scholarly journals Genetic Profiling of Sida rhombifolia Originated from Several Indonesian Ethnicities Based on Sequence-Related Amplified Polymorphism Markers

2021 ◽  
Vol 6 (2) ◽  
pp. 203-212
Author(s):  
Jumailatus Solihah ◽  
Isma Kurniatanty ◽  
Dyah Subositi ◽  
Anshary Maruzy ◽  
Ika Nugraheny Ari Martiwi ◽  
...  
Keyword(s):  
Gene Flow ◽  
High Rate ◽  
Srap Marker ◽  
Plant Populations ◽  
Analysis Of Molecular Variance ◽  
Genetic Profiling ◽  
Molecular Variance ◽  
Genetic Characters ◽  
Sida Rhombifolia

Sida rhombifolia is one of wild flowering plants that grows easily in many habitats with moderate humidity, with some usefulness in traditional medicine. Genetic characterization of Sida rhombifolia accessions originated from 12 ethnicities of Indonesia was analyzed based on Sequence-Related Amplified Polymorphism (SRAP) Markers. The genomic DNA were extracted from leaf samples and then were characterized by using the SRAP marker system according to Li and Quiros (2001). Nine pairs of SRAP primer resulted high polymorphic bands and were used in the genetic profiling. The data analysis was performed using GenAlEx to calculate genetic distance, Principal coordinate analysis, and Analysis of Molecular Variance (AMOVA), also using POPGENE to assess genetic diversity (Hs and Ht) and Nm to predict gene flow among populations. The coordinate analysis showed that the accessions originated from ethnicities along Wallacean line tend to differ genetically from most other locations. However, the results of analysis of molecular variance suggested that there were only slight differences (0.1%) found between ethnicities, while most genetic variances (99.9%) were found mostly among accessions within populations. The results suggested that there was an extensive genetic flow and plant spreading among Sida rhombifolia plant populations, resulting more homogenous genetic characters among most populations, while high diversity within population. The calculation of the number of migration (Nm = 1.7341) confirmed that the high rate of gene flow had occurred between populations.

Incidence and molecular characterization of fungi and yeast isolated from cultured catfish and Nile tilapia

2020 ◽  
Vol 21 (3) ◽  
pp. 61-66
Author(s):  
Ola Hashem ◽  
Viola Zaki ◽  
Rawia Adawy
Keyword(s):  
Molecular Characterization ◽  
Oreochromis Niloticus ◽  
Nile Tilapia ◽  
Clarias Gariepinus ◽  
Fungal Species ◽  
High Rate ◽  
Fish Farms ◽  
Isolation And Identification ◽  
Penicillium Spp

Objective: To study the incidence and seasonal dynamics of different fungi affected freshwater fishes in Lake Manzala with molecular identification of the isolated fungi. Animals: 300 Nile tilapia (Oreochromis niloticus) and 300 catfish (Clarias gariepinus). Design: Descriptive study. Procedures: Random samples of Oreochromis niloticus (O. niloticus) and Clarias gariepinus (C. gariepinus) were collected from Manzala fish farms. Clinical and postmortem examination of fish was applied. Isolation and identification of different fungi were performed by conventional methods. Furthermore, the molecular characterization of isolated fungi was carried out. Results: C. gariepinus had a higher rate of infection with different fungal species than O. niloticus. Aspergillus spp. (Aspergillus niger and Aspergillus flavus) were the most fungal isolated from the examined fishes, followed by Penicillium spp. and Candida albicans. Aspergillus spp were detected in all seasons with a higher rate in summer and spring. A. flavus, A. niger, Penicillium spp. and C.albicans isolates were amplified from both C. gariepinus and O. niloticus at the specified molecular weight using PCR. Conclusion and clinical relevance: Fungal infection affected the fish showing different external and internal lesions, all species of Aspergillus were found in all seasons with a high rate in, hot seasons, summer and spring. The Prevalence of Penicillium and C. albicans were also reported. All fungal isolates were identified on the phenotypic and molecular bases.

Genetic Differentiation in Isolated Populations of Hakea carinata (Proteaceae)

1998 ◽  
Vol 46 (6) ◽  
pp. 671 ◽  
Author(s):  
G. J. Starr ◽  
S. M. Carthew
Keyword(s):  
Gene Flow ◽  
Habitat Fragmentation ◽  
Gene Diversity ◽  
South Australia ◽  
Similar Species ◽  
Isolated Populations ◽  
Plant Populations ◽  
Evolutionary Condition ◽  
Private Alleles

Fragmentation of the landscape by human activity has created small, isolated plant populations. Hakea carinata F. Muell. ex Meissner, a sclerophyllous shrub, is common in isolated fragments of vegetation in South Australia. This study investigated whether habitat fragmentation has caused restrictions to gene flow between populations. Gene diversity (HT = 0.317) is average for similar species but little is held within populations (HS = 0.168) and 46.9% of gene diversity is accounted for between populations. Estimates of gene flow are NM = 0.270 (based on FST) and NM = 0.129 (based on private alleles). Populations are substantially selfing (t = 0.111). Small isolated populations appears to be a long-term evolutionary condition in this species rather than a consequence of habitat fragmentation; however, population extinctions are occurring. Conservation will require the reservation of many populations to represent the genetic variation present in the species.

Landscape genetics in mammals

Mammalia ◽  
2014 ◽  
Vol 78 (2) ◽  
Author(s):  
Claudine Montgelard ◽  
Saliha Zenboudji ◽  
Anne-Laure Ferchaud ◽  
Véronique Arnal ◽  
Bettine Jansen van Vuuren
Keyword(s):  
Genetic Diversity ◽  
Gene Flow ◽  
Landscape Genetics ◽  
Metapopulation Dynamics ◽  
Local Adaptations ◽  
Future Developments ◽  
Ecological Features ◽  
Genetic Patterns ◽  
The Individual

AbstractThe focus of this review is on landscape genetics (LG), a relatively new discipline that arose approximately 10 years ago. LG spans the interface between population genetics and landscape ecology and thus incorporates the concepts, methods, and tools from both disciplines. On the basis of an understanding of the spatial distribution of genetic diversity, LG aims to explain how landscape and environmental characteristics influence microevolutionary processes and metapopulation dynamics, including gene flow (i.e., connectivity) and selection (i.e., local adaptations). LG is concerned with events that occurred during the recent time scale, and the individual is the operational unit. As a discipline that combines spatial genetic diversity with ecological features, LG is able to address questions relating to different evolutionary processes. We illustrate some of these here using examples taken from mammals: population structure; gene flow and the identification of barriers; fragmentation, connectivity, and corridors; local adaptation and selection; there are two different questions: applications in conservation genetics; and future developments in LG. We will then present the methods and tools commonly used in the different steps of LG analyses: the genetic and landscape sampling, the quantification of genetic variation, the characterization of spatial landscape structures, and finally, the correlation between genetic patterns and landscape features.

scholarly journals Microsatellite development via next-generation sequencing in Acacia stenophylla (Fabaceae) and Duma florulenta (Polygonaceae): two ecologically important plant species of Australian dryland floodplains

2018 ◽  
Author(s):  
Bruce F Murray ◽  
Michael A Reid ◽  
Shu-Biao Wu
Keyword(s):  
Gene Flow ◽  
Next Generation Sequencing ◽  
Microsatellite Markers ◽  
Information Content ◽  
Polymorphic Information Content ◽  
Extreme Variability ◽  
Polymorphic Microsatellite ◽  
Generation Sequencing ◽  
Semi Arid

Duma florulenta and Acacia stenophylla are two ecologically important but understudied species that naturally occur on the floodplains and riverbanks of Australia’s arid and semi-arid river systems. This paper describes the discovery and characterization of 12 and 13 polymorphic microsatellite markers for D. florulenta and A. stenophylla respectively. The number of alleles per locus for D. florulenta ranged from 2-12 with an average of 6.1. Across all samples, observed and expected heterozygosities ranged from 0.026 to 0.784 and 0.026 to 0.824 respectively and mean polymorphic information content was equal to 0.453. For A. stenophylla, the number of alleles per locus ranged between 2 and 8 with an overall mean of 4.8. Across all samples, observed and expected heterozygosities ranged from 0.029 to 0.650 and 0.029 to 0.761 respectively and mean polymorphic information content was 0.388. The developed suites of 12 and 13 microsatellite markers for D. florulenta and A. stenophylla respectively provide opportunity for novel research into mechanisms of gene flow, dispersal and breeding system and how they operate under the extreme variability these species are exposed to in the environments in which they live.

Analysis of molecular variance and population structure in southern Indian finger millet genotypes using three different molecular markers

2016 ◽  
Vol 19 (4) ◽  
pp. 275-283 ◽  
Author(s):  
Host Antony David Rajendran ◽  
Ramakrishnan Muthusamy ◽  
Antony Caesar Stanislaus ◽  
Thirugnanasambantham Krishnaraj ◽  
Sivasankaran Kuppusamy ◽  
...  
Keyword(s):  
Population Structure ◽  
Molecular Markers ◽  
Finger Millet ◽  
Analysis Of Molecular Variance ◽  
Molecular Variance

scholarly journals Lactate Production Precedes Inflammatory Cell Recruitment in Arthritic Ankles: an Imaging Study

2020 ◽  
Vol 22 (5) ◽  
pp. 1324-1332
Author(s):  
Marie-Aline Neveu ◽  
Nicolas Beziere ◽  
Rolf Daniels ◽  
Caroline Bouzin ◽  
Arnaud Comment ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Inflammatory Cell ◽  
Immune Cell ◽  
Lactate Production ◽  
High Rate ◽  
Metabolic Shift ◽  
Pyruvate Metabolism ◽  
Cell Recruitment ◽  
Inflammatory Cell Recruitment

Abstract Purpose Inflammation is involved in many disease processes. However, accurate imaging tools permitting diagnosis and characterization of inflammation are still missing. As inflamed tissues exhibit a high rate of glycolysis, pyruvate metabolism may offer a unique approach to follow the inflammatory response and disease progression. Therefore, the aim of the study was to follow metabolic changes and recruitment of inflammatory cells after onset of inflammation in arthritic ankles using hyperpolarized 1-13C-pyruvate magnetic resonance spectroscopy (MRS) and 19F magnetic resonance imaging (MRI), respectively. Procedure Experimental rheumatoid arthritis (RA) was induced by intraperitoneal injection of glucose-6-phosphate-isomerase-specific antibodies (GPI) containing serum. To monitor pyruvate metabolism, the transformation of hyperpolarized 1-13C-pyruvate into hyperpolarized 1-13C-lactate was followed using MRS. To track phagocytic immune cell homing, we intravenously injected a perfluorocarbon emulsion 48 h before imaging. The animals were scanned at days 1, 3, or 6 after GPI-serum injection to examine the different stages of arthritic inflammation. Finally, to confirm the pyruvate metabolic activity and the link to inflammatory cell recruitment, we conducted hematoxylin-eosin histopathology and monocarboxylase transporter (MCT-1) immune histochemistry (IHC) of inflamed ankles. Results Hyperpolarized 1-13C-pyruvate MRS revealed a high rate of lactate production immediately at day 1 after GPI-serum transfer, which remained elevated during the progression of the disease, while 19F-MRI exhibited a gradual recruitment of phagocytic immune cells in arthritic ankles, which correlated well with the course of ankle swelling. Histopathology and IHC revealed that MCT-1 was expressed in regions with inflammatory cell recruitment, confirming the metabolic shift identified in arthritic ankles. Conclusions Our study demonstrated the presence of a very early metabolic shift in arthritic joints independent of phagocytic immune cell recruitment. Thus, hyperpolarized 1-13C-pyruvate represents a promising tracer to monitor acute arthritic joint inflammation, even with minor ankle swelling. Furthermore, translated to the clinics, these methods add a detailed characterization of disease status and could substantially support patient stratification and therapy monitoring.

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