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Hilke Schröder, Celine Blanc-Jolivet, Bernd Degen Thuenen-Institute of Forest Genetics 08.06.2017 Application of DNA fingerprints to control tree species and geographic origin of timber
Hilke Schröder, Celine Blanc-Jolivet, Bernd Degen
Thuenen-Institute of Forest Genetics
08.06.2017
Application of DNA fingerprints to control tree species and geographic origin of timber
Content
08.06.2017 page 2
1. Introduction • Control on different scales • Marker development
2. Control of species identity / geographic origin
• species from Europe + Asia • species from (South) America • species from Africa
3. Reference database
4. Thünen Centre of Competence – Forest Genetics
5. Outlook
1. Introduction: control on different scales
08.06.2017 page 3
Control of species identity and origin on different scales:
• Is the timber from the declared species?
• Control of species identity
• Is the timber from the declared country / region or forest concession?
• Control of geographic origin
• Is the timber from the declared individual tree(s)?
• Tree by tree approach to check the chain of custody
• DNA analysis starts when wood anatomists can go no further species and origin
1. Introduction: Marker development
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A) Choice of Next Generation Sequencing (NGS) method
B) Mapping / de novo assembly
C) search for SNPs:
Differences among species = species identity
Differences within species = identification of origin
D) Screening with many SNPs:
Up to 400 for species identity
≈ 1000 for identification of origin
A)
B)
C)
D)
1. Introduction: Marker development
08.06.2017 page 5
E) Choice of best SNPs (quality check)
F) genotyping of reference material (many individuals)
G) Development and optimization of markersets
Locus % Data(0-100) Mean F(-1-+1) Mean Div (1-NA) Mean Dif(0-1) Cor Dis (-1-+1) Rank
RAD_1161_352 100 0.044 1.467 0.303 0.014 1
RAD_3719_232 91.67 -0.186 1.548 0.277 0.097 2
RAD_5156_367 97.92 0.064 1.459 0.276 -0.089 3
RAD_5716_436 100 0.114 1.521 0.272 0.009 4
RAD_1001_403 93.75 -0.062 1.569 0.261 -0.061 5
RAD_4119_391 100 0.176 1.569 0.253 -0.061 6
RAD_7731_292 91.67 0.627 1.237 0.253 -0.022 7
RAD_6458_424 97.92 0.064 1.459 0.25 0.064 8
RAD_6345_507 95.83 0.497 1.612 0.244 -0.128 9
RAD_1744_292 100 -0.121 1.458 0.244 -0.106 10
RAD_7333_220 97.92 1 1.2 0.244 -0.162 11
RAD_8042_239 91.67 -0.156 1.519 0.24 0.065 12
RAD_6988_218 100 -0.227 1.618 0.236 -0.047 13
RAD_6731_338 97.92 0.076 1.647 0.233 0.037 14
RAD_5688_62 100 -0.129 1.634 0.233 -0.035 15
RAD_3846_320 100 -0.186 1.611 0.233 0.048 16
RAD_5331_464 93.75 0.423 1.447 0.233 0.054 17
RAD_4626_467 95.83 -0.082 1.611 0.226 0.098 18
RAD_6513_111 97.92 -0.281 1.672 0.219 -0.124 19
RAD_3028_421 100 -0.25 1.383 0.217 0.083 20
RAD_6287_193 100 -0.221 1.682 0.214 -0.007 21
RAD_159_295 100 -0.045 1.671 0.214 0.012 22
RAD_3102_420 100 0.142 1.497 0.211 -0.143 23
RAD_2092_263 97.92 -0.224 1.471 0.211 -0.092 24
RAD_1792_305 93.75 -0.431 1.47 0.211 -0.162 25
RAD_3995_238 93.75 -0.233 1.509 0.206 -0.173 26
RAD_6984_183 97.92 0.05 1.37 0.202 0.169 27
RAD_1803_395 100 -0.224 1.471 0.2 -0.107 28
RAD_869_363 100 0.519 1.337 0.2 0.016 29
RAD_2074_348 91.67 0.319 1.346 0.196 -0.201 30
E)
F) G)
1. Introduction: Marker development
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Strategy for marker development for control of species identity and origin:
• Always start with a high number of SNPs (markers)
• Selection of the most effective SNPs (markers)
• Further selection of „golden markers“ (100% differentiation) or „silver markers“ (high statistical probability for differentation)
• Development of small markersets for low-cost and easy application
• Thus, application possible in most laboratories
• Support of genetic reference labs in Kumasi (Ghana) and Iquitos (Peru) (training workshops)
2. Control of species identity / origin: Europe + Asia
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Oaks: Identification of species • Gene markersets to distinguish continental origin (species) of white oaks
Asia
America
Europe
Set of six “golden markers” from the chloroplast genome
Set of 179 SNPs from the whole genome
2. Control of species identity / origin: Europe + Asia
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Mongolian oak: Identification of geographic origin in Asia • (another markerset for Europe with even higher solution)
• HT1: West distributed • HT2: widely distributed, East • HT3: Kind of West-East gradient • HT4: rare, mainly Central • HT5: „private“, in 1 Pop. only • HT6: „private“, in 1 Pop. Only
• twelve of the Chinese populations
are from Zheng et al. (2011)
2. Control of species identity / origin: Europe + Asia
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Example: Genetic control of continental and geographic origin of oaks • Test of whisky barrels because origin is essential for the flavour
2. Control of species identity / origin: Europe + Asia
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Larch: Identification of species and geographic origin
• Overall 253 SNPs included
• Differentiation of five species and eight haplotypes is possible using a set of 13 of these SNPs
• Larch is often used for wood flooring (indoor and outdoor)
2. Control of species identity / origin: (South) America
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Mahogany: Control of species and geographic origin • (only 1 SNP and 1 InDel), additional markerset of 14 SNPs within South America
100
400
300
200
500
bp
Echtes Mahagoni
(Swietenia macrophylla)
Westindisches Mahagoni
(Swietenia mahagoni)
Swietenia macrophylla Swietenia mahagoni
Differentiation between Swietenia macrophylla and S. mahagoni
Geographic origin within Swietenia macrophylla
2. Control of species identity / origin: (South) America
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Jatoba (Hymenaea courbaril): Genetic control of geographic origin • cooperation Large-Scale project and doctoral thesis Camila Chaves (University
Londrina, Brazil)
• Using 33 SNPs + 1 Indel • Identification of 14
haplotypes • Some are only present in
one population (HT 2, 9, 14)
• No „golden markers“ (100% differentiation)
• But, overall differentiation between populations possible using probability statistics
2. Control of species identity / origin: Africa
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Khaya spp.: Differentiation of species • cooperation Large-Scale project + doctoral thesis of Gael Bouka-Dipelet
(Congo) + Khaya project at Bioversity International (Marius Ekue)
• Sampling of six Khaya species in > 20 African countries
• Selection of 480 SNPs based on sequencing (NGS) of four species
• Final set of 101 markers used for screening of 1900 individuals (five species from 18 countries)
2. Control of species identity / origin: Africa
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Khaya spp.: Differentiation of species • Statistical approach for self assignment to the different species
• Within the 101 selected SNPs are 15 „golden markers“
• Assignment to species is equal / better when using only these golden markers except for one species
2. Control of species identity / origin: Africa
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Khaya anthotheca: Identification of geographic origin • Statistical approach (Structure analysis)
• 101 selected SNPs • Identification of seven
clusters within K. anthotheca
• Assignment to some countries with ≈ 95% probability (Cameroon, Congo_Brazzaville, DRC, Ghana)
2. Control of species identity / origin: Africa
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Entandrophragma spp.: Differentiation of species • 14 chloroplast markers for species verification of reference samples
• Species differentiation is difficult in the field! • With genetic approach species-specific markers for four species found
2. Control of species identity / origin: Africa
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Entandrophragma utile: Identification of geographic origin • First statistical approach, (comparable results for Sapeli, E. cylindricum)
• 446 SNPs used • Identification of
five clusters within E. utile
• Heterogen within DRC and Congo
2. Control of species identity / origin: Africa
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Iroko (Milicia spp.): Identification of species and geographic origin • From Kasso Daïnou & Olivier J. Hardy
• 67 SNPs used • ≈ 1800 individuals • Identification of
five genepools • Differentiation of
the two species M. regia and M. excelsa
• Four clusters within M. excelsa
3. Reference database
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Species within the project „Large scale“
3. Reference database
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Development of databases • Nearly 30,000 entries because of worldwide cooperations
4. Thünen Centre of Competence: Forest Genetics
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Analysed wood samples at the genetic lab • 2013 160 wood samples • 2014 436 wood samples • 2015 400 wood samples • 2016 245 wood samples
• Mostly: oak, larch, mahogany • Some: Khaya, Merbau, Sapeli
• In 10-20 % of the cases doubts on the correctness of the claim
4. Thünen Centre of Competence: Forest Genetics
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5. Outlook
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Up-scaling • DNA barcodes of 10 to 30 new trees
species per year • Genetic reference maps of 2 to 4
additional species per year • Increase resolution and precision of
existing reference data by adding more gene markers and more samples
• Increase capacities and success rate for DNA extraction of wood samples, especially highly processed timber
• Intelligent combinations of all available methods
Example: Merbau
More gene markers = higher spatial resolution
5. Outlook
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Cooperations, projects and networks • Continuation and improvement of:
• Generating reference data • Setting standards and ring tests • Databases and sample repositories • Communication and training
Thank you for your attention !
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NGS machines (www.slideshare.net)
