Download talk Breman 2013 cichlid fish bol5 cover

DNA barcoding LT cichlids of the
rocky shores
Breman FC1, Van Steenberge M2,
Jordaens K1 & Snoeks J2
1 Royal Museum for Central Africa
2 Royal Museum for Central Africa and Catholic University of Leuven
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DNA barcoding of LT cichlids of the
rocky shores
Introduction to the topic
Methods
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Collection
Specimens
Methods
• Specimens
• Data and library setup
• Sequence based
• Species based
Analysis
• Sequence based identification
• Species based identification
Results
Tropheus duboisi
• Sequence based
• Species based
• Species complexes
• Example of a complex and a newly described species
Testing OTU´s
Discussion
Questions?
Introduction
• Fish DNA barcoding successful so far
• Most species can be identified
• Different methods can be used
Introduction
• Habitat
– rocky shores of Lake
Tanganyika
– Alkaline environment
(average pH 8,4)
– Highly diverse habitats
– Highly specialized
• Breeding strategies
– Mouth brooders
– Shell brooders
– Substrate brooders
• Feeding strategies
– Predation
– Algae scraping
Introduction
• 200+ recognized species of cichlids
– Dozens remain to be described
– >95% endemic
• Model organisms for evolution and speciation
• Economic importance with aquarium
enthusiasts
• 75 non cichlid fishes are also present in LT
Lake Tanganyika
Collection sites
• 676 km from N-S and
average 50 km across
• Average depth 570m
(max 1470m)
• 4 countries
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Tanzania
Congo
Burundi
Zambia
Collection sites
• 15 sites
• 3 expeditions (1992,
1995, 2010)
• 1000s of specimens
Lobochilotus
labiatus
Lepdiolamprologus
elongatus
Tropheus
brichardi
Gnatohochromis
pfefferi
Methods
Specimens
• Covering 11 tribii and 37 genera
• Library A) 78 (98 with singletons) OTUs
• Library B) 70 (91 with singletons) OTUs
• Library C) 52 (66 with singletons) OTUs (11
complexes)
Methods
Data setup
• Three groups
– A) all taxonomic, behavioural and distributional
knowledge (published and unpublished) were
used to assign a name to a specimen
– B) only currently recognized species used for
assigning a name to a specimen
– C) groups with known difficulties in evolutionary
history (hybridization, incomplete lineage sorting)
and taxonomy are grouped in species clusters
Methods
Sequence based
– BM/BCM method
– Software compares each sequence to all the
others and the chosen threshold for the dataset
– Returns a statement on the sequence/specimen
with regard to threshold and presence of
same/related species
– Returns a success percentage in terms of
sequences
– Influenced by dataset properties
Methods
Species based
– Uses the sequences assigned in the sequence
based method, but now classified according to
threshold per species
– Species identifiable or not
– Returns success percentage in terms of species
Analysis
Species based BM/BCM
• Categories
– True Negative (TN) Best match above threshold
and allospecific
– True Positive (TP) Best match is same species
below threshold
– False Positive (FP) Closest match is below
threshold but is an allospecific
– False Negative (FN) Intraspecific distances are
above threshold and conspecific
FP
Threshold
FN
• Fixed or based on dataset, in our case
threshold was determined via an R script
• Obtained via two curves of intra and inter
specific distances
• The optimum is then chosen as threshold
Analysis
Species based using a NJ tree
• Using a NJ tree
• Counting species in
distinct clusters
Results
Sequence based
(A)morphospecies
1.91%
398
(B)accepted names
2.37%
398
(C) species complexes
2.20%
398
Correct id's according to "Best Match":
Ambiguous according to "Best Match":
Incorrect id's according to "Best Match":
276 (69.34%)
80 (20.1%)
42 (10.55%)
320 (80.4%)
36 (9.04%)
42 (10.55%)
352 (88.44%)
21 (5.27%)
25 (6.28%)
Correct id's according to "Best Close Match":
Ambiguous according to "Best Close Match":
274 (68.84%)
80 (20.1%)
318 (79.89%)
36 (9.04%)
349 (87.68%)
21 (5.27%)
31 (7.78%)
34 (8.54%)
17 (4.27%)
13 (3.26%)
10 (2.51%)
11 (2.76%)
optimal threshold
Sequences:
Incorrect id's according to "Best Close Match":
Sequences without any match closer than
threshold
Results
Species based
Library
A
B
C
# species
78
70
52
TP
55
46
40
A
B
C
Relative ID error
0.20
0.31
0.07
FP
14
21
3
Precision
0.80
0.69
0.93
TN
5
2
6
FN
4
1
3
Overall ID error
0.23
0.31
0.12
-Marginal improvement when species complexes in success %,
-but an increase in accuracy and precision
percentage ID
success
0.71
0.59
0.51
Accuracy
0.77
0.69
0.88
% success NJ
0.74
0.74
0.81
Results
Species complexes
Results
Species complex and new species
• Examples of species complexes with unresolved clusters
• Eretmodus cyanostictus specimens have recently been
described as Eretmodus marksmithi
Results
• Identification of putative new species with
DNA barcodes
intrasp. dist. < intersp
putative species based on
# sequences dist. to nearest other dist. to nearest
expert opinion
in dataset
species (y/n)
other species
Chalinochromis spbifrenatus
1
NA
2.33
Ectodus cfdescampsi
3
y
1.7
Neolamprologus cfpetricola
1
NA
0.61
Neolamprologus speseki
3
y
1.07
Petrochromis cfmacrognathus
2
y
0.15
Petrochromis
spephippiumsouth
2
y
1.39
Petrochromis
sppolyodonelongate
3
y
0.76
Petrochromis sppolyodonhigh
2
n
0.15
Tropheus cfannectens
8
y
1.54
Tropheus ikola
3
n
0
Tropheus mpimbwe
51
n
0
average generic
distance +/- se
1.84 +/- 0.42
1.45 +/- 0.33
5.70 +/- 0.55
5.70 +/- 0.55
2.45 +/- 0.36
putative species y/n
(difference > generic
average +/- se)
y
n
n
n
n
2.45 +/- 0.36
n
2.45 +/- 0.36
2.45 +/- 0.36
1.55 +/- 0.26
1.55 +/- 0.26
1.55 +/- 0.26
n
n
n
n
n
Discussion
• LT cichlids well studied
– Genetically and morphologically
• They are examples of ongoing speciation
– mtDNA evolution is slower than morphological
evolution
• Hybridisation is common
Discussion
• Incomplete taxonomy
• Unbalanced dataset, influence of sequence
composition
• Success percentages not high compared to other
fish groups, however still ok for a complex group
such as this.
• Distance method not very useful for detecting
potential new species
• Single sequences cannot be evaluated with either
method
Thank you for your
attention
感谢您的关注
Questions?
Foto credits: Royal Museum for Central Africa
Maarten Van Steenberge
Dimitri Geelhand de Merxem