Association mapping in a collection of tobacco reference cultivars. Step One: Variability of smoke constituents

Transcription

1 SMOKE SCIENCE / PRODUCT TECHNOLOGY Jeju Island, South Korea 4-8 October 2015 Association mapping in a collection of tobacco reference cultivars. Step One: Variability of smoke constituents Emilie JULIO, Thomas VERRON, Xavier CAHOURS, François DORLHAC de BORNE and Stéphane COLARD

2 Context WHO Study Group on Tobacco Product Regulation (5th report, 2015) «Non-exhaustive priority list of tobacco and smoke constituents» The list of tobacco contents and emissions of cigarette smoke was drawn up on the basis of the following criteria: the presence of specific chemicals in cigarette smoke at levels that are toxic for smokers as determined by well-established scientific toxicity indices; variations in concentrations among cigarette brands that are substantially greater than the variation in repeated measurements of the toxicant in a single brand; the existence of technological routes to mitigate these yields Are there constituents that can be reduced by modifying the tobacco plant? 2

3 Are there constituents that can be reduced by modifying the tobacco plant? Many constituents in tobacco and tobacco smoke are influenced by the genetics of the tobacco plant, or might be affected by processes occurring in the plant during growing, senescence, curing, as well as blending and pyrolysis. Use of molecular markers to identify and follow genes involved could be used in traditional breeding in order to develop new plants that result in lower toxicants both in the tobacco and in cigarette smoke. Objective Identify the direct links between gene variability and chemical variability observed in tobacco and/or in tobacco smoke using genetic association methodology. 3

4 Methodology of association mapping SNP detection mrna sequencing Extraction of mrna from leaves, stems and roots Association mapping Statistical analysis GLM/MLM The germplasm group Population Structure 162 Tobacco varieties Structure + Kinship (SSR/SNP) 69 Dark air-cured 24 Burley 46 Flue-cured 16 Oriental 6 Experimental 1 «Ancestral» Tobacco analysis Cigarette making Hand made cigarettes Tobacco weight: 750 mg +- 5mg. Smoke analysis Aromatic amines (1-AMN, 2AMN 3-ABP, 4-ABP) BaP Volatiles (1-3 butadiene, isoprene, acrylonitrile, benzene, toluene) Carbonyles (Formaldehyde, acetaldehyde, acetone, acrolein, crotonaldehyde, butyraldehyde, propionaldehyde) Hydrogen cyanide Phenols 4

5 Strategy for tobacco: RNA-Seq Tobacco has a large genome compared to other species Genome size (Mb) Chromosome (n) Whole genome sequencing would be too expensive! Advantages of RNA-Seq: most repetitive regions are ignored: cost efficiency Simultaneous SNPs (Single Nucleotide Polymorphism) detection and expression profile analysis Also useful for candidate gene approach Pre-requisite Reference transcriptome available RNA preparation of multiple tissues at multiple time points 5

6 CORESTA 2015 Step One: Variability of smoke constituents The germplasm group 162 Tobacco varieties 1. Experimental design 2. Statistical approach 3. Preliminary results 4. Next steps 69 Dark air-cured 24 Burley 46 Flue-cured 16 Oriental 6 Experimental 1 «Ancestral» Tobacco analysis Cigarette making Hand made cigarettes Tobacco weight: 750 mg +- 5mg. 120 cig./sample Smoke analysis Aromatic amines (1-AMN, 2AMN 3-ABP, 4-ABP) BaP Volatiles (1-3 butadiene, isoprene, acrylonitrile, benzene, toluene) Carbonyles (Formaldehyde, acetaldehyde, acetone, acrolein, crotonaldehyde, butyraldehyde, propionaldehyde) Hydrogen cyanide Phenols 6

7 Experimental Design Flue-cured (46 varieties) 3 blocks 3 squares per block 3 bands per square 6 parcels per square A B C D E F To take into account environmental factors: 3 varieties are used as control 3 controls per square 3 replicates for the other varieties (1 per block) Block 1 Block 2 Block 3 7

8 Statistical approach Analysis of covariance to evaluate the varieties effect Analytical method variability Non significant Effect Significant Effect Remove confounding or interacting effect due to environmental factors (soil, weather ) Association Analysis Raw data (yield/cigarette) Aromatic amines BaP Volatiles Carbonyles Hydrogen cyanide Phenols Reduce the effects of certain gross influences (e.g. active burnt weight tobacco) TASSEL 5.0 8

9 Normalisation Eliminate the effects of certain gross influences Active burnt weight tobacco estimation* Burning model BaP (raw data) Normalization 4K CASH COKER 347 COKER 371 GOLD DELCREST Delgold DIXIE BRIGHT LEAF 101 ELKA 245 GOLDEN WILT GOLTA GOSPAYA HARRISSON SPECIAL HERCEGOVAC HICKS BROADLEAF ITB32 K 326 Kutsaga51 LECHIA A LECHIA LB 838 MAC NAIR 135 NC 2326 NC 95 NYIRSEGI 1 OXFORD 1 OXFORD 26 /56 POLALTA STOLAC 17 VAMOR 48 VESTA 30 VIRGINIA 115 VIRGINIA 21 VIRGINIA SP278 VIRGINIE 400 FLUE CURED (56) VIRGINIE GOLD A VIRGINIE PLOVDIV VZ WARNE = VIRGINIE OLD BELT WARTA WIKA WISLICA YELLOW ORONOCO = VIRGINIE NEW BELT YELLOW PRIOR YELLOW SPECIAL 390 ZAMOJSKA 4 ZAMOYSKA 4K CASH COKER 347 COKER 371 GOLD DELCREST Delgold DIXIE BRIGHT LEAF 101 ELKA 245 GOLDEN WILT GOLTA GOSPAYA HARRISSON SPECIAL HERCEGOVAC HICKS BROADLEAF ITB32 K 326 Kutsaga51 LECHIA A LECHIA LB 838 MAC NAIR 135 NC 2326 NC 95 NYIRSEGI 1 OXFORD 1 OXFORD 26 /56 POLALTA STOLAC 17 VAMOR 48 VESTA 30 VIRGINIA 115 VIRGINIA 21 VIRGINIA SP278 VIRGINIE 400 FLUE CURED (56) VIRGINIE GOLD A VIRGINIE PLOVDIV VZ WARNE = VIRGINIE OLD BELT WARTA WIKA WISLICA YELLOW ORONOCO = VIRGINIE NEW BELT YELLOW PRIOR YELLOW SPECIAL 390 ZAMOJSKA 4 ZAMOYSKA S. param. SR param. Cig. param. *S. Colard Prediction Model for Cigarette Yields Derived from Data Obtained under Two Different Machine Smoking Regimes. Beitrage zur Tabakforschung International/Contributions to Tobacco Research. issue No. 7 of Vol. 26. BaP (Normalized) = BaP / actburntw 9

10 Covariate Estimation Remove confounding effect due to environmental factors Experimental Design Measurements Covariate Controls: = 4K78-5 = ITB32 = ZAMOYSKA Base line effect: Differences observed are considered to be the consequence of environmental factors (soil, sun ) 10

11 Variety effect: ANCOVA Evaluate the varieties effect while statistically controlling for the covariable effect Effect of variety i Covariate: Impact of environment conditions on the controls in the square j Yij = µ + µi + α Xj + εij Yields of the variety i in the square j Mean effect Residuals: uncontrolled variability DoF Sum of sq. Mean Sq. F value P-value Covariable Variety Residuals

12 Preliminary results 21 flue-cured varieties FLORIDA17 CRIOLLOCOR TUAYEPOCA PETICO G1 PARAGUAYCL AMARELLOM2 RUSSIANB SANTACRUZ GAT4 MADOLE CORDOBA TI657 MACNAIR135 MACOUBA TI448A AMBALEMASR PERALTERO MAZINGA BUS63 START ZERLINA SKRO70 BURSAN VUELTAAB BOHEMEAND JAUNEDEBEL NIJKERK BURLEYDL BURLEYDC SEMOY DRAGONVERT 21 varieties, 3 repeats + control = 81 samples of cigarettes 100 SKROCL56 NUCATORCIDA OXFORD2656 PULAWSKY66 TRUMPF WODECQ LITTLECRI PHILIPPIN PAESANA GALPAO PARAGUAYPE COULO MANILLA BRASILD ZIMMERSP COMSTOCKSP WARTA VIRGPLOV ELKA245 DIXIEBL101 WESTERNDM BLACKMAM KENTUCKYG KENTUCKYPU KENTUCKYFLO KENTUCKYPA OXFORD1 ROBUSTA 4K785 VAMOR48VESTA30 GOSPAYA LECHIAA LECHIALB WISLICA WIKA POLALTA BARAGAN102 VIRGSP278 VZ3719 NYIRSEGI1 ZAMOJSKA4 ZAMOYSKA SHIROENSHU BB16 KENTUCKY14 BANKETA1 BURLEY21 TN86 TN90 BB16A BURLEY64 HARROWVEL BURLEYAM WHITEBUR JUDYSPRID STOLA7 MARYLANDBL ARAPIRA BRESILMATTA BRESILBAHIA BAHIA BEINHART PERIQUE SANTAFE RIVET CHEBLI CABOT BANAT125 BASMAD2 XANTHI TOMBACK SAMSOUN BULGARE2 KABAKOULAK DAMAS ROUM BATROUM1 UCHATYKUC HERCEGOVAC HERCEGOVINE IZMIR PORTORICO MULTAN NOVACRNJA BRASILAND UNGARISCH TI567 SUMATRA SIMMABA KUOFAN KOKUBU CABAIGUAN PARTIDOS CRIOLLOESP COROJO CRIOLLO HAVANACUQ FLORIDA301 BIGCUBA CASH YELLOWPR VIRG400 YELLOWSP VIRG21 HARRISSONSP VIRGGOLDA 728 ITB32 WALKERSBL WARNEYELLOWMAM YELLOWOR BURLEY49 WHITESO GOLDENWILT COKER347 ORONOCORH HICKSBL N326 GOLTA NC95 VIRG115 DELGOLD DELCREST MACHUPIC KUTSAGA51 K326 COKER371G Analyses Aromatic amines 1-aminonaphtalene (1-AMN), 2-aminonaphtalene (2-AMN), 3-aminobiphenyl (3-ABP), 4-aminobipheny (4-ABP) Carbonyles Formaldehyde, acetaldehyde, acetone, acrolein, crotonaldehyde, butyraldehyde, propionaldehyde,) Benzo[a]Pyrene (BaP) Volatiles 1-3 butadiene, isoprene, acrylonitrile, benzene, toluene Hydrogen cyanide Phenols Hydroquinone, resorcinol, catechol, phenol, gaiacol, m/p/o cresol TNCO 6000 cigarettes 12

13 Normalisation Raw data Normalized data TPM CO TAR O.cresol p.cresol TPM CO TAR O.cresol p.cresol WATER m.cresol WATER m.cresol NICO Gayacol NICO Gayacol BaP Phenol BaP Phenol Formaldehyde Cathecol Formaldehyde Cathecol Acetaldehyde Resorcinol Acetaldehyde Resorcinol Acetone Hydroquinone Acetone Hydroquinone Acrolein HCN.TPM Acrolein HCN.TPM Crotonaldehyde HCN.GP Crotonaldehyde HCN.GP MethylEthylKeton Toluene MethylEthylKeton Toluene Butyraldehyde Benzene Butyraldehyde Benzene X1AMN X2AMN X3ABP Isoprene X4ABP Butadiene Acrylonitrile X1AMN X2AMN X3ABP Isoprene X4ABP Butadiene Acrylonitrile Normalisation allows accurate comparison based on mg of tobacco burnt 13

14 V8 V19 V18 V1 V9 V4 V5 V15 V12 V16 V21 V3 V2 V17 V13 V7 V10 V14 V6 V11 V20 Method variability Variability of smoke constituents 7 Resorcinol P value = = no variability between varieties 14

15 Variability of smoke constituents Benzene V11 V17 V1 V8 V14 V5 V6 V18 V13 V10 V4 V12 V9 V16 V3 V2 V21 V19 V7 V20 V15 Method variability = low variability between varieties 15

16 V20 V10 V14 V6 V5 V12 V16 V7 V13 V17 V1 V4 V11 V15 V3 V19 V8 V18 V9 V21 V2 Method variability Variability of smoke constituents 1-aminonaphthalene = Medium variability between varieties 16

17 Variability of smoke constituents Acetaldehyde V3 V17 V12 V20 V13 V14 V16 V10 V7 V6 V5 V4 V11 V15 V8 V9 V18 V1 V19 V2 V21 Method variability = High variability between varieties 17

18 Variability of smoke constituents 1AMN CO 1,3-Butadiene 2 AMN Isoprene HCN Toluene 3ABP Benzene 4ABP Acrolein o, m, p.cresol Crotonaldehyde Cathecol Phenol BaP Acetone Resorcinol Hydroquinone O.cresol Gayacol Formaldehyde Butyraldehyde Acetaldehyde Acrylonitrile MethylEthylKeton 18

19 Negative correlation V2 V8 V9 V18 V21 V19 V3 V15 V5 V4 V1 V12 V13 V17 V11 V16 V7 V20 V10 V6 V14 Formaldehyde 1-aminonaphtalene In some cases lowering the yield of one smoke constituent may result in increasing the yield of another. 19

20 Conclusion 1. Normalisation using active burnt weight tobacco allows an accurate comparison between tobacco varieties 2. To avoid misleading conclusion: Confounding effect due to environmental factors (soil, weather ) is corrected using tobacco controls in the fields Variability of analytical methods has to be added in the comparison 20

21 Conclusion 3. From the preliminary results Wide variability range for certain smoke constituents (e.g. Formaldehyde, acetaldehyde, etc.) = molecular markers can be expected Low variability range for some constituents (e.g. 1,3-butadiene, catechol, etc.) = This has to be confirmed with other varieties Negative correlations exist = It is very difficult to predict the ultimate impact that reducing, or selectively eliminating, a specific smoke constituent may have. 21

22 Perspectives Smoke analyses for the 140 additional varieties are in progress RNA-seq completed At least 6,000 SNPs have been detected into the transcriptome Association mapping will be presented soon 22

23 Association mapping in a collection of tobacco reference cultivars. Step One: Variability of smoke constituents Emilie JULIO, Thomas VERRON, Xavier CAHOURS, François DORLHAC de BORNE, and Stéphane COLARD