Thumbnail Image

Acharya N G Ranga Agricultural University, Guntur

The Andhra Pradesh Agricultural University (APAU) was established on 12th June 1964 at Hyderabad. The University was formally inaugurated on 20th March 1965 by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India. Another significant milestone was the inauguration of the building programme of the university by Late Smt. Indira Gandhi,the then Hon`ble Prime Minister of India on 23rd June 1966. The University was renamed as Acharya N. G. Ranga Agricultural University on 7th November 1996 in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga, who rendered remarkable selfless service for the cause of farmers and is regarded as an outstanding educationist, kisan leader and freedom fighter. HISTORICAL MILESTONE Acharya N. G. Ranga Agricultural University (ANGRAU) was established under the name of Andhra Pradesh Agricultural University (APAU) on the 12th of June 1964 through the APAU Act 1963. Later, it was renamed as Acharya N. G. Ranga Agricultural University on the 7th of November, 1996 in honour and memory of the noted Parliamentarian and Kisan Leader, Acharya N. G. Ranga. At the verge of completion of Golden Jubilee Year of the ANGRAU, it has given birth to a new State Agricultural University namely Prof. Jayashankar Telangana State Agricultural University with the bifurcation of the state of Andhra Pradesh as per the Andhra Pradesh Reorganization Act 2014. The ANGRAU at LAM, Guntur is serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication. Genesis of ANGRAU in service of the farmers 1926: The Royal Commission emphasized the need for a strong research base for agricultural development in the country... 1949: The Radhakrishnan Commission (1949) on University Education led to the establishment of Rural Universities for the overall development of agriculture and rural life in the country... 1955: First Joint Indo-American Team studied the status and future needs of agricultural education in the country... 1960: Second Joint Indo-American Team (1960) headed by Dr. M. S. Randhawa, the then Vice-President of Indian Council of Agricultural Research recommended specifically the establishment of Farm Universities and spelt out the basic objectives of these Universities as Institutional Autonomy, inclusion of Agriculture, Veterinary / Animal Husbandry and Home Science, Integration of Teaching, Research and Extension... 1963: The Andhra Pradesh Agricultural University (APAU) Act enacted... June 12th 1964: Andhra Pradesh Agricultural University (APAU) was established at Hyderabad with Shri. O. Pulla Reddi, I.C.S. (Retired) was the first founder Vice-Chancellor of the University... June 1964: Re-affilitation of Colleges of Agriculture and Veterinary Science, Hyderabad (estt. in 1961, affiliated to Osmania University), Agricultural College, Bapatla (estt. in 1945, affiliated to Andhra University), Sri Venkateswara Agricultural College, Tirupati and Andhra Veterinary College, Tirupati (estt. in 1961, affiliated to Sri Venkateswara University)... 20th March 1965: Formal inauguration of APAU by Late Shri. Lal Bahadur Shastri, the then Hon`ble Prime Minister of India... 1964-66: The report of the Second National Education Commission headed by Dr. D.S. Kothari, Chairman of the University Grants Commission stressed the need for establishing at least one Agricultural University in each Indian State... 23, June 1966: Inauguration of the Administrative building of the university by Late Smt. Indira Gandhi, the then Hon`ble Prime Minister of India... July, 1966: Transfer of 41 Agricultural Research Stations, functioning under the Department of Agriculture... May, 1967: Transfer of Four Research Stations of the Animal Husbandry Department... 7th November 1996: Renaming of University as Acharya N. G. Ranga Agricultural University in honour and memory of an outstanding parliamentarian Acharya Nayukulu Gogineni Ranga... 15th July 2005: Establishment of Sri Venkateswara Veterinary University (SVVU) bifurcating ANGRAU by Act 18 of 2005... 26th June 2007: Establishment of Andhra Pradesh Horticultural University (APHU) bifurcating ANGRAU by the Act 30 of 2007... 2nd June 2014 As per the Andhra Pradesh Reorganization Act 2014, ANGRAU is now... serving the students and the farmers of 13 districts of new State of Andhra Pradesh with renewed interest and dedication...

News

https://angrau.ac.in/ANGRU/Library_Resources.aspx

Browse

2022 - 20247
Reset filters
Subject: Biotechnology and molecular Biology × End date: 2024 × Start date: 2022 ×
Reset filters

Search Results

Now showing 1 - 7 of 7
  • Thumbnail Image
    ThesisItemOpen Access
    DEVELOPMENT OF DIGENIC LINES HAVING RESISTANCE TO BLAST AND BACTERIAL LEAF BLIGHT THROUGH MARKER ASSISTED SELECTION IN RICE (Oryza sativa L.)
    (Acharya N G Ranga Agricultural University, 2024-05-01) G. USHA; Dr. J.V. RAMANA
    Rice (Oryza sativa L.) being staple source of food for nearly 65% of the world’s population, plays a predominant role in global food security. However, rice production is constrained by several biotic and abiotic stresses. Among the biotic stresses, blast caused by Magnaporthe oryzae and Bacterial Leaf Blight (BLB) caused by Xanthomonas oryzae pv. oryzae are the important diseases as they cause significant yield reduction. Hence, developing disease resistance lines pyramided with two or more genes is viable and eco-friendly approach to achieve greater yields. Pyramiding of two or more effective resistance genes/alleles into elite rice lines enhances the durability and broadens the disease resistance spectrum. In the present study, four monogenic Improved Samba Mahsuri (ISM) lines, ISM-MLPi9, ISM-MLPi20, ISM-MLPi40 and ISM-MLPita having blast resistance genes Pi9, Pi20, Pi40 and Pita, respectively, were used as donors to transfer corresponding blast genes into the genetic background of recurrent parent, Improved Samba Mahsuri (ISM-MLPi54) which is an elite, stable line having medium-slender grain type possessing three BLB genes (Xa21, xa13 and xa5) and one blast resistance gene (Pi54) by employing marker-assisted backcross breeding strategy. The experiment was conducted for seven seasons from Kharif 2017 to Kharif 2020. Molecular characterization of parental lines using five blast resistant genes-specific/linked markers, viz., Pikh-MAS (Pi54), NMSM-Pi9 (Pi9), RM1337 (Pi20), MSM-6 (Pi40) and RM5364 (Pita) confirmed the polymorphism for the respective targeted genes among parental lines along with three BLB resistance genes-specific markers, pTA248 (Xa21), xa13 prom (xa13) and xa5FM (xa5). These genes-specific/linked markers were used for foreground selection during the introgression programme. Parental lines were screened with 1800 simple sequence repeats markers distributed uniformly over the 12 rice chromosomes and identified 104 polymorphic markers (5.77%) among the five parental lines used. A total of four cross combinations were effected to develop digenic lines carrying blast gene combinations of Pi54+Pi9, Pi54+Pi20, Pi54+Pi40 and Pi54+Pita through marker assisted backcross breeding strategy. Development of digenic lines with blast genes combination of Pi54+Pi9 using parental combination of ISM-MLPi54/ISM-MLPi9 (Cross-I) identified five homozygous BC2F2 digenic lines (ISM-DLPi54+Pi9-9-9-32-4, ISM-DLPi54+Pi9-9-9-32-7, ISM-DLPi54+Pi9-9-9-42-3, ISM-DLPi54+Pi9-9-9-42-18 and ISM-DLPi54+Pi9-9-9-42-23). In Cross-II (ISM-MLPi54/ISM-MLPi20), nine homozygous BC2F2 plants were identified as digenic plants (ISM-DLPi54+Pi20-20-5-65-2, ISM-DLPi54+Pi20-20-5-65-11, ISM-DLPi54+Pi20-20-5-65-15, ISM- ISM-DLPi54+Pi20-20-5-66-2, ISM-DLPi54+Pi20-20-5-66-11, ISM-DLPi54+Pi20-20-5-66-12, ISM-DLPi54+Pi20-20-5-66-16, ISM-DLPi54+Pi20-20-5-69-9 and ISM-DLPi54+Pi20-20-5-69-15) carrying blast genes combination of Pi54+Pi20. While, seven plants were identified (ISM-DLPi54+Pi40-40-3-120-2, ISM-DLPi54+Pi40-40-3-120-10, ISM-DLPi54+Pi40-40-3-120-12, ISM-DLPi54+Pi40-40-3-120-16, ISM-DLPi54+Pi40-40-4-122-5, ISM-DLPi54+Pi40-40-4-122-9 and ISM-DLPi54+Pi40-40-4-122-13) having Pi54+Pi40 genes combination in Cross-III (ISM-MLPi54/ISM-MLPi40). Similarly, in Cross-IV (ISM-MLPi54/ISM-MLPita), six digenic plants with genes combination Pi54+Pita (ISM-DLPi54+Pita-ta-9-256-2, ISM-DLPi54+Pita-ta-9-256-16, ISM-DLPi54+Pita-ta-10-270-12, ISM-DLPi54+Pita-ta-10-270-15, ISM-DLPi54+Pita-ta-10-272-14 and ISM-DLPi54+Pita-ta-11-273-9) were identified. The digenic blast lines pyramided with bacterial leaf blight genes (Xa21, xa13 and xa5) were identified by employing gene-specific markers in BC2F2. In the Cross-I (ISM-MLPi54/ISM-MLPi9), three BC2F2 plants (ISM-PYLPi54+Pi9-9-9-32-1, ISM-PYLPi54+Pi9-9-9-42-6 and ISM-PYLPi54+Pi9-9-9-42-9) homozygous for 5 genes (Pi54+Pi9+Xa21+xa13+xa5) were identified. Among these, ISM-PYLPi54+Pi9-9-9-42-9 had maximum recurrent parent genome recovery (RPGR) of ~96.8%. In Cross-II, a total of eight true BC2F2 plants (ISM-PYLPi54+Pi20-20-5-65-4, ISM-PYLPi54+Pi20-20-5-66-8, ISM-PYLPi54+Pi20-20-5-66-10, ISM-PYLPi54+Pi20-20-5-69-1, ISM-PYLPi54+Pi20-20-5-69-2, ISM-PYLPi54+Pi20-20-5-69-7, ISM-PYLPi54+Pi20-20-5-69-13 and ISM-PYLPi54+Pi20-20-5-69-14) were identified as homozygous for all five genes (Pi54+Pi20+Xa21+xa13+xa5). Among these, ISM-PYLPi54+Pi20-20-5-66-8 showed the highest (96.5%) RPGR. In Cross-III, four BC2F2 plants (ISM-PYLPi54+Pi40-40-3-120-7, ISM-PYLPi54+Pi40-40-3-122-4, ISM-PYLPi54+Pi40-40-3-122-6 and ISM-PYLPi54+Pi40-40-4-122-16) were homozygous for all the 5 targeted genes (Pi54+Pi40+Xa21+xa13+xa5). Among them, ISM-PYLPi54+Pi40-40-4-122-16 showed the highest (96.4%) RPGR. Similarly, in Cross-IV five BC2F2 plants (ISM-PYLPi54+Pita-ta-9-256-8, ISM-PYLPi54+Pita-ta-9-270-2, ISM-PYLPi54+Pita-ta-11-270-3, ISM-PYLPi54+Pita-ta-10-272-2 and ISM-PYLPi54+Pita-ta-11-273-4) were identified as homozygous for all 5 genes (Pi54+Pita+Xa21+xa13+xa5) while, ISM-PYLPi54+Pita-ta-10-272-2 showed 95% of RPGR. The pyramided lines with blast and BLB genes from all cross combinations were evaluated for yield, yield attributing traits along with grain and cooking quality parameters including parents in BC2F2:3. Grain yield as high as 37.9 g plant-1 was observed among, some of the derived pyramided lines as compared to 36.20±0.2 g plant-1 of recurrent parent, ISM-MLPi54 indicating no yield penalty for resistance in the pyramided lines. The pyramided lines, ISM-PYLPi54+Pi9-9-9-42-9 (37.7 g plant-1), ISM-PYLPi54+Pi20-20-5-66-8 (36.8 g plant-1), ISM-PYLPi54+Pi40-40-4-122-16 (36.9 g plant-1) and ISM-PYLPi54+Pita-ta-10-272-2 (37.9 g plant-1) were identified as the best from four crosses and out yielded the recurrent parent, because of their more number of productive tillers per plant, high spikelet fertility (%), larger panicle length and higher thousand grain weight. The cooking quality parameters of pyramided lines developed from this study were similar to the previously released variety, Improved Samba Mahsuri. Pyramided lines obtained from four independent crosses were subjected to disease screening at seedling stage for blast with Magnaporthe and at maximum tillering stage with Xoo for BLB. All the pyramided lines showed high disease resistance reaction for blast (score 0-2) and few lines showed highly resistance (score 0) disease reaction and BLB (score 1). The pyramided lines, ISM-PYLPi54+Pi40 gene combinations showed very high levels of blast disease resistance (score 0). Thus, the developed digenic lines for blast are of novel importance for durable resistance breeding and serve as a valuable source for present and future blast resistance breeding. These lines needs to be further screened in Donor Screening Nursery (DSN) and in hotspots with differential isolates in order to confirm their stability and durability of resistance before their commercial exploitation. These pyramided lines may be utilized directly for release after further testing and evaluation.
  • Thumbnail Image
    ThesisItemOpen Access
    GENOME WIDE ASSOCIATION STUDIES FOR GRAIN IRON AND ZINC CONTENTS IN CHICKPEA (Cicer arietinum L.)
    (Acharya N G Ranga Agricultural University, 2024-05-01) SRUNGARAPU RAJASEKHAR; Dr. LAL AHAMED M.
    Chickpea is a cheap source of protein and micronutrients to the poor people living in arid and semi-arid regions of Southern Asia and Sub-Saharan Africa and contribute towards reducing malnutrition resulting from protein and micronutrient deficiency. The current study evaluated chickpea reference set of 280 accessions (landraces, breeding lines, and advanced cultivars) to study the variability, diversity and to delineate the genetic nature of grain nutrient (protein, Fe, Zn content) and agronomic traits in normal (NS) and heat stress (HS) conditions using genome-wide association studies. The analysis of variance (ANOVA) revealed highly significant difference among the accessions for grain nutrients and agronomic traits under normal and heat stress seasons. Genetic diversity studies revealed a wide range of variability for grain protein (15.7–25.3%), Fe (44.8–74.9 mg kg-1 ) and Zn (38.4–65.7 mg kg-1 ) contents along with agronomic traits. The accessions, ICC 9848 (NS-Protein: 26.21%, Fe: 76.74 mg kg-1 , Zn: 55.74 mg kg-1 ; HS-Protein: 25.25%, Fe: 65.52 mg kg-1 , Zn: 59.71 mg kg-1 ), ICC 9895 (NS-Protein: 25.49%, Fe: 75.65 mg kg-1 , Zn: 52.48 mg kg 1 ; HS-Protein: 24.19%, Fe: 70.90 mg kg-1 , Zn: 59.92 mg kg-1 ), ICC 9862 (NS-Protein: 25.69%, Fe: 72.78 mg kg-1 , Zn: 52.53 mg kg-1 ; HS-Protein: 24.85%, Fe: 67.74 mg kg 1 , Zn: 63.27 mg kg-1 ) and ICC 9872 (NS-Protein: 25.70%, Fe: 69.85 mg kg-1 , Zn: 52.46 mg kg-1 ; HS-Protein: 25.13%, Fe: 73.84 mg kg-1 , Zn: 63.27 mg kg-1 ) were found promising for grain protein, Fe and Zn content across the environments. The kabuli accessions showed high average grain protein and Fe content when compared with the desi types. The PCV and GCV of nutrient traits was low to moderate across the environments. High heritability was noted for all the traits under individual seasons of normal and heat stress whereas pooled seasons noted moderate heritability for grain Fe and Zn contents. High heritability with high GAM was recorded for days to first flower, days to 50% flowering, plant height, number of filled pods per plant, number of unfilled pods per plant, number of pods per plant, number of seeds per plant, 100 seed weight, harvest index and seed yield across the environments. The xvii association among the nutrient traits across the environments was positive and was negative with seed yield. The principal component analysis revealed first four PCs under normal season1 (NSI) and three PCs under normal season2 (NSII), Pooled and heat stress (HS) contributed maximum per cent of total variation for nutrient and agronomic traits. Cluster analysis grouped the accessions into two clusters across the environments. GT biplot identified the accessions, ICC 9848, ICC 9872, ICC 9895 and ICC 9862 with high grain protein and Fe content; ICC 1161, ICC 8522 and ICC 2242 with high Zn content; and ICC 6874 and ICC 1392 with high values for seed yield over the seasons. The genotyping of chickpea reference set using mid-density 5k SNP array panel resulted in 4603 highly informative SNPs distributed across the chickpea genome. Population structure analysis revealed three subpopulations (K=3) in the reference set. PCA using SNP markers data revealed three distinct clusters where PC1 explained 38.2% and PC2 revealed 9.31% of total variance. The unweighted neighbor-joining (NJ) tree method grouped the accessions into three clusters. Linkage disequilibrium (LD) was extensive across the chickpea genome and LD decay was relatively low at a physical distance of 4032Kb across the genome. Genome-wide association analysis revealed a total of 20 and 73 marker-trait associations (MTAs) for grain nutrient and agronomic traits over normal seasons while a total of 11 and 45 MTAs were significantly associated with grain Fe and agronomic traits under HS using FarmCPU and BLINK models. The marker, S4_4477846 on chr4, was found to be co-associated with grain protein over seasons. The markers, S1_11613376 and S1_2772537 on chr1, co-associated with grain Fe content under NSII and pooled seasons and the marker, S7_9379786 on chr7, was co associated with grain Fe content under NSI, pooled and HS. SNP annotation of associated markers was found to be related to gene functions of metal ion binding, transporters, protein kinases, transcription factors, and many more functions involved in plant metabolism along with Fe and protein homeostasis. The identified significant MTAs require further validation and characterization to elucidate the exact role of these genes in chickpea. Further, it was noted, 92.9%, 74.3% and 10.4% of the accessions showed reduction of ~25% of grain protein, 22% of Fe and 16% of Zn under heat stress. The accessions, ICC 9848, ICC 9895, ICC 9862 and ICC 9872 were least affected by heat for protein, ICC 9895 and ICC 9643 for grain Fe content can be exploited in breeding programmes to develop nutrient-rich climate resilient chickpea cultivars. The present study highlighted the use of chickpea reference set for exploitation in marker-assisted selection to develop nutrient dense climate resilient chickpea varieties
  • Thumbnail Image
    ThesisItemOpen Access
    PRIORITIZATION AND VALIDATION OF CANDIDATE GENES FROM DATABASES OF QTLs GOVERNING ECONOMICALLY IMPORTANT TRAITS IN RICE (Oryza sativa L.)
    (Acharya N G Ranga Agricultural University, 2024-05-01) ISSA KEERTHI; Dr. V. LAKSHMI NARAYANA REDDY
    Rice (Oryza sativa L.) yield is a complex trait and is controlled by several minor genes with small effects. Elucidation of the genetic architecture of the complexly inherited yield and its associated traits is essential for progressive rice improvement. To this end, it is a prelude to pinpointing the genes and their intrinsic regulatory networks. For the past two decades, several genomic regions or QTLs have been uncovered for important agronomic traits. However, due to their large confidence intervals, pinpointing their candidate genes becomes difficult and prevents them from deploying straight away into rice breeding. The present investigation aimed to prioritize the candidate genes underlying important QTLs governing various yield traits based on publicly available diverse multi-omics databases. In order to prioritize candidate genes, a pipeline has been developed. As per the pipeline, a total of 99 QTLs consisting of six QTLs for heading date, five for tiller number, three for panicle number, five for panicle length, nine for plant height, 25 for grain number, five for spikelet fertility, 18 for grain length, 12 for grain weight and 11 for yield were targeted for gene prioritization. Among the selected QTLs, the range of PVE is 10-43% while LOD is 3-53.71. In addition, the QTL, qSNP-4a (12.53Mb) has the longest confidence interval while the QTL qDTY1.1 has the shortest interval of 0.08Mb. The QTL qGRL7.1 (398) has more annotated genes while qGL-3a (8) has the least annotated genes within the QTL region. These targeted QTLs have been distributed on all chromosomes except chromosome 11. More QTLs i.e., 23 have been found to be located on chromosomes 1 and 3 while fewer are on chromosome 3 with 8 QTLs. In total, 206 candidate genes have been predicted for 99 QTLs governing 10 economically important yield traits. To be specific, for heading date 15 candidate genes from six QTLs, for plant height 15 candidate genes from nine QTLs, for tiller number 11 candidate genes from five QTLs, for panicle number eight candidate genes from three QTLs, for panicle length nine candidate genes from five QTLs, for spikelet fertility nine candidate genes from five QTLs, for grain weight 28 candidate genes from 12 QTLs, for grain length 31 candidate genes from 18 QTLs, for grain number 59 candidate genes from 25 QTLs and for yield 21 candidate genes from 11 QTLs were prioritized. Among the candidate genes, some of the important transcription factors were also identified such as MADS-box transcription factor, growth-regulating factor, WRKY34, helix-loop-helix DNA-binding domain-containing protein, TCP family transcription factor, MYB family transcription factors, GRAS family transcription factor containing protein, auxin response factor, and nuclear transcription factor Y subunit. The role of the prioritized candidate genes is also predicted in already-known pathways of the targeted traits. To select the contrasting genotypes for the targeted traits, 102 diverse rice genotypes have been evaluated under field conditions and recorded data of the 10 economically important agronomic traits. Analysis of the variance of rice genotypes for yield traits revealed that there is a significant difference among all the genotypes suggesting considerable variability for the selection of contrasting rice genotypes. The majority of the traits have shown normal distribution except spikelet fertility and chaffy grains indicating that these traits are typical quantitative traits controlled by several genes with small effects. For validation of sequence variants from prioritized candidate genes, 22 primers have been designed for large frameshift mutations of 22 prioritized genes underlying 21 QTLs governing eight traits. Of them, 11 markers showed polymorphism, and 8 showed monomorphism while five markers were not amplified or produced inconsistent results in agarose gel electrophoresis. In general, none of the markers showed clear polymorphism between the contrasting rice genotype groups for the selected traits. However, few markers showed polymorphism between selected genotypes of the contrasting characters. The polymorphism witnessed between a few contrasting genotypes can be assumed as genotype-specific and therefore, these markers can be used for the marker-assisted improvement of the specific genotypes. Sequencing of the selected prioritized genes such as (LOC_Os04g22120) for the plant height QTL qPHT4-2, (LOC_Os03g28270) for the grain length QTL GL1 and (LOC_Os02g57290) for the panicle length QTL, pl2.1 revealed several sequence variations such as SNPs, multiple SNPs, insertions, and deletions. The gene expression analysis revealed significant fold changes in three predicted genes viz., LOC_Os03g28270 (Leucine Rich Repeat family protein) for the grain length QTL, GL1 LOC_Os06g16400 (helix-loop-helix DNA-binding domain-containing protein) for the grain weight QTL, gw-6 and LOC_Os02g57290 (cytochrome P450) for the panicle length QTL, pl2.1. Interestingly, the genes GL1 (LOC_Os03g28270) and pl2.1 (LOC_Os02g57290) exhibited clear variations in both gene sequences and gene expression. Through the present investigation, it was obvious that it is possible to narrow down a large number of annotated genes in a QTL to very few numbers of the most probable candidates using the pipeline developed in the study. Based on the findings of the prioritization of candidate genes for QTLs based on multi-omics databases, validation of sequence, and gene expression, it is very obvious that the candidate genes are very specific to genotypes. In order to find the function of each prioritized candidate gene, their evolution and domestication have to be elucidated besides functional characterization through the development of mutants or overexpression lines or gene editing by CRISPR and marker-assisted breeding before being exploited in rice breeding. Employing the pipeline developed in the study, other crops as well as animal species can be targeted to dissect the causal genes from QTL regions
  • Thumbnail Image
    ThesisItemOpen Access
    GENETIC DIVERSITY, POPULATION STRUCTURE AND ASSOCIATION ANALYSIS FOR FIBER QUALITY TRAITS IN COTTON (Gossypium hirsutum L.) USING SIMPLE SEQUENCE REPEAT MARKERS
    (Acharya N G Ranga Agricultural University, 2024-05-01) CHILAPARTHI VAMSI KRISHNA; Dr. V. ROJA
    The present investigation entitled “Genetic diversity, population structure and association analysis for fiber quality traits in cotton (Gossypium hirsutum L.) using simple sequence repeat markers” was carried out at the Regional Agricultural Research Station (RARS), Lam, Guntur, Andhra Pradesh during kharif 2021-22. A total of 48 cotton genotypes (Gossypium hirsutum L.) including two checks (NDLH1938 and LHDP-1) were studied for important fibre quality and yield attributing traits. The diversity among 48 genotypes were studied at the molecular level, using SSR markers. Sigle marker analysis was conducted to identify the markers that are significantly associated with the fibre quality traits. The observations were recorded for 48 genotypes on different plant morphological and yield attributing traits such as, plant height (cm), number of monopodia per plant, number of sympodia per plant, number of bolls per plant, boll weight (g), ginning outturn (%), seed index (g), lint index (g) and fibre quality traits i.e., upper half mean length (mm), micronaire value (μg/inch), fibre strength (g/tex), fibre uniformity (%) and fibre elongation (%). Among all the genotypes studied, five genotypes performed better for the yield and fibre quality traits. Among them, GP144 (number of sympodia per plant, seed index, fibre strength and fibre elongation) , GP55 (boll weight, ginning outturn (GOT), micronaire and fibre elongation), GP73 (boll weight, lint index, upper half mean length (UHML) and fibre uniformity), GP66 (lint index, upper half mean length (UHML) and elongation) and GP5 (number of sympodia per plant, boll weight, fibre strength and fibre elongation) exhibited good phenotypic performance. Correlation studies among the yield and fibre quality traits revealed that the number of sympodia per plant exhibited significant and positive correlation with number of bolls, lint index and ginning outturn (GOT). The upper half mean length (UHML) exhibited significant positive correlation with fibre uniformity. The fibre strength and fibre uniformity recorded significant positive correlation with fibre elongation. xv Among the 26 SSR markers studied, only six were found to be polymorphic. The six polymorphic SSR markers amplified a total of 12 alleles. Polymorphic information content (PIC) ranged from 0.40 to 0.50 with an average of 0.46. The highest PIC value was exhibited by the markers, JESPR204 (0.50), DPL0068 (0.50) and NAU2443 (0.49). The number of effective alleles ranged from 1.60 (NAU3467) to 2.00 (JESPR204) with a mean value of 1.83. The highest number of effective alleles were recorded by JESPR204 (2.00), DPL0068 (1.98) and NAU2443 (1.96). The shannon's information index varied between 0.56 (NAU3467) to JESPR204 (0.69) with a mean of 0.64. The cluster analysis based on UPGMA method revealed that the 48 genotypes were grouped into three major clusters. The cluster I comprised of 32 genotypes, cluster II comprised of 12 genotypes and cluster III comprised of 4 genotypes. The dissimilarity values obtained between the genotypes GP131 and GP138 was found to be 0.07, which indicated that these two genotypes having least dissimilarity, where as dissimilarity value of 0.11 was observed between GP101 and GP105, 0.125 was observed between the genotypes GP88 and GP109 and GP90 and GP92. The population structure analysis revealed that the entire 48 genotypes were divided into two subgroups based on the ΔK value (ΔK = 2). The marker trait association study conducted using single marker analysis revealed that the marker DPL0041 on chromosome 9 was significantly found to be associated with the trait boll weight with a phenotypic variance of 17.22%. Hence the marker can be utilized for the selection of genotypes with high boll weight using marker assisted selection. Among all the genotypes studied, five genotypes namely, GP144, GP55, GP73, GP66 and GP5 performed better for both yield and fibre quality traits. Hence, the above genotypes may be considered as the best donors for the breeding programme when aiming for development of high yielding hybrids coupled with good fibre quality
  • Thumbnail Image
    ThesisItemOpen Access
    IDENTIFICATION OF QTLs FOR LOW GRAIN SHATTERING IN BACKCROSS INBRED LINES OF RICE VARIETY MTU1010
    (Acharya N G Ranga Agricultural University, 2024-05-01) V. S. SAMPATH; Dr. P. VENKATA RAMANA RAO
    Rice is one of the major crops cultivated in Asia and is staple food in India. Grain shattering causes significant yield loss in MTU 1010, a mega rice variety cultivated in Andhra Pradesh and other states of India. The present investigation was aimed to identify QTLs for low grain shattering in backcross inbred lines (BC2F8 generation) developed from the cross between MTU1010 (high grain shattering variety) and JGL17004 (low grain shattering variety). Phenotyping for low grain shattering and yield traits was carried out in the BILs. The phenotypic data was collected for ten traits viz., score for grain shattering (Sh), plant height (PHt), days to fifty percent flowering (DFF), number of ear bearing tillers per plant (EBT), panicle length (PL), number of filled grains per panicle (FG), number of unfilled grains per panicle (UFG), spikelet fertility (SF), grain yield per plant (GYPP) and test weight (TW). Score for shattering was estimated and categorized as low, medium and high (Low - <5%, Medium- 5 to 10%, and High- >10%). Proper methods were followed to record and compute yield traits. Out of 84 BILs 54 BILs showed low grain shattering, 20 BILs showed moderate shattering and 10 BILs showed high shattering. Recurrent parent recorded high grain shattering than the donor parent. For yield traits BILs recorded higher values than the parents. The BILs 55 and 53 recorded a low shattering of 1.52% and 0.34 % respectively with a high grain yield per plant (35.7 g and 33.8 g respectively). The data recorded from phenotyping was subjected to ANOVA using augmented RBD. The genetic parameters were also computed for the phenotypic data. The results showed that the data was significant among BILs for most of the traits. Some of the traits showed higher values for genetic parameters like GCV and PCV (Sh, FG, UFG, and GYPP). Heritability was high for shattering and yield traits. The parental polymorphism survey was carried out with 626 SSR markers. Out of these, 88 markers were polymorphic (14.05%) between the parents. The population was subjected to genotyping with the eighty eight polymorphic markers. xiv The genotyping data was used in QTL ICImapping Version 4.2 to generate a linkage map which covered 2381cM. The IM and ICIM analysis detected 29 and 22 QTLs respectively at a LOD threshold of 2.0. The epistatic analysis detected 453 epistatic QTLs. Four novel QTLs viz., qSh-2-1, qSh-2-2, qSh-3-1 and qSh-10-1 for shattering were detected in both ICIM and IM. These four QTLs were also co-localized with 24 epistatic QTLs. Among the four QTLs identified in the present study, qSh-3-1 on chromosome 3 is far away from the QTLs reported earlier While, the QTL qSh-2-2 might be nearer to the gene (OsGRF4) for moderate grain shattering identified in earlier studies. But till date, none of the QTLs were identified for low grain shattering on chromosome 10. The current study also identified some major QTLs viz., qPHt-3-1 , qDFF-6-1, qPL-8-1, qUFG-2-1, qSF-2-1 and qTW-6-1 with high phenotypic variance. The BILs with low grain shattering can be utilized for further confirmation studies and the regions with QTLs for low grain shattering can be analyzed more precisely. So that they can be introgressed into the varieties with high grain shattering.
  • Thumbnail Image
    ThesisItemOpen Access
    IDENTIFICATION AND MOLECULAR CHARACTERIZATION OF WILD SPECIES OF RICE FOR RESISTANCE TO BACTERIAL BLIGHT
    (Acharya N G Ranga Agricultural University, 2024-04-30) TANNIDI BHAGYASRI; Dr. C. GIREESH
    WILD RICE are known to be a resources for many useful biotic and abiotic resistant genes which can be used in improvement of rice. They are reported to be resistant to bacterial blight (BB) caused by Xanthomonas oryzae pv. oryzae (Xoo) which causes severe infection in rainfed and irrigated conditions especially yield loss. Till now 46 different bacterial blight resistant genes are identified from diverse genotypes out of that 12 genes were identified from wild species The current study was aimed to identify and characterize wild rice accessions for resistance to bacterial blight. One hundred and sixteen wild rice accessions comprising of 63 accessions of Oryza rufipogon, nine of Oryza nivara, four of Oryza officinalis, four of Oryza latifolia, five of Oryza australiensis, two of Oryza minuta, five of Oryza punctata, three of Oryza eichingeri, five of Oryza rhizomatis, two of Oryza longistaminata, two of Oryza barthii, one of Oryza glumipatula, one of Oryza ridleyi, four of Oryza alta, one of Oryza longiglumis, four of Oryza grandiglumis and one of Oryza meridionalis along with susceptible check Samba Mahsuri are screened for Bacterial Blight resistance for three seasons Kharif 2020, Rabi 2020-21, Kharif 2021. Artificial inoculation of bacterial strain IXO-20 was done at maximum tillering stage by leaf clip inoculation method and disease score was taken after 14 days and 21 days of inoculation. Considering the performance of accessions of different wild species across three seasons 40 xiii promising accessions showing consistence and high level of resistance e mean lesion length data, 40 resistant accessions which had shown consistent resistance both on 14 and 21 days after inoculation over the three seasons were used for characterization of BB resistant genes. 40 promising accessions comprising of 22 of Oryza rufipogon, two of Oryza nivara, three of Oryza officinalis, two of Oryza latifolia, two of Oryza australiensis, one of Oryza minuta, two of Oryza punctata, three of Oryza eichingeri, one of Oryza rhizomatis, two of Oryza alta identified for bacterial leaf blight resistance were characterised for 11 Xa genes viz., Xa4, xa5, xa13, Xa21, Xa23, Xa27, Xa32, Xa33, Xa35, Xa38 and Xa41(t) using gene specific markers RM224, xa5FM, xa13 PROMOTER, pTA248, RM254, BDTG19, RM5926, RMWR7.1-7.6,RM144, Oso4g53050-1, Osweet-14 respectively. Out of the 40 BB resistant accessions, seven accessions shown the presence of single gene 10 accessions had shown the presence of two genes, 12 accessions were with three genes, whereas two accessions with combination of four genes and one accessions with five genes. Molecular characterisation of BB resistance genes showed that 4 accessions (IC521672, EC861677, EC861700, EC861711) did not show the presence of any gene studied indicating the possibility of novel gene conferring BB resistance in these accessions. It is further inferred that they are no reported BB resistant genes in Oryza latifolia and Oryza punctata which showed high level of resistance in present study indicating that novel gene conferring BB resistance, However, further inheritance and mapping studies are required to be carried out to ascertain the novelty of the sources.
  • Thumbnail Image
    ThesisItemOpen Access
    MORPHOLOGICAL, BIOCHEMICAL AND MOLECULAR CHARACTERIZATION OF FOXTAIL MILLET [Setaria italica (L.) Beauv.] GERMPLASM
    (guntur, 2022-08-25) SANDHYA, MUNAGAPATI; RAMANA, J. V.
    The present study was carried out with the prime objective of assessing morphological, biochemical and molecular diversity in 100 genotypes of foxtail millet. The experiment was conducted at Regional Agricultural Research Station (RARS), Lam, Guntur in Augmented Randomized Complete Block Design (ARCBD) during kharif, 2017 and rabi, 2017-18. Morphological and biochemical data for 21 parameters collected from these genotypes was pooled over seasons and analyzed for divergence using Mahalanobis’ D2 statistic and PCA analysis. Molecular divergence was estimated using 85 SSR markers. Highly significant variability was observed among the 100 genotypes for plant height (PH), carbohydrate (CARB), calcium (Ca), carotene (CARO) and phenols (PHE); whereas moderate variability was observed for days to 50% flowering (DFF), panicle length (PL), days to maturity (DM), grain yield (GYP), protein (PRO) and folic acid (FOA). Eight genotypes viz. ISe 1286, ISe 751, ISe 1201, ISe 1181, ISe 1674, ISe 1511, ISe 1704 and ISe 1338 were observed to be superior for at least four nutritional parameters (carbohydrate (CARB), protein (PRO), fat (FAT), crude fibre (CF), calcium (Ca), iron (Fe), phosphorous (P), potassium (K), niacin (NI), thiamine (TH), carotene (CARO), phenols (PHE), folic acid (FOA), lysine (Lys)) while, the genotypes ISe 1286, ISe 1674, ISe 1511, ISe 1704 and ISe 1338 are calcium rich genotypes. High PCV and GCV (>20%) were recorded for majority of the traits viz. plant height (PH), panicle length (PL), test weight (TW), productive tillers per plant (NPT), grain yield (GYP), crude fibre (CF), calcium (Ca), iron (Fe), phosphorous (P), niacin (NI), thiamine (TH), carotene (CARO), folic acid (FOA) and lysine (Lys) indicating the presence of high amount of variability. Low PCV and GCV (20%) was reported for the traits, days to 50% flowering (DFF), plant height (PH), panicle length (PL), test weight (TW), productive tillers per plant (NPT), days to maturity (DM), protein (PRO), fat, crude fibre (CF), calcium (Ca), iron (Fe), phosphorous (P), niacin (NI), thiamine (TH), carotene (CARO), folic acid (FOA), lysine (Lys) and grain yield (GYP) indicating the operation of additive gene action in the expression and exploitation of these traits by simple selection is suggested for improvement. The correlation studies of present investigation had revealed that the dependent variable grain yield had significant positive correlation with days to 50% flowering (DFF), plant height (PH), panicle length (PL), no. of productive tillers (NPT), days to maturity (DM) and test weight (TW) indicating their key role in selection for improvement of grain yield/plant (GYP). Path analysis also revealed days to 50% flowering (DFF), plant height (PH), panicle length (PL), no. of productive tillers (NPT), days to maturity (DM) and test weight (TW) had true relationship with grain yield per plant (GYP) by establishing significant positive association and positive direct effect revealing their importance in selection of high yielding genotypes in foxtail millet. Mahalanobis’ D2 analysis indicated the presence of substantial diversity in the studied material by forming nine clusters and maximum number of genotypes were present in cluster I (58 genotypes) followed by cluster IV (20 genotypes), cluster II (nine genotypes) and cluster V (eight genotypes). Clusters III, VI, VIII and IX were solitary clusters containing single genotype, ISe 1789, ISe 1685, ISe 1181and ISe 1201, respectively. Among the characters studied highest percentage of contribution towards divergence was noted by grain yield/plant (38.22%) followed by productive tillers per plant (35.46%), plant height (21.21%) and phosphorus (1.9%). The maximum inter cluster distance was observed between clusters, VII and IX (46356.45), followed by clusters VIII and IX (30901.85) and clusters V and VII (27950.79) which suggested the presence of broad genetic divergence among these clusters and can be exploited to generate transgressive segregants for the desired traits. It is apparent that the productive crosses can be expected from ISe 969 (cluster VII with higher mean values for grain yield (GYP), test weight (TW), panicle length (PL), no. of productive tillers (NPT) and calcium (Ca)) with ISe 1201 of cluster IX (higher mean values for fat (FAT), potassium (K), thiamine (TH), folic acid (FOA) and lysine (Lys)) by considering significant divergence and higher mean values for yield and its contributing traits. The principal component analysis (PCA) indicated the contribution of first ten principal components for about 76.59% variability and the contribution of first principal component (PC1) towards variability was 17.651% while PC2 was 10.753% and PC3 was 9.189%. The traits, panicle length (PL), grain yield (GYP) and number of productive tillers (NPT) contributed maximum towards divergence in PC1. Two dimensional (2D) plot based on PCA scores showed that the genotypes ISe 710, ISe 1181, ISe 771 and ISe 969 were scattered relatively away from the other genotypes indicating their usefulness in hybridization programmes. Molecular divergence analysis with 85 simple sequence repeats (SSR) markers resulted thirty polymorphic markers. The Polymorphism Information Content (PIC) values ranged from 0.037 to 0.573 with the mean value of 0.30. High PIC markers with better discriminatory power were SICAAS4007, SICAAS2043, SICAAS6067 and SICAAS9130 and these can be used for diversity studies, gene mapping, molecular breeding and germplasm evaluation. The number of alleles per primer was varied from two to six with an average of 2.56 alleles per primer. The dendrogram prepared from the UPGMA grouped the genotypes into 3 clusters with similarity coefficient value of 0.69. Cluster I had fifty five genotypes and the similarity coefficient range was 0.27 to 0.50. Cluster II had two sub-clusters with similarity coefficient values ranged from 0.33 to 0.69 while cluster III had ten genotypes and the similarity coefficient values ranged from 0.23 to 0.58.The genotype, ISe 746, formed a separate sub-cluster in cluster III as IIIC indicating its’ differentiation from other genotypes of this cluster Morphological, biochemical and molecular diversity of 100 foxtail millet genotypes clearly reported the presence of huge variability for yield and quality parameters. The genotypes viz. Ise237, ISe 710, ISe 1685, ISe 1767, ISe 1773, ISe 1808, ISe 1859, Ise 1888, Ise 90, Ise 771 and Ise 969 recorded high grain yield whereas ISe 1227, ISe 1286, ISe, 1674, Ise 1312 and Ise 1320 are early maturing genotypes. The genotype, ISe 1286, is rich in eight nutritional parameters (protein (PRO), fat, calcium (Ca), iron (Fe), niacin (NI), phenols (PHE), folic acid (FOA) and lysine (Lys)).The superior millet genotypes identified with high yield and nutritive values can be explored for the identification, characterization and mining of genes/alleles governing these traits and this forms the future line of study for other researchers.