VIETNAM NATIONAL UNIVERSITY OF AGRICULTURE FACULTY OF BIOTECHNOLOGY ---***--- UNDERGRADUATE THESIS TOPIC: IDENTIFICATION OF ORANGE VARIETIES BY USING ITS, MATK AND RBCL PRIMERS HAN
INTRODUCTION
The urgent of undergraduate thesis
As of 2022, the Department of Horticulture (Ministry of Agriculture and Rural Development) reports that the total area dedicated to citrus trees in the country is 210,000 hectares, with oranges occupying approximately 100,000 hectares The area devoted to orange cultivation has seen significant growth since 2013, expanding from 53,800 hectares to 97,400 hectares by 2018, resulting in an impressive output of over 840,000 tons and an average annual increase of 14%, which translates to an addition of 9,200 hectares each year.
Currently, 19 provinces have orange cultivation areas exceeding 1,000 hectares, with significant farming regions in northern provinces like Ha Giang, Hung Yen, Hoa Binh, and Phu Tho This has resulted in an oversupply of oranges Additionally, many citrus varieties lack state protection.
Vietnam is home to a diverse range of native orange varieties, representing a valuable resource for sustainable economic and social development in agriculture These specialty oranges contribute to high-quality agricultural products and possess resistance to pests, diseases, and adverse conditions, making them essential for creating safe agricultural outputs This approach aligns with sustainable development goals, particularly in the face of climate change.
With the integration into the WTO, our country's agricultural products, including oranges, are poised for global export opportunities Currently, only a limited number of products, such as Ha Giang, Ham Yen, and Cao Phong oranges, are in the process of establishing their names, geographical indications, and origins However, the National Office of Intellectual Property of Vietnam reports that only 15% of agricultural products are registered for protection in the country To enhance the protection of plant varieties and biological resources, the Ministry of Natural Resources and Environment has proposed the advancement of molecular techniques.
2 identification of varieties, parents of hybrid, and biodiversity individuals to help resolve disputes over gene sources and plant varieties
In our country, native orange varieties have been collected and stored, but research and systematic evaluation remain limited There is a pressing need for comprehensive data at the molecular and genetic levels, including DNA barcoding, to effectively preserve, exploit, classify, and identify the origins of these genetic resources Addressing this urgent requirement is essential for ensuring the sovereignty of our native orange gene sources.
In order to gain the development goal, apply DNA database and DNA barcode for native orange varieties for the registration of copyright, conservation, breeding, we have implemented the content
“IDENTIFICATION OF ORANGE VARIETIES ( CITRUS SPP.) WITH
HIGH ECONOMIC VALUE, HIGH YIELD, AND HIGH-QUALITY ORANGE VARIETIES BY USING ITS, MATK, RBCL PRIMERS”
Objectives and requirements
Identification and classification of some Orange varieties by using ITS, matK, rbcL primer and SSR primer
The selection of an appropriate DNA extraction protocol is crucial for ensuring the purity and integrity of the extracted DNA The results of the PCR analysis revealed clear and distinct bands, confirming the effectiveness of the extraction process Additionally, the accurate identification of specific DNA barcodes is essential for the reliable identification of orange species.
The SSR method was successfully employed to assess genetic variations in the studied orange samples By sequencing the ITS, matK, and rbcL regions, we were able to classify the samples and determine their relationships.
LITERATURE REVIEW
The situation of studying the DNA barcode of Citrus in the world and
2.1.1 The situation of studying the DNA barcode of Citrus in the world
In 2003, Paul Hebert from the University of Guelph introduced the concept of "DNA barcoding" to identify species This innovative method utilizes a short DNA sequence from an organism's genome, functioning like a supermarket scanner that differentiates between similar-looking products DNA barcodes provide a standardized approach to determine the species classification of an organism based on its unique genetic markers.
Scientists worldwide are actively developing a DNA barcode database, with the Barcode of Life (CBOL) establishing a global standard for DNA barcoding This initiative has resulted in a comprehensive library containing 3,483,696 DNA barcode sequences across 215,513 species, including 144,402 animal species, 54,478 plant species, and 16,663 fungal species DNA barcodes serve as a powerful tool for classifying and detecting new species, examining samples from both living and deceased organisms, protecting endangered species, and identifying the value of endemic species through standardized DNA regions Their applications extend widely in both research and practical fields.
Research indicates that the mitochondrial genes CO1 and Cytb are effective in identifying various animal and algal species However, their application to terrestrial plants shows different results.
4 high conservatism and therefore not suitable for barcode DNA (Fazekas et al.,
In phylogenomic analysis, discrete regions of the chloroplast genome, including the exon regions of genes such as rbcL, atpB, ndhF, and matK, as well as the intron regions of the trnL and trnL-F genes, are commonly utilized (Cowan et al., 2006; Chase et al., 2005) Additionally, the ribosomal ITS nucleus, specifically the buffer zone of the large subunit of ribosomal DNA, serves as another important sequence area for studying plant phylogenomics (Kress et al., 2007; Vere, 2012; Peter, 2012).
Research indicates that the combination of the matK and rbcL genes in chloroplasts serves as an effective DNA barcode for molecular identification of various plant species These coding regions facilitate DNA translation into amino acid sequences, making them suitable for sequencing The BOLD community suggests using additional primers, such as those from the intergenic spacer trnH-psbA and the ITS nuclear ribosome transcription sequence, for enhanced plant identification For distinguishing varieties and ecological types, primers based on SSR, retrotransposon, or SNP in nuclear genes are recommended, as they are effective in assessing plant purity These marker systems can directly detect DNA sequence variations and can be automated with sequencing technology.
Gene loci in the nucleus and chloroplast genomes, such as the atpF-atpH, rbcL, rpoC1, rpoB, matK, ycf5, trnL, psbK-psbI, psbA-trnH, and ITS genes, serve as common DNA barcodes for plant identification In Citrus plants, these DNA barcodes have proven effective for classification and identification purposes, as demonstrated by Luo et al (2010).
Seven DNA barcodes, including psbA-trnH, matK, ycf5, RpoC1, rbcL, ITS2, and ITS, were sequenced to differentiate 300 samples from 192 species across 72 genera of oranges The findings indicate that the ITS2 region is the most effective for distinguishing a broad range of plant taxa, particularly among closely related species within the orange family (Luo et al., 2010).
A study by a Chinese team in 2011 evaluated the effectiveness of DNA barcoding in seed plants, revealing that the rbcL, matK, and trnH-psbA markers were the most prevalent, with rates between 87.1% and 92.7% In contrast, the ITS marker showed a lower prevalence of 79% in angiosperms and the lowest in gymnosperms Despite its lower prevalence, the ITS marker exhibited the highest species differentiation, and when used in combination with the rbcL, matK, and trnH-psbA primers, the differentiation efficiency could reach 69.9%.
A study by the China Plant BOL Group (2011) found that 79.1% of species can be identified using both rbcL and matK primers Additionally, Penjor et al (2013) demonstrated the successful classification of Citrus species in Japan using the matK gene region.
Citrus exhibits a widespread distribution, but accurately identifying its various lines and varieties necessitates a combination of morphological, biochemical, and molecular marker evaluations Numerous studies have utilized SSR primers to establish genetic relationships among Citrus lines and varieties, with research by Barkley et al (2006), Shrestha et al (2012), Liu et al (2013), Shahzadi et al (2014), Sharma et al (2015), Mahjbi et al (2016), and Ahmed et al (2017) demonstrating that SSR markers are highly effective for constructing DNA barcodes within Citrus groups.
In 2009, Chinese scientists developed barcodes for economically significant citrus crops, including oranges, tangerines, and grapefruits The study revealed that SSR markers are essential for constructing DNA specimens of Citrus trees, while ISSR serves as a supplementary technique Out of 126 varieties examined, 93 were successfully identified using both SSR and ISSR methods.
The analysis of DNA barcode data reveals that 12 SSR markers and 2 ISSR primers exhibit high polymorphism, establishing them as a reliable standard set of primers for DNA barcoding in Citrus, surpassing traditional methods (Lei, 2009).
Research by Ollitrault et al (2012) demonstrated the effectiveness of SNP markers in evaluating genetic diversity and mapping within the Citrus L genus Subsequent studies by Garcia-Lor et al (2013a, b), Curk et al (2015), and Shimizu et al (2016) further established the development of SNP primers for investigating genetic relationships and identifying species among Citrus trees.
2.1.2 The situation of studying the DNA barcode of Citrus in Vietnam
So far, there has not been systematic research about the DNA barcodes of
Citrus cultivation in Vietnam has seen limited research focused on genetic diversity, particularly in forestry and medicinal plants Recent studies have utilized DNA barcoding techniques to classify and assess this diversity effectively.
Duong Van Tang, Nguyen Quoc Binh, and Dinh Thi Phong (2011) identified the nuclear sequence of the ITS region for three valuable wood species in Vietnam: Trac (D cochinensis), Cam Lai (D oliveri), and Sua (D tonkinensis) This data has been added to the International Bank for DNA Sequencing Genetic analysis of the ITS sequence revealed that D tonkinensis is most closely related to D sissi and is grouped with D frutescens, D decipularis, and D brasiliensis.
D congestiflora D cochinchinensis is the closest relative of D oliveri
Introduction of Citrus (Orange)
The orange, scientifically known as Citrus and belonging to the Rutaceae family, originates from southern Asia, spanning regions from India and the Himalayas to China, the Philippines, Malaysia, southern Indonesia, and mainland Australia Recent research indicates that Yunnan Province in northern China may be the original source of many Citrus species, attributed to its rich biodiversity and distribution along the river system According to Hodgson's classification system, the orange group is categorized into two primary species: Citrus aurantium (sour orange) and Citrus sinensis (sweet orange).
Sour orange (Citrus aurantium [L] Osbeck), originally from Southeast Asia, particularly India, was introduced to Western Asia in the first century AD This introduction occurred around 700 AD, facilitated by Arab traders during their conquests in North Africa and Spain.
Sweet orange (Citrus Sinensis) originates from Southern China, India, and Southern Indonesia This species was introduced to Iran around 330 BC during Alexander the Great's campaign and later spread to Europe through the Romans Sweet oranges are categorized into various types, including Navel, Valencia, Yellow, and Red oranges.
Some methods used in species identification and genetic relationship
Various research methods exist for classifying and identifying animal and plant species, primarily based on the principle of common ancestry Species that share a closer evolutionary relationship tend to exhibit more similar characteristics These similarities can manifest in various forms, contributing to the classification process.
Plants exhibit various morphological, anatomical, biophysical, and embryonic features, with key characteristics including leaf shape, flower structure, fruit type, and branch division While these observable traits can be analyzed statistically, their effectiveness is limited, especially when specimens are damaged or lack their original form Consequently, traditional methods of identification based on morphology and folk knowledge can be significantly enhanced through the application of modern molecular biology techniques.
Molecular classification and species identification methods are rapidly advancing, focusing on the composition and structure of genes in organisms Today, DNA analysis techniques are proving to be highly effective for classifying and testing various species.
Molecular classification relies on analyzing nuclear genes, organelle genomes, and gene products like proteins and enzymes, with the selection of specific genes and proteins being crucial for research success Techniques such as isozyme analysis, restriction fragment length polymorphism (RFLP), PCR-based methods like Simple Sequence Repeats (SSR), Random Amplified Polymorphic DNA (RAPD), and Amplified Fragment Length Polymorphism (AFLP) are commonly employed These methods, along with DNA sequence analysis, have been instrumental in clarifying classification, assessing genetic diversity, and understanding evolutionary relationships among various animal, plant, and microbial species Additionally, these techniques serve as molecular indicators for gene identification.
11 that control or are related to certain traits of individuals, species, or species groups
Scientists worldwide are increasingly studying the use of DNA barcodes for species identification, significantly enhancing species classification Key gene groups utilized for identifying genes and assessing species evolution include ribosomal rRNA genes, mitochondrial genes, and chloroplast genes in plants, specifically the rRNA 18S, 5S, and 16S genes, which help evaluate evolutionary relationships among organisms DNA primers offer greater accuracy compared to morphological and chemical methods, as they are not influenced by subjective factors.
2.3.1 Classification based on DNA barcode technique
DNA barcodes serve as a rapid and accurate method for species identification, utilizing genomic data from both the nucleus and cytoplasm Their key characteristics include being widely applicable across various classification units while maintaining high stability and minimal variation within species An ideal DNA barcode consists of a short nucleotide sequence and specific primers that facilitate easy amplification through PCR.
Identifying common DNA barcodes for plants presents significant challenges The chloroplast genome contains various characteristics that are suitable for DNA primers, while the Internal Transcribed Spacer (ITS) region, located between genes, is frequently utilized as a DNA marker in research (Borsch et al., 2003; Shaw et al., 2007; Van et al., 2000) In recent years, numerous gene regions have been investigated and suggested as potential DNA primers for plants However, no single DNA primer has gained universal acceptance, leading researchers to conclude that multiple designated primers may be necessary for effective identification.
DNA primers are essential for species identification in plants (Chase et al., 2005; Kress et al., 2008) By 2009, eight locus genes, encompassing both nuclear and chloroplast gene regions, were utilized as DNA barcodes for plant identification.
2.3.2 Locus used in DNA barcode methods in plants
2.3.2.1 Sequence of the nucleus gene
The nuclear genome is the largest among the three genomes in plants, ranging from 1.1 × 10^6 to 110 × 10^6 kbp and containing numerous genes Most research on relationships utilizes ribosomal DNA (rDNA) sequences from the nucleus, which consist of repeating units that can be replicated thousands of times The rDNA includes coding regions such as External Transcribed Spacers (ETS), the 18S gene for the small subunit, and the 26S gene for the large subunit, separated by the 5.8S gene The lengths of these coding regions are consistent across plants, with the 18S gene approximately 1800 bp, the 26S gene about 3300 bp, and the 5.8S gene around 160 bp, while the gaps between them vary from 1 to 8 kb The stable regions, like 18S and 26S, are useful for inferring high-level classifications, whereas the rapidly evolving Internal Transcribed Spacers (ITS) are better suited for comparing closely related species and populations Although both rDNA regions are widely applicable, the larger size of the 26S rDNA (over 3000 bp) poses challenges for sequencing, making the smaller 18S rDNA (about 1800 bp) a preferred choice for PCR amplification and sequencing.
The phylogenetic tree constructed using the 18S rDNA sequence closely resembles that created with the rbcL sequence across various classification levels in angiosperm plants However, despite its significant potential for phylogenetic analysis, the 18S rDNA region has not yet been utilized in the angiosperm system (Soltis and Soltis).
The 26S rDNA gene is recognized for its role in replacing the 18S rDNA gene Notably, the 26S rDNA gene has evolved 1.6 to 2.2 times faster and offers three times more informative characteristics compared to the 18S rDNA gene.
The 5.8S rDNA gene is easily amplified and sequenced when using positioning primer on the 18S and 26S rDNA genes The 5.8S rDNA gene is rarely used for the inference of relationships because of ITS high conservation and small size (164-165bp) The ratio of potentially informative sites for relationship analysis in seed plants is similar to that of the 18S rDNA gene
The Internal Transcribed Spacer (ITS) region plays a crucial role in separating different ribosomal DNA (rDNA) genes in flowering plants Specifically, ITS1 separates the 18S rDNA gene from the 5.8S rDNA gene, while ITS2 separates the 5.8S rDNA gene from the 26S rDNA gene This region is commonly found to be less than 700 base pairs in length.
The ITS region is characterized by high conservation sequences, leading to the development of numerous primers for amplification and sequencing However, the GC-rich nature of ITS1 and ITS2 poses challenges for sequencing, which varies among different plant groups The incorporation of DMSO or BSA into PCR or sequencing reactions has proven to be highly effective in overcoming these difficulties Sequencing of ITS from various angiosperm families reveals that the diversity of ITS1 and ITS2 sequences surpasses that of rDNA genes.
ITS sequences exhibit significant variability, making them valuable for addressing relationship inquiries among closely related species Numerous studies, such as those by Linder et al (2000) and Bellarosa et al (2005), have successfully utilized ITS sequences to reconstruct evolutionary histories Additionally, the inheritance of the ITS region allows it to be an effective tool for investigating cross-breeding.
MATERIALS AND METHODS
Location and time for research
Research scope: Agricultural Genetics Institute
Address: 6th floor, Phamvandong, Conhue, Tuliem, Hanoi
The project is conducted from 1st October, 2021 to 25th March, 2022
Fifteen orange leaves were gathered from nine provinces in Vietnam, including Quang Nam, Dong Thap, Nghe An, Ha Tinh, Bac Giang, Quang Ninh, Ha Giang, Ha Noi, and Cao Bang The collected samples were thoroughly washed to eliminate any mud and then dried at room temperature After cleaning, the samples were stored in a refrigerator in preparation for the subsequent research phase.
Materials
Fifteen samples of orange leaves were collected from various provinces, as detailed in Table 3.1, which lists the sample names and collection locations The samples were cleaned with water, dried with tissue, and then cut into 2-7 cm pieces using knives These leaf pieces were placed in 2ml Eppendorf tubes and stored at -20 °C to prepare for total DNA extraction.
Table 3.1 The list of 15 studied orange samples were collected from 9 provinces in Vietnam
No Name Collecting place Sign
1 Cam Tay Giang TayGiang-QuangNam C1
4 Cam xa Doai NamDan-NgheAn C4
5 Cam Song Con NamDan-NgheAn C5
6 Cam Van Du NamDan-NgheAn C6
10 Cam sanh Bo Ha BoHa-YenThe-BacGiang C10
In molecular biology, several essential chemicals are commonly utilized, including Sigma and Merck products such as CTAB, TRIS base, boric acid, and NaCl Key reagents like dNTPs, EDTA, and 6X orange loading dye solution are vital for various applications Taq Polymerase is crucial for DNA amplification, while solvents like ethanol, 2-propanol, and glacial acetic acid play important roles in purification processes Additionally, phenol, chloroform, and isoamyl alcohol are used in nucleic acid extraction Agarose is commonly employed for gel electrophoresis, and specific primers such as SSR primers and gene area amplification primers (ITS, matK, rbcL) are essential for targeted genetic studies.
Vortex machine, thermostat tank, microwave, centrifuge, electrophoresis, spectrometer, PCR running machine, electrophoresis camera
Instruments include Eppendorf tube (1.5ml; 2ml; 200μl), pipette of all kinds, type head, knife, scissors, adhesive tape
In this research, 10 available primers are used, including: 1 ITS primer
(White et al., 1990), 1 matK primer (Y.Nagano et al., 2014), 1 rbcL primer
(Hasebe et al., 1994) and 7 SSR primers (Froelicher et al., 2008, Corazza-Nunes et al., 2002, Barkley et al., 2006)
Table 3.2 The list of DNA barcodes’ primers was used in the study
1 ITS1 - F TCCGTAGGTGAACCTTGCGG 51 White et al., 1990
2 ITS4 - R TCCTCCGCTTATTGATATGC 51 White et al., 1990
3 MatKCi1- F ACGGTTCTTTCTCCACGAGT 63 Y.Nagano et al., 2014
4 MatKCi1- R AGAATCAGAGAAATCGGACC 63 Y.Nagano et al., 2014 44
5 RbcLCi2- F ATGTCACCACAAACAGAGACTAAAGC 57 Hasebe et al., 1994
6 RbcLCi2- R CGTTCACCTTCTAGTTTACCTACAACAGT 57 Hasebe et al., 1994
Table 3.3 The list of SSR primers were used in the study
No Name Primer sequecne (5′–3′) Tm
Methods
In this study, we chose the method of using CTAB (P Doyle and Doyle,
1990) that had some minor improvements to conduct DNA extraction from the study samples
The extraction buffer CTAB was prepared at 60 °C, consisting of 100 mM Tris-base, 20 mM EDTA, 1.4 M NaCl, 2% CTAB, and 1% PVP Initially, 0.3 grams of crushed orange leaves were mixed with 800 µl of extraction buffer and 60 µl of 10% SDS in micro test-tubes, followed by grinding until homogeneous The samples were then incubated at 65 °C for 30 minutes, cooled to room temperature, and treated with 200 µl of 5M potassium acetate, mixed, and chilled on ice for 45 minutes Next, an equal volume of chloroform-isoamyl alcohol (24:1) was added, gently shaken to form a milk emulsion, and centrifuged at 11,000 rpm for 30 minutes at 4 °C to obtain the supernatant A second extraction with chloroform-isoamyl alcohol was performed to isolate the DNA The DNA was precipitated using cooled isopropanol at -20 °C for 1 hour, followed by centrifugation at 11,000 rpm for 15 minutes at 4 °C and washing with 70% ethanol Finally, the DNA was dried at room temperature, dissolved, and treated to remove RNA, resulting in DNA solubilized in TE buffer.
3.3.2 Quantification of DNA by spectrophotometer
The varying light absorption properties of nitrogen bases in double-stranded and single-stranded DNA molecules can influence the functional behavior of DNA in solution The optical density measured at 260 nm (OD260) serves as a key indicator of DNA concentration and quality.
The analysis of 21 samples enables the determination of DNA levels in solution, while the purity of the DNA is assessed through OD280 value measurement Proteins exhibit peak absorption at 280 nm and also absorb at 260 nm, which can lead to inaccuracies in nucleic acid concentration calculations A ratio of OD260/OD280 between 1.8 and 2.0 indicates that the DNA extraction is of high purity.
To prepare for measurement, dilute the DNA solution 100 times using a 1/8 TE solution Transfer 2μl of the diluted DNA solution into a cuvette for optical density (OD) measurements After extraction and testing, store the DNA at -20°C for future experiments.
3.3.3 PCR process (Polymerase Chain Reaction)
3.3.3.1 PCR amplification using ITS, matK, rbcL primers
After extracting the total DNA, it is utilized for PCR amplification using ITS, matK, and rbcL primers (see Table 3.2) The resulting PCR products are then analyzed through 1% agarose gel electrophoresis to verify the quantity of the amplified DNA in comparison to the marker.
Table 3.4 PCR unit for a reaction with ITS, matK, rbcL primers
The PCR reaction is conducted in a 0.2 ml Eppendorf tube and performed on the Mastercycler epgradient S machine in the following cycle (Table 3.5)
Table 3.5 PCR program with ITS, matK, rbcL primer
After completing the PCR program, the PCR product is supplemented with 4 μl loading dye and conducted electrophoresis
3.3.3.2 PCR amplification using SSR primer
Seven specific SSR primers were utilized for the Orange samples (Citrus spp.) as detailed in Table 3.3 The attachment temperature and duration of the primers were experimentally optimized to achieve specific and stable bands The resulting PCR products were analyzed through electrophoresis on a 1.5% agarose gel, with the size of the amplified alleles determined using a DNA standard ladder.
Using 7 SSR primers in Table 3.3 for 15 samples
To prepare the Master mix, start by adding 160μl of 2X Buffer to a 1.5ml Eppendorf tube, followed by 16μl of primer Mix the solution thoroughly, then add 112μl of distilled water and vortex to ensure even mixing Transfer 18μl of this mixture into each of the 15 Eppendorf tubes (0.2ml), along with 1 blank sample Finally, add 2μl of total DNA to each tube, ensuring a uniform mix, resulting in a total reaction volume of 20μl per tube.
Table 3.6 PCR unit for a reaction with SSR primers
Table 3.7 PCR program with SSR primers
3.3.3.3 Agarose gel electrophoresis a Principle of agarose gel electrophoresis
Electrophoresis is used to analyze DNA characteristics by extracting samples onto agarose gel DNA, which carries a negative charge due to its phosphate groups, migrates from the negative electrode As it moves through the agarose gel, friction between the agarose particles and DNA molecules affects its movement; larger DNA molecules move faster, while smaller ones experience more resistance.
24 the slower movements In this way, we can separate the DNA fragments of different sizes on the agarose gel
After electrophoresis on the gel, the DNA fragments are separated according to the molecular mass and observed under UV light through a specific post-electrophoresis camera b Prepare agarose gel 1.5%
To create a balanced setup, first, use tape to secure the two ends of the tray Next, position the comb at one end of the tray and place the tray on a flat surface Finally, utilize tools to verify the balance level.
0.6 grams agarose were weighted in 40 ml solution TAE 1X, shaking well The solution was heated in the microwave machine for the fully soluble agarose Then, cooling the solution to 45-50 o C by leaving the glass at room temperature Next, 2.5 l Ethidium Bromide are added carefully, shaking well then pour lightly gently and continuously into the mold, avoiding foam creation Let agarose freeze (for 15 minutes), remove the comb c Agarose electrophoresis
To perform gel electrophoresis, prepare a 1X TAE buffer and flood the electric tray Mix 5 mL of DNA solution with the sample buffer, then pipette the mixture into the electric wells Connect the electrodes to ensure current flows from the negative to the positive side Set the power supply to a fixed voltage of 130 volts Finally, observe and document the gel electrophoresis profile under UV light, noting the DNA bands illuminated by the ethidium bromide (EtBr) staining.
3.3.4 Purification DNA after gel electrophoresis
The desired piece of DNA was cut off from the agarose gel then it was put into the 2ml Eppendorf tube QG buffer was supplied into the previous
To prepare the sample, mix 3 volumes of QG buffer with 1 volume of gel (approximately 100 mg to 100 μl) in a 2 mL Eppendorf tube Incubate the mixture at 50°C for about 10 minutes until the gel is fully dissolved, resulting in a yellow solution If the solution appears orange or blue-purple, add 10 μl of 3M sodium acetate, pH 5 Subsequently, transfer the dissolved sample solution into the QIAquick column and centrifuge.
To purify DNA, first centrifuge the QIAquick column at 13,000 rpm for 1 minute Next, add 500 μl of QG buffer to the column and centrifuge again at the same speed to eliminate excess agarose Then, introduce 750 μl of PE buffer, allowing the column to stand upright for 5 minutes before another centrifugation at 13,000 rpm for 1 minute Finally, transfer the QIAquick column to a new 1.5 ml microcentrifuge tube, add 30 μl of water (pH 7 - 8.5) to dissolve the DNA, and centrifuge once more at 13,000 rpm for 1 minute to collect the purified DNA.
3.3.5 Sequencing and designing phylogenic tree
The purified DNA products amplified by ITS, matK, and rbcL primers are sent to Apical Scientific in Malaysia for sequencing The sequencing results are compared to corresponding sequences in the NCBI database using the Megablast tool Subsequently, the sequences are collected and analyzed with the MEGA v6.06 program for DNA sequence alignment, nucleotide sorting, and percent identity assessment.
Phylogenic trees allow the studies of evolutionary relationships between species, strains, genes, or metabolic ways Phylogenic trees are built on morphological or molecular characteristics
Purposes of designing phylogenic tree are reconstructing the history of evolution and giving conclusions about some biological functions
To create phylogenetic trees, the essential steps include collecting and identifying the sequences necessary for tree construction, organizing these sequences, and then utilizing various methods, such as MEGA v6.06 or CLC Main Workbench, to build the tree and analyze the data.
3.3.6 Analysis the data of SSR gel electrophoresis to identify the genetics of specific Orange varieties in collected samples
The tapes are derived from SSR electrophoresis results and observed the polymorphic bands to give the conclusions SSR polymorphisms are based on number of repeat ITS and are hypervariable
SSRs have suitable amplification and good repeatability
SSR are easy to run and automate
RESULTS AND DISCUSSION
Total DNA extraction of 15 orange leaves
The total DNA extraction of 15 studied samples were separated and purified according to the CTAB method
The testing of 15 DNA extractions revealed bright bands in all wells of the 1% agarose gel, indicating a successful extraction method The results of these DNA extractions are illustrated in Figure 4.1.
Figure 4.1 Testing 15 total DNA extraction samples on 1% agarose gel electrophoresis
Quantification of DNA by spectrophotometer
Nucleic acid quantification is commonly performed in a cuvette spectrophotometer, where the monochromator optical system provides light at
The absorbance peak for DNA and RNA occurs at 260 nm, making microplate spectrophotometers increasingly popular for quantifying nucleic acids This trend is driven by the need for enhanced sample processing, as the light absorbed by nucleic acids in the sample provides critical information for analysis.
The concentration of nucleic acids, including both DNA and RNA, is measured by their absorbance at 260 nm, which indicates the total nucleic acid present Additionally, nucleic acid samples are assessed at 280 nm, the absorbance peak for proteins The ratio of absorbance at 260 nm to that at 280 nm helps determine the purity of the nucleic acid, with a ratio close to 2 (ideally around 1.8) signifying a highly pure sample.
The results in Table 4.1 indicate high concentration and purity of DNA, with values ranging from 1.75 to 1.93, which fall within the standard purity range of 1.8 to 2.0 Following extraction, the DNA was purified using Thermo Scientific GeneJET's DNA purification test (#K0722) and quantified with a Nanodrop (Eppendorf, USA) to determine the concentration for subsequent PCR reactions The DNA concentrations measured by Nanodrop varied from 397 to 585 ng/mL The purified DNA samples were stored at -20°C for the next steps of the research.
Table 4.1 OD measurement results and concentration of 15 samples’
PCR amplification using ITS, matK, rbcL primers
A PCR reaction using the ITS1/ITS4 primer pair was conducted, as shown in Figure 4.2 The results indicated that all studied samples produced distinct 750 bp bands on a 1.5% agarose gel Additionally, the bands were bright and clear, with sizes suitable for sequencing.
Figure 4.2 1.5% gel electrophoresis of 15 studied samples by using ITS1/ITS4 primers M: Marker generuler 100bp plus DNA
PCR products were sequenced directly using ITS1/ITS4 primers on an ABI 3730 XL machine by Apical Scientific in Malaysia The sequences of 15 orange samples were then compared to the reference gene sequence available in NCBI using MEGA v6.06 software.
The analysis presented in Figure 4.3 indicates that nucleotide insertions or deletions at specific locations within the gene segment resulted in varying total nucleotide counts among the study samples The ITS region length of 15 orange-like samples ranged from 719 to 734 nucleotides, exhibiting significant polymorphism with 14 distinct nucleotide variations compared to the reference varieties Notably, six samples—C1, C8, C9, C10, C12, and C13—displayed unique nucleotide variants that set them apart from other breeds and the reference sample JN681155.1 Citrus maxima.
JN681165.1 Citrus sinensis, MH721728.1 Citrus reticulata, JN681150.1 Citrus sinensis and MF797953.1 Citrus maxima (Table 4.2)
The comparison of nucleotide sequences in Figure 4.3 and the statistical data in Table 4.2 indicates that the ITS sequence amplified with the ITS1/ITS4 primer can effectively distinguish and identify six orange samples: C1 (Cam Tay Giang), C8 (Cam giay), C9 (Cam duong Ha Tinh), C10 (Cam sanh Bo Ha), C12 (Cam sap), and C13 (Cam sanh).
C1 (Cam Tay Giang) is characterized by a unique nucleotide substitution at position 597, where cytosine (C) is replaced by thymine (T), distinguishing it from the five reference varieties listed in NCBI This specific alteration allows for precise identification of the C1 sample.
C8 (Cam giay) is replaced nucleotides at positions 618, 635, 661, 698,
704 and 714, where the replacement occurs C to G, C to T, G to C, T to A, C to
T, G to C respectively Based on this difference, it is possible to accurately identify C8 sample in the researched orange group
At position 489, the only C9 (Cam duong Ha Tinh) has a replacement of
C to T similar to the JN681155.1 Citrus maxima, differs from other samples in the researched group
C10 (Cam sanh Bo Ha) exhibits a nucleotide replacement at position 561 and an additional nucleotide at position 727 Notably, the replacement of C with G at position 561 is a key identifier for this orange sample, distinguishing it from other researched orange varieties.
C12 (Cam sap) there are replacements of nucleotides C, C, T to A at positions 635, 700, 719 respectively and additional nucleotides A at position
727 Thanks to differences in positions 700, 719 and 727, C12 samples can be accurately identified in the researched orange group
The C13 sample (Cam sanh) exhibits a nucleotide replacement from C to A at positions 635 and 688 Notably, the C12 sample also shows this replacement at position 635, making it essential to focus on the unique pattern of the C13 sample for accurate identification.
31 based on the difference at position 688 compared to other samples in the researched group
Table 4.2 Statistical table of different locations in ITS sequences of researched samples and reference samples
Figure 4.3 Alignment of the ITS sequences of 15 studied samples and reference samples
PCR products from 15 samples amplified with MatKCi1 primers are presented in Figure 4.4 The results indicate that all samples exhibit a single band of 800 bp on a 1.5% agarose gel Additionally, the bands are bright and clear, confirming that the size of the amplified products is suitable for sequencing.
Figure 4.4 1.5% gel electrophoresis of 15 studied samples by using MatKCi1 primers M: Marker generuler 100bp plus DNA
The analysis in Figure 4.5 reveals that the presence of insertion and deletion nucleotides at various locations within the gene segment leads to variability in the total nucleotide count across the study samples Specifically, the length of the chloroplast gene region among the 15 orange samples examined ranged from 794 to 797 nucleotides.
The comparison of nucleotide sequences in Figure 4.5 and the statistical data in Table 4.3 revealed that the MatK sequence using the MatKCi1 primer does not allow for the differentiation or identification of any orange samples within the studied group This group was evaluated against a reference group that includes AB626794 Citrus maxima, NC037463 Citrus sinensis, and HM163958 Citrus reticulata.
Table 4.3 Statistical table of different locations in MatKCi1 sequences of researched samples and reference samples
Distinct nucleotide positions Accession name
Figure 4.5 Alignment of the MatKCi1 sequences of 15 studied samples and reference samples 4.3.3 rbcL region sequence results
The PCR reaction using the RbcLCi2 primer pair yielded single-shaped bands approximately 800 bp in size on a 1.5% agarose gel, as shown in Figure 4.6 The bands are bright and clear, indicating successful amplification suitable for sequencing.
Figure 4.6 1.5% gel electrophoresis of 15 studied samples by using RbcLCi2 primers M: Marker generuler 100bp plus DNA
The analysis presented in Figure 4.7 indicates that variations in nucleotide sequences among the study samples are due to deletions or insertions at specific locations within the gene segment The chloroplast gene region of the 15 orange samples examined ranged from 768 to 770 nucleotides in length Statistical analysis revealed 10 distinct positions of variation in the nucleotide sequences (Table 4.4) Notably, samples C9, C12, and C15 exhibited different nucleotide variations compared to the reference samples AB505955.1 Citrus maxima, AB505952.1 Citrus reticulata, and AB505957.1 Citrus sinensis.
The chloroplast gene region sequence using the RbcLCi2 marker enables the precise identification of three distinct samples of the studied orange variety: C9 (Cam duong), C12 (Cam sap), and C15 (Cam Trung Vuong).
C9 (Cam duong) at position 708 has a replacement of G to C Therefore, C9 can be accurately distinguish from the other samples in the researched group and compared to the referenced samples
C12 (Cam sap) exhibits a unique nucleotide substitution, where G is replaced by C at position 593 This distinct genetic variation sets C12 apart from other breed patterns and reference samples, allowing for precise differentiation and comparison within the studied group.
The C15 (Cam Trung Vuong) has replacement nucleotides at 5, 60, 760,
761 and 762 position However, the C15 model can only be accurately identified due to differences in position 60 (InDel A) compared to other samples in the research group and reference samples
Table 4.4 8 Statistical table of different locations in RbcLCi2 sequence of researched samples and reference samples
Figure 4.7 Alignment of the RbcLCi2 sequences of 15 studied samples and reference samples
Results of nucleotide sequencing analysis of the ITS, matK, rbcL gene
region between 15 studied orange samples and reference samples
4.4.1 Using DNA barcode (ITS) to identify studied Orange
The analysis of the DNA barcode sequences from 15 studied orange samples revealed a similarity range of 94.60% to 99.86% and coverage between 97% and 99% when compared to reference samples on NCBI This indicates a high degree of similarity in the amplified ITS regional sequences of the samples to those published in the NCBI database Notably, the C9 sample (Cam duong Ha Tinh) exhibited a similarity of 99.72% to the reference sample JN681155.1 (Citrus maxima), surpassing its similarity to the reference sample JN681165.1 (Citrus sinensis).
(98.46%) The C10 sample has a similarity to the reference model MH721728.1
Citrus reticulata (99.72%) higher than the reference model JN681150.1 Citrus sinensis (99.45%) (Table 4.9)
Table 4.5 Evaluation of the identity and coverage between ITS sequences of the studied samples and the corresponding sequence on NCBI
The findings illustrated in Figure 4.8 indicate that variations in the total nucleotide count of each sequence among the study samples are attributed to the deletion or insertion of nucleotides at specific locations within the gene segment The ITS region length for the 15 orange samples analyzed ranged from 719 nucleotides.
734 nucleotides It has a very high polymorphism in nucleotide sequences with
The analysis revealed 78 unique positions when comparing the studied samples to the reference samples Notably, six samples—C1, C8, C9, C10, C12, and C13—exhibited distinct nucleotide variations that set them apart from both the other samples and the reference.
56 samples JN681155.1 Citrus maxima, JN681165.1 Citrus sinensis, MH721728.1
Citrus reticulata and JN681150.1 Citrus sinensis (Table 4.2)
Table 4.6 Genetics similarity coefficient between ITS sequences of studied samples and reference samples
The results of the analysis based on DNA sequencing of the ITS region showed that the phylogenic tree had 3 separated groups (Figure 4.8, Table 4.10)
The first group includes 10 orange varieties: C2, C3, C4, C5, C6, C7, C8, C10, C14, and C15 This group exhibited high genetic similarities, with coefficients ranging from 95.2% between C8 and both C3 and C10, to 99.7% between C6 and C2, as well as C4 and C5 Additionally, the genetic similarity coefficient of the studied samples compared to the reference sample JN681150.1_Citrus_sinensis varied from 95.4% for C8 to 99.2% for C2.
The second branch consists of a single C9 sample, which has a coefficient similar to the reference pattern JN681150.1_Citrus_sinensis of 95.2%
The third branch consists of 4 samples, C1, C11, C12 and C13, which have a coefficient similar to the reference pattern JN681165.1_Citrus_sinensis ranging from 93.2% (C12) to 98.6% (C11)
Figure 4.8 The phylogenic tree generated the ITS gene region of 15 studied orange samples studied with reference samples
4.4.2 Using DNA barcode (matK) to identify studied Orange varieties
The percent identity sequence analysis of the DNA barcodes from 15 studied samples revealed a similarity range of 98.99% to 99.75% when compared to the reference sequence on NCBI, with query coverage between 96% and 99% (Table 4.11).
Table 4.7 Evaluation of the identity and coverage between matK sequences of studied samples and the corresponding sequence on NCBI
Sequence analysis using the MEGA v6.06 program revealed that the genetic similarity coefficients among the 15 orange varieties ranged from 99.1% to 100% The lowest genetic similarity coefficient of 99.1% was observed between the C3 and C9 samples.
Based on the results of DNA sequencing analysis of the matK gene region, the 15 varieties of oranges studied were divided into 2 groups (Figure 4.9, Table 4.12)
The first group consisted of C9 and C11 samples with genetic similar coefficients to the reference sample NC_037463.1_Citrus_sinensis of 99.3 and 99.4%
The second group consists of the remaining 13 samples with a genetic similar coefficient with the reference sample NC_037463.1_Citrus_sinensis ranging from 99.5% (C3) to 99.9% (between C1, C2, C4, C5 and C6 with the reference sample)
Table 4.8 Genetics similarity coefficient between matK sequence of studied samples and reference samples
Figure 4.9 The phylogenic tree generated the matK gene region of 15 studied orange samples studied with reference samples
4.4.3 Using DNA barcode (rcbL) to identify studied Orange varieties
The analysis of DNA barcodes from 15 studied samples revealed a high degree of similarity to reference sequences on NCBI, with similarity percentages ranging from 98.99% to 99.49% and coverage between 93% and 98% These findings indicate that the amplified RbcL gene region sequences of the samples closely match those published in NCBI.
Table 4.9 Evaluation of the identity and coverage between rbcL sequences of studied samples and the corresponding sequence on NCBI
The results in Table 4.13 of the analysis of sequences through MEGA v6.06 program obtained showed that there were genetic similar coefficients of
61 the 15 orange varieties ranging from 98.9 to 100% The lowest genetic similarity coefficient was 98.9% between the C15 sample and C3 and C8
Based on the results of DNA sequencing analysis of the rbcL gene region, the 15 varieties of oranges studied were divided into 3 groups (figure 4.10, Table 4.14)
The first group consisted of seven samples of C13, C11, C10, C3, C7, C8 and C14 varieties with genetic similar coefficients to the reference sample AB505957.1_Citrus_sinensis of 99.4 (C10) and 99.7% (C7)
The second group consisted of three C4, C5 and C15-like samples with a genetic similarity coefficient to the reference sample AB505957.1_Citrus_sinensis of 99.4 (C15) and 99.7% (C4)
The third group includes five varieties: C1, C2, C6, C9, and C12, which exhibit a high genetic similarity coefficient with the AB505957.1_Citrus_sinensis reference sample, ranging from 99.7% for forms C9 and C12 to 100% for sample C2.
Table 4.10 Genetics similarity coefficient between rbcL sequence of studied samples and reference samples
Figure 4.10 The phylogenic tree generated the rbcL gene region of 15 studied orange samples studied with reference samples
The study revealed that matK and rbcL can effectively identify Citrus and related taxa, although their species-level identification frequencies were 55.9% and 37.3%, respectively.
MatK was shown to be more strong than rbcL, meaning that it can be used to identify Citrus species and their related genera (Yu Jie et al., 2011)
My data in Citrus spp (Orange) does not agree with this general trend
By using matK primers, I can not identify any varieties but by using rbcL primers, 3 samples can be identified.
Identify specific primer to accurately identify certain varieties of
The PCR program utilized 7 SSR primers, but only 4 of them produced polymorphic results The other primers either failed to yield products, exhibited homomorphism across all samples, or generated varying tape numbers in different runs.
4.5.1 Identify Cam Tay Giang varieties by the mCrCiR01D06a, CT02 and Ci07B09 primers
Electrophoresis analysis with the mCrCiR01D06a primer showed three types of alleles In particular, the group of 15 orange varieties (symbols from C1 to C15) has 4 samples: C1, C3, C8 and C13 in a heterogeneous state; the
The analysis of 63 remaining samples reveals a homogeneous state, with Tay Giang orange (C1) exhibiting unique alleles Specifically, it shows a 240bp allele with the C1 primer, distinguishing it from other varieties in the studied group Additionally, the CT02 primer reveals a 130bp allele in Tay Giang orange, which is lower than that of other varieties Furthermore, the Ci07B09 primer indicates a 150bp allele for Tay Giang orange, again lower than its counterparts These distinct genetic characteristics enable the identification of Tay Giang orange among the researched orange varieties.
Figure 4.11 Electrophoresis results of the PCR products with mCrCiR01D06a, CT02 and Ci07B09 primers (M: marker generuler 50bp) mCrCiR01D06a
4.5.2 Duong Orange variety identification by using Ci02F07 primer
Electrophoresis analysis using the Ci02F07 primer reveals two types of alleles among the 15 samples (C1 - C15) Notably, only the Duong orange (C11) exhibits a distinct 190bp homogeneous band at the first allele, while the other orange samples show either heterogeneous or homogeneous patterns at the second allele position This indicates that the Ci02F07 marker can effectively identify the Duong orange variety within the studied group.
Figure 4.12 Electrophoresis results of the PCR products with Ci02F07 primer (M: marker generuler 50bp)
The entire genome sequencing assembly of Clementine mandarin has been analyzed for the frequency and distribution of SSRs, revealing that di-nucleotides and tri-nucleotides comprise approximately 89% of all identified SSRs Additionally, the examination of repeat numbers indicates that the distribution of di-, tri-, tetra-, penta-, and hexa-nucleotide transcript-SSRs is predominantly skewed towards smaller repeat counts.
In my work 7 microsatellite markers were used 4/7 (57.14%) markers that was used in my research agrees apartly with this general trend.
CONCLUSIONS AND RECOMMENDATIONS
Conclusions
The ITS, matK and rbcL gene regions of the studied orange group have been sequenced In which the amplified success rate was 100% for ITS, matK and rbcL primers
The sequencing analysis of three gene regions—ITS, matK, and rbcL—across 15 orange samples revealed that the ITS region exhibited the highest level of nucleotide polymorphism among the studied gene regions.
The results of sequencing of the 3 gene regions ITS, MatK, rbcL of 15 orange samples can identify 8 orange samples (C1, C5, C8, C9, C10, C12, C13 and C15)
The ITS gene region sequence, utilizing the ITS1/ITS4 marker, effectively distinguished and identified six orange samples: C1 (Cam Tay Giang), C8 (Cam giay), C9 (Cam duong Ha Tinh), C10 (Cam sanh Bo Ha), C12 (Cam sap), and C13 (Cam sanh).
Based on the chloroplast gene region sequence with the RbcLCi2 marker, it was possible to accurately distinguish and identify 2 samples of orange as C12 (Cam sap), C15 (cam Trung Vuong)
By using ITS1/ITS4 marker for 15 researched oranges, the number of orange varieties could be distinguished is the highest, up to 40% distinguished samples
5.1.2 Observe genetic diversity of research species
Using SSR markers, the Tay Giang orange variety (C1) was identified with the primers mCrCiR01D06a, CT02, and Ci07B09, while the Duong orange variety (C11) was identified using the Ci02F07 marker.
Recommendations
To enhance the assessment of genetic diversity and classification of 15 Citrus spp accessions, it is essential to broaden research by incorporating various molecular markers and additional gene regions.
Research’s data can be analyzed in other software to compare the differences and decide which software is the highest efficiency
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