DNA Fingerprinting of Prokaryotic Genomes

Information of legitimacy of oil palm progenies is important to guaranty the quality and to control commercial seeds procedures. A true and legitimate cross will produce progeny which has a combination of their parent's allele. The information could be obtained early in the nursery stage through DNA fingerprinting analysis. Simple Sequence Repeats (SSR) is one of DNA markers used for DNA fingerprinting, since the marker system has advantages to acquire information of allele per individual in population and efficiency diverse allele of progeny and their parents. The aim of the research is to obtain legitimacy of 12 progenies analyzing in the oil palm nursery stage. Thirteen SSR markers were used to analyze 12 crossings number of oil palm. The genotypes data by alleles of SSR inferred and quantified using Gene Marker® Software version 2.4.0 Soft Genetics® LLC and analyzed based on Mendel's Law of Segregation. The result showed based on heredity pattern of progeny and their parent's allele that progenies H were indicated genetically derived from their known parents while progenies from A and G indicated as illegitimate crossing. Probability value for legitimacy of progenies of 9 other crosses has 0.031 and 0.5. Legitimacy analysis of progeny using SSR markers could be used to control the quality of crossing material and earlier selection in the oil palm nursery.

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OPTIMATION OF DNA EXTRACTION PROTOCOL OF Elaeidobius kamerunicus

Jurnal Penelitian Kelapa Sawit ◽

10.22302/10.22302/iopri.jur.jpks.v24i2.10 ◽

2018 ◽

Vol 24 (2) ◽

pp. 77-86

Author(s):

Sri Wening ◽

Agus Eko Prasetyo ◽

Tjut Ahmad Perdana Rozziansha ◽

Agus Susanto

Keyword(s):

Dna Fingerprinting ◽

Dna Extraction ◽

Oil Palm ◽

Fruit Set ◽

Fragment Length Polymorphism ◽

Basic Knowledge ◽

Biological Study ◽

Palm Fruit ◽

Extraction Protocol ◽

Elaeidobius Kamerunicus

African pollination weevil (Elaeidobius kamerunicus Faust) has an important role in the productivity of Indonesian oil palm plantation. Up to now, there has not been a comprehensive biological study of the species at molecular level. The basic knowledge is very useful for exploitation of the weevil for effective oil palm fruit set development. This research aimed to obtain DNA extraction protocol of E. kamerunicus for DNA fingerprinting of the species. Results showed that using a DNA extraction kit,material disruption by using micro pestle resulted the highest quantity of DNA, while there were no significant differences of resulted DNA quantity among treatments using tissue lyser for material disruption. DNA extracted by using micro pestle or tissue lyser for material disruption is adequate for DNA fingerprinting using AFLP (Amplified Fragment Length Polymorphism) and sequencing techniques.

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DNA Fingerprinting Reveals a Lack of Genetic Variation in Northern Populations of the Western Pond Turtle (Clemmys marmorata)

Conservation Biology ◽

10.1046/j.1523-1739.1995.9051244.x ◽

1995 ◽

Vol 9 (5) ◽

pp. 1244-1255 ◽

Cited By ~ 7

Author(s):

ELIZABETH M. GRAY

Keyword(s):

Genetic Variation ◽

Dna Fingerprinting ◽

Pond Turtle ◽

Western Pond Turtle

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panRGP: a pangenome-based method to predict genomic islands and explore their diversity

Bioinformatics ◽

10.1093/bioinformatics/btaa792 ◽

2020 ◽

Vol 36 (Supplement_2) ◽

pp. i651-i658 ◽

Cited By ~ 1

Author(s):

Adelme Bazin ◽

Guillaume Gautreau ◽

Claudine Médigue ◽

David Vallenet ◽

Alexandra Calteau

Keyword(s):

Escherichia Coli ◽

Gene Transfer ◽

Horizontal Gene Transfer ◽

Species Level ◽

Genomic Islands ◽

Genome Plasticity ◽

Reference Dataset ◽

Prokaryotic Genomes ◽

Ideal Approach ◽

Genomic Regions

Abstract Motivation Horizontal gene transfer (HGT) is a major source of variability in prokaryotic genomes. Regions of genome plasticity (RGPs) are clusters of genes located in highly variable genomic regions. Most of them arise from HGT and correspond to genomic islands (GIs). The study of those regions at the species level has become increasingly difficult with the data deluge of genomes. To date, no methods are available to identify GIs using hundreds of genomes to explore their diversity. Results We present here the panRGP method that predicts RGPs using pangenome graphs made of all available genomes for a given species. It allows the study of thousands of genomes in order to access the diversity of RGPs and to predict spots of insertions. It gave the best predictions when benchmarked along other GI detection tools against a reference dataset. In addition, we illustrated its use on metagenome assembled genomes by redefining the borders of the leuX tRNA hotspot, a well-studied spot of insertion in Escherichia coli. panRPG is a scalable and reliable tool to predict GIs and spots making it an ideal approach for large comparative studies. Availability and implementation The methods presented in the current work are available through the following software: https://github.com/labgem/PPanGGOLiN. Detailed results and scripts to compute the benchmark metrics are available at https://github.com/axbazin/panrgp_supdata.

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