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Dna Based Identification and Genetic Diversity Studies of Antlion Species of Pakistan

Thesis Info

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Author

Saleem. Akhtar

Program

PhD

Institute

The University of Agriculture

City

Peshawar

Province

KPK

Country

Pakistan

Thesis Completing Year

2018

Thesis Completion Status

Completed

Subject

Biotechnology

Language

English

Link

http://prr.hec.gov.pk/jspui/bitstream/123456789/9279/1/Saleem%20Akhtar_Plant%20Genomics_2018_UAP_PRR.pdf

Added

2021-02-17 19:49:13

Modified

2024-03-24 20:25:49

ARI ID

1676725920382

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Antlions, a group of popular predatory insects, comes under the family Myrmeleontidae and the order Neuroptera. Both adults and larvae are predatory in nature. The proper identification of an organism is a key factor in understanding its biology. Due to their unique biology and mysterious living antlions generally remain under-explored. A large number of antlion species have been described from around world; still there is a lot of confusion in their taxonomy. In Pakistan, antlion fauna is not fully explored prior to this study only 28 species have been reported so far from the country. This study steps forward in exploration of Pakistan’s rich antlion faunal diversity. Still lot of it needs to be explored. This study improved the species number of Pakistan to 44. Which blong to 2 subfamilies 8 tribes and 20 genera. Subfamily Palparinae of Pakistan is represented with five genera and eight species. Species Palparellus astutus and Palpares rajasthanicus first time reportd from Pakistan. While Palpares trichogaster Navas, 1913 reinstate as valid species also P. cephalotes by Iqbal and Yousuf (1997) identified as junior synonym for the species. Genus Stenares Hagen, 1866 two species recorded Stenares hyaena clarus Navas, 1932 and Stenares improbus (Walker, 1853). Species S. improbus first time recorded from Pakistan. Author was not able to collect any specimen of genus Tomatares from Pakistan. Subfamily Myrmeleontinae is represented by seven tribes, eighteen genera and thirty five species. Tribe Acanthaclisini Navas, 1911 constitutes two genera Acanthaclisis and Centroclisis. Acanthaclisis obscura Hölzel, 1972 first time reported form Pakistan. Genus Centroclisis is represented by two species with one new species refered as Centroclisis thari.Tribe Dendroleontini Banks, 1912 is represented by one species Epacanthaclisis alaica first time recorded from Pakistan. In Tribe Nemoleontini Banks, 1911 represented by first time reported species Pseudoformicaleo gracilis. Tribe Neuroleontini Navas, 1912 with seven genera; genus Delfimeus Navas, 1912 monotypic Delfimeus intricatus. Genus Distoleon Banks, 1910 with four species Distoleon nefandus, Distoleon cyrus, Distoleon obducens and Distoleon tesselatus all four first reported from Pakistan Genus Ganguilus Navas, 1912 one species Ganguilus pulchellus (Banks, 1911). Genus Indoleon Banks (1913) presentdd with one species Indoleon vartianorum (Hölzel, 1972). Genus Neuroleon Navas, 1909 four species Neuroleon tenellus, Neuroleon (Ganussa) leptaleus, Neuroleon egenus and Neuroleon asiricus all first time reported. Myrmecaelurini Esben-Petersen, 1918 having six genera: Genus Gepus Navas, 1912 with one species Gepus invisus Navas, 1912 first time recorded from Pakistan. Genus Iranoleon, Hölzel, 1968 monotypic Iranoleon vartianae Hölzel, 1968. Genus Myrmecaelurus Costa, 1855 having four species. Myrmecaelurus laetus, Myrmecaelurus paghmanus and Myrmecaelurus (Nohoveus) vanharteni first time reported from Pakistan. Genus Solter with two species and Solter Solter felderi first time reported from Pakistan. Tribe Nesoleontini Markl, 1954 with three genera: Genus Cueta having five specie. While four species Cueta striata, Cueta thaliae, Cueta minervae and Cueta plexiformia first time recorded from Pakistan. Tribe Myrmeleontini only genus Myrmeleon with six species. Five species Myrmeleon trivialis,Myrmeleon bore, Myrmeleon hyalinus, Myrmeleon noacki and Myrmeleon inconspicuous are first time reported from Pakistan. Species were identified morphologically and 703 specimens were selected for DNA barcoding. Maximum 10 specimens from each species were selected. The Barcode Index Number (BIN) analysis using BOLD Systems Version 3.0 assigned 40 BINs to total 359 Antlion DNA sequences recorded for DNA barcode region. To find maximum distance distribution in species Barcode Gape Analysis and Automated Barcode Gap Analysis was performed using BOLD and online resource respectively. Results showed that maximum intera specific distance was 0 to 2.69%. While comparison with other countries was not possible as there was no data available for same species from other countries. This may be due to non processing of specimens from other countries or species endemism. The analysis showed that no species have been already sequenced and added to BOLD. So it has been added first time at least for local fauna. Value of maximum interspecific distance was less than nearresrt neighbor distance. Distance analysis of the barcode sequences showed an interspecific.divergence of at least 2%. Nearest neighbor joining (NNJ) tree also revealed that close taxa were grouped together more precisely than distant species. An online DNA based reference library was created, for species collected in the present study, on the Barcode of Life Data Systems (http://www.boldsystems.org). Results revealed that antlions exist throughout Pakistan in all geographical and environmental conditions and were not restricted to dry hot and arid areas. They are much abundant in undisturbed and non polluted areas. Collection and survey records revealed that in intensive crop zones due to habitat loss and higher chemical pollution antlion population has almost been eliminated.
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108. Al-Kawthar/The Abundance

108. Al-Kawthar/The Abundance

I/We begin by the Blessed Name of Allah

The Immensely Merciful to all, The Infinitely Compassionate to everyone.

108:01
a. O The Prophet!
b. Surely WE have granted you unceasing abundance.

108:02
a. So stand in Salat/Prayers for your Rabb - The Lord with devotion and dedication, and
b. make sacrifice for HIM in gratitude.

108:03
a. Indeed, your opponent who satirizes you and detests you – he has been cut off from all that is good and posterity.

Biological activity of Citrus paradisi peel

Citrus paradisi (Grapefruit) peel oil has medicinal properties which shows beneficial effects against plant pathogenic fungi Objective: The aim of this research was to investigate the antifungal potential of Citrus paradisi peel oil against different plant pathogenic fungal strainsMethods: The essential oil of Grapefruit peel was provided in different concentrations 0.25 to 0.75ml per 100 ml of media to 3 different plant pathogenic fungal strains i.e, Fusarium oxysporum, Fusarium solani and Dreschlera tetramera and its effect on the growth of fungi was recorded Results: The studies provided the results compared with the controlled media, which showed the fungal growth was almost completely inhibited at 0.75ml concentration of oil, even the lower concentration was sufficient to retard the growth Conclusions: The study provided the blue print for fungicidal spray to cure serious diseases in plants, such as, rice blast, papaya fruit rot, seedling collar rot and wilt diseases.

Reconstruction of Qualitative Gene Regulatory Networks

Genes provide instructions for the synthesis of functional products, such as, proteins. Gene expression develops the functional products using the instructions encoded in the genes. Gene regulation controls the process of gene expression in a way that it can regulate the increase or decrease of the gene expression resulting in the synthesis of specific functional products. It also controls when or when not to express a particular gene to produce a particular protein. Collection of regulatory elements, such as, genes and their interconnections showing the gene expression levels, are visualized as a Gene Regulatory Network (GRN). GRNs act as a tool for understanding the causation relationships between the genes and proteins representing complex cellular functionalities. Computational biology has laid its main focus nowadays on the reverse engineering or reconstruction of GRNs from gene expression data to decode the complex mechanism of the cellular functionalities. These efforts have resulted in improved and more precise diagnostics and therapeutics. Microarray technology of analyzing gene expressions calculates expression of thousands of genes simultaneously under different conditions, like, control or disease conditions. It helps in identifying over-expressed genes likely to be associated with the disease. Multiple approaches to reconstruct GRNs from gene expression data, apply various techniques, such as, distance measures, correlations, mutual information algorithms, dynamic and quantitative probabilities. These approaches result in identifying symmetric and diagonal gene pair interactions. Symmetric gene pair interactions cannot be modeled as direct activation and inhibition interactions. Moreover, diagonal nature shows that a gene cannot self-regulates itself, which is also contradictory with the true nature of gene pair regulatory interactions. Compromising the true asymmetric and non-diagonal nature of the actual gene pair regulatory interactions, can lead to incomplete and inferior predictions. To our knowledge, no such complete model exists to generate GRN representing all possible network motifs between gene pairs, such as, activation, inhibition and self-regulations. The proposed approach, named as, Multivariate Covariance Network (MCNet), aims at reconstructing GRN applies multivariate co-variance analysis and Principal Component Analysis (PCA) to identify asymmetric and non-diagonal gene interactions. The GRN developed using the MCNet approach holds all the possible network motifs, representing all kinds of gene-pair regulatory interactions (i.e., positive and negative feedback loops as well as self-loops). The asymmetry is achieved by computing the distance measure of the genes with respect to the eigen values of the related genes showing variable behaviors under different conditions. PCA in the MCNet approach selects gene-pair interactions showing maximum variances in gene regulatory expressions. Asymmetric gene regulatory interactions help in identifying the controlling regulatory agents, thus, lowering the false positive rate of interacting genes by minimizing the connections between previously unlinked network components. The performance of the proposed approach, MCNet, has been evaluated using a real data set as well as three synthetic and gold standard data sets. The MCNet approach predicts the regulatory vi interactions with higher precision and accuracy as compared to some currently state-of-the-art approaches. The results of the MCNet approach using the real time-series RTX therapy data set identified self-regulatory interactions of the differentially expressed (DE) genes with 80.6% accuracy. The MCNet approach predicted the gene regulatory interactions of the time-series synthetic Arabidopsis Thaliana circadian clock data set with 90.3% accuracy. The self-regulatory interactions identified in the RTX therapy and synthetic Arabidopsis Thaliana data sets are further verified from the literature because gold standards are not available for these data sets. Gold standard DREAM-3 and DREAM-8 in silico data sets, are also used to evaluate the performance of the proposed approach, while comparing with some existing approaches. The DREAM-3 in silico E-coli gold standard data set does not contain any self-regulations, while the DREAM-8 in silico phosphoproteins gold standard data set hold self-regulations. The results demonstrate the enhanced performance of the MCNet approach for predicting self-regulations only in the DREAM-8 in silico phosphoproteins data set with 75.8% accuracy. The MCNet approach for reconstructing GRN identifies direct activation and inhibition interactions as well as self-regulatory interactions from microarray gene expression data sets. The generated GRN can constitute positive and negative feedback loops as well as self-loops to demonstrate true nature of the gene-pair regulatory interactions. In future, it is aimed to enhance the functionality of the MCNet approach by modeling the dynamics of the GRNs, such as, oscillations and bifurcations towards steady state