WORK DONE REPORT-2015 B. Srikanth Senior Research Fellow Biotechnology Division National Initiative on Climate Resilient Agriculture Principal Investigator Co principal Investigator Dr. C N Neeraja Dr. S. R. Voleti Principal Scientist, Principal Scientist, Head- Plant physiology, Biotechnology Division, Indian Institute of Rice Research, Indian Institute of Rice Research, Hyderabad-500030. Hyderabad-500030.
“Identification of genes associated with nitrogen use efficiency in rice ( Oryza sativa L.)” Introduction Rice is the most important staple food and Enhanced Yield Enhanced Translocation of potential source of calorie intake for two thirds of Indians Efficiency of Nonstructural C & N Enzymes to grains and play a key role in the national food and Efficient C:N livelihood security. metabolism N Structural N Functional The present trend of rice production is in line N Utilization Tissue N Tissue N Efficiency flowering Maturity N Lost with the country’s requirement, but India’s rice N Lost production needs to be enhanced to about 120 Biological N Supplied N Taken UP Nitrification N Uptake Efficiency million tons from the current level of 105 million Inhibition Nitrate Transporter tons by the year 2025 A.D. Efficient root Rane et al 2009 system Nitrogen fertilizer and its environmental impacts The production of high-yielding crops is associated with the application of large quantity of nitrogen (N) fertilizers. N is the most important macro nutrient for plant growth and developing high yields. Urea is the major N fertilizer and it contributes about 80% to the total fertilizer consumption in India. Incomplete capture or poor conversion of fertilizer N also causes global warming through nitrous oxide emissions. Thus, development of rice genotypes with Nitrogen Use Efficiency is need of the hour for cost effective, economically sustainable and environment friendly agriculture.
Nitrogen Use Efficiency Nitrogen use efficiency (NUE) can be defined as genotypes which can uptake and accumulate higher N content and able to yield better under low N conditions. NUE is a complex trait, it can be influenced by both internal and external factors. In India, the current average NUE in the field is approximately 33%. Improving NUE will ensure lower level of N fertilizer usage thus reduce environmental contamination. There fore, It is important to screen large number of genotypes under differential N conditions and identify the genotypes with high NUE. Identification of genes associated with NUE is important for the development of efficient breeding varieties with high NUE and reducing nitrogen inputs from farming to the environment. Objectives 1. To screen rice genotypes for nitrogen use efficiency with zero and recommended dose of nitrogen application. 2. To identify genes/genomic regions associated with nitrogen use efficiency in rice. 3. To study the expression of identified candidate genes during zero and recommended dose of nitrogen application.
Screening of rice genotypes for NUE in low and recommended N conditions ( Kharif 2011 and Rabi 2012) 155 rice genotypes (11 categories) Agro-physiological , biochemical and yield attributes were recorded Leaf length, width, area, Chlorophyll content N-0 Days to 50% flowering , days to maturity, plant height, number of tillers, number of productive tillers, number of filled grains/ panicle, spikelet sterility, and grain yield/plant N content in straw, grain and plant NUE Indicators Under low N conditions 25 best performers were identified ( Utilized for breeding) N-100 Candidate gene based association mapping (CGAM) for identification of genes and genomic regions associated with NUE Diversity analysis Polymorphism survey with 12 genotypes QQ-Plot MLM (Neibour joining method) SC29 SC25 20 82 SC29 SC25 12 86
Two way analysis of variance (ANOVA) revealed significant variability among genotypes . Wide genetic variability was observed for 22 yield, yield related parameters and 13 NUE indicators in 155 genotypes under low and recommended N conditions. Significant interactions for the treatments (low and recommended N) have been observed for leaf length, filled grain weight and grain yield suggesting the importance of N in filled grain weight and thereby yield. Significant interactions for seasons and treatments were observed for majority of the traits suggesting the complexity of yield and NUE. Correlation coefficient of the different yield and yield related parameters along with NUE indicators confirmed the significance of panicle weight, straw yield, total dry matter, total grain weight and N content in plant under low N conditions. Several significant, common correlations across the seasons ( kh11 and rb12 ) were observed
Correlation graphs (Kharif 2011) 11,457 11,457 11,457 11,457 11,457 5,743 5,743 5,743 5,743 5,743 28 2.4 13.5 24.7 28 28 28 28 0.070 0.200 0.330 Grain_yield__kg_ha v 11.9 34.5 57.0 0.71 1.26 1.80 3 76 149 No._of_Tillers … Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Leaf_Len_cm___Rep … N.W_cm___Rep … Leaf_Thickness__Rep … P_Height … 11,457 11,457 11,457 11,457 11,457 5,743 5,743 5,743 5,743 5,743 28 28 28 28 28 1.6 9.7 17.8 2.4 10.1 17.9 0.4 16.9 33.4 31 48,179 96,326 0.0 7.3 14.5 Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. No._of_PB_Tillers … Pa.No_hill … Pan.Wt__G__hill … Filled_gr.wt_g_hill … Unfilled_gr.wt_g__hill … 11,457 11,457 11,457 11,457 11,457 5,743 5,743 5,743 5,743 5,743 28 28 0.6 41.7 82.7 28 28 28 0.0 5.7 11.5 0.2 18.1 35.9 3.4 25.9 48.4 169 4,148 Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. HI … Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. To_Gr_Wt__g__hill … Grain_yield__t_ha … TDM … STRAW.WT_kg_ha … 11,457 11,457 11,457 11,457 11,457 5,743 5,743 5,743 5,743 5,743 28 28 28 28 28 0.280 0.500 0.720 1.14 1.70 2.26 4.4 51.9 99.5 11.5 34.5 57.5 0.73 1.26 1.79 Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs. Grain_yield__kg_ha vs Grain_yield__kg_ha vs. N__in_Straw … Total_N__in_plant … GF … SPAD__Rep … N__in_Grain …
Correlation graphs (Rabi 2012) 63,142 63,142 63,142 63,142 63,142 31,604 31,604 31,604 31,604 31,604 66 66 66 66 66 0.50 1.15 1.79 0.080 0.155 0.230 14.0 35.7 57.5 45.7 82.9 7.3 26.4 45.5 Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. N.W_cm___Rep … Leaf_Thickness__Rep … SPAD__Rep … P_Height … Leaf_Len_cm___Rep … 63,142 63,142 63,142 63,142 63,142 31,604 31,604 31,604 31,604 31,604 66 66 66 66 66 0.7 7.4 14.2 0.7 14.2 27.7 0.2 11.2 22.3 2.1 8.7 15.4 2.1 8.4 14.7 Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Pa.No_hill … Pan.Wt__G__hill … Filled_gr.wt_g__hill … No._of_Tillers … No._of_PB_Tillers … 63,142 63,142 63,142 63,142 63,142 31,604 31,604 31,604 31,604 31,604 66 66 66 66 66 0.6 15.3 30.0 6 2,667 5,328 23.8 61.7 0.06 3.71 7.36 965 4,916 Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. To_Gr_Wt__g__hill … Unfilled_gr.wt__kg_ha … GF … Grain_yield__t_ha … STRAW.WT_kg_ha … 63,142 63,142 63,142 63,142 63,142 31,604 31,604 31,604 31,604 31,604 66 66 66 66 66 5.8 25.5 45.2 3.1 42.1 81.1 0.10 0.88 1.66 0.200 0.400 0.600 0.42 1.24 2.06 Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. Filled_gr.wt_kg_ha vs. TDM … HI … N__in_Grain … N__in_Straw … Total_N__in_plant …
Several best and poor performers were identified in each category based on yield AROMATIC GERMPLASM UPLAND AEROBIC HEAT TOLERANT IRHTN N-100 -TOP N-100 -TOP N-100 -TOP N-100 -TOP N-100 -TOP N-100 -TOP Basmati 242 IC-462350 IR72876-62-2-2-2 IR 82639-B-B-3-3 NCR 606 IR 1561-228-3-3 Basmati Kamon IC-462316 IR 82635-B-B-47-1 IR 82639-B-B-140-1 ARC 14088 GIZA 178 N-100 -LEAST N-100 -LEAST N-100 -LEAST N-100 -LEAST N-100 -LEAST KHASRAN (ACC Kola Joha 3 IC-463176 IR 82590-B-B-102-4 IR88633:20-125-B-1 76382) PARO DUMBJA(WHITE) Ratnasundari IC-466475 IR 83754-B-B-46-4 IR88633:5-54-B-1 (ACC 75200) DRR RELEASED RESTORER LINES A LINES B LINES HYBRIDS N-100 -TOP N-100 -TOP N-100 -TOP N-100 -TOP N-100 -TOP Pooja BCW-56 DRR10A DRR12B DRRH-3 Sasyasree KMR-3 DRR13A IR80555B PA6444 N-100 -LEAST N-100 -LEAST N-0 -LEAST N-0 -LEAST N-0 -LEAST Swarna PSBRC80 DRR13A IR80561B PA6201 Rpbio 226 IR82039-B-B-140-1 DRR12A DRR10B DRRH-3 A total of 325 marker trait associations were observed in the present study. In kh11 season, a total of 161 marker trait associations were observed in which 94 under recommended N and 67 under low N conditions. In rb12 season, a total of 164 marker trait associations were observed in which 113 under recommended N and 51 under low N conditions.
16 genes /genomic regions associated with NUE were identified on different chromosomes (CHR.1,2,3,4,8 and 10).
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