DOI: https://doi.org/10.21203/rs.3.rs-811077/v1
The mitochondrial genome is highly informative for evolutionary analysis of organism lineages and phylogenetic studies. The availability of robust primers for amplifying complete mitochondrial genomes is a crucial step in current mitogenome studies. However, organism specific characteristics such as variable transition to transversion substitution ratios seen in some groups pose challenges for the development of universal, or at least broadly applicable, primer pairs for this purpose. This study reports on a strategy of primer design and optimization (PDO) where regions of known mtDNA genescan be used for choosing primers for amplification, sequencing and assembly of entire mitochondrial genomes of several closely-related species. In brief, taking advantage of the circular organization of mtDNA, primers are first designed for amplification of “long” products using the 5’ region of one conserved gene and a 3’region from another conserved gene. Additional primers are then used to amplify “short” regions to fill in gaps to allow for complete assembly of the genome. We show how we were able to use this approach to successfully amplify entire mitochondrial genomes from a non-human primate species (Semnopithecus hypoleucos), and also how this provided data useful for annotation of the assembled genome data.
A thorough understanding of genetic diversity is an important step for developing appropriate conservation plans for any group of organisms (Oakenfull et al. 2000). Mitochondrial (mt) DNA has become popular for these studies since it provides rich sets of information relevant to evolutionary biology, population genetics and phylogenetics through its maternal inheritance and relatively high mutational rates (Avise and Saunders 1984; Avise 1986; Dasmahapatra et al. 2010; Nabholz et al. 2019). Moreover, the high copy number and circular nature of mtDNA tends to make it less prone to degradation and therefore may provide material for complete analysis compared, for example, to nuclear sequences. These qualities have shown mtDNA to an important genetic tool in tracking large scale comparative studies of evolutionary relationships among individuals, populations and species.
Construction of phylogenetic trees is a useful tool for analyzing evolutionary relationships of genes between species. Many of these studies rely exclusively on a small part of the mtDNA, such as cytochrome oxidase subunit I(COI) (Webb and Moore 2000; Kerr et al. 2009; Khedkar et al. 2016a); cytochrome b (cyt b) (Chang et al. 2010; Khedkar et al. 2016b), or others. Such approaches are known, however, to underestimate the influence of variation seen in the complete mitochondrial genome on evolutionary processes (Springer et al. 2012; Pozzi et al. 2014). For example, comparative studies of protein coding genes tend show high levels of similarity compared to non-coding regions which can be more highly variable. It is also well known that certain parts of the mitochondrial genome, such as the D-loop region evolve faster than the highly conserved 16S rRNA and 12S genes (Gerber et al. 2001). This implies that phylogenetic relationships among species are better inferred from the use of the complete mitochondrial genome sequences.
Although several complete mitochondrial genome sequences have been published (Matsui et al. 2009; Li et al. 2009; Kim et al. 2009; Ma et al. 2010; Kurabayashi et al. 2010; Finstermeier et al. 2013; Pozzi et al. 2014; Zhang et al. 2017), data for several species and/or species groups is still incomplete due to technical problems related to the availability of robust primers (Ramos et al. 2011; de Freitas et al. 2018). This is especially true for closely-related species such as some of those belonging to primate clades. In some groups such as humans, for example, high mutation rates in the mtDNA can lead to a high degree of variability between individuals (Howell et al. 1996; Wilson et al. 1985). In other primates, the transition to transversion substitution ratio was found to be high in mtDNA (Brown et al. 1982).
Generally three strategies (described below) are in use for obtaining complete mitochondrial genome sequences, but each of them still include procedural challenges (Rizzi et al. 2012),
Our study reports a method for designing primers that can be effectively applied in amplification of entire mitochondrial genomes of S. hypoleucos an endangered primate species in India and may this strategy can be applied to closely related primate species. Primer pairs are specifically designed for covering both large and small segments of the mitochondrial genome which demonstrate amplification challenges.
Ethical Statement
We did not perform experimentation directly on any animals; therefore ethical permission was nonobligatory for this study. The authors do not have conflict of interest to declare.
Experimental outline
The flowchart of the primer design and optimization (PDO) protocol is provided (Fig. 1). Some of the important steps of the PDO method are discussed in the following section.
Downloaded reference mitochondrial sequences
For the initial design of robust primer pairs, 25 whole mitochondrial genome sequences were downloaded from NCBI Genbank and other reference sequence databases (Table 1). Among 25 species studied here, 16 belonged to Colobinae family, two are from the Ponginae, two are from the Homininae, two are from Cercopithecinae, and one each from the Cebinae, Gorillinae and Hylobatidae.
Alignment of Sequences
The mt DNA sequences of these primate species were aligned using CodonCode aligner. Aligned regions longer than typical primer sequences were selected to represent conserved sequences, and forward and reverse primers were designed from them.
Primer design and testing its applicability in primate clade
Primer design is a critical part of any PCR based study. Considerations for primer design include: (i) primer melting temperature, (ii) length and GC content of the primer, (iii) resultant PCR amplified product length, (iv) formations of hair pin loops or other secondary structures, (v) primer specificity. In this study, twenty four primers (12 pairs) were designed using the software program Primer3 ver. 0.4.0 (Unterssaar et al. 2012) and confirmed for their quality criteria as described above using the online tool Oligocalc (Kibbe 2007) (Table 2).
Test data
This study used pre-collected and catalogued material from S. hypoleucos from the DNA repository of Paul Hebert Centre for DNA Barcoding and Biodiversity Studies, Aurangabad for testing the efficiency of newly designed primers.
Using the multiple sequence alignment, primers for amplifying mitochondrial DNA from the primate species studied here were designed (Fig. 1; Table 2). As shown in Table 2, these primers have similar length, GC content and annealing temperature requirements.
Primers designed for covering small fragments of mitochondrial region
Some primers were designed to cover shorter segments of the mitochondrial genome. Primers for the ND1, ND2, COI, COII, 16S rRNA genes along with trnaL, trnaI, trnaQ, trnaM, trnaW, trnaA, trnaN, trnaC, trnaY, trnaS2, trnaD, trnaK are shown in Table 2, part B. For PCR amplification, template DNAs (30 ng/µL) were added to the PCR reaction mixture (23.7 µL) containing 2.5 µL of 10x PCR buffer (KAPA Biosystems, Inc. Wilmington, Massachusetts, United States), 0.5 µL of 50 mM MgCl2, 2.0 µL of 2.5 mM dNTPs, 0.2 µL of Taq polymerase enzyme (5 units/µL), 0.5µL of each primer (10 mM) and 16.5 µL of nuclease free water. The thermal cycling program used was set as follows: 950C (3 min, 1 cycle) followed by 35 cycles of 95 0C (30 s), 480C (40 s), 72 0C (1 min) and a final extension at 72 0C (10 min). Figure 2 shows the products generated using these primer pairs.
Primers for longer regions of the mitochondrial genome
Two primer pairs designated as PHCDBS 1F, 1R and PHCDBS 2F, 2R were designed to amplify larger portions of the mitochondrial DNA. A combination involving other primer sets such as PHCDBS 3F and PHCDBS 14R were also used to cover a region of 10kb (Table 2). Another primer combination (PHCDBS 14F + PHCDBS3R) was used to cover the remaining mitochondrial region of 7kb (Table 2). For PCR amplification, template DNA samples (30 ng/µL) were added to the PCR reaction mixture (27.5 µL) containing 12.5 µL of Q5 high fidelity 2X master mix (New England Biolabs, Ipswich, Massachusetts, United States), 5.0 µL of template DNA and 7.5 µL nuclease free water, 1.25 µL of Forward and reverse Primer each. The PCR thermal cycling program set as follows: 98 0C (30 s); 35 cycles of 98 0C (10 s), 50 0C (30 s), 72 0C (6 min) followed by final extension at 72 0C (2 min). As shown in the Fig. 3, the designed primer sets were successfully amplified by PCR.
Tests of sequence coverage
To test the sequence coverage of different primer pairs, the larger fragments (I and II) were sequenced using a next generation sequencer (Illumina HiSeq 2500). Small fragments were sequenced bidirectionally on a Sanger Sequencing Platform (Genetic Analyzer ABI 3730 xl) using standard operating protocols. Sequences obtained were analyzed using bioinformatic curation methods, and mitochondrial assemblies were obtained. A graphical representation of actual primer positions and the regions covered are depicted in Fig. 4.
This genome assembly was also compared to reference genomes and found to be fully aligned in respect to gene order and genome coverage.
Studies have shown that datasets derived from complete mitochondrial genome sequences appear to offer more consistent information about evolutionary relationships among species of higher taxa such as primates, and that these can be used effectively to establish the timescale of their evolution (Finstermeier et al. 2013; Kurabayashi and Sumida 2013). In contrast, studies using single or small numbers of genes to analyze evolutionary relationships have often reported rapid radiations or unresolved relationships, largely because the conclusions are based on the use of relatively small numbers of informative sites (Matsui et al. 2009). Phylogenies generated using complete mitochondrial genomes have also been shown to have considerably higher levels of statistical support when compared to analyses based on single genes (Liedigk et al. 2014). Therefore, the use of these larger datasets also has the potential to raise even a weak phylogenetic signal to a level above that of random noise (Hillis and Bull 1993).
However, owing to factors such as differing transition to transversion substitution ratios between even closely related species, it is often challenging to find primers suitable for comparative studies of complete mitochondrial genomes. More specifically, for many primate species, even for closely related species, attempts to use the same pair of primers for cross species amplification often fails.
The present study was planned with the goal of studying evolutionary questions related to primate phylogeny that are yet to be resolved in general for several species (Pozzi et al. 2014), and in particular for resolution of relationships among several primate species found in India. For this goal, a new approach was developed to obtain complete mitochondrial genome sequences from a collection of closely related primate species. The approach we have used is novel compared to methods used and proposed by others (Wu et al. 2004; Chuang et al. 2006; Chen et al. 2009; Yang et al. 2009; Chang et al. 2010; Yang et al. 2010).
The protocol shown in Fig. 1 describes the method that relies first on the use of conserved regions identified from alignments of published primate mitochondrial genomes. These alignments reveal several conserved regions where primer design algorithms are then used to identify primers for amplification beginning at the 5’ end of one region (such as PHCDBS 3F) and the 3’ end primer of another region (such as PHCDBS14R). This single primer pair can amplify approximately half (6726 bp) of the entire mitochondrial genome. In a similar manner, another primer pair using PHCDBS 14F as the 5’ prime end primer and PHCDBS 3R as a 3’ prime end primer was used to cover another large segment (9837 bp) of the mitochondrial genome (Fig. 5).
One of the potential challenges of using this method is the possibility of poor coverage in certain regions (Fig. 4, Table 2). This may be due to uncertain rates of substitutions or the possible existence of pseudogenes inserted into the nuclear genome, as suggested by various authors (Thalmann et al. 2004; Raaum et al. 2005; Pozzi et al. 2014; Finstermeier et al. 2013). To address this, apart from the primers used above to amplify large portions of mitochondrial genome, twelve other primer pairs were also designed for the amplification of fragments covering smaller segments of the genome. Most of these smaller amplification products represent the conserved regions of individual genes. These smaller products can also be used to detect amplification of any pseudogene copies of mitochondrial genes that may have inserted into the nuclear genome (Chiou et al. 2011). These primers were also optimized for annealing temperatures to minimize the possibility of non-specific amplification (Figs. 1 & 2). Even at annealing temperatures 60C lower, non-specific amplification was not observed (Schoenbrunner et al. 2017). The primers used to successfully amplify the primate mitochondrial genome of S. hypoleucos along with their resultant sequence analysis are shown in the supporting data (Supplementary Fig. S1; Supplementary Table S1).
Overall, this strategy may help in minimizing sequencing costs using Sanger sequencing platforms (Ughade et al. 2019) and for validation of NGS based data in genome assemblies. The primer design also ensures that there is sufficient overlap of the different amplified fragments in order to obtain the complete genome sequences, including the primer sites and flanking nucleotides (Fig. 3).
Applying the strategy mentioned in Fig. 1 of designing primers for amplification of both long and short segments of the mitochondrial genome can be applied to characterization of the entire mitochondrial genome of many different closely-related species to S. hypoleucos. Beginning with a download of the entire mitochondrial genomic sequences of a species within a given family (from Genbank or other sources) our algorithm to design appropriate primers (Fig. 4) can easily be implemented. Subsequently, the designed primer sets are used to validate successful PCR amplification and build the genome assembly representing the entire mitochondrial genome from species with mitochondrial genomes that have not yet been adequately characterized and analyzed.
Mitochondrial DNA represents one of the most informative molecules for evolutionary studies. Amplification of the entire mitochondrial genome requires the use of robust primers. This study suggests a method of primer design and optimization (PDO) where first long amplification products are produced using 5’ primers from the conserved region of one gene and 3’ primers from conserved region of another gene. Additional primer sets representing shorter segments of the genome are also used to fill in gaps in order to complete the mitogenome sequencing. Using this strategy, the mitochondrial genome of S. hypoleucos was successfully amplified and sequenced. Applying this strategy of designing primers using conserved regions of known mtDNA sequences may be utilized for amplification and characterization of the entire mitochondrial genome sequences from many other species where groups of closely related species are known to exist.
Acknowledgement
Authors are thankful to University Grants Commission, New Delhi, India for providing Junior Research Fellowship to Vipin Hiremath. Non-invasive samples were provided by Director, Pilikula Biological Park, Mangalore is highly acknowledged. Also we are thankful to Dr. Bharathi Prakash for her assistance in sample collection. We sincerely thank all staff member and students at Paul Hebert Centre for DNA Barcoding and Biodiversity Studies, Aurangabad for their assistance in completing this work.
Authors Contribution:
Vipin Hiremath: Conceiving research idea; sample collection, conduction of experiments;
Chandrakant Jadhav: Data analysis;
GD Khedkar: Conceiving research idea; writing manuscript
Competing interests: The authors do not have conflict of interest to declare.
Consent for publication: Not applicable.
Ethics approval consent to participate: Not applicable.
Mitochondrial DNA; PDO:Primer design and optimization; COI:cytochrome oxidase subunit I
Avise JC. 1986. Mitochondrial DNA and the evolutionary genetics of higher animals. Philos Trans R Soc Lond B Biol Sci 312:325–342.
Avise JC, Saunders NC. 1984. Hybridization and introgression among species of sunfish (Lepomis): analysis by mitochondrial DNA and allozyme markers. Genetics 108:237–255.
Brown WM, Prager EM, Wang A, Wilson AC. 1982. Mitochondrial DNA sequences of primates: Tempo and mode of evolution. Jour of Mol Evol 18:225–239.
Chang HW, Chou YC, Su YF, Cheng CA, Yao CT. 2010. Molecular phylogeny of the Pycnonotus sinensis and Pycnonotus taivanus in Taiwan based on sequence variations of nuclear CHD and mitochondrial cytochrome b genes. Biochem Syst and Eco 38:195–201.
Chang HW, Chuang LY, Cheng YH, Gu DL, Huang HW. 2010. An introduction to mitochondrial informatics. Meth in Mol Bio 628:259–274.
Chen YF, Chen RC, Chan YK, Pan RH, Hseu YC. 2009. Design of multiplex PCR primers using heuristic algorithm for sequential deletion applications. Comp Bio and Chem 33:181–188.
Chiou KL, Pozzi L, Lynch AJW, Di Fiore A. 2011. Pleistocene diversification of living squirrel monkeys (Saimiri spp.) inferred from complete mitochondrial genome sequences. Mol Phylo and Evol 59 (3):736–745. https://doi.org/10.1016/j.ympev.2011.03.025.
Dasmahapatra KK, Elias M, Hill RI, Hoffman JI, Mallet J. 2010. Mitochondrial DNA barcoding detects some species that are real, and some that are not. Mol Eco Res 10:264–273.
de Freitas PD, Fernando LM, Karla CC, Pedro MG, Luiz LC, Alcides P, Carlos DB. 2018. Next-Generation Sequencing of the Complete Mitochondrial Genome of the Endangered Species Black Lion Tamarin Leontopithecus chrysopygus (Primates) and Mitogenomic Phylogeny Focusing on the Callitrichidae Family. G3: Genes, Genomes, Genetics 8 (6):1985–1991; https://doi.org/10.1534/g3.118.200153.
Finstermeier K, Zinner D, Brameier M, Meyer M, Kreuz E, Hofreiter M, Roos C. 2013. A Mitogenomic Phylogeny of Living Primates. PLoS ONE 8(7) https://doi.org/10.1371/journal.pone.0069504
Gerber AS, Loggins R, Kumar S, Dowling TE. 2001. Does non neutral evolution shape observed patterns of DNA variation in animal mitochondrial genomes? Annual Reviews in Genetics 35:539–566.
Khedkar GD, Abhayankar SB, Nalage D, Shaikh NA, Khedkar CD. 2016a. DNA barcode based wildlife forensics for resolving the origin of claw samples using a novel primer cocktail. Mitochondrial DNA Part A 27(6):3932–3935.
Khedkar GD, Tiknaik A, Kalyankar AD, Reddy CA, Khedkar CD, Ron TB, Haymer D. 2016b. Genetic structure of populations and conservation issues relating to an endangered catfish, Clarias batrachus, in India. Mitochondrial DNA Part A 27(2):1181–1187.
Hillis DM, Bull JJ. 1993.An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis. Syst Biol 42(2):182–192. https://doi.org/10.1093/sysbio/42.2.182.
Howell N, Kubacka I, Mackey DA. 1996. How rapidly does the human mitochondrial genome evolve? Am J Hum Genet 59:501–509.
Kerr KCR, Lijtmaer DA, Barreira AS, Hebert PDN, Tubaro PL. 2009. Probing evolutionary patterns in neotropical birds through DNA barcodes. PLoS ONE 4: e4379.
Kibbe WA. 2007.OligoCalc: an online oligonucleotide properties calculator.
Nucleic Acids Res. 35(Web Server issue):W43-6.
Kim SR, Kim MI, Hong MY, Kim KY, Kang PD, Hwang JS, Han YS, Jin BR, Kim I. 2009. The complete mitogenome sequence of the Japanese oak silkmoth, Antheraea yamamai (Lepidoptera: Saturniidae). Mol Bio Rep 36: 1871–1880
Kurabayashi A, Sumida M. 2013.Afrobatrachian mitochondrial genomes: Genome reorganization, gene rearrangement mechanisms and evolutionary trends of duplicated and rearranged genes. BMC Genomics 14 (1). https://doi.org/10.1186/1471-2164-14-633.
Kurabayashi A, Yoshikawa N, Sato N, Hayashi Y, Oumi S, Fujii T, Sumida M. 2010.Complete mitochondrial DNA sequence of the endangered frog Odorranaishikawae (family Ranidae) and unexpected diversity of mt gene arrangements in ranids. Mol Phylo and Evol 56 (2):543–553. https://doi.org/10.1016/j.ympev.2010.01.022
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J. 2009. The Sequence Alignment/Map format and SAM tools. Bioinformatics 25 (16):2078–2079. doi:10.1093/bioinformatics/btp352.
Liedigk R, Yang M, Jablonski NG, Momberg F, Geissmann T, Lwin N, Roos C. 2012. Evolutionary history of the odd-nosed monkeys and the phylogenetic position of the newly described Myanmar snub-nosed monkey Rhinopithecus strykeri. PLoS ONE7 (5). https://doi.org/10.1371/journal.pone.0037418.
Pozzi L, Hodgson JA, Burrell AS, Sterner KN, Raaum RL, Disotell TR. 2014. Primate phylogenetic relationships and divergence dates inferred from complete mitochondrial genomes. Mol Phylo and Evol 75(2014):165–183.
Ma LL, Zhang XY, Yue BS, Ran JH. 2010. Complete mitochondrial genome of the Chinese Monal pheasant Lophophorus lhuysii, with phylogenetic implication in Phasianidae. Mitochondrial DNA 21:5–7.
Matsui A, Rakotondraparany F, Munechika I, Hasegawa M, Horai S. 2009.Molecular phylogeny and evolution of prosimians based on complete sequences of mitochondrial DNAs. Gene 441(1–2):53–66. https://doi.org/10.1016/j.gene.2008.08.024
Nabholz B, Glemin S, Galtier N. 2009. The erratic mitochondrial clock: variations of mutation rate, not population size, affect mtDNA diversity across birds and mammals. BMC Evol Bio 9:54.
Oakenfull EA, Lim HN, Ryder AO. 2000. A survey of equid mitochondrial DNA: Implications for the evolution, genetic diversity and conservation of Equus. Cons Genet 1:341–355.
Pozzi L, Hodgson JA, Burrell AS, Sterner KN, Raaum RL, Disotell TR. 2014. Primate phylogenetic relationships and divergence dates inferred from complete mitochondrial genomes. Mol phylo and evol 75:165–183. doi:10.1016/j.ympev.2014.02.023
Raaum RL, Sterner KN, Noviello CM, Stewart CB, Disotell TR. 2005. Catarrhine primate divergence dates estimated from complete mitochondrial genomes: Concordance with fossil and nuclear DNA evidence. Jourl of Hum Evol 48(3): 237–257. https://doi.org/10.1016/j.jhevol.2004.11.007.
Ramos A, Santos C, Barbena E, Mateiu L, Alvarez L, Nogués R, Aluja MP. 2011. Validated primer set that prevents nuclear DNA sequences of mitochondrial origin co-amplification: A revision based on the New Human Genome Reference Sequence (GRCh37). Electrophoresis 32 (6–7):782–783. https://doi.org/10.1002/elps.201000583.
Rizzi E, Lari M, Gigli E, De Bellis G, Caramelli D. 2012.Ancient DNA studies: New perspectives on old samples. Gen Sel Evol https://doi.org/10.1186/1297-9686-44-21.
Roos C, Zinner D, Kubatko LS, Schwarz C, Yang M, Meyer D, Osterholz M. 2011. Nuclear versus mitochondrial DNA: Evidence for hybridization in colobine monkeys. BMC Evol Bio 11(1). https://doi.org/10.1186/1471-2148-11-77.
Schoenbrunner NJ, Gupta AP, Young KKY, Will SG. 2017. Covalent modification of primers improves PCR amplification specificity and yield. Bio Meth and Proto 2 (1). https://doi.org/10.1093/biomethods/bpx011.
Thalmann O, Hebler J, Poinar HN, Pääbo S, Vigilant L. 2004. Unreliable mtDNA data due to nuclear insertions: A cautionary tale from analysis of humans and other great apes. Mol Eco 13 (2):321–335. https://doi.org/10.1046/j.1365-294X.2003.02070.x
Ughade BR, Khilare VC, Sangale DM, Korhale GA, Ingle P, Tathe, AE, Khedkar GD. 2019. A definitive method for distinguishing cultivated onion from its weedy mimic, Asphodelus fistulosus, at multiple developmental stages. Weed Research 59(1):39–48. https://doi.org/10.1111/wre.12337.
Untergasser A, Cutcutache I, Koressaar T, Ye J, Faircloth BC, Remm M, Rozen SG. 2012. Primer3 - new capabilities and interfaces. Nucl Acids Res 40 (15):e115.
Webb DM, Moore WS. 2005.A phylogenetic analysis of woodpeckers and their allies using 12S, Cytb, COI nucleotide sequences (class Aves; order Piciformes). Mol Phylo and Evol 36:233–248.
Wilson AC, Cann RL, Carr SM, George M, Gyllensten UB, Bychowski KMH, Higuchi RG. 1985. Mitochondrial DNA and Two Perspectives on Evolutionary Genetics. Bio Jour of the Linn Soc 26(4):375–400. doi:10.1111/j.1095-8312.1985.tb02048.x.
Wu JS, Lee C, Wu CC, Shiue YL. 2004. Primer design using genetic algorithm. Bioinformatics 20:1710–1717.
Yang CH, Cheng YH, Chuang LY, Chang HW. 2009. Specific PCR product primer design using memetic algorithm. Biotechnological Progress 25:745–753.
Yang CH, Cheng YH, Chang HW, Chuang LY. 2010. Primer design with specific PCR product using particle swarm optimization. Inter Jour of Chem and Bio Eng 3:18–23.
Zhang K, Xiang HT, Zhao, SC. 2017. The complete mitochondrial genome of the drill (Mandrillus leucophaeus). Mitochondrial DNA Part A 28(1):69–70. https://doi.org/10.3109/19401736.2015.1110802
Table 1. List of reference sequences of primate species used for primer designing
Sr. No. |
Species Name |
Accession number |
Sub family |
Family |
1 |
T. vetulus |
NC_019582.1 |
Colobinae |
Cercopithecidae |
2 |
T. shortridgei |
KP834334.1 |
Colobinae |
Cercopithecidae |
3 |
T. pileatus |
NC_024529.1 |
Colobinae |
Cercopithecidae |
4 |
T. obscurus |
AY863425.1 |
Colobinae |
Cercopithecidae |
5 |
T. johnii |
NC_019583.1 |
Colobinae |
Cercopithecidae |
6 |
T. hatinhensis |
NC_019579.1 |
Colobinae |
Cercopithecidae |
7 |
T. germaini |
NC_019580.1 |
Colobinae |
Cercopithecidae |
8 |
T. francoisi |
NC_023970.1 |
Colobinae |
Cercopithecidae |
9 |
T. cristatus |
NC_023971.1 |
Colobinae |
Cercopithecidae |
10 |
S. entellus |
DQ355297.1 |
Colobinae |
Cercopithecidae |
11 |
P. roxellana |
DQ355300.1 |
Colobinae |
Cercopithecidae |
12 |
P. nemaeus |
DQ355302.1 |
Colobinae |
Cercopithecidae |
13 |
P. badius |
DQ355301.1 |
Colobinae |
Cercopithecidae |
14 |
P. melalophos |
DQ355299.1 |
Colobinae |
Cercopithecidae |
15 |
P. pygmaeus |
NC_001646.1 |
Ponginae |
Hominidae |
16 |
P. abelii |
NC_002083.1 |
Ponginae |
Hominidae |
17 |
P. hamadryas |
NC_001992.1 |
Cercopithecinae |
Cercopithecidae |
18 |
P. troglodytes |
NC_001643.1 |
Homininae |
Hominidae |
19 |
P. paniscus |
NC_001644.1 |
Homininae |
Hominidae |
20 |
N. larvatus |
DQ355298.1 |
Colobinae |
Cercopithecidae |
21 |
M. sylvanus |
NC_002764.1 |
Cercopithecinae |
Cercopithecidae |
22 |
H. lar |
NC_002082.1 |
-- |
Halobatidae |
23 |
G. gorilla |
NC_001645.1 |
Gorillinae |
Hominidae |
24 |
C. guereza |
AY863427.1 |
Colobinae |
Cercopithecidae |
25 |
C. albifrons |
NC_002763.1 |
Cebinae |
Cebidae |
Table 2. Details of primers designed to amplify mitochondrial genome of S. hypoleucos
Primer name |
Forward Primer Sequence |
Products |
Tm (0C) |
GC% |
Annealing temp. (0C) |
Predicted product size |
Primer position |
|||||||
Start |
End |
|||||||||||||
A. Primers designed for amplification of large fragments |
|
|
|
|
|
|||||||||
PHCDBS 1F |
ATAC TAGC CCAA ATCC CAAC |
Left half region between 16S rRNA and COII |
46 |
45 |
55.3 |
6726 |
1092 |
7818 |
||||||
PHCDBS 1R |
TTTA GCTG AGGC ATTT CACT |
|
40 |
53.2 |
|
|
|
|||||||
PHCDBS 2F |
CCCG CAGT TATT TTAG TCTT |
Right half region between COII and 16S rRNA |
46 |
40 |
53.2 |
9837 |
7819 |
1091* |
||||||
PHCDBS 2R |
CCAG GAGA ATTC ATTC ATGT |
|
40 |
53.2 |
|
|
|
|||||||
B. Primers designed for amplification of small fragments |
|
|
|
|
|
|
||||||||
PHCDBS 3F |
ATAC TAGC CCAA ATCC CAAC |
16SrRNA |
44 |
45 |
55.3 53.2 |
659 |
1092 |
1750 |
||||||
PHCDBS 3R |
CCAG GAGA ATTC ATTC ATGT |
|
40 |
|
|
|||||||||
PHCDBS 4F |
ACCT AGAA AAAT CCCA GACA |
16SrRNA |
48 |
40 |
53.2 55.3 |
651 |
1640 |
2290 |
||||||
PHCDBS 4R |
TGAC TTGT GTGG TCTT AGCA |
|
45 |
|
|
|||||||||
PHCDBS 5F |
TAAA TCCA CGGA CCTA ACAC |
16SrRNA, tRNA-L, ND1 |
48 |
45 |
55.3 55.3 |
656 |
2182 |
2837 |
||||||
PHCDBS 5R |
TGGG TCCT TTAC GTAG TTGT |
|
45 |
|
|
|||||||||
PHCDBS 6F |
TTAC TTTA CCCA TCCT AGCC |
ND1, tRNA-I, tRNA-Q |
48 |
45 |
55.3 51.2 |
650 |
2751 |
3400 |
||||||
PHCDBS 6R |
TATG AAGA AAAG GGCA AATG |
|
35 |
|
|
|||||||||
PHCDBS 7F |
CCCT TTTC TTCA TAGC TGAG |
tRNA-Q, tRNA-M, ND2 |
48 |
45 |
55.3 57.3 |
576 |
3387 |
3962 |
||||||
PHCDBS 7R |
GTGG GAGC TAAG TGAG GTAA |
|
50 |
|
|
|||||||||
PHCDBS 8F |
TTGG TTAT ATCC TTCC CATA CT |
ND2, tRNA-W, tRNA-A |
48 |
36.36 |
54.7 57.3 |
685 |
3865 |
4549 |
||||||
PHCDBS 8R |
AGGC TTAG AGCT AGGA ATGC |
|
50 |
|
|
|||||||||
PHCDBS 9F |
TCCT AGCA TACT CTTC AATCA |
tRNA-N, tRNA-C, tRNAY, COI |
46 |
38.10 |
54.0 51.2 |
689 |
4420 |
5108 |
||||||
PHCDBS 9R |
AGGT TTTT GTGG GTTT GAAT |
|
35 |
|
|
|||||||||
PHCDBS 10F |
TACT CTGC ATCA ACTG AACG |
COI |
48 |
45 |
55.3 55.3 |
632 |
5023 |
5654 |
||||||
PHCDBS 10R |
GTAG AAAT GATG GTGG GAGA |
|
45 |
|
|
|||||||||
PHCDBS 11F |
ATTT CCCC GTCT AAAC AATA |
COI |
48 |
35 |
51.2 53.2 |
581 |
5602 |
6182 |
||||||
PHCDBS 11R |
CAAT AAAG CCTA GGAA TCCA |
|
40 |
|
|
|||||||||
PHCDBS 12F |
TGGA TTCC TAGG CTTT ATTG |
COI, tRNA-S2, tRNA-D |
48 |
40 |
53.2 51.2 |
610 |
6163 |
6772 |
||||||
PHCDBS 12R |
TAGA ACTT TGCG TTTT GAAG |
|
35 |
|
|
|||||||||
PHCDBS 13F |
GGCT CCTT TATT TCCC TAGT |
COII |
48 |
45 |
55.3 55.3 |
606 |
6692 |
7297 |
||||||
PHCDBS 13R |
GATG GTAA AGGA GGGG TTAT |
|
45 |
|
|
|||||||||
PHCDBS 14F |
CCCG CAGT TATT TTAG TCTT |
COII, tRNA-K |
48 |
40 |
53.2 |
608 |
7211 |
7818 |
||||||
PHCDBS 14R |
TTTA GCTG AGGC ATTT CACT |
|
40 |
53.2 |
|
|
||||||||