CHARACTERIZATION OF HOX 10 MUTANT ALLELE BY SELECTIVE GENOTYPING OF F 2 MUTMAP POPULATION IN RICE (Oryza sativa L.) RAJESH KUMAR SINGHAL PALB 3188 DEPARTMENT OF CROP PHYSIOLOGY UNIVERSITY OF AGRICULTURAL SCIENCES BENGALURU - 560 065 2015
CHARACTERIZATION OF HOX 10 MUTANT ALLELE BY SELECTIVE GENOTYPING OF F 2 MUTMAP POPULATION IN RICE (Oryza sativa L.) RAJESH KUMAR SINGHAL PALB 3188 Thesis submitted to the UNIVERSITY OF AGRICULTURAL SCIENCES, BENGALURU in partial fulfilment of the requirements for the award of the degree MASTER OF SCIENCE (Agriculture) in CROP PHYSIOLOGY BENGALURU JULY, 2015
Affectionately Dedicated To My Beloved Parents
DEPARTMENT OF CROP PHYSIOLOGY UNIVERSITY OF AGRICULTURAL SCIENCES G.K.V.K. CAMPUS, BENGALURU 560065 CERTIFICATE This is to certify that the thesis entitled CHARACTERIZATION OF HOX 10 MUTANT ALLELE BY SELECTIVE GENOTYPING OF F 2 MUTMAP POPULATION IN RICE (Oryza sativa L.)" submitted by Mr. Rajesh Kumar Singhal, ID No. PALB 3188 for the degree of MASTER OF SCIENCE (Agriculture) in CROP PHYSIOLOGY to the University of Agricultural Sciences, Bangalore, is a record of bonafide research work done by him during the period of her study in this University under my guidance and supervision and the thesis has not previously formed the basis of the award of degree, diploma, associateship, fellowship or any other similar titles. Bangalore July, 2015 (M.S. SHESHSHAYEE) Major Advisor APPROVED BY: Chairman : (M.S. SHESHSHAYEE) Members : 1. (B. MOHAN RAJU) 2. (A.G SHANKAR) 3. (M.P. RAJANNA)
ACKNOWLEDGEMENT I humbly place before my parents, my most sincere gratitude. Their blessings have renewed me every day, all the way on the journey through my life. It is with immense pleasure that I express my profound gratitude to Dr. M.S. Sheshshayee, the Chairman of my Advisory Committee. He was more a mentor and friend than just a guide, who was a strong pillar of support in all my attempts with adequate appreciation as well as criticisms. He helped me to inculcate a logical way of approaching science with accuracy and I extend my warm regards for him for being whatever he has been to me. The relentless hard work of M.P. Rajanna, to extend his scientific knowledge has been a sheer source of inspiration. I am so grateful to him for the priceless guidance that he has given, not only as an Advisory Committee member but also as a terrific teacher, which helped me to excel in the field of science. Dr. B. Mohan Raju B and Dr. A.G. Shankar surely has infused an insight into me to think, speak and write with a good vocabulary. As an Advisory Committee member, it was so kind of him to give his valuable and frank remarks which helped me interpret my research well. I find no words to express many heartful thanks to my lab members, batch mates and to Senior friends for their constant help, guidance and encouragement during my research work. Bengaluru July, 2015 (Rajesh Kumar Singhal)
CHARACTERIZATION OF THE HOX 10 MUTANT ALLELE BY SELECTIVE GENOTYPING OF F MUTMAP POPULATIONS IN RICE (Oryza sativa L.) RAJESH KUMAR SINGHAL ABSTRACT Root growth in rice possess a remarkable diversity in terms of growth pattern, development, and architecture for adverse environmental adaptation. In this study, a few contrasting EMS induced mutagenized rice lines in the background of N22 were characterized under well-watered and water limited condition. Mutant N22_BADT_392_9_1 had high root volume, high lateral root number, high root biomass, low root length, high WUE. A MUTMAP population consisting of 500 F 2 lines was developed by crossing 392_9_1 with N22.These segregating lines were screened for root trait diversity in hydroponics up to 25 DAS. The seedlings were then transplanted to root structure. Though there was no significant difference in root length and lateral root number between the mutant and N22 up to 30 DAS, significant variation was noticed in root structure on 80 DAS. An intense characterization of the mutants revealed that 392_9_1 had a significantly higher photosynthetic rate, perhaps due to higher chlorophyll content and stomatal conductance. The segregation of the mutant allele, a non-synonymous SNPs in HOX 10, was traced in a selected group of MUTMAP individuals differing in root traits. The conspicuous segregation of the mutant allele in high root volume type emphasized the role of HOX 10 gene in governing the transcription activity of gene responsible for RSA in rice. This study is a significant step towards understanding the functional genomics of root traits in rice. July, 2015 Department of Crop Physiology University of Agricultural sciences, Banglore-65 (M.S.Sheshshayee) Major Advisor
ಭತ ದ ನ ಳವ ಯ ವ ಹ MUTMAP ತ ತ ವನ ಅಳವ HOX 10 ಪ ವ ತ ವ ಶ ತ ನ ಗಡ ಕ ಘ ಪ ಬ ಧ ಶ ಉದ, ಆಳ, ಹರಡ ಯನ ಒಳ ಡ ಭತ ದ ರ ಬಹ ಕ ಧ ಯನ ಪ ದ ಸ ತ. ಈ ಧ ಯ ಬತ ದ ಡಗ ಬರ ಧಕ ಗ ಣಗಳನ ಸ ವ ಸ ಯಕ ಗ ತ. ನ ಧ ಯ ಅಧ ಯನ ಬತ ದ ಅ ವ ಬಹ ಮ ಖ. ಈ ನ ಪ ಸ ತ ಅಧ ಯನವ ಭತ ದ ನ ಅಣ ವ ಕ ವ ಹ ಯನ ಪ ಸ ವ ಸ ಧ ಯನ ಹ ತ. EMS ಎನ ವ ಯ ಕವನ ಬಳ ನ ನ ೨೨ ಎನ ವ ಬತ ದ ತ ಯ ಣ ಪ ವತ ಯನ ಡ ತ. ಈ ಣ ಪ ವ ತ ತ ಗಳನ ಅ ವ ಪ ಯ ಅಧ, ಅ ಕ ಮತ ಕ ರ ಳ ಣ ಪ ವ ತಗಳನ ಗ ರ ಸ ತ. ಅ ಕ ನ ಪ ವ ತ ಗಳನ ನ ನ ೨೨ ಸ ಕರಣ MUTMAP ತ ಗಳನ ವ ಸ ತ. ಅ ಕ ನ ಪ ವ ತ ಗಳ HOX 10 ಎ ಬ ಅನ ವ ಕ ತ ನ ಒ ದ SNP ವ ಸ ರ ವ ದ ಕ ಡ ಬ ತ. ಈ SNP ವ ಸವನ MUTMAP ತ ಗಳ ಪ ಗ ನ ಪ ಣವ ಳ ನ ಎ ತ ಗಳ ಈ SNP ವ ಸವ ಕ ಡ ಬ ತ. ಈ ಅಧ ಯನ ದ HOX 10 ಎ ಬ ವ ಶ ಯ ನ ಪ ಣ ಳವ ಅ ಮ ಖ ದದ ಎ ಬ ಅ ಶವನ ಕ ಡ ಯ ತ. ಮ ದ ವ ದ, ಬರ ಧಕ ಶ ನ ಮ ಖ ಯನ ರ ಪ ತ ಸ ತ. ಜ, ೨೦೧೫ ಶ ರ ಸ ಗ, ಕ ಶ ಲಯ ಗಳ ರ ೫೬೦೦೬೫ (ಎ. ಎ. ಷ ) ಪ ನ ಸಲ ರರ
CONTENTS CHAPTER TITLE PAGE No. I INTRODUCTION 1-3 II REVIEW OF LITERATURE 4-16 III MATERIAL AND METHODS 17-28 IV EXPERIMENTAL RESULTS 29-41 V DISCUSSION 42-45 VI SUMMARY 46 VII REFERENCES 47-58 APPENDICES
LIST OF TABLES Table No Titles of the Tables Page No. 1 Diversity of Root traits and function in plant (restructured from Gowda, et. al., 2011 7 2 Rice root anatomy traits and function in plant 8 3 EMS induced mutant and their function in plant 11 4 The four HD-Zip subfamilies and their function 15 5 Gas exchange parameter in mutants and wild type in control and stress condition. 6 Gas exchange derivative traits in control and stress condition in gravimetry experiment. 7 Average Root length and lateral root number measured in hydroponics system at 7,14, 17, 23 days after sowing (DAS) in wild type N22 and high root mutant 392-9-1. 8 Descriptive statistics of Root length and lateral root number measured in hydroponics system after 7,14, 17, 23 days after sowing (DAS) in F₂ population. 9 Variation in root traits among the MUTMAP population grown in root structure 10 Measurement of gas exchange of the F 2 MUTMAP population. 11 Variation in shoot traits among the MUTMAP population grown in root structure harvested 80 days after sowing. 12 Grouping of F 2 lines according to root length and root volume for HOX10 allele segregation. 13 Variation in ¹³C values observed in groups formed by contrasting root traits. 14 Summary of results obtained by Sanger re-sequencing of HOX 10 allele in selected 4 groups. 32 32 34 34 36 37 38 40 40 41
LIST OF FIGURES Fig. No. Title of the figures Between Page 1 Measurement on total leaf area (TLA), total dry matter (TDM), ¹³C in control and stress condition in gravimetry experiment 70 DAS. 2 Measurement on Net assimilation rate (NAR) and mean transpiration ratio (MTR) in control and stress condition. 3 Measurement on water use efficiency (WUE) and ¹³C in control and stress condition. 4 Measurement of root traits under control and stress condition in gravimetry experiment @ 70 days after sowing (DAS). 5 Variation in Stomatal frequency in wild type and mutants in control and stress condition 6 Relationship between root weight and total dry matter, root weight and root length, root weight and root volume, root weight and shoot weight in F 2 population in root structure experiment. 7 Frequency distribution of Root length and Root volume observed in F 2 population in root structure at 80 DAS (N=170) 32-33 32-33 32-33 32-33 32-33 38-39 38-39
LIST OF PLATES Plates No Titles of the Plate Between page 1 Picture depicting the crossing process of N22 (female) and N22_BADT_392_9_1 (male) for development MUTMAP population. 2 Comparison of stomatal frequency in N22_BADT_392_9_1 and N22 3 F 1 s obtained by crossing wild type (N22) and high root mutant (N22_BADT_392_9_1) 24-25 32-33 36-37 4 Identification of true F1 by using SSR markers 36-37 5 SSR markers showing polymorphism between N22 and N22_BADT_392_9_1. 6 Measurement on root length and lateral root number on 7 day after sowing 17 DAS, and 23 day after sowing in hydroponics system. 7 Root variability observed in root structure at 80 day after sowing in F 2 population 8 Sanger resequencing of HOX 10 allele in selected genotype and in parent 36-37 38-39 38-39 41-42
LIST OF APPENDICES Appendices No Appendices Titles 1 Gas exchange parameter taken in root structure after 45DAS 2 Biomass observation taken in F 2 MUTMAP population in root structure @80 DAS
I INTRODUCTION Rice (Oryza sativa L.) is the primary source of food, nutrients, and energy for more than 3.5 billion people across the world. In addition to food security, plays an important role in socioeconomic and political stability in many countries in Asia and Africa. It is estimated that, with every additional of 1 billion people, 100 million tons additional requirement of rice need to be produced but with limited and highly competitive land and water resources (GRiSP, 2010). FAO forecast global paddy production in 2015 by a modest 1.1 percent growth rate to 749.8 million tonnes (499.9 million tonnes, milled basis). The food security of many poor countries depends on the productive capacity of irrigated areas. Increasing water scarcity in all over world is expected to further shift rice production to more water-abundant delta areas and to lead to crop diversification and more aerobic soil conditions in rice fields in water-short areas.to meet the dual challenge of producing enough food and alleviating poverty, more rice needs to be produced at a low unit cost. Productive capacity of rice environments is being threatened by increasing water scarcity in irrigated systems and by droughts, salinity, flooding, heat stress and climate change. This is because many stresses on rice production are mainly related to water, increasing water productivity is especially important for rice production.drought is a major abiotic stress, affecting 20 % of the total rice-growing area in Asia (Pandey and Bhandari., 2008). Achieving drought tolerance in rice is necessary to meet the growing water shortage of the world and it requires a deeper understanding of the mechanisms that could facilitate drought resistance Understanding the physiology of drought response can contribute to plant breeding efforts toward drought resistance (Fukai and Cooper., 1995; Serraj et al., 2009). Traits associated with water mining i.e. roots, have been claimed to be critical for increasing yield under soil-related stresses (Lynch, 2007; Serraj et al., 2004).Growth of the rice root, in terms of total dry matter, maximum root depth, and root length density, increases until flowering stage and then decreases sharply to maturity (Yoshida and Hasegawa,1982). Kawata and Soejima (1974)indicated that roots produced after flowering may play an important role during the grain-filling period.rice is characterized by a shallow root system compared with other cereal crops (Angus et al., 1983), which have limited water extraction below 60 cm (Fukai and Inthapan,1988).Lateral roots, which comprise a greater proportion of the root system in total length and number (Yamauchi et al., 1987a, b; Harada and Yamazaki, 1993), are responsible for the greatest amount of water and nutrient absorption (Yoshida et al., 1982). Productivity of rice can be increased by three ways: First is to preserve the gains achieved in first green revolution, second is increasing the yield potential of seed material, third integrated farm management and fourth is policy approach. Among these improving the seed material is the most effective low cost method of improving productivity. In world 60 % of rice is grown under rainfed condition (upland) which contributes 25 % to total rice production, varietal improvement is the major strategy for increasing productivity in upland areas. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 1
Drought and erratic rainfall controls the productivity of rice under upland condition. So understanding the physiology of factors contributing to drought tolerance like, water relations and cellular level tolerance are important. Water relations can be maintained by improving the roots and WUE. Cellular level tolerance involves intrinsic ability of the plant to maintain its metabolism. Increase in WUE without decrease in transpiration is necessary to reduce yield penalty under water limited condition. This can be achieved by increasing the roots. Stomatal regulation (transpiration) and water uptake (roots) contributes to sustain yield under aberrant condition. Higher root surface area determines water uptake and hence helps in sustaining growth under water limited condition. There are three strategies for improving and studying roots: A forward genetic approach of QTL mapping followed by fine mapping for tracking the gene of interest and further marker assisted introgression of trait. Reverse genetic approach to ascertain the function of gene by analysing the phenotypic effect of specific gene sequences. Functional and molecular understanding of root growth is achieved by studying mutants and transgenics Availability of genetic variability for required trait limits the application of the first two strategies. Variability created by induced mutation is a valuable tool to understand the physiological mechanism of root traits. Mutagenic agents, such as radiation and some certain chemicals, can be used to induce mutations and generate genetic variation from which desired mutants may be selected. The identification and analysis of gene mutations in plants are also fundamental to the investigation of gene function. Ethyl Methane Sulfonate (EMS) has been widely used as a chemical mutagen in both plant and animal studies to generate mutant populations (Henikoff and Comai, 2003). EMS typically produces transition mutations (G/C: A/T) because it alkylates G residues (Comai and Henikoff, 2006) and the alkylated G residue pairs with T instead of forming the conventional base pair with C. This transition generates multiple alleles within a given gene, giving rise to several classes of mutations including nonsense; mis-sense and splicing mutants (McCallum et al., 2000). Sumanth Kumar (2014) reported 3 non-synonymous SNP in N22_BADT_392_9_1 mutant. In which one non-synonymous SNP in homeobox region HOX10 amino acid change from arginine to leucine control root development. Abe et al., 2012 developed MUTMAP a method of rapid gene isolation using a cross of the mutant to wild-type parental line based on whole-genome resequencing of pooled DNA from a F 2 segregating population of plants that show a useful phenotype. A population of EMS induced mutant lines of rice in the background of an upland rice cultivar Nagina 22 was analyzed for variation in complex drought adaptive traits like WUE and roots. Contrasting root mutants were identified in M4 generation. The present 2 Rajesh Kumar Singhal
study aims at physiological screening and development of MUTMAP population to understand the genetics and functional genomics of roots. This approach could markedly accelerate crop breeding and genetics for important agronomic trait. Specific objectives are formulated as mentioned below: 1. Generation of F₂ MUTMAP population by crossing high root mutant with wild type (N22) 2. Physiological characterization of F 2 MUTMAP population 3. To assess the segregation of HOX10 mutant allele by selective genotyping of F 2 mutant population Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 3
II REVIEW OF LITERATURE 2.1 Rice: Climate, production, productivity, future challenge Rice is the most important staple food crop of the world, is grown over160 million hectares and providing 20 % daily calories for half of the world s population. More than 3.5 billion people are depending upon rice as a staple food and one fifth of the world population depend on rice cultivation for their livelihoods. Asia produces and consumes about 90 % of the world s rice (http://www.sustainablerice.org/).the international grain council estimated the 2015 global rice production at about 474 million tons. Rice consumption will increase everyday with increase in population. Rice account for 26.6 % of worldwide cereal production and consumption. The international rice research institute (IRRI 2000) studies the food problem in relation to world population, and predict that 800 million tons of rice will be required in 2025.A study by the University of Minnesota, U.S, has found that the current growth in rice production is not sufficient to global rice demand by 2050. Further many studies says that to ensure food security in future, production of rice and other crop have to double by 2050. However, rice yield is growing around 1 % growth now, which means global rice production will around 750 million ton instead 1000 tons in 2050. Thus, enhancing food production under the looming and crisis resource condition like water scarcity and limited land resources are becomes one of the major challenges to modern agriculture research. 2.2 Improve production and productivity under water limited conditions Rice is highly susceptible to drought stress throughout its life cycle, mainly during flowering time. The capacity of the rice plant to sustain itself and to reproduce in limited water conditions is main limiting factor for rice production in drought situation (Pantuwan et al., 2002). Thus, it is imperative for rice breeders or physiologist to develop drought tolerant high yielding rice cultivars. Even though several efforts were made to breed for drought tolerance by including tolerant donor s parent line in breeding programs; there are few successful examples of improved rice cultivars that combine acceptable yield potential and drought tolerance. This is mainly because of the genetic complexity of drought tolerance due to its polygenic inheritance, low to medium heritability, significant genotype and environmental interactions, and the confounding effects of other abiotic stresses on drought. From plant physiologist' point of view, drought is defined as a shortfall of water availability sufficient to cause loss in yield or a period of no rainfall or irrigation that results in insufficient soil moisture leading to reduced crop growth and yield. Drought situation is the major abiotic stress which affect rice yield, for this discovery of novel new genes, QTLs, breeding approaches, molecular biology, development of new varieties for drought tolerance is major challenge to increase yield in drought condition. From the crop physiologist s perspective, plant water relations play a very crucial role in determining the level of drought tolerance in plants. Furthermore, any trait would have relevance only when it sustains productivity by maintaining better water relation with superior crop growth rates (Richard et. al., 2002; Udaya kumar and Prasad., 1994). Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 4
2.3 Drought and coping mechanism in crop plants Drought is a major abiotic stress, affecting 20 % of the total rice-growing area in Asia (Pandey and Bhandari, 2008). Roots are the principal plant organ for nutrient and water uptake. Therefore, improving our understanding of the interactions between root function and drought in rice could have a significant impact on global food security. Plants use different mechanisms to cope with drought stress, namely, drought escape, drought tolerance, drought recovery, and drought avoidance (Levitt, 1972; O Toole and Chang, 1979). Blum et al., 1989 reported that among these four mechanisms, the mode of drought resistance with which roots are most likely associated is drought avoidance. Genotypes that have deep, coarse roots with a high ability of branching and penetration, higher root to shoot ratio, elasticity in leaf rolling, early stomatal closure, and high cuticular resistance are component traits of drought avoidance. Achieving drought resistance in rice will be necessary for meeting the growing water shortage of the world, and it requires a deeper understanding of the mechanisms that could facilitate drought resistance. To enable scientists of different disciplines (e.g., agronomists, physiologists, molecular biologists, and plant breeders) to better understand plant responses to water deficits and link this understanding with breeding of improved cultivars, drought resistance traits are divided into primary traits, secondary traits, integrative traits, phenology, and plant-type traits.primary traits are further divided into constitutive traits ( under no drought stress: e.g., rooting depth, root thickness, branching angle, and root distribution pattern(lafitte et al., 2001; Kato et al., 2006), and induced traits (e.g., hardpan penetration and osmotic adjustment). Constitutive root traits, interacted with drought intensity, have a large effect on extractable soil water during drought (Lilley and Fukai, 1994). This influences expression both of induced and secondary traits such as maintenance of plant water status, canopy temperature, leaf rolling score, and leaf death score. These secondary traits may then reduce spikelet fertility and yield components (i.e., integrative traits), and ultimately, yield (Kobata et al., 1994). Selection for yield under terminal drought conditions was not essentially dependent on deeper/profuse root systems, but rather on several other critical traits that contribute to soil moisture conservation during late season water deficits (Zaman Allah et al., 2011a). These traits include: (1) low leaf conductance under non-limited water conditions during the vegetative stage, which could be measured by a warmer canopy, (2) a low leaf expansion rate when soil moisture is still non-limiting for plant growth and a restriction of plant growth under progressive exposure to stress and (3) a higher fraction of transpirable soil water (FTSW) thresholds that reduce transpiration, thus avoiding rapid soil water depletion.several studies have shown that FTSW can be linked to variables describing plant water status such as midday leaf water potential, leaf relative water content and stomatal conductance, which are known to be contribute to drought adaptation. In addition to the above positive effects of the stay green trait, enhanced remobilization of stored assimilates will lead to identify the important targets for enhancing seed sink strength under drought, thus helping to achieve yield stability under drought 5 Rajesh Kumar Singhal
2.4 Models to improve yield under resource limited conditions: Various models are proposed to improve yield under resource limited condition Passioura (1977) proposed a model for yield under water limited condition GY = W x WUE x HI eq-1 Where W is water transpired by a crop, WUE is water use efficiency and HI is harvest index, GY is grain yield. A general model for drought adaptation of wheat was developed by Reynolds et al., 2005.It encompasses traits which possess a potential role in dry environments. In this model, some of the important traits included: (1) Pre-anthesis growth, (2) access to water as a result of rooting depth or intensity that would be expressed by a relatively cool canopy (3) water-use efficiency (WUE) as indicated by relatively higher biomass/mm of water extracted from the soil, transpiration efficiency of growth (TE = biomass/mm water transpired) indicated by C-isotope discrimination ( 13 C) of leaves, and WUE of canopy photosynthesis associated with re-fixation of respiratoryco 2, (4) Photo protection including energy dissipation anti-oxidant systems and anatomical traits such as leaf wax. 2.5 Traits and its importance in improving rice crop productivity under water limitation: 2.5.1. Root anatomical and morphological trait and water relation Rice plants have adopted several drought resistance mechanisms to overcome drought effects, which ranges from cellular level to whole plant level. Rice plants maintain growth and productivity by maintaining tissue water relations and positive carbon by mining water from deeper soil profiles (Fukai and Copper et al., 1995). Root system architecture (RSA) describes the spatial organization of root systems, which is critical for root function in challenging environments, and it has potential to boost or stabilize yields in drought, and reduce the need for unsustainable fertilizers (Christopher et al., 2013). Roots exhibit an surprising level of morphological plasticity in response to soil physical conditions (Kato et al., 2006; Lynch, 2007; Siopongco et al., 2009), a peculiarity that allows plants to adapt better to the chemical and physical properties of the soil, particularly under drought conditions (Bacon et al., 2000; Yu et al., 2007). Genetic variation in rice root morphological traits (root length, root diameter, root depth root pulling force, deep root to shoot ratio, root number, root growth plasticity, root penetration ability and root length density) has been exploited greatly than anatomy traits (under different moisture regimes with using phenotyping methods in diverse genetic resources in rice (Table1). Root traits have been claimed to be critical in improving water relation which in turn increases yield, apart from nutrient absorption under moisture stress (Serraj et al., 2004; Li et al., 2005; Lynch 2007; Araus et al., 2008; Songsri et al., 2008). Despite a few contradicting evidences, there is equivocal consensus on the importance of root traits for drought adoption (Pantuwan et al., 2002). Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 6
Water before reaching transpiring leaves; it must penetrate through a series of concentric cell layers. In rice, these layers include the root epidermis, hypodermis (exodermis), schlerenchyma layer, several layers of cortex cells, endodermis, pericycle, and xylem vessels. Once water has reached the xylem vessels, it moves axially toward the aerial parts of the plant. Rice root anatomy characteristically exhibits cortical aerenchyma, which are associated with gas transport to roots growing in anaerobic conditions (Steudle and Peterson, 1998).Aerenchyma formation has been observed under drought conditions in both aerobic and lowland genotypes, although to a lesser extent than under flooded conditions (Colmer et al., 2003, Suralta and Yamauchi, 2008). The extent and rate of Casparian band and suberin lamella formation depend on environmental conditions (drought, hypoxia, salt, heavy metal, and nutrient availability) (Hoseet al. 2001) Typically, a greater degree of Casparian band and suberin lamella development resulted in less water permeability of the root. Hydraulic conductance of whole root systems in rice has been recently reported in rice roots from both solution and soil culture (Matsuo et al., 2008). In solution culture, root hydraulic conductance was greater in a lowland japonica variety (Koshihikari; previously classified as drought-susceptible) than in an upland variety (Sensho; mildly drought-resistant). Xylem sap flux of lowland variety Koshihikari decreased with decreasing water availability in a water-saving trial, but did not change in two upland varieties (Beodin and Shensho; Matsuo and Mochizuki, 2009b). Aquaporin expression has been reported to correlate directly with root hydraulic (Javot et al., 2003 in Arabidopsisand Sakurai et al., 2005 in rice). Table 1: Diversity of Root traits and function in plant (restructured from Gowda, et. al. (2011)) Root character Proposed functions References Root length Potential for absorption of soil moisture and nutrients in deeper soil layer Nicou et al., 1970; Kato et al.,2006 Root branching Power of soil exploration(the major contribution to total root length) Fitter, 1991; Ingram et. al.,1994 Root diameter Potential for penetration ability, branching, hydraulic conductivity Armenta-Soto et al.,1983 Root dry weight To explore a greater soil volume Yadav et al., 1997 Root length density Rate of water and nutrient uptake Mohankumar et al., 2010 Root number Physical strength, potential for root system architecture Armenta-Soto et al.,1983 Root pulling force For root penetration into deeper soil layers O Toole and Bland,1987 Root to shoot ratio Assimilate allocation Yoshida and Hasegawa,1982 Root volume The ability to permeate large volume of soil Mohankumar et al., 2012 Hardpan penetration ability Ability to penetrate subsurface hardpans Babu et al., 2001; Clarket al., 2000, 2008 Deep root to shoot ratio Potential for absorption of soil moisture and nutrient in deeper soil layers Yoshida and Hasegawa,1982 Hydraulic conductivity Rate of water uptake Henry et al., 2011 7 Rajesh Kumar Singhal
Table: 2 Rice root anatomy and function in plant Traits Functions References Cortical aerenchyma Associated with gas transport to roots growing in anaerobic conditions. Colmer et al,(2003) Apoplastic barriers Water uptake and transport Kondo et al, (2000) Root hydraulic conductivity Affecting water movement. Ranathunge et al, (2003) Xylem sap flux Decrease in drought condition Matsuo and Mochizuki, (2009) Aquaporin expression Correlate directly with root hydraulic conductance 2.5.2Importance of WUE in crop productivity Javot et al, (2003) Apart from root traits other important traits which can has stimulated yield under water limited condition is Water use Efficiency (WUE). At whole plant level water use efficiency is defined as the ratio of biomass produced to water used. According to Passioura (1996) crop yield is given by Seed yield (Y) = Water Use (T) x Water Use Efficiency (WUE) x Harvest Index (HI). Where T is the water transpired, HI is the harvest index; ratio of the economical yield to total biomass produced which has already stagnated in most of the crops. Therefore at a given level of T, breeding for improved water use efficiency may be beneficial for improved productivity under water limited condition. Mostly yield improvements have achieved by increasing the transpirational component through management and breeding, and by increasing HI in certain grain crops (Austin et al., 1978). C 4 species typically have a WUE of 4 to 5.5 g. kg-¹ compared to the C 3 species (1.5 3.0 g. kg-¹). Perhaps because of this trait, the C 4 species have significantly higher productive compared to the C 3 species under arid and semi-arid tropics where water availability is the major constraint. These observations suggest that improving WUE of our crop species have relevance with crop productivity. 2.5.3 Carbon Isotope Discrimination Plants discriminate against the heavy isotope of carbon ( ¹³C) during photosynthesis diffusion process resulting in the depletion of the ¹³C content in the biomass (O Leary, 1981). this deviation of the carbon isotopic ratio (13C/12C) of biomass from that of air, called discrimination (D¹³C) is related to the ratio of the partial pressures of CO2 inside the leaf to that in ambient air (Pi/Pa) (O Leary, 1981; Farquhar et al, 1982; Farquhar et al, 1989a; Hubick and Farquhar, 1989) as follows; ¹³C = a + (b a) Pi/ Pa, (eq-2) Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 8
Where, a and b are fractionation against ¹³C during diffusion through stomata and carboxylation by RuBisCO respectively. Pi and Pa are partial pressures of CO 2 in air and inside the leaf tissue, respectively. Since WUE is also related to the CO 2 partial pressures, at a given VPD, a strong inter-relationship between ¹³C and WUE is expected (Hubick and Farquhar, 1989; O Leary, 1993). There are two naturally occurring stable isotopes of carbon, ¹²C and ¹³C. Most of the carbon is ¹²C (98.9%) with 1.1% being ¹³C. The overall abundance of ¹³C relative to ¹²C in plant tissue is commonly less than in the carbon of atmospheric CO 2, indicating that carbon isotope discrimination occurs during the incorporation of CO 2 into plant biomass. Because the isotopes are stable and non-radioactive in nature, the information is inherent in the ratio of abundance of carbon isotopes, presented by convention as ¹³C/¹²C, is invariant as long as carbon is not lost. The ¹³13C in plant samples is generally determined using a sophisticated analytical instrument called Isotope Ratio Mass Spectrometer (IRMS) specially designed for high precision measurements of the ratio R, defined as: R = ¹³CO2/¹²CO2 (eq-3) The plant material is converted to CO₂ by combustion to determine the isotope composition. In general R is low in organic sample. The atmosphere has a relatively higher fractionation value of around 7.8 per mil ( ), which is in comparison with a standard PDB (Pee Dee Belemnite, from North Carolina, USA). The R in this standard is 0.0124 and in many of the plant material it is approximately 0.012, suggesting a very minor changes in the R value, and hence R in a sample can be compared with that of standard and expressed as 13C in units per mil or parts per thousand ( ). ¹³C = Rsample Rstandard/Rstandard * 1000 (eq-4) Since the organic sample has less R-value than the standard, ¹³C of organic material is more negative, i.e., less ¹³C content hence more discrimination and vice versa (O Leary, 1984). 2.5.4. Relationship between ¹³13C and WUE Carbon isotope discrimination is a function of Pi/Pa. Both stomata conductance (g s ) and chloroplast capacity determine the differences in Pi and hence, these two parameters would also control the variability in ¹³C. WUE = {(1 -θ) (b d-θ)}/1.6v (b a) (eq-5) Where, θ is the proportion of fixed CO2 lost in respiration, V is the leaf-air vapor pressure gradient. An inverse relationship between A/gs and ¹³C (Meinzer et al., 9 Rajesh Kumar Singhal
1990; Richards and Tieszen, 1993) and a positive relationship between Pi/Pa and ¹³C signify that Pi determines the variability in ¹³C (Hubick et al., 1988; Gutterrez and Meinzer, 1994). Plant WUE in pot grown sunflower and negative relationship was obtained between these two traits in structural carbon both in well watered and drought conditions (Johnson et al., 1993). In wheat, as in other C 3 species, genetic variability in ¹³C is reflected in variation in WUE at both the leaf and at the wholeplant level (Condon and Richards, 1993). 2.5.5 Differentstrategies usedfor root phenotyping Nevertheless, progressing in screening for root traits and capturing genetic variability in this trait has been extremely slow. The main drawback is being difficulty in phenotyping and their use as selection criteria in field-grown plants. A number of techniques are available for the estimation of root traits in the soil profile As an alternative to root phenotyping in field experiments, a number of studies have measured roots in plants grown under controlled conditions. This allows more rapid and accurate analysis of root features. A reasonable compromise to avoid both the unnatural conditions present in hydroponics and/or aeroponics and the difficulty of studying roots in the field is circumvented by growing plants in pots, columns (PVC pipes), root structures, monolith, mini-rhizotrons, and/or observation chambers filled with soil (Smit et al., 2000; Azhiri-Sigari et al., 2000; Wade et al., 2000; Sheshshayee et al., 2011a, b). Apart from these methods for root phenotyping, recently several new methods have been developed for precision phenotyping for yield trait in drought (Table: 3). As Near infra red spectroscopy used for physical and chemical characteristics of the harvested seed material are captured. Several traits can be determined on the basis of a single spectrum (dry matter, protein, nitrogen, starch and oil content, grain texture and grain weight, etc); Montes et al., 2007. Canopy spectral reflectance (SR) and infrared thermography (IRT) measure photosynthetic capacity, leaf area index, intercepted radiation and chlorophyll content Gutierrez et al, 2010. Magnetic resonance imaging (MRI) and positron emission tomography (PET) to investigate root/shoot systems growing in sand or soil which allow assessing structure, transport routes and the translocation dynamics of recently fixedphotoassimilates labelled with short-lived radioactive carbon isotope (d¹¹c). (Jahnkeet al., 2009). Nuclear magnetic resonance (NMR) measure sucrose and water movement imaged and quantified Sardans etal., 2010. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 10
11 Rajesh Kumar Singhal Table:3 EMS induced mutant and their function in plant Mutant/Gene name Physiological function Mutagen References Brassinosteroid insensitive mutant Hypocotyl elongation and primary root inhibition assay EMS Clouse et al.,(1996) Cpr (Constitutive expresser of PRgenes) Resistant to two virulent pathogens, fseudomonas syringae pv maculicola ES4326 and feronospora parasitica NocoS; EMS Bowling et al.,(1997) Starch less mutant Alterations in Growth, Photosynthesis, and Respiration EMS Casper et al., (1985) Ahr1(altered hydrotropic response) Recover root hydrotropism with cytokinin EMS Saucedo et al.,(2012) moots koom 1 (mko1) involved in the maintenance of the root apical meristem EMS Barrera et al., (2011) CULLIN1 suppressors of Arabidopsis thaliana super root phenotype EMS Pacurar et al., (2014) antifolate insensitive (afi1) folate biosynthetic pathway EMS avarrete et al., (2012) BrMYB4 Suppressor of genes for phenylpropanoid and anthocyanin biosynthesis EMS Zhang et al., (2014) brown midrib (bmr) educe lignin concentration EMS Sattleret al.,(2014) MEF14 (mitochondrial editing factor 14) ROOT HAIR DEFECTIVE3 (RHD3) Specific trans-factor required for C to U editing EMS Verbitskiy et al.,(2011) Anthocyanin overaccumulation phenotype under nitrogen starvation conditions EMS Wang et al.,(2015) rugosa1 (rug1) irregularly shaped leaves and reduced growth EMS Quesad et al., (2013) Scarlet ABA-insensitive (ScABI) reduced grain dormancy EMS Elizabeth C.et al., (2012)
2.6: Mutagenesis source for crop improvement During crop evolution there has been a continuous reduction in genetic diversity. This genetic erosion eventually became a bottleneck and exploiting natural or induced genetic diversity is a major strategy in the improvement of all major food crops. For this various techniques adopted to induce mutations and artificially increase variation emerged in the middle of the last century. Historically the use of mutagenesis in breeding has involved forward genetic screens and the selection of individual mutants with improved traits and their incorporation into breeding programmes. The goal in mutagenesis breeding is to cause maximal genomic variation with a minimum decrease in viability. Initially X-ray radiation was used as a mutagen since it was readily available to researchers. Muller (1927) showed that X -ray treatment could increase the mutation rate in a Drosophila population later Stadler (1928) observed a strong phenotypic variation in barley seedlings and sterility in maize tassels after exposure to X-rays. More sophisticated techniques such as gamma and neutron radiation were developed at research centers. Chemical mutagens are mostly used in research because they are easy to use, do not require any specialized equipment, and can provide a very high mutation frequency. Compared to radiological methods, chemical mutagens tend to cause single base-pair (bp) changes, or single nucleotide polymorphisms (SNPs) as they are more commonly referred to, rather than deletions and translocations. Of the chemical mutagens, EMS (ethyl methane sulfonate) is today the most widely used. EMS selectively alkylates guanine bases causing the DNA- polymerase to favor placing a thymine residue over a cytosine residue opposite to the O-6-ethyl guanine during DNA replication, which results in a random point mutation. A majority of the changes (70 99 %) in EMS mutated populations are GC to AT base pair transitions (Till et al., 2004). Mutant developed by EMS and their functional role is given in (table 4). 2.6.1 Induced mutant as a source for functional genomics Rice is the first sequenced crop plant (Goff et al., 2002; International Rice Genome Sequencing Project, 2005; Yu et al., 2002). According to the latest release of the Rice Genome Annotation Project (RGAP 6.1, http://rice.plantbiology.msu.edu/), the rice genome size is ~ 370 Mb. A total of 56,797 loci are predicted, including 40,577 non-te (transposable element) loci encoding 50,939 gene models, and 16,220 TE loci encoding 16,454 gene models. The overall goal of rice functional genomic research is to understand how the genome functions to make the plant and produce phenotype, by deciphering the information conserved in the sequences, including genes and regulatory elements at the whole genome level, also equally important goal is the application of the findings to genetic improvement of rice which may also serve as a model for other crops. 2.6.2: Development of technical and research platform for rice functional genomics The overall goal of the platforms is to provide toolkits and resources for high throughput identification of genes and pathways. Efforts in the last decade have been Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 12
focused on (1) Large mutant libraries (2) Full length cdna (3) Global expression profile and (4) Bioinformatics analyzing and mining of data sets produced by diverse research teams. Mutant libraries Changing expression level or pattern of the gene by knocking-out, knockingdown, overexpression and ectopic expression are among the frequently used strategies for deciphering the gene function. Thus construction of saturated mutant libraries is essential for identification of gene function. Now a day, mutant libraries, making use of several strategies including T-DNA, transposon and retrotransposon insertions, have been developed in a number of laboratories in different countries and can be modified by adding the functional elements such as activation tag, gene trap tag, promoter trap tag and enhancer trap tag. DNA microarray and expression profiling Information of gene expression profile is useful for functional genomics studies. The expression pattern of the gene would provide clue to understanding the gene function. Information about expression of a genome sequence is useful for genome annotation. Furthermore, co-expression analysis lead to identification of regulatory network involving sets of genes. Full-length cdna collections Information provided by full-length cdnas can greatly help annotation of the genomic sequences by identifying transcription units, introns and exons as well as likely promoters, and predicting gene products. Moreover, a collection of full-length cdnas may provide an inventory of gene clones that are frequently needed for gene isolation. Recently, insertional mutant libraries have become a major source of gene cloning, using both forward and reverse genetic approaches. By forward genetic approach, the insertion lines are screened by phenotype, co-segregation between the phenotype and T-DNA insertion is analyzed, and usually a complementation test is performed for further confirmation of the phenotypic effect of the gene. In reverse genetic approach, the candidate gene is used to search the FSTs of the mutant databases, and the mutant obtained is then analyzed forphenotype. Another major approach of cloning genes is functional characterization of genes that show differential expression mostly from microarray analyses (chip-based approach), also most commonly by including functional tests of candidates selected by their homology to known genes. Phenotypic characterization across individuals in a heterogeneous population provides a powerful approach to understanding gene function. Greene et al., (2003) reported that Knockout and missense alleles occur at known frequencies and populations of a few thousand individuals enable searches targeted to specific genes. This approach, called targeting induced local lesion in genome (TILLING). 13 Rajesh Kumar Singhal
2.8 Mutant for genetic or plant breeding and crop improvement approach Crop breeding is important for improving yield and tolerance to for biotic and abiotic stresses. Most crop traits relevant to agronomic improvement are controlled by several loci, including quantitative trait loci (QTL), that lead to minor phenotypic change. To enable plant breeding by marker-assisted selection, it is important to identify the locus or chromosome region harboring each gene contributing to an improved trait. Abe et al., (2012) develop a new breeding strategy to identifying agronomically important loci in rice. A method of rapid gene isolation using a cross of the mutant to wild type parental line in Japanese rice cultivar. MutMap is used to localize genomic position of rice gene controlling agronomically important traits like semi dwarfism, leaf colour and plant height. As mutant plant and associated molecular marker can be made available to plant breeders, this approach could markedly accelerate crop breeding and genetics. MutMap method can use for rice and in other crop to rapidly identify genomic region controlling a causal mutation for a given phenotype. Hiroki Takagi et al., (2015), use MUTMAP breeding approach for developing salt tolerance rice cultivar. So MUTMAP is new breeding approaches which can be used for develop varieties for biotic and abiotic stress line ads drought stress, salt stress, heat stress etc. MUTMAP also important for knowing the genomic position for important agronomically and physiologically traits like plant height, WUE, root trait, and other important trait. 2.9: Recent advances in genomics for analysis of a trait The recent advances in molecular biology techniques have made high throughput genome sequencing, genome characterization, and gene expression analyses faster, cheaper, and more affordable, and some of these techniques can be routinely applied in breeding programs (Collard et al., 2008). Further, the advances in bioinformatics tools and genomics databases have made the processing of molecular information easier and more accessible to the scientific community. Mutants are the best resources for the functional genomics or understand a trait. Hirochika et al., 1996reported positional cloning approach, systematic functional genomics approaches to screen mutants using insertion mutagenesis. Integration of the omics tools and techniques accelerated the crop improvement programme by understanding the causal mutation at molecular level. Molecular variation in DNA was first start with RAPD, RFLP, AFLP, and SSR marker. Due to reliability and specificity, SSR marker most commonly used for looking variation in DNA caused by deletion and insertion. To identify the SNPs resulted by single base substitution with chemical mutagens like EMS is challenge. Rice has more than 20,000 SSR markers and over one million SNPs and Indels, which include both functional and non-functional markers (Mcnally, et al., 2009; McCouch et al., 2010). This has opened up huge opportunities for the use of molecular markers in diversity analysis, mapping genes/qtls for various agronomic traits under drought, and their use in marker-assisted breeding (MAB) and also in positional cloning of QTLs to identify candidate genes for complex traits. Single nucleotide polymorphisms (SNPs) are becoming the markers of choice in breeding programs. Several SNP chips have been developed based on genome sequence information and are available for large-scale genotyping. Next-generation sequencing (NGS) technologies such as Roche (454), GSFLX sequencer, Illumina Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 14
genome analyzer (Solexa), Applied Biosystems SOLiD sequencer, and HeliScope have made the resequencingof several rice genomes possible. The low sequencing costs associated with these technologies created huge opportunitiesfor large-scale genotyping to discover novel genes for allele mining (Varshney et al., 2009). 2.10 Homeobox gene and their function in plant development Homeobox genes are large family of transcription factor which encode a typical DNA-binding domain of 60 amino acids, known as homeodomain (HD) and conserved motif in all eukaryotes. The homeo-domain (HD) folds into a characteristic 3D structure containing three alpha-helices, in which the second and third form a helix-turn-helix motif. Ghering et al., 1994 reported first homeobox genes from the fruit fly Drosophila melanogaster and were subsequently found to be involved in many aspects of development. Erik volbrecht and co-worker in 1991 identified first homeobox containing gene KNOTTED1 in maize by transposon tagging. Table 4: The four HD-Zip subfamilies and their function Subfamily Functions References p I Response to abiotic stress Olsson, A.S.et al. (2004) Response to abiotic stress Gago, G.M. et al. (2002) De-etiolation Henriksson, E. et al. (2005 Blue light signaling Wang, Y. et al. (2003) p II Response to illumination conditions Rueda, E.C. et al. (2005) Shade avoidance Morelli, G. and Ruberti, I. (2002) Response to Auxins Sawa, S. et al. (2002) p III Embryogenesis Prigge, M.J. et al. (2005) Meristem regulation Baima, S. et al. (2001) Lateral organ initiation Otsuga, D. et al. (2001) Leaf polarity Mallory, A.C. et al. (2004) Vascular system Development Kim, J. et al. (2005) Auxin transport Mattsson, J. et al. (2003) p IV Epidermal cells differentiation Abe, M. et al. (2003) Anthocyanin accumulation Kubo, H. et al. (1999) Root development Nakamura, M. et al. (2006) Trichrome development Perazza, D. et al. (1999) 15 Rajesh Kumar Singhal
Hawker et.al (2004) have confirmed the role of Hox10 as a transcription factor which has a role in root growth and development and has similar role with REV gene a class-iii HD-ZIP family of transcription factor. Co expression In -silico analysis of HOX10 revealed various genes like GRAS family transcription factors known as short root gene are expressed with the HOX10 gene. Reports show that GRAS is involved in the control of root radial patterning and root growth in Arabidopsis thaliana. This transcription factor regulates root growth by producing single layer of endodermis (Helariutta et al., 2000). Genome wide survey of rice revealed 33 hox genes. The differential expression done by revealed specificity of expression with HOX genes. So the H0X gene is important for development. Carlsbecker et al.,2010, reported that in the Arabidopsis root meristem, mir165/166 are produced mostly in the endodermis layer, but they spread into other cell layers to suppress HD-ZIP III expression. Zhu H et al., 2011 reported that AGO10 (also known as PINHEAD or ZWILLE) gene is required for SAM maintenance. Expression levels of HD-ZIP III transcripts are decreased in ago10 mutant. AGO10; that is, sequestration of mir165/166 to protect HD-ZIP III mrnas. Sumanth kumar (2014) Targeted resequencing for 115 genes in high root mutant N22BADT-392-9-1, low root mutant N22BADT-491-3-2, and wildtype-n22 revealed a total number of 950 SNPs. Among the SNPs identified 3 No synonymous SNPs one each in HOX10, Zeaxanthin epoxidase and citrate synthase genes were identified in high root mutant N22BADT-392-9-1 alligned with N22-wildtype.The Non-synonymous SNP in HOX10 changed amino acid from arginine to leucine has role in lateral root development Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 16
III MATERIAL AND METHODS Nagina 22 (N22), an upland rice variety was mutagenized using Ethyl Methane Sulphonate. Mutagenized seeds of M2 generation were obtained from NRCPB, New Delhi (Mohapatra et al., 2014). This material was screened in M2, M3 and M4 generation for roots, water use efficiency and yield (Sumanth, 2014). Contrasting root mutants (high root mutant N22 BADT _392_9_1 and low root mutant N22 BADT_491_3_2) were selected from the stabilized M4 population, and were advanced till M6 generation. This material has been used in the present study for development of MUTMAP population. 3.1 Physiological characterisation of high root mutant (392-9-1), low root mutant 491-3-2 & wild type (N22). A gravimetry experiment was conducted for physiological screening of the high root mutant (N22 BADT-392-9-1), low root mutant (N 22 BADT-491-3-2) and wild type (N22). Details of the experiments Before sowing, empty pot weights were taken before pot filling and the known weight of soil is added for all the pots. About 4 seeds weresown in each pot, eight replicates (pot) for each cultivar was used. Therecommended dosage of fertilizers to be applied was calculated based onsoil volume in the pots. Later, the plant population was thinned to maintain two plants per pot. All the pots were irrigated to maintain 100 per cent field capacity until 35-40 days after sowing (DAS). Prophylactic plant protection measures were taken to contain the damage by pests and diseases.at 40 DAS, the drainage holes of the containers were closed using cementpaste. The exposed soil surface in the containers was mulched by spreading pebbles (500 g) to reduce soil evaporative losses. The weight of individual container with soil at field capacity, plastic pieces and plant was recorded with the help of a mobile electronic load cell balance of 60 kg capacity with a resolution of 100 g. The load cell balance was fixed on a mobile gantry system with a provision for movement along the rails horizontally to access every pot. The containers were placed in an open area and protected from any external moisture entry (rain interruption) by using a mobile rain out shelter (ROS). Whenever required and during nights the ROS was drawn over the experimental area, thus the containers were maintained at specified water regime Once the plants have produced sufficient leaves, the moisture stress was imposed. Two levels of moisture regimes were maintained in the pots by withholding / regulating watering. The experimental details are as follows. Number of contrasting lines = 3 Treatments: T1 = 100 % FC T2 = 70 % FC Number of replications = 8 Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 17
In each pot, two uniformly grown plants were maintained. Soil moisture stress was imposed gradually following gravimetric approach. Before the imposition of stress, the initial observations on plant height and number of leaves were recorded. Once the desired level of stress was reached (70 % of FC), the same level of stress was maintained for the next 30 days following gravimetric approach. During the experimental period, several physiological parameters were also recorded besides quantifying the EWC once again in the contrasting genotypes both under 100 % and 70 % FC. 3.2 Creation and imposition of desired levels of stress following gravimetric approach In order to create and impose the desired level of moisture stress in pots, containers weight was measured initially and a known weight of planting mixture (Soil + FYM) was filled. To this, sufficient water was added until soil capillary pores were completely filled with water. When the excess water was drained out, the pot weight with wet soil was taken to arrive at the weight of the pot at 100 % FC. To arrive at the soil moisture content at 100 % FC, the dry soil weight along with empty pot weight was deducted from the wet soil weight. Once the soil moisture content is known to attain 100 % FC, the water requirement to attain desired level of stress and in this, case70 % FC was determined and accordingly, the required amount of water was added to the designated pots. Therefore, the weight of the pots for a desired level of stress should be as follows. Weight of individual pot at a desired level of stress = (empty pot weight + known weight of dry soil + the required amount of water to reach desired level of stress) As the moisture stress was created gradually, the individual pots were weighed every day until the desired level of stress was reached. Initially to begin with, the soil moisture status in each pot irrespective of the treatments was at 100 % FC. However with time, through evaporation and transpiration, these pots started losing water and for those pots which were designated as 100 % FC, were replaced with the same amount of water, while for those pots designated as 70 % FC, the water was not added until they reached designated level of field capacity. This was done every day by weighing all the pots. Once the desired level of stress was created and in order to maintain the desired level of stress throughout the experimental period, the pots were weighed every day and whatever the loss of water occurred was added to see that the soil moisture stress reached to the desired level. Observations The following observations were recorded during the experimental period. Cumulative Water Added (CWA) Whole plant leaf area at the beginning and end of the experiment Total dry matter accumulated at the beginning and end of the experiment. 18 Rajesh Kumar Singhal
Based on these primary observations the following parameters werecomputed Cumulative Water Transpired (CWT) Water Use Efficiency (WUE) Mean Transpiration Rate (MTR) Net Assimilation Rate (NAR) Total dry matter accumulation (TDM) Entire plants including roots were harvested by washing with water without causing any damage to the roots and oven dried at 80 o C for three days. The biomass accumulated during the experimental period was computed as the difference in initial and final dry matter, expressed as gram per pot. Functional leaf area (LAD) Leaf area duration (LAD) is a reflection of functional leaf area available for assimilation of photosynthates during the experimental period. LAD was calculated using following formula: Where, LAD = L2 L1_ 2 Number of days L1: initial leaf area L2: leaf area at the end of experiment (final leaf area) Cumulative Water Transpired (CWT) The amount of water added daily to each container after weighing to bring back the soil to 100 per cent field capacity (FC) was summationed individually for each pot during the experiment period (50 to 79 DAS) and was expressed as cumulative water added (CWA). Evaporation loss was determined by weighing the empty pots. The soil evaporation was removed from the CWA to arrive at the cumulative water transpired (CWT). CWT = CWA CWA* Where, CWA: cumulative water added to each pot. CWA*: cumulative water added to empty pot. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 19
Mean transpiration rate (MTR) The total transpiration over the entire experimental period was measured as the mean transpiration rate. This parameter was arrived by computing the ratio of cumulative water transpired to the functional leaf area and is expressed as gram or ml of water per day (Lm -2 day -1 ). The MTR is considered as the time integrated measure of Transpiration. MTR = CWT/LAD 3.3 Water Use Efficiency (WUE) Measurement of Water use efficiency by gravimetric approach involves the measurement of total dry matter (TDM) accumulated over a period of time and the total water transpired by the plant during the same period. The ratio of the TDM during the experimental period tothe total water transpired was computed to arrive at the whole plant WUE and expressed as gm/kg of water transpired. WUE = Where, DM₂-DM₁/ CWT DM1: dry matter at beginning of experiment (50 DAS). DM2: dry matter at end of experiment (79 DAS) CWT: cumulative water transpired. 3.4.1 Net Assimilation Rate (NAR) This was computed using the dry matter accumulated during the experimental period and functional leaf area of that period, and expressed as mg dm -2 day -1. The net carbon gain, a measure of photosynthates accumulated over time was gravimetrically determined using the following formula: NAR = DM2 - DM1/ LAD Where, DM1 & DM2: are initial and final dry matters. LAD: leaf area functions during the experimental period. The major feature of the gravimetric approach standardized at our centre is that the genetic variability in WUE as well as the physiological traits like MTR and NAR could be determined simultaneously. 20 Rajesh Kumar Singhal
3.4.2 Photosynthesis related traits Gas exchange Gas exchange traits such as net CO 2 assimilation rate (A), stomatal conductance (gs), intercellular CO 2 concentration (Ci) etc., were measured using portable photosynthesis system. LI- 6400 (LICOR 6400, Lincoln, Nebraska, USA). Principle of IRGA Infrared Red Gas Analyzers (IRGA) were used for the measurement of a wide spectrum of hetero-atomic gas molecules including CO 2, H 2 O, NH 3, CO, SO 2, N 2 O, NO and gaseous hydrocarbons like CH 3. Heteroatomic molecules have characteristic absorption spectra in the infrared region. Therefore, absorption of radiation by a specific hetero-atomic molecule is directly proportional to its concentration in a given air sample. LICOR- 6400 This equipment, Li 6400 (LiCOR-Inc. Lincoln, Nebraska, USA), operates in the open mode, which facilitates the maintenance of constant CO 2 and water vapour concentrations in the leaf chamber during measurements. The change in the CO 2 concentration and water vapour was determined by separating infrared gas analyzers, which are located in the leaf chamber. This ensures real time measurements of gas exchange parameters. This system consists of the main console and a leaf chamber. The main console is equipped with a peristaltic pump and the necessary software for the computation of gas exchange parameters from certain primary values measured by the equipment. This software permits precise control of the flow rate, CO 2 and water vapour concentrations in the leaf chamber. The leaf chamber which also houses the IRGA has an external as well as an internal quantum sensor to determine photon flux density in the PAR range. The leaf chamber has a provision to expose a leaf area of 6 cm2 at the sensor head. A thermocouple is placed in such a way that it would touch the leaf to determine leaf temperature. A speed variable mixing fan ensures proper mixing of air in the leaf chamber. Theleaf chamber is also fitted with blue and red LEDs (Light Emitting Diode), which can give a PPFD (Photosynthetic Photon Flux Density) up to 2000 moles m -2 s -1. The leaf chamber is equipped with a Peltier cooling system that can maintain the chamber temperature. The operational option provided with the system also maintains a constant chamber RH around that of the ambient air. CO 2 control A CO 2 cartridge normally carrying 8 g of pure CO 2 in liquid form was used to get the requisite CO 2 concentration in the leaf chamber. With some minor replacement of scrubbers, ambient air could also be conveniently used for measuring photosynthetic traits at ambient CO 2 concentration. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 21
Observations The instrument measures the following primary parameters: a. Volume flow rate of dry air into the cuvette (cm 3 s -1 ) b. Photon flux density incident on cuvette (moles m -2 s -1 ) c. CO 2 concentration and water vapour pressure of air entering and leaving the leaf cuvette d. Leaf area (cm 2 ) e. Boundary layer resistance to water vapour (m 2 s -1 mol -1 ) f. Leaf temperature Using several physical constants and measured parameters, the equipment computes the following gas exchange parameters: 1. Stomatal conductance to water vapour (mol m -2 s -1 ) (g s ) 2. Photosynthetic rate (µmol m -2 s -1 ) (A) 3. Transpiration Rate (mole m -2 s -1 ) (T) 4. Sub-stomatal cavity CO 2 concentration (Ci) (ppm) Recording gas exchange parameters The gas exchange parameters were recorded on the second fully expanded from the apex (leaf emerged during stress period). The leaf was clamped to the leaf chamber and the observations were recorded when A, g s and Ci reached a steady value. All gas exchange parameters were recorded between 9 am and12 pm on bright sunny days. The leaf chamber is equipped with a peltier cooling system that can maintain the chamber temperature. The operational option provided with the system also maintains a constant chamber RH around that of the ambient air. Determination of specific leaf area (SLA) in the contrasting genotypes of rice In order to determine the SLA, the leaves from all the genotypes were removed and immediately the leaf length and width was measured, the leaves were kept for drying and end of which, the dry weight was recorded. Following the formula given below, SLA was determined in all the genotypes and compared with EWC. SLA = (LL LW/ LWt) (cm 2 g -1 ) Where, LWt= Leaf weight LL= Leaf length LW= Leaf width 22 Rajesh Kumar Singhal
Determination of stomatal frequency in the contrasting genotypes of rice Xylene and thermocoal paste was smeared on the both side of the leaves and was allowed to dry. The epidermal imprint was then peeled off and was put onto a glass slide with cover slip to observe under microscope. The number of stomatal per microscopic field was counted to estimate the stomatal frequency. Stomatal frequency was calculated using the formula given below. Stomatal frequency = Stomatal number/ unit leaf area Area covered at 40x magnification is 0.00086 cm 2 Determination of leaf nitrogen status as indicated by SPAD meter Leaf nitrogen status is normally manifested with the leaf chlorophyll content. A device developed by Minolta corp., Ramsey, NJ measures the light attenuation at 430nm (the peak wavelength for chlorophyll a and b absorption) and that at 750 nm (near infrared) with no transmittance. The unit less value measured by the chlorophyll meter (SPAD-502) termed as SCMR (SPAD Chlorophyll Meter Reading), is a good estimate of chlorophyll content and hence N content. The SPAD meter (Soil Plant Analysis Development) is a simple hand held equipment which operates with DC power (Volts) and is portable. SCMR values were recorded in the selected mutants. The third fully expanded leaf from the apex was used for the SCMR determination. Several measurements were made on each leaf and averaged to make an approximate estimate of leaf chlorophyll and hence the leaf N status of the plant. Carbon isotope discrimination: Stable carbon isotope ratio was measured using an Isotope Ratio Mass Spectrometer (Delta plus, Thermo Fischer scientific, Bredmen, Germany) interfaced with an elemental analyzer (NA112, Carlo-Erba, Italy) through a continuous flow device (Conflo-III, Thermo Fischer scientific), installed at the Department of Crop Physiology, UAS, Bangalore. Dried leaf samples used for estimating SLA were ground to a fine powder with a ball mill. Carbon isotope discrimination ( 13 C), expressed in per mill ( ), was computed as per the notation proposed by Farquhar et al., 1989. 13C = (δ 13 Ca-δ 13 Cp)/ (1+δ 13 Cp/1000) Where; δ 13 Ca and δ 13 Cp are the carbon isotope composition of atmospheric air and plant sample, respectively. The δ 13 Ca was considered as -8 for the computation. The analytical uncertainty was better than 0.15 which was determined by using an external standard calibrated against international standards such as ANU-Sucrose (Potato starch, Sigma Aldrich δ13 = -26.85 ). Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 23
3.5 Crossing of high root mutant (392-9-1) & wild type (N22) to generate MUTMAP population A high root mutant N22BADT-392-9-1 was crossed with the wild type (N22). The crossing was performed at ZARS, V.C. farm, Mandya. True F 1 plants were identified using SSR markers andselfed to generate a segregating F 2 population. This population comprising of 250 segregates was characterized for phenotypictraits (root related traits) and segregation of HOX10 allele. Phenotyping for the F 2 populations: Initially F 2 phenotyping for roots was carried out in a standardized hydroponic system at Department of crop physiology, UAS, Bangalore (Plate: 5). Root length and lateral root number was measured at 20 and 30 days after sowing. After 30 days the seedlings were transplanted to the root structure to measure root and other physiological traits. A simple method for the determination of root traits in young seedlings was developed and standardized by growing young seedlings on plastic tubes that are 50 X 25 X 20 cm 3 filled with Hoagland solution. Germinated seedlingswere fixed to small hole of thermocoal sheet using cotton plug. The thermocoal sheets were then floated over the Hoagland solution in plastic tubs in such a way that the young growing root tips were in contact with the Hoagland solution. Air circulation was provided using air circulation motor. Root length: Roots length was measured without disturbing using 30 cm scale. Root length was expressed in centimeters. Lateral root numbers Lateral Roots arising from root primordium was countedat 7 day interval. Phenotyping for root traits in root structures: Plants were raised in specially constructed root structures that measured 150 cm tall, 300 cm wide and 1800 cm long. An additional 150 cm tall wall was built in the middle of the structure all along the length to make two halves each 150 cm wide. Top soil dug out from another field was transported to fill these structures. Soil was compacted to mimic the real field conditions. Seedlings were transplanted in a randomized block design (RBD) with three replications. Plant population was maintained with 25 X 25 cm spacing, which ensured that plants experienced the inter-plant competition as in field conditions thus leading to more realistic phenotypic expression. The soils in the GKVK campus had been previously estimated to hold 23 % water (W/W) 24 Rajesh Kumar Singhal
Flow chart: Generation of F 2 MUTMAP population by crossing high root mutant (N22_BADT_392_9_1) with wild type (N22), Note: The strategy of MUTMAP strategy is applied mainly in F 2 generation. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 25
Plate 1: Picture depicting the crossing process of N22 (female) and 392-9-1 (male) for development MUTMAP population. Note: Emasculation was done in early morning 6 am and male parent pannicle was incubated in high light and high RH. Dusting was done at 11am. 26 Rajesh Kumar Singhal
at 100 % field capacity. On an average, surface irrigation was provided once every 5 7 days to bring the soil to 100 % FC. On the 80 th day after sowing (DAS), the side walls of root structures were dismantled and roots were extracted carefully with a jet of water to wash away the soil from roots. Roots were separated from the shoot and several parameters including root length, root volume were recorded before transferring the plant parts to a drying hot air oven. The samples were oven-dried at 70 0 C and their weights recorded after the Dry weights reached constant values. Root structure dismantling Root structure was dismantled by removing each brick units at 80days after sowing (50 % flowering). High pressure of water was applied tothe soil in the structure and roots were taken without damaging alongwith the whole plant. Roots were separated from the shoot at the node between the shoot and the root. Observations Recorded Shoot length: The shoots were separated from the plants and the shoot length was recorded using a graduated scale. Root length: The roots were separated from the plants and the root length was recorded using a graduated scale Root volume: A known volume of water was taken in a measuring cylinder, and the separated roots were immersed into this beaker and then the volume of displaced water was taken as the root volume which is expressed in cm 3. Total leaf area: All the leaves were collected separately and ovendried at 70 0 C for at least 48 hrs to determine the leaf dry weight.immediately after drying, the leaves were weighed and the total leafarea was computed by multiplying leaf weight with SLA. Total leaf area (cm 2 p -1 ) = total leaf dry weight (g p -1 ) x SLA cm 2 g -1 Shoot weight: All shoots were collected separately and oven dried at70 0 C for 48 h to determine the dry weight for other biometric analysis. Root weight: Roots were washed from the structure, then oven-driedat 80 0 C for 48 h and dry weights were recorded. Deep root weight: The weight of root below 30 cm was recorded as deep root weight Total biomass (TDM): The biomass accumulated during theexperimental period was computed by summing up leaf, stem androot dry weights. Specific leaf area (SLA): Calculate area of the leaf (L x B) and divide it by leaf weight. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 27
3.6 Selective genotyping for HOX 10 allele in F 2 segregating population Based onroot length and root volume the F 2 population was divided into 4 groups. 1. High root length, high root volume 2. High root length, low root volume 3. Low root length, high root volume 4. Low root length,low root volume Genotypes were selected from each group for genotyping for HOX10 allele 3.7.1 DNA extraction The young leaves of the parents and selected F 2 progenies were collected and frozen in liquid nitrogen. DNA was extracted from all the samples using CTAB method explained by Saghai Maroof, et al., 1984. Procedure 1. One gram of fresh young leaf was powdered using liquid nitrogen. 2. The ground tissue was transferred to a 2.0 ml eppendorf tubes by adding 1.0 ml of CTAB buffer (Extraction buffer- 2 % C-TAB, 1.4 M NaCl, 20 mm EDTA (Disodium) & 10 Mm Trisbase (ph 8). Then 15 µl of β- mercapta ethanol was added to each tube. 3. The extract was mixed by inverting the tubes several times then tubes were incubated in a water bath at 65 0 C for an hour with constant stirring at an interval of 15 minutes. 4. After an hour, 700 µl of chloroform: isoamyl alcohol (24:1) was added to the incubated sample and mixed well by inverting. The tubes were then centrifuged at 6000 rpm for 20 minutes. 5. The aqueous upper phase was carefully transferred using the 1mL cut tips into fresh sterile eppendrof tubes. To this supernatant, 5µL of RNAase (10mg/µL) was added into the DNA solution and incubated at 37 0 C in a water bath for 1 hour to remove RNase. 6. Again the DNA solution was further purified by washing with equal volume (500 µl) of phenol: choloroform:isoamyl alcohol (25:24:1) by inverting several times and centrifuging at 6000 rpm for 15 minutes to separate the two phases. 7. The aqueous upper phase was carefully transferred using the 1mL cut tips into fresh sterile Eppendorf tubes. To this supernatant, 0.7 volume (10.5mL) of cold isopropanol was added. 28 Rajesh Kumar Singhal
8. The tubes were carefully inverted and kept for 30 minutes on ice or in -20 0 C to get DNA precipitation. The tubes were then centrifuged at 6000 rpm for 20 minutes and sedimentation of DNA as a hard pellet was seen. 9. The pellet was washed twice by suspending in 1mL of 70 % ethanol for 5 to 10 minutes and the DNA was centrifuged at 6000 rpm for five minutes. 10. Ethanol was drained off slowly and the pellet was air dried. The pellet was then dissolved in 500µL of TE buffer by flicking the tubes. (Sterile H 2 O /TE buffer = 0.1mM Tris + 0.05 mm EDTA) 11. The extracted DNA was subjected for checking quality and quantification using both Biospec-nano (Spectrophotometer for life science) and by 0.8 % agarose gel electrophoresis. 3.7.2 DNA purity and quantification Using advanced automated DNA quantifier Biospec-nano (Spectrophotometer for life science), the ratios between 260 nm and 280 nm was estimated and used to estimate the DNA purity. Pure DNA samples will have a ratio of 1.8 to 2.0. If the sample is contaminated by protein the ratio will be significantly less than 1.8. Ratio of 2.0 or more indicates a high proportion of RNA in the sample. With this information the pure DNA prepared (ratios of 1.8 to 2.0) and further dilution was performed. All the samples were diluted to a final concentration of 15 ng/µl. Preparation of agarose gel Agarose was weighed (0.8or 3.0g, for genotyping) and taken in a clean 250mL conical flask. To this 100 ml of 1x TBE buffer was added. [TBE buffer contains; 0.89M Tris base, 0.02 MEDTA, 0.89M Boric acid) ph = 8]. Agarose was dissolved by heating. After agarose completely melts, it was cooled to 60 0 C and 3.5 µl of ethidium bromide was added (10mg / 3.5 µl) and mixed. Casting trays ends were sealed with tapes, comb was inserted and agarose was poured, allowed to solidify. After solidification the tape on either side was removed and the gel tray was immersed in electrophoresis tank containing 1x TBE buffer. Then the comb was removed. To genomic DNA (3µL) or PCR amplified samples (15 µl,), 3µL of 6x loading dye (Loading buffer or tracking dye 6x 40 % sucrose, 0.025 % bromophenol blue, 0.25 % xylene cyanol) was added, mixed well and loaded into the well. 3µL of standard uncut Lambda DNA and 100bp ladder was used as marker for DNA check, and PCR amplified samples respectively. Electrophoresis was carried out at 120 V for 1 to 2 hours until the bromophenol blue dye migrated two-thirds of the gel. The gel tray was removed and the gel was observed under UV trans-illuminator and documented using VILBER LOURMAT gel doc system (version 14.2). Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 29
3.7.3 Standardization of annealing temperatures Primers were custom synthesized from Bioserve Biotechnology Pvt. Ltd, Hyderabad and were diluted to 5 pmole µl -1 concentration. The annealing temperature was standardized by setting up gradient for each primer to get locus specific amplification. The gradient temperature was set based on the melting temperature (T m ) of the primer i.e., +/-5 o C of T m. Total PCR amplifications were performed in a reaction volume of 10µL containing 1µL (25 ng/µl) of genomic DNA template, 1.0µL Taq buffer (1X), 1.0µL of dntps (2.0 mm), 1.0µL (5 pmole µl -1 ) forward primer and reverse SSR primers, 1U of Taq polymerase and 5.60 µl of sterile water. The PCR cycling conditions consisted of 94 0 C for 5 min for initial denaturation followed by 30 cycles consisting of 94 0 C for 1 sec denaturation, annealing temperature at 50-62 0 C (depending on the specific primer sequence) for 45 sec and 72 0 C for 2 min polymerization. A final treatment of 72 0 Cwas provided for a period of 10 min for final extension of the amplicons. DNA amplifications were performed using eppendrof master cyclers. 3.8 Genotyping for HOX 10 allele DNA was extracted from parents and 20 genotypes, (5 each from the 4 groups formed by considering the root traits). Part of the HOX10 gene containing SNP was amplified with gene specific primer (FP-GTTGTGCTTGCTTGGCTCC, RP- GCAAGTATGGGGCACTCAC) and the amplified PCR product was forward and reverse sequenced by Sanger sequencing (Chromos Biotech, Bangalore). The forward and reverse sequences were aligned using CLASTALW software. The same software was again used for presence of SNP in above mentioned groups. 30 Rajesh Kumar Singhal
IV EXPERIMENTAL RESULTS Understanding the molecular and genetics of root traits has paramount significance in improving crop productivity in water limited conditions. This understanding can be achieved by the adoption of forward and reverse genetic approaches. Considering the importance of forward genetic approaches, significant progress in QTL mapping and fine mapping the QTL region governing root traits have been achieved. Developing and characterization of mutant population is also a useful approach for discovering genes that may control root growth. From this context a stabilized population of EMS induced mutants in the background of a drought tolerance upland rice cultivar N22 was developed at our collaborating center (IARI) and extensively characterized at our center UAS (B). The mutants were phenotyped for various traits related to drought adoption and specific contrasts were identified in previous studies. The major goal of this investigation was to develop a segregating population by crossing a promising mutant with the wild type. Phenotypic characterization and a bulk segregation analysis with specific gene that have a certain role in drought adoptive traits were performed to provide functional relevance to specific genes. The result obtained from various chapters described here. Objective 1: Generation of F₂ MUTMAP population by crossing high root mutant with wild type (N22) 4.1 Characterization of identified mutants in water control and limited condition. The selected mutant mainly N22_BADT_392_9_1 which has high root biomass, high root volume, but low root length and a contrasting low root mutant which has low root weight, low root volume and high root length were used for accessing the water use (WU), and water use efficiency (WUE) traits in a well standardized gravimetry approach along with a wild type N22. The total leaf area (TLA), total biomass (TDM) and total water use (CWT) of these lines were measured under well watered and water limited condition (70 % FC). A significant reduction in several of this parameter under stress was noticed. The reduction of total leaf area under stress was highest in N22_BADT_392_9_1 while it was lowest in N22_BADT_491_3_2. Similarly total biomass also showed a significant reduction under stress. The high root biomass mutant N22_BADT_392_9_1 recorded highest reduction in total biomass and total leaf area (Fig. 1A and 1B). Further, cumulative water transpired (CWT) over the experiment also showed a significant reduction under stress and variability under mutants (Fig. 1C). Gravimetry approach provides a unique option to access the physiological traits associated with WUE. Biomass derivative trait: The Net assimilation rate (NAR), a reflection of time averaged Photosynthesis per unit Leaf area and mean transpiration rate (MTR) a measure of stomata conductance show significant variability among the mutants as well as in water stress treatment. NAR Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 29
was high in N22_BADT_392_9_1 both under well watered and water limited conditions and N22 showed the lowest NAR (Fig. 2A). Interestingly the low root biomass mutant, N22_BADT_491_3_2 recorded the highest mean transpiration ratio. N22 recorded the lowest mean transpiration ratio (Fig. 2B). WUE, the ratio of total biomass to the total water transpired, ranged from 2.6 g.kg -1 in N22_BADT_392_9_1 to 2.0 in N22 (well watered). There was an increase in WUE in the wild type and two contrasting mutants when subjected to water limited conditions (Fig. 3A). Carbon Isotope Discrimination ( ¹³C) is often used as a surrogate for WUE, ranged from 22.5 % in N22 (control) to 20.9 in N22_BADT_392_9_1 (control). A subtle reduction in ¹³C is noticed in the two mutants as well as the wild type under water limited conditions (Fig. 3B). A significant variability in root traits was noticed among the mutants. The mutant N22_BADT_491_3_2 has the highest root length under well watered conditions which is comparable to N22. On the other hand, mutant N22_BADT_392_9_1 had a lower root length (Fig. 4A). A significant reduction in root length was noticed in the mutant and wild type when the plant experienced water limited conditions. A contrasting picture emerged when the other root parameters were compared. Root biomass was highest in N22_BADT_392_9_1 as compared to N22. Similarly root volume was also significantly high for mutant N22_BADT_392_9_1.To assesses the extent of biomass in deeper profiles of soil the deep root biomass was computed by measuring the root biomass longer than 30cm. Both N22_BADT_392_9_1 and N22 has higher biomass both under well watered and water limited conditions (Fig. 4D). Deep root biomass in N22 decreased significantly under water limited conditions while N22_BADT_392_9_1 had a significantly higher root biomass in deeper profile in the soil. Gas Exchange Parameters: Gas exchange parameters, Assimilation rate, Stomatal conductance, Ci, Transpiration rate were recorded between 10 and 15 days after stress imposition in leaves which developed during the stress period. Photosynthetic rate of the mutant differ from the wild type with mutant N22_BADT_392_9_1 having the highest assimilation as well as stomatal conductance both under well watered and water limited conditions (Table 5). The low root biomass mutant N22_BADT_491_3_2 recorded the largest reduction in both assimilation rate and stomatal conductance under stress, illustrating the relevance of root traits in maintaining water relations. A/gs and A/T that are often considered as instrument measured for WUE were computed to reveal a significant variability among mutants and wild type (Table 6). An 30 Rajesh Kumar Singhal
increase in A/gs and A/T in mutant and stress reiterated the increase in WUE that was observed in gravimetry experiment. The ratio of Ci to the stomatal conductance (Ci/gs) is often considered as a measure of carboxylation efficiency. The two mutants recorded higher carboxylation efficiency compared to N22 in well watered conditions. A significant decrease in carboxylation efficiency was noticed under water limited conditions. The high root biomass mutant N22_BADT_392_9_1 showed a remarkable maintenance of carboxylation efficiency under water limited conditions. The data revealed that maintenance of water relations by virtue of root biomass was significantly advantageous during water limited conditions. Stomatal frequency represented an interesting trend. Though the mutant N22_BADT_392-9-1 recorded higher number of stomata per unit area in the abaxial surface where there was no difference between the mutants under water limited conditions. On the other hand the abaxial surface revealed significant variability among the mutants. It was interesting that N22_BADT_392_9_1 recorded higher stomatal frequency in abaxial surface under water limited conditions. (Fig. 5: Plate: 1) Based on gravimetric characterization of mutant following inferences can be drawn 1. The mutant N22_BADT_392_9_1 has significantly higher biomass 2. Higher deep root weight in N22_BADT_392_9_1 help in maintaining tissue water relations enhance metabolism in this mutant. 4.2 DEVELOPMENT OF F₂ MUTMAP population The mutant N22_BADT_392_9_1 was crossed with N22 (female) used as the male parent. A set of 400 genome wide SSR markers available at our center were used to screen for polymorphism between N22 and N22_BADT_392-9-1. A representative gel picture given in plate: 5 out of 400 markers 80 SSR were found to be polymorphic between N22_BADT_392_9_1 and N22. Fifteen of these polymorphic markers were used to screen for heterozygosity among several F 1 developed by crossing N22 and N22_BADT_392_9_1 Plate 3 and Plate 4. The true F 1 s were selfed to generate 500 F 2 MUTMAP populations Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 31
Table 5: Gas exchange parameter in mutants and wild type in control and stress condition. Traits Treatment N22_BAD T_392_9_1 N22_BADT _491_3_2 N22 CD @5%(A) CD @5%(B) CD @5% (A B) A Control 24.20 21.78 19.19 Stress 22.35 16.56 17.19 2.72* 3.34 NS 1.92 NS Control 0.92 1.01 0.59 g s Stress 0.66 0.31 0.37 0.23* 0.29* 0.16* Tr Ci Control 13.23 14.18 11.15 Stress 11.43 7.78 8.13 Control 326.67 349.64 334.64 Stress 303.67 319.75 311.76 6.44 NS 7.88 NS 4.55 NS 84.23 NS NS 59.55NS 103.16 Note: A (Assimilation rate in µmolm ²sec ¹), g s (Conductance in µmolm ²sec ¹), T r (Transpiration rate in µmolm ²sec ¹), Ci (internal CO 2 concentration in ppm). CD verities (Critical difference between different genotype), CD treatments ( critical difference between control and water stress condition. NS (non-significant). * Significant (at p=0.05) Table 6: Gas exchange derivative traits in control and stress condition in gravimetry experiment. Genotypes Treatment A/g s Ci/g s A/Tr A/Ci 392_9-1 N22_BADT_491_3_2 N22 Control 26.53 358.61 1.88.07 Stress 34.14 466.68 1.95.07 Control 22.19 353.18 1.72.06 Stress 53.92 1029.38 2.11.05 Control 33.33 571.42 1.53.05 Stress 51.47 882.27 2.12.05 Note: A/g s and A/Tr (Intrinsic water use efficiency), Ci/gs: and A/Ci indicates carboxylation efficiency. 32 Rajesh Kumar Singhal
(A) 3000 TLA(cm²/Plant) 2000 1000 Control stress 0 392-9-1 N22 491-3-2 (B) 40 30 20 TDM (g/plant) Control stress 10 0 392-9-1 N22 491-3-2 (C) 20.00 15.00 CWT(L) 10.00 5.00 Control stress 0.00 392-9-1 N22 491-3-2 Fig. 1: Measurement on total leaf area (TLA), total dry matter (TDM), ¹³C in control and stress condition in gravimetry experiment 70 DAS. Note: The per cent decrease in 392-9-1 was high for TLA, TDM and CWT then other genotypes. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 33
(A) 9 8 7 6 5 4 3 2 1 0 NAR 392-9-1 N22 491-3-2 Control Stress (B) 4 4 3 3 2 2 1 1 0 MTR 392-9-1 N22 491-3-2 Control Stress Fig.2: Measurement on Net assimilation rate (NAR) and mean transpiration ratio (MTR)in control and stress condition. 34 Rajesh Kumar Singhal
(A) 4 WUE(g/Kgˉ¹) 4 3 3 2 2 1 Control stress 1 0 392-9-1 N22 491-3-2 (B) 25 20 ¹³C( ) O Control O Stress 15 10 5 0 392-9-1 N22-WT 491-3-2 Fig.3: Measurement on water use efficiency (WUE) and ¹³C in control and stress condition. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 35
(A) 80 Root length (cm) 60 40 20 Control Stress 0 392-9-1 N22 491-3-2 (B) 15 Total Root biomass (g) 10 5 Control stress 0 392-9-1 N22 491-3-2 (C) 60 Root volume (cm³) 40 20 Control Stress 0 392-9-1 N22 491-3-2 36 Rajesh Kumar Singhal
(D) 3.50 Deep root biomass (g) 3.00 2.50 2.00 1.50 1.00 0.50 Control Stress 0.00 392-9-1 N22 491-3-2 Fig. 4: Measurement of root traits under control and stress condition in gravimetry experiment @ 70 days after sowing (DAS). Note: Total Root weight up to 30 cm (RW in grams), Root volume (RV in cm³), Deep root weight (grams), Root length (RL in cm). Deep root weight was the weight beyond 30 cm of root length. 70 60 50 40 30 20 10 0 Stomatal number Adaxial Abaxial control stress control stress 392-9-1 N22 491-3-2 Note: Obtained values are per microscopic field in 40X. Fig. 5: Variation in Stomatal frequency in wild type and mutants in control and stress condition. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 37
392-9-1 N22 Plate 2: Comparison of stomatal frequency in N22_BADT_392_9_1and N22 Note: The pictures are representative photos under 100X 38 Rajesh Kumar Singhal
Objective: 2. Physiological characterization of F 2 MUTMAP population The following experiments were carried out to characterize F 2 MUTMAP population for root and WUE traits using carbon isotopic ratio. Experiment 1: Determination of root traits in hydroponic systems. Experiment 2: Determination of root traits in root structure. Result of these two experiments are described in this chapter Experiment 1: Determination of root traits in MUTMAP population in hydroponic systems. The MUTMAP population comprises of 500 F 2 lines were raised in hydroponics condition and the root length was determined at various times viz. 7 days, 14 days, 17 days, and 23 days after sowing (DAS). The root length increased significantly from 6.68 cm at 7 DAS to 17.65 cm at 23 DAS in N22 whereas for N22_BADT_392_9_1 the root length was 7.19 cm at 7 th day which increased to 18.17 at 23 DAS and results presented in Table. 7. N22_BADT_392_9_1 had slightly longer roots but there was no significant difference between both of them. The same seedlings were transplanted to the root structure with a spacing recommended for rice (20 cm X 20 cm). The F2 population had a mean root length of 6.94 cm with maximum 12.5 cm and minimum 3.5 cm. These data illustrate that there was significant trangressive segregation in the root length on all days of measurement. On 14 DAS the mean was 14.28 with a range of 7 to 20 cm. On 17 th day the mean root length is 16.63 which ranged of 9 to 26 and at 23 rd day mean was 19.18 cm that ranged from 10 to 31. On all the days of measurement, there was significant trangressive segregation, illustrating the possibility of recombination of mutant alleles to alter root length. In the MUTMAP population the number of lateral root were also determined at same day an interval which was used for root length measurement for the parents. The number of lateral roots was not significantly different in the hydroponics measurement. N22 had a mean number of lateral roots of 6.26 and N22_BADT_392_9_1 was 8.76 on 7 th day (Table 7 and 8). In the case of the F 2 lines, on the day of 23 rd DAS, the number of lateral roots was 17.98 with a range of 8 to 25 (Table 8). The hydroponic system was illustrated in Plate. 6. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 39
Table 7: Average Root length and lateral root number measured in hydroponics system at 7,14, 17, 23 days after sowing (DAS) in wild type N22 and high root mutant 392-9-1. Root length (cm) Parental lines 7 DAS 14 DAS 17 DAS 23 DAS N22 6.68±1.43 13.42±2.62 15.98±2.73 17.65±2.94 392-9-1 7.19±1.96 13.28±2.10 15.46±2.97 18.17±2.68 Lateral root number N22 6.26±1.31 11.30±1.71 14.03±2.06 17.23±2.19 392-9-1 8.76±1.36 13.26±1.78 16.42±2.18 19.34±2.38 Note: There is no difference in root length and root number between N22 and 392-9-1 Table 8: Descriptive statistics of Root length and lateral root number measured in hydroponics system after 7, 14, 17, 23 days after sowing (DAS) in F₂ population. Root length Lateral root number F 2 population Mean Max Min Mean Max Min 7DAS 6.94±1.44 12.5 3.5 6.46±1.19 10 4 14DAS 14.28±2.03 20 7 11.75±1.48 17 7 17DAS 16.63±2.81 26 9 14.41±2.09 21 8 23DAS 19.18±3.12 31 10 17.98±2.47 25 8 Note: The variability in F 2 population is higher than parents. 40 Rajesh Kumar Singhal
Experiment 2: Determination of root traits in root structure. The 500 MUTMAP population was classified into two sets, One set of 250 lines was raised in root structure for the determination of root traits after a prolong growth of 80 days. The other set was sown in field for advancing to F 3. The results of the root structure experiment are presented in this chapter. The root length, root weight and the root volume of the parents as well as of the 250 F 2 populations was determined on the 80 th DAS. In root structure, N22 and N22_BADT_392_9_1 were not significantly different in root length on 80 th day; there was a significant variation in root volume and root biomass (Table 9). The root volume of N22 was 16.6 cm 3 where as N22_BADT_392_9_1 had two times more volume at 35 cm3. Similarly the root biomass of N22 was 1.8 g on 80 th day and it was 4 g/plant for N22_BADT_392_9_1. Illustrating a huge increase in biomass and therefore the volume of this mutant N22_BADT_392_9_1 when compared to wild type N22. The individuals of MUTMAP population were also used for determining these traits. Root length showed a significant variation with a mean of 31.35 cm which ranged from 14 cm to 50 cm in the MUTMAP population. The normal distribution of the root length was observed, though the parent didn t have any significant variation in root length, there was significant trangressive segregation among population. Illustrating the recombination between alleles in the mutant and its wild type as that is capable of causing a large variation in the root length as well. However, the most interesting data was represented by the root volume and the root biomass. Root volume and had a mean of 26.77 ± 12.24 cm which was in the middle of the two parents. While the population segregated as low as 5 cm³ to as high as 65 cm³. Similarly the mean root biomass of the MUTMAP population was 2.85 ± 1.24 g, which was again in between the two parents, while the segregation of the MUTMAP population ranged from as low as from 0.20 g to as high as 6.4 g. (Table 9) (Appendices:2) Correlation between root trait and biomass are sown in fig.6. The root to shoot ratio in terms of the root length and shoot length as well as the root biomass to shoot biomass were calculated. While the parents once again didn t differ between themselves among root length and shoot length ratios or root biomass to shoot biomass ratio showed significant variation. The F 2 lines showed a much larger variation which ranges from 0.21 to 0.85 for the root length to the shoot length ratio from 0.07 to 0.46 in the root weight to shoot weight ratios. This data once again revealed the possibility that the recombination of the mutant allele between the wild type and its mutant which causes a tremendous variation in the root to shoot ratio in both the root length to shoot length and root biomass to shoot biomass ratios. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 41
The shoot parameters such as leaf area, leaf weight, shoot weight and total biomass were also determined among the plants. The leaf area of the two parents was significantly different with N22_BADT_392_9_1 recording higher leaf area of 537 cm 2 per plant when compared to a low 217 cm 2 in the case of N22. Table 9: Variation in root traits among the MUTMAP population grown in root structure Genotype RW(g) RL(cm) RV(cm³) RL/SL RW/SW N22 1.81±.85 36.67±1.37 16.67±6.83 0.53±.04 0.21±.02 392-9-1 4.04±1.43 33±1.90 35±7.07 0.59±.24 0.29±.08 F 2 2.85±1.24 31.35±6.27 26.77±12.24 0.42±.10 0.21±.08 Max 6.40 50.00 65.00 0.85 0.46 Min 0.20 14.00 5.00 0.21 0.07 Note: photosynthetic traits: Photosynthetic rate (A), Stomataol conductance (g s ), Internal CO 2 (C i ), :Transpiration (T r ), Air temperature (T air ), Leaf temperature (T leaf ). The MUTMAP population had a mean leaf area of 506 cm 2 which was closer to the high root N22_BADT_392_9_1 but ranged between 80 and 1200 cm 2 among the population. Similarly, leaf weight, shoot weight showed a similar trend where the leaf weight of the mutant N22_BADT_392_9_1 was significantly higher than that of N22 and the MUTMAP population had a mean leaf weight closer to the N22_BADT_392_9_1 parent ranging from 0.36 g to as high as 18.35 g (Table 11).(Appendices : 2) Significant variation was also noticed in gas exchange parameter like A, gs, Ci, T between MUTMAP populations. Range between 13.93 and 39.07, 0.14 and 1.05, 164.87 and 319.27, 3.60 and 10.24 among F 2 MUTMAP populations. (Table 10). (Appendices: 1). Significant variation was also noticed in total number of tillers per plant. The parent N22_BADT_392_9_1 had 28 tillers it was comparable to that of N22 which had 20 tillers on 80 th day of sowing, Where as MUTMAP population showed a 10 fold variation in the tiller number which ranged from 5 to 52 with a mean of 25. Total 42 Rajesh Kumar Singhal
Plate 3: F 1 s obtained by crossing wild type (N22) and high root mutant (N22_BADT_392_9_1) Note : The F 1 plant had high tiller number, intermidiate between parents in plant height and seed type and dispayed hybrid vigour. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 43
True F 1 N22 392-9-1 F 1 F 1 F 1 F 1 F 1 F 1 F 1 F 1 Plate 4: Identification of true F1 by using SSR markers Note: Among 50 SSR markers tested for polymorphism 15 were polymorphic for N22 andbadt_n22_ 392_9_1 Plate 5: SSR markers showing polymorphism between N22 and N22_BADT_392_9_1. Note: The polymorphic markers between N22 and 392_9_1 are indicated by red circle. 44 Rajesh Kumar Singhal
biomass, a factor which is representative of the growth rates had a significant difference between the two parents. Mutant N22_BADT_392_9_1 was twice higher in total biomass at 21 g per plant against 12.6 g biomass of N22. The MUTMAP showed a much larger variation indicating that a large of transgrassive segregation where the total biomass range from 1.3 g per plant as high as 52 gm per plant which was significantly more several F 2 MUTMAP population lines than the high parent and significantly lower than the low biomass parent.the SPAD chlorophyll meter value which is an indication of the greenness of the leaf was measured in parents as well as in the entire population in the root structure of 50 DAS. There was a significant difference in the two parents in N22_BADT_392_9_1 recording a higher SCMR. Vale of 49 compared to 38 by N22. The MUTMAP population on the other hand showed a significant variation with a mean of 41 which range between 28 and 50. The SCMR value of SCMR value didn t reveal higher values then high SCMR patent N22_BADT_392_9_1. And the data of these shoot parameters is given in Table 11. Table 10: Measurement of gas exchange of the F 2 MUTMAP population. Genotype A g s Ci Tr Tair Tleaf N22 Mean 25.58±1.92 0.43±.10 263.98±17.80 6.04±.76 28.62±.39 28.69±.83 392-9-1 Mean 29.74±2.41 0.65±.13 283.67±19.19 7.61±.46 28.63±.37 28.15±.88 Mean 26.93±4.85 0.55±.20 271.25±26.31 7.03±1.45 28.78±.38 28.73±.97 F 2 population Max 39.07 1.05 319.27 10.24 30.11 31.71 Min 13.93 0.14 164.87 3.60 27.48 26.80 Note: The values were average of 3 replications, measured in 170 F 2 lines. The observations were recorded washing the root just before flowering. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 45
46 Rajesh Kumar Singhal Table 11: Variation in shoot traits among the MUTMAP population grown in root structure harvested 80 days after sowing. Genotype LW(g) SW(g) SPAD TLA(cm²) TDW(g) T.N SLA N22 4.04±1.97 8.58±4.16 38.64±4.53 217.13±29.82 12.62±5.7 20±9.47 77.31±10.9 392-9-1 8.24±.79 13.41±2.17 49.15±4.84 537.36±71.08 21.65±2.0 28.83±6.8 66.87±15.6 F2 8.33±3.60 15.08±6.95 41.07±3.59 506.03±227.94 23.40±10.2 25.44±8.7 66.75±9.74 Max 18.35 34.30 50.9 1207.1818 52.15 52.00 45.65 Min 0.36 0.70 28.66 80.882353 1.27 5.00 107.14 Note: Average of F 2 population values were on par with that of N22_BADT_392_9_1.
TDM(g) 60 50 40 30 20 10 0 0 1 2 3 4 5 6 7 RW(g) y = 5.8118x + 6.8289 R² = 0.4973 RL(cm) 60 50 40 30 20 10 0 y = 1.8615x + 26.039 R² = 0.1351 0 1 2 3 4 5 6 7 RW(g) Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 47
RW(g) 7 6 5 4 3 2 1 0 y = 0.1206x + 1.0339 R² = 0.4584 0 5 10 15 20 25 30 35 40 SW(g) RV(cm³) 70 60 50 40 30 20 10 0 y = 7.8364x + 4.4228 R² = 0.6275 0 1 2 3 4 5 6 7 RW(g) Fig. 6: Relationship between root weight and total dry matter, root weight and root length, root weight and root volume, root weight and shoot weight in F 2 population in root structure experiment. 48 Rajesh Kumar Singhal
P₁ P₂ 80 70 60 Root length Chi-Square test = 9.66053, df df = 3 (adjusted), p = 0.02168 P₂ P₁ No. of of observations 50 40 30 20 10 0-10 -5 0 5 10 15 20 25 30 35 40 45 50 55 Root length in in cm Fig. 7: Frequency distribution of Root length and Root volume observed in F 2 population in root structure at 80 DAS (N=170) Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 49
7 Days after sowing 14 Days after sowing 23 Days after sowing Plate 6: Measurement on root length and lateral root number on 7 day after sowing 17 DAS, and 23 day after sowing in hydroponics system. 50 Rajesh Kumar Singhal
N22, 392-9-1, F2 population N22, 392-9-1, F2 population N22, 392-9-1, F2 population N22, 392-9-1, F 2 population Plate 7: Root variability observed in root structure at 80 day after sowing in F 2 population Note: The first root in all the above picture was N22 and second was 392-9-1, remaining all root are from F 2 population. Characterization of HOX 10 mutant allele in rice (Oryza sativa L.) 51