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Home > Association Mapping for Drought Sress Tollerance in Cotton Gossypium Hirsutum L.

Association Mapping for Drought Sress Tollerance in Cotton Gossypium Hirsutum L.

Thesis Info

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Author

Dahab, Abdelhafiz Adam

Program

PhD

Institute

University of the Punjab

City

Lahore

Province

Punjab

Country

Pakistan

Thesis Completing Year

2012

Thesis Completion Status

Completed

Subject

Natural Sciences

Language

English

Link

http://prr.hec.gov.pk/jspui/handle/123456789/882

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676725549995

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Currently, agriculture is facing a great threat from the risk of climate change. The productivity of the agriculture is also being seriously affected as a significance of key changes in the pattern of temperature and rainfall. It is expected that such changes will affect water availability to plants, especially for those native to the arid and semi-arid tropics (Giorgi, 2005). The genus Gossypium L. has long focused of genetic and breeding research. Cotton was one of the first species to which the Mendelian philosophies were applied and has a long history of progress through breeding with continual long-term yield gains. For sustained cotton production under global climate change an integrated approach, involving all available resources and techniques is needed. One potential and promising part of this integrated approach is the development of crop varieties tolerant to these abiotic stresses. Molecular Association mapping techniques can be successfully used to tag the genomic regions harboring loci involved in abiotic stress tolerance in cotton to help develop cotton cultivars with promising stress tolerance. Keeping in view this objective, projects were designed to tag genomic regions involved in drought tolerance in cotton. In order to achieve such evidence in G. hirsutum, ninety genotypes of Pakistani cotton population were evaluated under well- watered and drought stress conditions for morpho-physiological, plant architecture and yield traits, under glasshouse and field on seasons 2010 and 2011 respectively. The first experiment was carried out under controlled glasshouse conditions for phenotypic variations of cotton germplasm for morpho-physiological traits. The cultivars were sown in polythene bags and arranged according to Completely Randomized Design (CRD) with four replications in each treatment. After the emergence of first true leaves, water stress was applied. Data were recorded for morpho-physiological traits. In the second experiment the genotypic responses to well irrigated (W1) and water stressed (W2) conditions were assessed under field conditions for Phenotypic variations of cotton germplasm for plant architecture and yield traits at CEMB field University of the Punjab. All ninety genotypes were evaluated in randomized complete block design (RCBD) with three replications. For molecular variations these cultivars were genotyped by using a set of ninety five SSR Maker pairs with ~3-5 marker/chromosome the study showed that microsatellite markers are efficient for measuring the genetic diversity, relatedness and identifying varieties of cotton. We performed Linkage disequilibrium (LD)-based Association mapping for morpho-physiological, plant architecture and yield cotton population using a general linear model (GLM). The genotypic data obtained from SSR screening were analyzed by software STRUCTURE2.2 for estimating subgroups in population. The phenotypic data and information about the ancestry of individuals obtained from STRUCTURE2.2 software was put in the software TASSEL 2.0.1, and then the association analysis was achieved including population structure (Q-matrix) to detect the marker genotype which associated with studied traits. In this study, from the glasshouse experiment a total of twenty three marker loci main effect were significantly associated (P < 0.05) with the morpho- physiological traits phenotyped under the drought treatment. Phenotypic variance explained (R2) value ranged from 4.7% to 19%. Highest phenotypic variance 2 explained (R ) was ascribed to NAU3011marker located in chromosome D13 associated with root length. Marker NAU3011 associated (P= 0.0012) with root length in drought treatment appeared to be a major locus as it ascribed with highest phenotypic variance explained (R2) value of 19%. Majority of the markers were found to be associated with more than one trait. NAU3414 located on chromosome A9 (Ch.9) was associated with maximum (7) number of morphological traits (shoot length, shoot fresh weight, fresh root weight, fresh plant weight, dry shoot weight, and dry plant weight). Out of total twenty three markers associated with drought treatment, nine markers were found to be common in control and drought treatment ,These markers will be helpful in future endeavors to explore the complex nature of drought tolerance in cotton and It is advised that for drought stress these markers can successfully employed for MAS in future molecular breeding programs. However From field experiments twenty marker loci were significantly associated (P < 0.05) with plant architecture and yield traits phenotyped under the drought treatment. Phenotypic variance explained (R2) value ranged from 4.26% to10.14%. Marker BNL946 (Ch.20) reported highest phenotypic variance explained (R2) value of 10.14% associated with seed cotton yield. There were twelve markers which found to be common in control and drought treatment. BNL946 D10 (Ch.20) was found to be associated with maximum number of traits (plant height, number of nodes, numbers of bolls, boll weight), this marker locus is of importance and it is recommended that this cotton genomic region is associated with plant architecture and yield traits. JESPR274 marker located in (Ch.9) is also another important locus which imparts high phenotypic variance explained (R2) value of 17.8% under control treatment. The positive results from this study encourage the further testing of these methods in different genetic systems, in the same manner as we applied to cotton. This is the first report on LD-based association mapping using G. hirsutum cultivars in Pakistan for Identification of molecular markers linked to phenotypic traits involved in drought stress tolerance. The results are helpful for application of ‘association study’ in cotton that will accelerate development of superior cotton cultivars through MAS programs.
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حسرت ہی رہی مجھ پہ و ہ احسان کرے گا

حسرت ہی رہی مجھ پہ وہ احسان کرے گا
دیدار سے ہر درد کا درمان کرے گا

ہے عید کا دن آج وہ نکلے گا سنور کے
وہ عید کے دن حشر کا سامان کرے گا

بے چین مرے دل نہ رقیبوں سے ہوا کر
دشمن ہے تو ہر حال میں نقصان کرے گا

بیمارِ محبت ہے نکل جائے مطب سے
یہ اور مریضوں کو پریشان کرے گا

تائبؔ سے کبھی جان کو تو مانگ کے تو دیکھ
سو بار ترے نام پہ قربان کرے گا

Hybrid Warfare and its Impacts on Pakistan

In modern times, the conventional means of warfare are increasingly becoming less usable. However, the states are involved in waging hybrid warfare to the maximum to fulfill their foreign policy goals. In nuclearized South Asia, direct war between India and Pakistan seems unlikely given that both the states know that escalation could lead to nuclear catastrophe in the region. This compels both the states to find other means of warfare to undermine each other’s interests. India wants to weaken Pakistan so that it may abandon claim on Indian occupied Jammu and Kashmir. For that, India is using all tools of hybrid warfare against Pakistan. In this context, this paper aims at to unearth India’s hybrid warfare in the region and its implications for Pakistan. The main focus of the paper is to explain tools and methods of India hybrid warfare. At the same time the research also tries to unravel few other case studies. It also notes how Pakistan can counter hybrid threats posed by its arch rival.

Developing a Sindhi Computational Resource Grammar in Lexical Functional Grammar Framework

Computational grammar development and deep linguistic analysis provides structural details for natural language understanding by machines. Modern multilingual information processing systems use these details for understanding and processing of information represented in different languages. While work in Sindhi language is focused in the areas like part of speech tagging and machine learning. Sindhi lacks resources like computational grammars and deep linguistic analysis systems. Development of such resources is open research area in computational linguistic and natural language processing domains. This work presents the development of Sindhi language morphology and grammar in Finite State Technology and Lexical Functional Grammar (LFG) frameworks. The work includes the investigation and identification of morphology and syntax patterns in Sindhi language, development of Sindhi finite state lexicon by modeling of identified morphological patters in LEXC, development of Sindhi LFG by incorporating the finite state lexicon in XLE, and evaluation of developed morphological lexicon and LFG grammar. Various parts of speech of Sindhi language are investigated and their morphological patterns are identified. Nouns are marked by number, gender and case. Ten different cases of nouns are identified namely nominative, accusative, dative, participant, instrumental, locative, ablative, agentive, genitive and vocative. Adjectives are also declined like nouns. Pronouns are declined for number and gender and are marked by nominative, oblique and genitive cases. Generally, adverbs are not inflected but when adjectives used as adverbs they hold the inflectional properties of adjectives. Genitive iv postpositions are inflected and marked by number and gender. Conjunctions and interjections do not inflect. Verbs are most complex part of speech and classified into main, auxiliary, copula and modal verbs. Verbs are conjugated by number and gender and are marked by tense, aspect and mood. Morphological analysis of developed model shows that a verb can have up to 75 different morphological forms in Sindhi. Present, past and future tense patterns along with aspect and mood are analyzed. Aspect in Sindhi can either be perfective or imperfective (continuous and habitual) and can be marked morphologically or syntactically. Many alternative patterns of different aspects exist. Nine different mood patterns are identified including subjunctive, presumptive, imperative, declarative, permissive, prohibitive, capacitive, compulsive and suggestive. Pronominal suffixes in Sindhi may appear on nouns, postpositions and verbs. Pronominal suffixation can possibly cause subject and object pro-drop. Sindhi syntax is analyzed with LFG perspective. Different noun phrase constructions are implemented with coordination patterns including adjective phrases, postpositional phrases, participle phrases, and relative clauses. Genitive case marking patterns along with syntactic agreement are identified and modeled in LFG. Verbal subcategorization frames are defined for different grammatical functions including SUBJ (Subject), OBJ (Object), OBJ2 (Secondary Object), OBL (Oblique), COMP (Complement), XCOMP (Open Complement), and PREDLINK (Predicate link). Phrase and sentence level adjuncts (ADJUNCT) and open adjunct (XADJUNCT) patterns are also identified and implemented in LFG. The developed grammar is tested against two different test suites. First v test suite contains 617 handcrafted sentences in 10 different test files containing sentences with different syntactic features. Second test suite contains real time corpus of two text books of Sindhi class one with 258 sentences. Results show 98.05% and 96.5% parsing percentage of test suite 1 and test suite 2 respectively. Morphology coverage includes 862 stems of different POS classes with total of 10327 inflectional forms. The developed finite state morphology is tested and evaluated against the corpus of 9050 words in terms of coverage, ambiguity, precision, recall and f-measure (F1). The results show 97.8% precision, 96.08% recall and average ambiguity of 1.65 solutions per word with 91.1% coverage. Coverage of different morphological features include number, gender, case, tense, aspect and mood. Syntactic coverage includes nominal elements, coordination, subordination, agreement, verbal subcategorization, tense, aspect and mood. Research and development results include Sindhi part of speech tagset, roman script for Sindhi language, morphological lexicon and LFG grammar of Sindhi. As a side development, a corpus of about 4 million words is also developed. In absence of linguistic resources for Sindhi language, these developments will have signification impact on Sindhi language processing and further research in computational linguistics and related domains.