taking an integrated approach for plant germplasm characterization and utilization ming li wang...

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Taking an Integrated Approach for Plant Germplasm Characterization and Utilization Ming Li Wang Molecular and Biochemical Genetics Laboratory PGRCU Curators Workshop at Atlanta, February 3, 2010

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Taking an Integrated Approach for Plant Germplasm Characterization and Utilization

Ming Li WangMolecular and Biochemical Genetics Laboratory

PGRCU

Curators Workshop at Atlanta, February 3, 2010

Our Mission for Plant Germplasm Research

Utilization

Preservation

Characteriza-tion

Evaluation

Distribution

Curation

Utilization

An Integrated Approachfor Plant Germplasm Research

Biochemical analysis

Genotypical analysis

Morphological analysis

► Genetic analysis of sweet sorghum germplasm

► Genetic and biochemical analysis of peanut germplasm

Sorghum

Grain sorghum

(Starch)

Forage sorghum

(Biomass)

Sweet sorghum

(Sugars)

Sorghum as Feedstock for Bioethanol Production

Pretreatment Fermentation Products Feedstock

Grain sorghum(Starch)

Sweet sorghum(Sugars)

Hydrolysis

Squeeze

GlucoseFructoseSucrose

C5 sugars

Animal feedEthanol

Chemicals

EthanolChemicals

Stalk residue

Forage orenergy sorghum

(Biomass)

DelignificationHydrolysis

There are about 3,000 sweet sorghum accessions in the U.S. germplasm collection

Selected 96 Sweet Sorghum Accessions for Genotyping

Country Line Number Country Line Number

Australia 1 Sudan 15

China 5 Swaziland 2

Ethiopia 5 Syria 2

Hungary 1 Tanzania 4

India 7 Turkey 3

Kenya 4 Uganda 4

Malawi 5 USA 23

Mexico 1 Zaire 4

Nigeria 1 Zambia 1

Pakistan 1 Others 2

South Africa 5 Total (22) 96

Sweet Sorghum Growing in the Field

Selected SSR Markers for Genotyping

Chromosome (LG) Number of markers Cover region (Mb)

Linkage Group 1 15 3.08-70.43

Linkage Group 2 12 1.02-77.62

Linkage Group 3 11 1.99-72.46

Linkage Group 4 6 48.57-67.96

Linkage Group 5 6 0.21-57.86

Linkage Group 6 6 3.17-58.26

Linkage Group 7 13 0.32-62.51

Linkage Group 8 11 0.16-54.56

Linkage Group 9 7 0.02-59.16

Linkage Group 10 8 10.89-60.57

Total 95 572 Mb (76.3%)

Genotyping Sweet Sorghum Accessions with SSRs

SSR marker Xcup1

Statistics Results

Statistics Overall G1 G2 G3 G4

Sample size 96 30 11 30 25

Total number of alleles 705 400 302 566 414

Number of alleles per locus 7.61 4.17 3.15 5.89 4.31

Major allele frequency 0.55 0.66 0.64 0.52 0.62

Genetic diversity 0.58 0.46 0.46 0.61 0.49

PIC* 0.54 0.42 0.41 0.57 0.46

* Polymorphism information content.

Determination of the Number of Subpopulations

1. Likelihood plot of the models,2. Stability of grouping patterns across ten runs,3. Germplasm information.

Analysis of Molecular Variation (AMOVA)

Source of variation

Degree of freedom

Sum of squares

Mean squares

Percentage of variation

Among population

3 643.66 214.56 13.99

Within population

188 4727.34 25.15 86.01

Total 191 5371.01

US historic syrup type

Race durra from Asia

Mainly from Africa

(26/29)

(16/20)

(10/14)

(24/33)

Genetic Distances between Sweet Sorghum Groups

Group G1 G2 G3 G4

G1 0 0.2399 0.1108 0.1643

G2 0.3156 0 0.1254 0.2191

G3 0.1246 0.1434 0 0.0781

G4 0.1965 0.2804 0.0848 0

Note: The top diagonal is Nei’s minimum distance and the bottom diagonal is pairwise Fst.

Genotyped Sweet Sorghum Accessions on the World Map

Principal Component Analysis (PCA)

Geographical and Genetic Distributions of Genotyped Sweet Sorghum Accessions

Wang et al., 2009 TAG

Summary of Sweet Sorghum Research Results

• Four subpopulations (G1, G2, G3, and G4) have been identified.• Four branching groups (B1, B2, B3, and B4) have been classified.• Results from genetic diversity and population structure analysis

were correlated well with the geographical locations where these accessions were curated.

• Geographical origin of accessions had significant influence on genetic similarity of sweet sorghum germplasm.

• Germplasm accessions curated from different geographical regions should be used for developing sweet sorghum cultivars.

Income

Fatty AcidComposition

(12 fatty acids)

Seed Oil Content(40-60%)

Grain Yield of Oilseed Crop(bushel/acre)

$

Biochemical and Genetic Analysis of Peanut Germplasm

Peanut as Nutritional and Bioenergy Crop

Peanut

Nutritional

Crop

High Protein

(25%)High Oil

(60%)

High Oleic Acid

(80%)

Bioenergy

Crop

First Used

Biodiesel

High Yield

Biodiesel

50 gallon oil /acre for soybean123 gallon oil /acre for peanut

Peanut oil extractionby ether solvent

Ankom XT15Fat Extractor

Measure Oil Content by Nuclear Magnetic Resonance (NMR)

Plant oil + Methanol Esters + GlycerolCatalyst

Convert Plant Oil to Fatty Acid Methyl Esters (FAME)

Linoleic acid

32.0%

Oleic acid

48.0%

Stearic acid

3.5%

Palmitic acid

11.0%

C18:1 C18:2 C16:0

C18:0

3.2%

Behenic acid

C22:0

1.6%

Arachidic acid

C20:0

80%(high oleic acid)

Peanut Fatty Acid Composition

GC Analysis of Peanut Fatty Acid Composition

0 2 4 6 8 10 12

F.A.M.E. Standard1 = C14:02 = C16:03 = C16:14 = C18:05 = C18:16 = C18:27 = C18:38 = C20:09 = C20:110 = C22:011 = C24:0

Time (min.)

1

2

3

4

5

6

7 8 9

10

11

Oil% C16:0 C18:0 C18:1 C18:2 C20:0 C20:1 C22:0 C24:00

10

20

30

40

50

60

FA = subspecies fastigiata

HY = subspecies hypogaea

FA

HY

AB

AB

A B

B

B

A

A

B BA AA A

A A

Oil Content and Fatty Acid Composition among Different Subspecies

Oil% C16:0 C18:0 C18:1 C18:2 C20:0 C20:1 C22:0 C24:00

10

20

30

40

50

60

Hi = botanical variety hirsuta

Hy = botanical variety hypogaea

Hi

Hy

A

B

A

A

A

A

A AA

A

B

B

B

B

B BB

B

Oil and FAC among Different Botanical Varieties

Stearic acidC18:0

COOH Oleic acid

COOH

C18:1

COOH Linoleic acidC18:2

COOH Linolenic acidC18:3

Fatty Acid Desaturase (FAD) with Fatty Acid Composition

Δ12 FAD2

ω-3 FAD3

Δ9 FAD1

x

From Gene Mutation to Fatty Acid Composition Change

A B A B A B A BGene mutation for FAD2

Wild type Mutation on A Mutation on B Mutation on A + B

FAD2 enzymeactivity

Normal ½ Normal ½ Normal Abnormal

Oleic acid level

48% 64% 64% 80%

Low Middle Middle High

Detection of FAD2 Mutation on B Genome by Real-time PCR

Barkley et al., 2009 Molecular Breeding

Ol2Ol2 ol2ol2

Ol2ol2

Ol2ol2

ol2ol2

Ol2Ol2

Wild type Mutant

Heterozygous

a. FAD2 mutation

b. Allele-specific PCR amplification prediction

Wild type Substitution Insertion SUB + INS

Detection of Mutation in FAD2 by Allele-Specific PCR

Wild typeLow oleate

Common bandWild type band

Common bandSubstitution band

Common bandInsertion band

Common bandSubstitution band

Common bandInsertion band

+

+

+ +

+

+ +

- -

- -

-

SubstitutionMid oleate

InsertionMid oleate

Sub + InsHigh oleate

Chen et al., 2010 Plant Molecular Biology Reporter

Wild TypeO/L = 43.2 / 34.2 = 1.3

Insertion on BO/L = 60.2 / 20.95 = 2.9

Substitution on AO/L = 63.6 / 18.5 = 3.4

Substitution + InsertionO/L = 80.0 / 2.9 = 27.4

2.0 4.0 6.0 8.0 10.0 12.0 14.0min

600

300

600

300

600

300

600

300

Oleic acid

Linoleic acid Low Oleic Acid Type

Mid Oleic Acid Type

Mid Oleic Acid Type

High Oleic Acid Type

Similar toOlive oil

(64%)

Summary of Peanut Germplasm Research Results

• Significant difference identified on oil content and fatty acid composition among botanical varieties and subspecies.

• Real-time PCR assay was developed for detection FAD2 mutation on B genome.• Allele-specific PCR assay was developed for detection FAD2 mutations on both A

and B genomes including: Wild type (no mutation), Substitution type (G→A) on A genome, Insertion type (→A) on B genome, Double mutation type (Substitution + Insertion).

• Real-time PCR and allele-specific PCR markers developed in our lab can be used for MAS and germplasm screening.

• GC analysis identified accessions with different levels (L, M, H) of oleic acid.• The results from Genetic analysis and GC analysis were consistent.• Genetic analysis in combination with biochemical analysis is a powerful approach

for germplasm research.

PGRCU CollaboratorsMr. Brandon Tonnis Dr. John Erpelding USDA-ARS, Puerto Rico Dr. Noelle Barkley Dr. Charles Chen USDA-ARS, DawsonMr. Dave Pinnow Dr. Paul Raymer UGA, GriffinMs. Sarah Moon Dr. Manjee Chinnan UGA, Food Science Dept.Ms. Jessica Norris Dr. Zhenbang Chen UGA, Crop & Soil Dept.

Dr. Corley Holbrook USDA-ARS, TiftonMr. Ken Manley Dr. Dick Auld Texas-Tech UniversityMs. Lee-Ann Chalkley Dr. Baozhu Guo USDA-ARS, TiftonMs. Tiffany Fields Mr. Jerry Davis UGA, Statistics Dept.Ms. Merrelyn Spinks Dr. Tom Stalker NCSU, Crop & Soil Dept.

Dr. Gorge Mosjidis Auburn University,All Supporting Staff Dr. Zhanguo Xin USDA-ARS, LubbockAll Curators Dr. Anna Resurrreccion UGA, Food Science Dept.Dr. Gary Pederson Dr. Jianming Yu Kansas State University

Acknowledgements