Characterization of Novel Rice Characterization of Novel Rice Germplasm from West Africa Germplasm from West Africa

and Genetic Marker and Genetic Marker Associations with Rice Associations with Rice

Cooking QualityCooking Quality

Dr. Karim Traore IER, MaliDr. Karim Traore IER, MaliDr. Anna McClung USDA Beaumont, TXDr. Anna McClung USDA Beaumont, TX

Dr. Robert Fjellstrom USDA Beaumont, TXDr. Robert Fjellstrom USDA Beaumont, TX

Consumers Around the World Have Different Consumers Around the World Have Different Preferences in Rice Cooking QualityPreferences in Rice Cooking Quality

The Japanese people prefer soft and sticky rice with The Japanese people prefer soft and sticky rice with short grain (japonica types)short grain (japonica types)

In the USA, medium and long grain rice varieties are In the USA, medium and long grain rice varieties are preferredpreferred

In South America and the Middle East, people prefer firm In South America and the Middle East, people prefer firm and non-sticky riceand non-sticky rice

Thai people prefer long grain soft and nonstickyThai people prefer long grain soft and nonsticky

In India, Pakistan, fragrant or scented rice is preferredIn India, Pakistan, fragrant or scented rice is preferred

In Brazil, people prefer long, slender, and translucent In Brazil, people prefer long, slender, and translucent graingrain

Consumer Preferences in West Consumer Preferences in West AfricaAfrica

In West Africa consumers prefer:In West Africa consumers prefer: long, slender, intermediate amylose long, slender, intermediate amylose AromaAroma Sticky rice to make rice porridge Sticky rice to make rice porridge Parboiled riceParboiled rice BrokensBrokens Farmers like rice that is slow to Farmers like rice that is slow to

digest giving longer satisfactiondigest giving longer satisfaction

Experiments ConductedExperiments Conducted

11. Conduct genotypic and phenotypic evaluation of . Conduct genotypic and phenotypic evaluation of West African germplasm for agronomic and West African germplasm for agronomic and quality traits to identify characteristics that can quality traits to identify characteristics that can benefit WA and USA rice breeding programs.benefit WA and USA rice breeding programs.

22. Determine genetic marker associations with key . Determine genetic marker associations with key cooking quality traits that can be used in rice cooking quality traits that can be used in rice cultivar improvement programs.cultivar improvement programs.

Data collected for the Quality testsData collected for the Quality tests

Alkali Spreading Value (ASV)Alkali Spreading Value (ASV)- - qualitative indicator of starch gelatinization temperaturequalitative indicator of starch gelatinization temperature, dispersion , dispersion of milled grain in 1.5% KOH solutionof milled grain in 1.5% KOH solution

Apparent Amylose Content (AA), Soluble Amylose (SA)Apparent Amylose Content (AA), Soluble Amylose (SA)- - indicator of cooked rice textureindicator of cooked rice texture, using , using wet chemistry auto analyzerwet chemistry auto analyzer

Rapid Visco Analyzer (RVA)Rapid Visco Analyzer (RVA)- - determines the viscosity of rice flour pasting subjected to cycles of determines the viscosity of rice flour pasting subjected to cycles of heating and cooling heating and cooling

Differential Scanning Calorimetry DSCDifferential Scanning Calorimetry DSC- - quantitativequantitative indicator of starch gelatinization temperatureindicator of starch gelatinization temperature, , using DSC 6 analyzer determines the temperature and heat of gelatinizationusing DSC 6 analyzer determines the temperature and heat of gelatinization

Cooking TimeCooking Time- - time required for 10 milled rice grains to be completely gelatinizedtime required for 10 milled rice grains to be completely gelatinized

Total and Whole Milling YieldTotal and Whole Milling Yield – – indicator of crop value,indicator of crop value, using McGill#2 Mill for 1 min. using McGill#2 Mill for 1 min.

Grain dimensions- Grain dimensions- indicator of crop value, indicator of crop value, using WinSEEDLEusing WinSEEDLE

Crude Protein Content-Crude Protein Content- indicator of nutritional value, indicator of nutritional value, using nitrogen gas analyzer LECO 528using nitrogen gas analyzer LECO 528

Aroma (2-Acetyl-1-pyrroline)-Aroma (2-Acetyl-1-pyrroline)-indicator of market value, indicator of market value, using gas chromatographyusing gas chromatography

Heading from the Agronomic Heading from the Agronomic Evaluation Field of WA GermplasmEvaluation Field of WA Germplasm

0

20

40

60

80

100

120

IMP INT LOC USA

Heading (days)

102

74

103

76

Same color =No differences

IMP = Improved Africa(6)Land = Landrace(13)INT = Interspecific (7)USA = checks (8)

020406080

100120140160180

IMP INT Land USA

Height (cm)

122 119

162

105

Same color =No differences

IMP = Improved Africa(6)Land = Landrace(13)INT = Interspecific (7)USA = checks (8)

Plant Height from the Agronomic Plant Height from the Agronomic Evaluation Field of WA GermplasmEvaluation Field of WA Germplasm

Plots: 6 rows of 4.57 m length; spacing Plots: 6 rows of 4.57 m length; spacing 17.78 cm between rows17.78 cm between rowsRCBD, 4 rep.RCBD, 4 rep.

0

1000

2000

3000

4000

5000

6000

7000

IMP INT Land USA

Yield (kg/ha)

43424579

2586

6200

Same color =No differences

IMP = Improved Africa(6)Land = Landrace(13)INT = Interspecific (7)USA = checks (8)

Grain Yield from the Agronomic Evaluation Grain Yield from the Agronomic Evaluation of WA Germplasmof WA Germplasm

0

.5

1

1.5

2

2.5

3

IMP INT Land USA

100 seeds (g)

2.59 2.78

2.372.51

Same color =No difference

IMP = Improved Africa(6)Land = Landrace(13)INT = Interspecific (7)USA = checks (8)

Grain weight from the Agronomic Evaluation Grain weight from the Agronomic Evaluation Field of WA GermplasmField of WA Germplasm

US variety CCDR and African US variety CCDR and African improved WAB 56-104improved WAB 56-104

CCDR7004 kg/ha74 days99.25 cm

WAB 56-1044540 kg/ha69 days127 cm

African Landrace Gninni Zeba and African Landrace Gninni Zeba and interspecific NERICA 5interspecific NERICA 5

Gninni Zeba3063 kg/ha105 days162 cm

NERICA 56229 kg/ha69 days109 cm

Total and Whole Milling Yield of Total and Whole Milling Yield of Varieties Grown in the USAVarieties Grown in the USA

% Total Mill-Top 10% Total Mill-Top 10Gnanle Gnan-Man (78)Gnanle Gnan-Man (78)Baldo (77)Baldo (77)Bengal (76.6)Bengal (76.6)Nerica 2 (76.5)Nerica 2 (76.5)Mahafin (76.4)Mahafin (76.4)Nerica 5 (76.2)Nerica 5 (76.2)ZHE733(BMT) (76)ZHE733(BMT) (76)Nerica 1 (76)Nerica 1 (76)Mokossi (76)Mokossi (76)Nerica 3 (76)Nerica 3 (76)

% Whole Mill-Top 10% Whole Mill-Top 10Bengal (70)Bengal (70)CPRS (68)CPRS (68)Saber (68)Saber (68)Nerica 3 (67.7)Nerica 3 (67.7)Saber (BMT) (67.5)Saber (BMT) (67.5)Cheniere (66.7)Cheniere (66.7)Nerica 4 (66.5)Nerica 4 (66.5)WAB 638-1 (66.1)WAB 638-1 (66.1)Bakue Danane (66.05)Bakue Danane (66.05)CCDR (65)CCDR (65)

Plots: 3 rows of 4.57 m length; spacing 17.78 cm Plots: 3 rows of 4.57 m length; spacing 17.78 cm between rowsbetween rowsRCBD, 4 RepRCBD, 4 Rep

Grain Characteristics like Grain Width and Grain Characteristics like Grain Width and Total Mill can affect Cooking timeTotal Mill can affect Cooking time

CTCT GLGL GWGW GLWRGLWR TOTALTOTAL

GLGL NSNS

GWGW 0.54**0.54** -0.41**-0.41**

GLWRGLWR NSNS 0.76**0.76** -0.89**-0.89**

TOTALTOTAL 0.66**0.66** NSNS 0.41**0.41** NSNS

WHOLEWHOLE NSNS NSNS -0.34*-0.34* 0.34*0.34* NSNS

1% change in breakage can cause a $100,000 difference in profit for an average-sized rice mill (Hosney 1998)

Aroma Content 2-AP (ng/g) ofAroma Content 2-AP (ng/g) ofCultivars grown in the USACultivars grown in the USA

SierraSierra 1258.83 a1258.83 a

Bakue DananeBakue Danane 1140 ab1140 ab

CocoteCocote 1102 ab1102 ab

WAB 638-1WAB 638-1 1075.33 b1075.33 b

Jasmine 85Jasmine 85 494 c494 c

Nerica 1Nerica 1 444 c444 c

Protein Content (%) ofProtein Content (%) ofCultivars Grown in the USACultivars Grown in the USA

Observations5.5

6

6.5

7

7.5

8

8.5

9

9.5

prot

ein

Mean

+1 SD

-1 SD

Cheniere (9.1)Cheniere (9.1)Jaya (9)Jaya (9)Nerica 2 (9)Nerica 2 (9)ZHE733 (BMT)(9)ZHE733 (BMT)(9)ZHE733 (8.8)ZHE733 (8.8)IITA 123(a) (8.8)IITA 123(a) (8.8)Bengal (8.7)Bengal (8.7)BG 90-2 (b) (8.6)BG 90-2 (b) (8.6)IITA 123 (b) (8.5)IITA 123 (b) (8.5)

Amylose classes and Amylose classes and WaxyWaxy gene gene

Starch = amylose + amylopectin (60-80%) of edible weight of Starch = amylose + amylopectin (60-80%) of edible weight of cereal.cereal.

Starch comprises 90% of the total dry matter of milled rice (Bao et Starch comprises 90% of the total dry matter of milled rice (Bao et al. 2002). al. 2002). The cooking and eating quality of rice is mainly The cooking and eating quality of rice is mainly influenced by the properties of starchinfluenced by the properties of starch. .

Smith et al. (1997): GBSS= Smith et al. (1997): GBSS= wxwx protein is the product of waxy protein is the product of waxy gene, plays roles in the synthesis of amylose.gene, plays roles in the synthesis of amylose.

Starch branching enzyme, soluble starch synthase, and starch Starch branching enzyme, soluble starch synthase, and starch debranching enzyme plays major role in the synthesis of debranching enzyme plays major role in the synthesis of amylopectin.amylopectin.

No amylose (waxyNo amylose (waxy): very soft and extremely sticky (0%)): very soft and extremely sticky (0%) Low amyloseLow amylose: firm, separate, non sticky (10-19%): firm, separate, non sticky (10-19%) Intermediate:Intermediate: (20-24%) (20-24%) High amyloseHigh amylose: extra firm, low solid loss during processing, : extra firm, low solid loss during processing,

superior kernel stability (>24%)superior kernel stability (>24%)

AmyloseAmylopectin

Glucose molecule

Distribution of Distribution of WaxyWaxy Alleles in Alleles in WARDA Materials Grown in AfricaWARDA Materials Grown in Africa

02468

101214

103 105 114 116 118 122 124 HEWaxy allele

Co

un

t

DXBL

Soft Cooking

Conv. LG

PB/Canning

Distribution of the Distribution of the Waxy Waxy allele among allele among the interspecifics Grown in Africathe interspecifics Grown in Africa

21.1 21.7 22.2 22.6 23.5 23.6 24.7 25.3 26.1

0

5

10

15

20

25

30

WAB 5

6-10

4

NERICA 3

NERICA 7

NERICA 4

NERICA 6

NERICA 2

NERICA 5

NERICA 1

CG14

AA

%

Waxy 103-105Waxy 124

Marker Associations with Cooking Marker Associations with Cooking Quality TraitsQuality Traits

Cocodrie CCDRCocodrie CCDR: Cypress//L-202/Tebonnet at Louisiana in : Cypress//L-202/Tebonnet at Louisiana in

1990. 1990.

Dixiebelle DXBLDixiebelle DXBL: RU8303181/CB801 at Beaumont in 1983: RU8303181/CB801 at Beaumont in 1983

Brown rice was used for DNA extraction using QiagenBrown rice was used for DNA extraction using Qiagen

Kit. Kit. PCR was used for amplification followed by evaluation for PCR was used for amplification followed by evaluation for

polymorphisms using ABI sequencerpolymorphisms using ABI sequencer

Diagrammatic Representation of the Waxy Gene

Exon 6: A C transversion and substitution changes a Tyrosine to SerineDifferences in DNA sequence of Rexmont, JODON, and Toro-2 from lemont-intermediate-High/lowLarkin and Park. 2003

CT repeats associated with apparent amylose content(CT)10 & (CT)11= high(CT)14 & (CT) 20= int(CT)17 & (ct)18= low

Ayres et al. (1997)Bergman et al. (2001)

Exon 1G T substitution is associated with low amylose varieties.-interm. /high-low amyloseAyres et al. (1997)

Exon 10: C T transition and substitution changes a Proline to Serine. Differences in DNA sequence of Rexmont from Jodon, Toro-2 and Lemont.-high amyl.strong RVA-othersLarkin and Park (2003)

G/TTATAC------ (CT)n--

Rexmont= high amylose strong RVALemont= intermediate amyloseJodon, L202= high amylose, weak RVAToro-2= low amylose Adapted from Chen (2004)

CCDR et DXBL ont la même teneur en CCDR et DXBL ont la même teneur en Amylose (~26%) mais DiffAmylose (~26%) mais Diffèèrent en RVArent en RVA

0

100

200

300

400

45

60

75

90

105

00 3 6 9 12 1515Time minutes

Temp oC

CCDR

DXBLTemperature profile

RVU

Peak

Hot

Cool

Bkdn=Peak- hotStbk= Cool-PeakCS= Cool- Hot

PCR Primers Used for Molecular PCR Primers Used for Molecular Marker AnalysisMarker Analysis

PrimersPrimers AnnealinAnnealing temp.g temp.

SequenceSequence Starch Starch metabolismetabolism genem gene

Map Map location location /Chromo. /Chromo. Loc.Loc.

WaxyWaxy 5555 5’-CTTTGTCTATCTCAAGACAC-5’-CTTTGTCTATCTCAAGACAC-3’3’

5’-TTGCAGATGTTCTTCCTGATG-5’-TTGCAGATGTTCTTCCTGATG-3’3’

GBSSGBSS 6-8.26-8.2

Exon 10Exon 10 6666 5’-GCGGCCATGACGTCTGG-3’5’-GCGGCCATGACGTCTGG-3’

5’-GGCGGCCATGACGTCTGA-3’5’-GGCGGCCATGACGTCTGA-3’GBSSGBSS 6-8.26-8.2

AB2628AB262855

5555 5’-CTAGCCATGCTCTCGTACC-3’5’-CTAGCCATGCTCTCGTACC-3’

5’-5’-CAACTTACTGTGACTGACTTGG-CAACTTACTGTGACTGACTTGG-3’3’

SSSISSSI 6-15.36-15.3

21 PCR markers were selected and screened for marker 21 PCR markers were selected and screened for marker association study. The markers were either:association study. The markers were either:-near starch metabolism (like SSS, SBE )-near starch metabolism (like SSS, SBE )-at a map position with significant effects on starch properties -at a map position with significant effects on starch properties (like amylose content, or RVA pasting properties(like amylose content, or RVA pasting properties

Waxy, exon10, and AB26285 showed association with the amylose and RVA properties.

Single Factor Analysis for the 3 Markers used for Single Factor Analysis for the 3 Markers used for Associations StudyAssociations Study

Source Source variationvariation

dfdf AAAA SASA IAIA PEAKPEAK HOTHOT COOLCOOL

WaxyWaxy 22 1.04*1.04* 78.00**78.00** 60.3360.33 116548.61**116548.61** 98433.24**98433.24** 26737.78**26737.78**

AdditiveAdditive 11 2.08*2.08* 155.75**155.75** 120.39120.39 232946.49**232946.49** 196828.50*196828.50***

52458.07**52458.07**

DominantDominant 11 NSNS NSNS NSNS 1124.02*1124.02* NSNS NSNS

R^2R^2 0.040.04 0.630.63 0.540.54 0.800.80 0.810.81 0.480.48

Exon 10Exon 10 22 1.18*1.18* 76.56**76.56** 58.02**58.02** 112729.13**112729.13** 95577.79**95577.79** 246835.08*246835.08***

AdditiveAdditive 11 2.35**2.35** 153.07**153.07** 115.99**115.99** 225123.11**225123.11** 190999.55*190999.55***

493627.87*493627.87***

DominantDominant 11 NSNS NSNS NSNS NSNS NSNS NSNS

R^2R^2 0.040.04 0.610.61 0.520.52 0.770.77 0.800.80 0.790.79

AB26285AB26285 22 NSNS 30.41**30.41** 24.52**24.52** 56690.88**56690.88** 46866.25**46866.25** 112115.44*112115.44***

AdditiveAdditive 11 NSNS 60.77**60.77** 48.92**48.92** 112538.50**112538.50** 93473.63**93473.63** 223082.71*223082.71***

DominantDominant 11 NSNS NSNS NSNS NSNS NSNS NSNS

R^2R^2 0.010.01 0.240.24 0.220.22 0.380.38 0.390.39 0.360.36

R^2= Total Phenotypic explanation (%)

Summary and ConclusionsSummary and Conclusions

Interspecifics were found interesting for reduced Interspecifics were found interesting for reduced water rice growing, more studies can elucidate water rice growing, more studies can elucidate these findingsthese findings

Nerica 2 had good agronomic and milling Nerica 2 had good agronomic and milling characteristicscharacteristics

Bakue Danane, Cocote, WAB 638-1 had strong Bakue Danane, Cocote, WAB 638-1 had strong aromaaroma

Jaya, Nerica 2, BG 90-2, IITA 123 had high level of Jaya, Nerica 2, BG 90-2, IITA 123 had high level of ProteinProtein

Summary and Conclusions (cont.)Summary and Conclusions (cont.)

Soluble Amylose (SA) explained more the Soluble Amylose (SA) explained more the difference in RVA profile than the Apparent difference in RVA profile than the Apparent Amylose (AA).Amylose (AA).

Different GBSS alleles may produce the same Different GBSS alleles may produce the same amount of total amylose but different proportions amount of total amylose but different proportions of soluble and insoluble amylose. of soluble and insoluble amylose.

The The Waxy Waxy microsatellite and waxy microsatellite and waxy exon 10 SNPexon 10 SNP markers are now useful molecular markers for markers are now useful molecular markers for rapid and efficient identification of cooking quality rapid and efficient identification of cooking quality traits that can be difficult to separate with only traits that can be difficult to separate with only physico-chemical data.physico-chemical data.

AcknowledgementsAcknowledgements

I wish to express my sincere I wish to express my sincere gratitude to:gratitude to:

WARDAWARDA Rockefeller Rockefeller

foundationfoundation Texas A&M (Soil and Texas A&M (Soil and

Crop Sciences)Crop Sciences) USDA-ARS BeaumontUSDA-ARS Beaumont