1 / 35

Nitrogen use efficiency in sorghum Ismail Dweikat University of Nebraska

Nitrogen use efficiency in sorghum Ismail Dweikat University of Nebraska. SORGHUM Sorghum bicolor L. 5 th most grown crop in the world. 214 Million bu in 2011 (USDA) Nigeria 13% India 11% Mexico 11% US 10%  KS TX OK SD NE. USES.

maeve
Télécharger la présentation

Nitrogen use efficiency in sorghum Ismail Dweikat University of Nebraska

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Nitrogen use efficiency in sorghum Ismail Dweikat University of Nebraska

  2. SORGHUM Sorghum bicolorL. 5th most grown crop in the world 214 Million bu in 2011 (USDA) Nigeria 13% India 11% Mexico 11% US 10%  KS TX OK SD NE USES • Cereal crop species such as sorghum, wheat, maize and rice, require large inputs of nitrogenous fertilizers in order to maximize yield

  3. N accounts for the highest costly input, needs to be reduced to increase the profit

  4. Nitrogen is one of the most important plant nutrients • N assimilation and remobilization is essential in plant growth and development 44 M MT increase of food production by 2050 Expected increase in N fertilizer 3 Fold ~ 30 – 50% is taken up by the plant • Most N is lost • Surface run off • Leaching of nitrates • Atmospheric NOxNH3 Producer input Environment contamination Increase NUE

  5. Nitrogen use efficiency: Objective 1: Identify quantitative trait loci (QTLs) analysis and marker identification for nitrogen use efficiency (NUE) in advanced using CK60, China17, and SanChi San Objective 2: Identify novel candidate genes for NUE using proteomic and gene expression profiling comparisons of high and low NUE RILs. Candidate genes will be brought into the pipeline for transgenic manipulation of NUE Objective 3: We have transform sorghum using glutamine synthetase (GS), glutamate synthase (GOGAT), Alanine aminotransferase(ALA-AT) and maize dof1 transcription factor genes to enhance NUE . We are in the process of genes stalking

  6. The China lines averaged approximately 94 g biomass g−1 N while the U.S. lines averaged 85 g g−1 when grown with N stress. This compared to 77 g g−1 and 76 g g−1,respectively, for these contrasting groups at normal N . Maranville and Madhavan. Plant and soil 202

  7. QTL mapping for nitrogen use efficiency (NUE) traits • Genetic linkage map • Genotyping By Sequencing facility, Cornell University • 844 SNPs (Ck60 X San Chi San), • 645 SNPs (Ck60 X China 17) 2 week seedlings grown under 0% N Population development: U.S line Ck60 China lines San Chi San, China 17 • 210 F6 RILs (Ck60 X San Chi San), • 136 F6 RILs (Ck60 X China 17)

  8. Mapping population development China-17 Ck60 136 F7 RILs

  9. Phenotypic characterization of RILs • Mead, NE • Alpha lattice incomplete Block Design with 2 reps Low-N (no fertilizer, rotated with oats in 2011 and Maize in 2012) Normal-N field (100Kg/ha fertilizer with soybean rotation)

  10. Phenotypic characterization of RILs • Mead, NE • Low N (0% synthetic fertilizer, rotated with oats in 2011 and Maize in 2012) • Normal N field (100Kg/ha fertilizer with soybean rotation) • Alpha lattice incomplete Block Design with 2 reps 14 x 15 incomplete blocks for Ck60 x San Chi San lines (210), 12 x 13 incomplete blocks for Ck60 x China 17 lines (136) with parents • 50 seeds per line were used • planting date was same in both fields

  11. Phenotypes • Measured in 3 randomly selected plants per plot (in two reps & two locations) • Leaf chlorophyll concentration • at 3 stages- before flowering, during flowering and after flowering • Anthesis date (days) • Plant height (cm) • Fresh and Dry weights of stover, head (g) • Moisture content of stover (MC1) and Head (MC2) • Total biomass yield (t/ha) • Grain Yield (t/ha) • Test weight (g) • Grain to stover ratio

  12. Data Analysis Chl-1, Chl-2, Chl-3 (chlorophyll-1, 2, 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover) df, degrees of freedom; ***p < 0.0001; **p < 0.01; *p < 0.05

  13. QTL analysis for Ck60 x San Chi San population (pop1) Chl- (chlorophyll 1, 2 and 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover)

  14. Data Analysis Chl-1, Chl-2, Chl-3 (chlorophyll-1, 2, 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover) df, degrees of freedom; ***p < 0.0001; **p < 0.01; *p < 0.05

  15. QTL analysis for Ck60 x China17 population • QTLs for PH, dry biomass (Ritter, 2008) • days to anthesis (Srinivas et al., 2009) • EST marker Drenshbm-19 encoding ETHYLENE INSENSITIVE3-1 (EIL-1) • Ma3 (Childs et al.,1997) Putative genes TOPLESS-related 1 (Sb01g040800)

  16. QTL analysis for Ck60 x San Chi San population Chl-(chlorophyll 1, 2 and 3), PH (plant height), AD (anthesis date), MC1 (stover moisture content), MC2 (head moisture content), BY (biomass yield), GY (grain yield), TW (test weight), and GS (grain/stover) .

  17. Validation of QTLs across two populations PopI PopI PopII PopII QTLs for grain yield, seed weight and plant height (Srinivas et al. 2009) Chromosome-6 Chromosome-3 Genes DW2(Srinivas 2009) Ma1 (Paterson 1995)

  18. Validation of QTLs across populations PopI PopII Chromosome-7 PopI PopII Chromosome-8 Grain yield and Plant height QTLs Dw3 gene (Srinivas et al.,2009)

  19. PopI PopII Chromosome-9 QTLs for PH, flowering time (Lin et al. 1995)

  20. Conclusions • Five genomic regions consistently detected across environments • Candidate genes • Marker assisted selection

  21. Objective 3: Identification of differentially expressed exons (DEGs) for NUE in known low-N tolerant and sensitive genotypes of sorghum

  22. Phenotypic performance Low NUE RILs Sensitive Sorghum Inbreds Tolerant High NUE RILs

  23. Seedlings growth under (0%) N conditions

  24. Differentially Expressed Genes 3) San Chi San 4) China17 5) KS-78 6)High bulk • Ck60 • Tx623 • 7) Low bulk vs

  25. Candidate genes in the QTL regions • QTLs for PH, dry biomass (Ritter, 2008) • days to anthesis (Srinivas et al., 2009) • EST marker Drenshbm-19 encoding ETHYLENE INSENSITIVE3-1 (EIL-1) • Ma3 (Childs et al.,1997) Putative DEGs

  26. Characterization and identification of lead events based on greenhouse phenotype studies for use in down-stream field evaluations.

  27. The modulation of nitrogen metabolism requires the understanding of the function and the means of regulation of the different enzymes involved in the process of nitrogen (N) uptake, assimilation and remobilization in order to develop plants with enhanced efficiency in nitrogen utilization. Glutamine synthetase (GS) is a key enzyme in N metabolism. GS together with glutamate synthase (GOGAT) are the main route for ammonium Alanine aminotransferase (ALa-AT) has been shown to allow the maintenance of the carbon-nitrogen balance in plants through the translocation of pyruvate or alanine Dof1 (DNA binding with one finger), which regulates C-skeleton production, including PEPC. These C-skeletons can then be utilized in N metabolism.

  28. SORGHUM WHEAT TX430 CBO37 Agrobacterium-mediated transformation C58C1/pMP90 NTL4/Chry5 pPTN1037 pPTN1034 pPTN1031 pPTN1040 pPTN1033 pPTN1036

  29. ZG 120 1-2a T1-3 ZG 120 4-8a T1-2 ZG 120 4-8a T1-6 ZG 127 3-3a T1-2 ZG 127 3-3a T1-4 ZG 123 3-4a T1-3 ZG 123 3-4a T1-6 TX 430 (- control) ZG 120 1-2a T1-5 (+ control) Molecular characterization of transgenic sorghum and wheat MW NPTII ELISA Southern/Northern blots 7.7 -- 6.2 -- 5.5 -- 3 — 2 — 1.5— 1— Southern blot, reprobe, Northern Blot pPTN1033 sorghum. DNA digested with Sst I. Probe: pUC 57-OsGSI digested with Xho I and Eco RI (666 bp) Southern Blot, Northern blot, RNA. pPTN1031 DNA digested with Eco RI. Probe: pUC 57-HV-ALA-AT digested with Xho I (504bp) S/N Blot pPTN1040 sorghum plants. Probe: pUC 57-HV-ALA-AT digested with Xho I (504bp)

  30. SELECTION OF LEAD EVENTS PCR SPECIFIC ENZYME ACTIVITY GS GS Acyl phosphate intermediate Glutamine Glutamate ϒGlutamylhydroxamate Hydroxylamine Glutamine GS FeCl3 540nm

  31. ALA AT Glutamate Pyruvate 2-oxoglutarate Alanine NADH LDH NAD+ Lactate

  32. Example of the pyramiding scheme for the NUE putative genes

  33. Conclusions and future work • A set of transgenic events have been developed in sorghum overexpressing enzymes involved in N/C metabolism. • Lead events from this set are currently under selection based on number of inserts, levels of expression and enzyme activities. • Moreover, an appropriate N regime has been determined to phenotype the selected lead events for NUE. The N regime selected was 5% N (0.75mM N) . • Furthermore, a set of gene stacks have been developed and its characterization is under progress. NUE evaluation for remaining events will be started. • Down-stream field evaluations of selected events and gene stacks for different levels of nitrogen conditions.

  34. Ethanol plants turning toward grain sorghum The future is bright Dorchester Co-op workers remove a pile of grain sorghum in this 2000 file photo, Lincoln Journal Star March 4, 2013

  35. Acknowledgment NE Grain Sorghum Board NSCP DOE John Rajewski Malli Geli Tom Clemente Pamela Peña

More Related