DNA Marker Based Diversity Across Rice Genotypes and Advanced Breeding Lines Bred for Temperate India

Nakeeb un Nisa Yetoo SKUAST Kashmir: Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir https://orcid.org/0000-00021316-179X Aafreen Sakina SKUAST Kashmir: Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Najeebul Rehman* So (  najeeb_so @rediffmail.com ) Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir https://orcid.org/0000-0002-8934-3936 Asif B. Shikari Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Reyaz R. Mir Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir M. Ashraf Bhat Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Showkat A. Waza Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Sofora Jan Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Sumira M.sc Ra qee Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Gazala H. Khan Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir Shabir H. Wani Sher-E-Kashmir University of Agricultural Sciences and Technology Kashmir


Introduction
Rice (Oryza sativa L.) is a staple crop of Kashmir Himalayas and covers an area of 150 thousand hectares grown above 1550msl. The cultivars grown include landraces and formally bred varieties which belong to cold tolerant indica and temperate japonica. Genetic improvement in any crop species is inexorable and a continuous process to meet the future challenges regarding food security. Evaluation, characterization and identi cation of plant genetic resources play an important role for their utilization in the crop improvement programmes [1,2]. The landraces, traditional and improved cultivarstogetherrepresent repositories of genetic diversity and can serve as resources for improving yield and resistance to pests and diseases [3][4][5] or else can be used as parents in development of superior recombinants [6]. Conventionally, morphological traits have been used to determine the genetic diversity and for classi cation ofthe germplasm into different groups. Alternately, the genetic diversity can be estimatedthrough the use of molecular markers which offer a high polymorphism range and reproducibility [7,8]. The PCR based markers such asmicrosatellites or simple sequence repeats (SSRs) are highly polymorphic, reproducible, codominant and widely distributed throughout the rice genome [9]. The two of the sub species viz., indica and temeperate japonica are being grown across irrigated ecologies of Kashmir valleywith 80% and 20% of the total (1.4 lakh ha) rice grown area, respectively [10]. The present study was undertaken to generate an information on genetic divergence and sub-species allocation of a set of elite rice genotypes which are targeted for different mountainous ecological niches across Kashmir valley.

Materials And Methods
Evaluation for agronomic and quality related traits  (Table 1). Thematerialswere raised in a randomized complete block design with three replications. Thirty days old seedlings of each accession were transplanted in the eldwith the standard spacing of 20cmx15cm and net plot size of 5 m² perreplication. Recommended package of practices were followed to raise a healthy crop. Five randomlyselected plants from each replication were selected for recording the observations on various agromorphological traits. However, owering, maturity and yield data was recorded on whole plot basis. The description of various agro-morphological traits along with grain quality features was carried outusing Standard Evaluation System of IRRI [11].
Amylose content and gel consistency were determined by the method developed by Juliano [12] and Cagampang [13], respectively. Alkali spreading value and Aroma were determined as per the procedure described by Jennings [14].
Similarly the list of germplasm lines (192 genotypes) for their classi cation into indica and temperate japonica groups are given in the Table 2.

DNA Marker analysis
The SSR markers used for the characterization of 38 varieties/advanced breeding lines were randomly selected from www.gramene.org. The selected microsatellite markers (two each for one chromosome) along with their chromosomal location and annealing temperature (Tm) are presented in the Table 3. Genomic DNA was extracted following the CTAB (Cetyl-Tri Methyl Ammonium Bromide) method with some modi cations [15]. Quanti cation of DNA samples was done spectrophotometrically and quality was estimated by using 0.8 % agarose gel electrophoresis. High concentration of DNA samples was further diluted in 10:1 Tris-EDTA to a working concentration of 50ng/μl and stored at 40C for PCR based marker analysis. PCR reaction was prepared with 50 ng of rice genomic DNA, 0.2 μg of 3¢ and 5¢ end primers, 200 mM of each dNTP, 1X PCR buffer containing 50 mM KCL, 10 mM Tris HCl (pH 8.9), 2.0 mM MgCl 2 and one unit of Taq Polymerase in a total of 25 μL solution individually for all 24 primer pairs. PCR thermal cycler was programmed for 1 min at 94 ο C, 1 min and 30 seconds at 55°C, 1 min at 72°C and a nal cycle of 10 min at 72°C. Ampli cation product was separated on 3.5% of agarose gel in 1X TBE buffer followed by staining with ethidium bromide. The SSR allele sizes were determined by the position of bands relative to the DNA ladder.
Number 1 was given to the allele having highest molecular weight. The ampli ed bands were recorded as 1 (band present) and 0 (band absent) in a binary matrix.

Statistical analysis
The set of observations recorded for was subjected to statistical analysis. Analysis of variance was carried out for various agro-morphological traits as per Gomez and Gomez [16]. Analysis of molecular variance was performed using software GenAlEx version 6.5. Euclidian distance and Jaccards coe cients were calculated from morphological and marker data, respectively. Unweighted Pair Group Method using Arithmetic Averages (UPGMA) method was used to obtain the disimilarity trees from the two matrices, respectively, with the help of DARwin software (version 6.0.21). PIC values for each of the 24 primers were estimated using the equation proposed by Anderson [17]: Where pij is the frequency of j th allele in i th primer and summation extends over 'n' patterns.
Furthermore, the list of markers used in indica-temperate japonica differenriation is given in Table 4.

Results
The mean squares due to present set of genotypes were highly signi cant for all the characters studied (S. Table 1). ANOVA of some important agronomic and cooking quality traits are given in Table 5.Among the various quality features, amylose content and presence of aroma in uence the consumer preferences and thus drive the breeding strategy. In the present study, amylose content ranged from 15.8% to 25.5% with minimum in Aromatic Zag and maximum in SKUA-420 (

Cluster analysis using morphological traits
Cluster analysis was carried out to assess the extent of divergence using UPGMA method. The set of genotypes got grouped into two major clusters. Cluster I had 15 genotypes, and was further sub grouped into cluster Ia, Ib, Ic and Id with four, ve, one and ve genotypes, respectively. The remaining 36 genotypes marked the cluster II and were sub grouped into IIa, IIb, IIc and IId with seven, eight, seven and 14, genotypes, respectively (Fig. 3).
The polymorphism information content (PIC) value ranged from 0 to 0.665 with an average of 0.37. High PIC values were observed for the primers RM263 (0.67), RM159 (0.59) and RM333 (0.50), while primers RM1, RM60 and RM308 (0) and RM105 (0.05) showed lower values of PIC (Table 3). PIC provides an estimate of discriminatory power of a marker by taking into account the relative frequency of the alleles. PIC values exceeding 0.5 re ects abetter polymorphism range [18]. Therefore, the markers RM 263, RM159 and RM333 can be effectively used for determining the genetic differences among the rice genotypes and to study their phylogenetic relationship.
The trend line of number of effective alleles (N e ) versus expected heterozygosity (H e ), was plotted and marked a maxiumum value of N e =2.5 that indicated the, high discriminatory power of the markers. Ideally the number of effective alleles should approximate to the number of actual alleles (Fig. 5).

Cluster analysis and genetic divergence pattern
The cluster analysis carried out through Unweighted Pair Group Method using Arithmetic Averages (UPGMA) helped to classify 38 genotypes into 2 clusters at an average dissimilarity of 30%. Cluster I consisted of 24 genotypes and got further divided into two sub clusters; sub-cluster Ia consisted of 9 genotypesand sub cluster Ib of 15 genotypes. Similarly, cluster II contained 13 genotypes and is divided into two sub clusters viz; IIa which consisted of 10 genotypes and IIb with 3 genotypes (Fig. 6).
Among the 192 genotypes 15 were indica and 28 temperate japonicas in addition to 149 varieties that belonged to intermediate type (Table 6). With respect to the ngerprint devised based on the four markers, genotypes which ampli ed 220, 182, 207 and 201 bp fragments were regarded as indica while 169, 207,175, 174 bp as temperate japonica (S. Table 2). Any genotype with mixed combination of these alleles was categorized as intermediate type.

Discussion
Characterization of germplasm accessions establishes distinctiveness among rice genotypes. It is not only important for utilizing the appropriate attribute based donors in breeding programmes, but also essential in the present era for protecting the uniqueness of germplasm collections. In the present investigation 51 rice genotypes were evaluated for different agromorphological and physiochemical parameters and 38 genotypes were evaluated for molecular characterization. Further, 192 rice germplasm lines were used for indica-japonica differentiation. The mean sums of squares due to genotype were signi cant for all agro-morphological and quality traits. The high variability for plant height is in agreement with Chakravorty and Priyanka [19,20]. Signi cant variability for days to 50% owering in the present study supports the ndings of Sajid [21]. Similarly, signi cant variability for grain yield as observed in this study was supported by the ndings of Vanisree and Tuhina-Khatun [22,23]. Nascimento [24] observed signi cant differences and high variability for ag leaf length, number of tillers per plant, panicle length, panicle fertility, 1000 grain weight which is similar to that in the present study. Similar results were reported by Sravan [25] for number of tillers, ag leaf length, plant height and panicle length. Richa [26] observed highly signi cant differences for the characters viz., plant height, tillers per plant, days to owering, days to maturity, grain yield per plant, effective tillers per plant, grain length, grain breadth, length-breadth ratio and 1000 grain weight. Signi cant variability for days to 50% owering, days to maturity, plant height, number of effective tillers per plant, panicle length, spikelet fertility percent, test weight, grain yield was reported by Kumari and Umesh [27][28]. Similarly, Waza and Jaiswal [29] reported signi cant variability for grain length, grain breadth, grain length/breadth ratio, 100 grain weight, kernel length, kernel breadth, kernel length/breadth ratio, kernel length after cooking, kernel elongation ratio, alkali spreading value, amylose content and aroma. These ndings are in conformation with the results of present study.
Pusa Sugandh 3 revealed 25.3% amylose content, which is similar to the previous reports by Bano and Majid [30,31]. Rice with low amylose content (10-20%) tends to be sticky and soft on cooking and becomes rmer as amylose content increases. Rice In the present study, based on morpgological diversity analysis, the set of genotypes were grouped into two major clusters In the molecular analysis, the 38 genotypes got grouped into 2 clusters (Fig. 6)

Conclusions
The genotypes which preserve the signi cant amount of genetic variability for the important agro-morphological traitswere broadly grouped into two clusters.The information on marker-based diversity and performance based on cooking quality and agronomic traitscan help with regard to the effective utilization of the germplasm. Further, the indica-japonica classi cation of the germplasm lines shall be helpful to devise a strategy for inter-sub species hybridization to breed for improved indicalinous and japanicalinous types that can t in temperate climatic conditions. Funding No funds/grants was received for conducting this study.

Declarations
Competing interests All the authors declare no relevant nancial or non-nancial interests.
Authors contribution Najeebul R. So and Asif Bashir Shikari conceived the experiment. Nakeeb-Un-Nisa, Sofora Jan, Reyaz R. Mir and Najeebul R. Tables Table 1 Experimental  Genotypes used in molecular analysis Table 2 Experimental material used for classification into indica and temperate      [] designates sub-cluster  supp.tables12.docx