 10.1177/0959683615612563.
350 400 450 500 550
CBOL PWG, Hollingsworth PM, Forrest LL, et al. 2009. A DNA barcode for land plants. Proceedings of the National Academy of
Depth (cm below sediment surface)
Sciences 106: 12794-12797.
Coissac E, Riaz T, Puillandre N. 2012. Bioinformatic challenges for DNA metabarcoding of plants and animals. Molecular Ecology
21: 1834-1847.
Jonsson H, Ginolhac A, Schubert M et al. 2013. mapDamage2. 0: fast approximate Bayesian estimates of ancient DNA damage
parameters. Bioinformatics btt193.
Pansu J, Giguet-Covex C, Ficetola GF, et al. 2015. Reconstructing long-term human impacts on plant communities: an ecological
approach based on lake sediment DNA. Molecular Ecology 24: 1485-1498.
Smith O, Momber G, Bates R, et al. 2015. Sedimentary DNA from a submerged site reveals wheat in the British Isles 8000 years
ago. Science 347: 998-1001.
Sønstebø JH, Gielly L, Brysting AK, et al. 2010. Using next-generation sequencing for molecular reconstruction of past Arctic
vegetation and climate. Molecular Ecology Resources 10: 1009-1018.
Taberlet P, Coissac E, Pompanon F, et al. 2007. Power and limitations of the chloroplast trnL (UAA) intron for plant DNA
barcoding. Nucleic Acids Research 35: e14.
Willerslev E, Davison J, Moora M, et al. 2014. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506: 47-51.
Yoccoz NG, Bråthen KA, Gielly L, et al. 2012. DNA from soil mirrors plant taxonomic and growth form diversity. Molecular
Ecology 21: 3647-3655.
2