2022.07.03.27
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Analysis a number of Quantitative Traits and Genetic Variation of Different Generation of Wheat (Tritecum aestivum) by using RAPD-PCR

Raed Salem Alsaffar
Department of Biology, Faculty of Science,
University of Mosul
Corresponding author. Raedsaffar19@gmail.com
Available
from: http://dx.doi.org/10.21931/RB/2022.07.03.27
ABSTRACT
RAPD-PCR
genetic markers were used to assess genetic variation in wheat plants and
connections among six wheat genotypes. Four random primers produced 140 DNA
fragments, averaging 6.7 identifiable bands per primer. Among the six
genotypes, 85 pieces (44.64 percent) were polymorphic. Several RAPD marker
bands had distinct signify recurrence patterns that thing differently amongst
germplasm of wheat plants groupings. Within-community genetic variation
accounted for 78 to 89 percent of the overall variance. Wheat genotypes may be characterized and
classified using RAPD analysis. These findings will be a benefit in wheat-producing
offspring efforts in the future.
Keywords. Barley, Genetic variation, RAPD-PCR.
INTRODUCTION
Wheat grains are the world's most critical
cultivated plants and humanity's most crucial nutritional staple1.
Wheat breeding changed forever with the development of short-statured,
fertilizer-responsive wheat cultivars. As a result, grain production potential
has increased significantly2,3,4.
Wheat is cultivated on 40% of Pakistan's
cultivable land, with an average output of 2495 kg/ha5,6. In comparison
to other agricultural countries, this is relatively low. Understanding local
variations' genetics and genomic structure using molecular markers are beneficial
for breeding purposes7,8. The first stage in wheat improvement, like any
other crop species, is a thorough examination of the local resources, including
the collection, appraisal, and molecular characterization of germplasm lines.
Crop development efforts might benefit significantly from understanding
germplasm diversity and genetic linkages among breeding materials. Data on
germplasm variety and genetic relatedness among high-quality breeding stock are
crucial in plant breeding6,5,4,3.
Although a varied genetic foundation has
recently been recommended for wheat disease resistance4, Future breeding efforts will
also rely on the availability of genetic diversity to enhance productivity5.
As a result, to attain self-sufficiency and
sustainability, cultivars with a broad genetic foundation must be developed6.
Breeders can better grasp the evolutionary
links between accessions if they know diversity trends7.
Traditionally, variations in morphological and
agronomic characteristics have been used to analyze wheat genetic diversity and
pedigree information8.
The focus today is on collecting genetic
diversity within and between accessions. SSR, RFLP, RAPD and AFLP analyses are
the finest approaches for achieving this9.
The current method for assessing genetic
diversity within germplasm collections is RAPD for cultivar identification
utilizing DNA profiling10.
PCR depends on the RAPD technique as genetic
markers are the prevailing marker widely utilized in genetic mapping11. And the identification of loci associated with
various phenotypes12.
RAPD – PCR technique has been utilized for
genetic variation studies in various plants because of its technical simplicity
and rapidity13.
This study's goal was to compare the qualities of
wheat plant phylogenetic groups depending on seed traits clustering to
phylogenetic groupings based on RAPD-PCR clustered using UPGMA14.
MATERIAL AND METHODS
DNA
extraction from the seed of Wheat
DNA of seed was isolated from 6 different wheat generation (Triticum
aestivum L.) immature leaves. At 25 °C in the dark, all generations were
planted in plastic pots (200 ml). The generated kit was used to extract DNA
from 15-day-old seedlings11. Then the DNA isolated was
kept at -80 C. To utilize for PCR amplifications.

Table 1. The 4 RAPD primers used are shown
and PCR conditions
RESULT AND DISCUSSION
Following electrophoresis in SB buffer, the
RAPD-PCR bands were specified on 2 percent (w/v) agarose gel electrophoresis
and observed under UV light after Red Safe staining.
All amplifications were
done twice to ensure that the amplification of scored fragments was repeatable.
All visible RAPD fragments were enumerated for each primer, and strong
polymorphic bands were graded as present (1) or absent (0). The number of
polymorphic bands for each primer was determined.

Figure 1. The RAPD-PCR product for 6 generations of Wheat with (GLE-01)
Primer and M ladder 100 bp

Figure 2. The RAPD-PCR product for 6 generations of
Wheat with (GLE-02) Primer and M ladder 100 bp

Figure 3. The RAPD-PCR product for 6 generations of Wheat with (GLE-03)
Primer and M ladder 100 bp

Figure 4. The RAPD-PCR product for 6 generations of
Wheat with (GLE-04) Primer and M ladder 100 bp
A dendrogram built with
UPGMA clustering was used to assess genetic connections between generations.

Figure 5.
The Dendrogram of 6 different wheat generations developed from RAPD-PCR data
utilizes unweighted pair grouping of arithmetic means (UPGMA).
The 4 primers produced
100 DNA fragments, with an average of 6.7 bands for each primer. 45.22 percent
of the amplified fragments were polymorphic. All the primers produced 4 to 11
amplification products ranging in size from 0.27 to 3.6 kb. The primer sequence
solely determined the size and quantity of DNA fragments (fir15(.With
various primers, the degree of polymorphism varied between generations. These
findings show that RAPD-PCR markers offered helpful information for wheat
generation identification. Momal-2002 produced the most DNA amplified bands
(85) of the 10 genotypes examined, whereas line CIM-31 produced the fewest16.
Several variables can
affect the repeatability of the RAPD method, including primer sequence,
template quality and amount, thermocycler type, and Taq-polymerase activity11,14.
The implementation of a
defined RAPD procedure, on the other hand, can assure that RAPD patterns are
repeatable. In each repeat, all of the amplified bands were identical. A
similarity matrix was generated using multivariate analysis to assess genetic
diversity among wheat generations18.
UPGMA analysis was used
to create a dendrogram (Fig. 5) to identify the grouping of the wheat generation
using these similarity coefficients.
Just 8670-3 was found
in a second cluster, the most different generation examined, with only 79.2
percent similarity to the other genotypes in our research9,10.
RAPD analysis proved highly
successful in detecting genetic diversity among wheat generations, despite the
small genetic basis among the 6 generations employed here, and can be used to
create DNA fingerprints for identifying different varieties13.
The genetic isolation
between generations (Fig. 5) might be due to a few seed firms' closed guild
marketing procedures.
CONCLUSION
The ramifications of
these discoveries for wheat plant breeding are significant. These genotypes'
genetic material links might aid in selecting genetically diverse parents for
germplasm production. The discovery of a minor genetic alteration in Wheat
emphasizes the need to expand the genetic base of wheat breeding materials.
This genetic diversity index might help researchers decide which parents to
employ for genome mapping 8,12.
Funding: self-funding
Acknowledgments: In this section, we acknowledge any
person who supports us in completing this project.
Conflicts of Interest: there is no conflict
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Received:
25 January 2022 / Accepted: 14 June 2022 / Published:15 Agoust 2022
Citation:
R
Salem Alsaffar. . Analysis a number of Quantitative Traits and Genetic
Variation of Different Generation of Wheat (Tritecum aestivum) by using
RAPD-PCR. Revis Bionatura 2022;7(27) 2. http://dx.doi.org/10.21931/RB/2022.07.03.27