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Phylogenetic relationships of Malaysia's
pig-tailed macaque Macaca nemestrina based on
D-loop region sequences
Conference Paper · April 2014 DOI: 10.1063/1.4895300
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4 authors:
Abdul-Latiff M.A.B
Universiti Tun Hussein Onn Malaysia
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Ahmad Ampeng
Forest Department Sarawak
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Salmah Yaakop
National University of Malaysia
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Badrul munir Md zain
National University of Malaysia
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Phylogenetic relationships of Malaysia's pig-tailed macaque Macaca nemestrina based
on D-loop region sequences
Abdul-Latiff M. A. B., Ampeng A., Yaakop S., and Md-Zain B. M.
Citation: AIP Conference Proceedings 1614, 772 (2014); doi: 10.1063/1.4895300
View online: http://dx.doi.org/10.1063/1.4895300
View Table of Contents: http://scitation.aip.org/content/aip/proceeding/aipcp/1614?ver=pdfcov
Published by the AIP Publishing
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Interaural timedifference threshold in pigtailed monkeys (M. nemestrina
Phylogenetic Relationships of Malaysia’s
Pig-Tailed
Macaque
Macaca nemestrina
Based on D-Loop
Region Sequences
Abdul-Latiff M.A.B.
a, Ampeng A.
b,Yaakop S.
aand Md-Zain B.M.
aaSchool of Environmental and Natural Resource Sciences, Faculty of Science and Technology,
UniversitiKebangsaan Malaysia, 43600 Bangi, Selangor Malaysia
bSarawak Forestry Department, Kuching, Sarawak, Malaysia
Abstract. Phylogenetic relationships among Malaysian pig-tailed macaques have never been established even though the data are crucial in aiding conservation plan for the species. The aims of this study is to establish the phylogenetic relationships of Macaca nemestrina in Malaysia. A total of 21 genetic samples of M. nemestrina yielding 458 bp of D-loop sequences were used in phylogenetic analyses, in addition to one sample of M. fascicularis which was used as an outgroup. Sequence character analysis revealed that D-loop locus contains 23% parsimony informative character detected among the ingroups. Further analysis indicated a clear separation between populations originating from different regions; the Malay Peninsula populations are separated from Borneo Insular population; and Perak population formed a distinctive clade within Peninsular Malaysia populations. Phylogenetic trees (NJ, MP and Bayesian) portray a consistent clustering paradigm as Borneo population was distinguished from Peninsula population (100% bootstrap value in theNJ, MP, 1.00 posterior probability in Bayesian trees). Perak’s population was separated from other Peninsula populations (100% in NJ, 99% in MP and1.00 in Bayesian). D-loop region of mtDNA is proven to be a suitable locus in studying the separation of
M. nemestrina at population level. These findings are crucial in aiding the conservation management and translocation
process of M. fascicularis populations in Malaysia.
Keywords: Pig-tailed macaque, Macaca nemestrina, D-loop, mtDNA, phylogenetic relationships.
INTRODUCTION
The conversion of tropical rainforest, home to the world’s highest species diversity is the key element that threats the survival of wild populations of mammals including non-human primates [1]. Wild populations of Macaca nemestrina are declining due to habitat loss and alteration [2]. M. nemestrina is listed as Vulnerable by IUCN [3] and this is mainly caused by human encroachment, illegal hunting for pet trade. Land use conflicts are steadily contributing to the declining of M. nemestrina as most of authorities in Southeast Asia practice the anthropocentric conservation plans. Two subspecies of M. nemestrina has been identified based on morphological characters such as pelage coloration and patter, as well as tail morphology [4]. M. n. leonine is distributed in southern mainland Southeast Asia and M. n. nemestrina in southern Peninsular Malaysia, Sumatra and Borneo [5-6]. Very little is known about the phylogenetic relationship of M. nemestrina especially in Malaysia, even though this data is very crucial for conservation plans executed by PERHILITAN (Department of Wildlife and Nature Park Malaysia). One of the measures taken by PERHILITAN is to translocate the wild populations of M. nemestrina in the case of human-wildlife conflict. To protect and manage macaque populations and their habitats effectively, the status of macaque populations in protected and unprotected areas must be evaluated continuously [2]. Thus the objective of this research is to determine the phylogenetic relationships of Malaysia’s M. nemestrina using mitochondrial D-loop sequences.
MATERIALS AND METHODS
A total of 20 genetic samples of M. nemestrina were used in this study, in addition of 1 sample of M. fascicularis was used as an outgroup. These genetic samples were obtained with the assistances of Department of Wildlife and Nature Parks (PERHILITAN). DNA was extracted from two types of genetic samples, tissue samples and FTA card samples. QIAGEN DNeasy Blood and Tissue extraction Kit and WHATMAN®Gensolve Recovery Kit were used
for tissue and FTA samples respectively, both following the manufacturer’s protocols. A 500-bp fragment of the Control Region (CR) or D-loop of mitochondrial DNA (mtDNA) was amplified by employing Polymerase Chain Reaction using Mastercycler Nexus (Eppendorf North America, Inc). PCR was performed by using PhusionTM Flash
High-Fidelity PCR Master Mix (Finnzymes, OY) which has high accuracy (proofreading DNA polymerase with a fidelity of 25 X Taq polymerase), extreme speed (extension times of 15 s/kb or less) and a very high yield in reduced time. We designed our own primers for the PCR in order to maximize the extent of D-loop sequence and to avoid amplifying NUMTs. The parameters for PCR were as follow: 98oC initial denaturation for 10 s, followed by
30 cycles of 98oC denaturation for 1 s, 52oC of annealing for 30 s, 72oC extension for 15 s and final extension stage
at 72oC for 1 min. Vivantis G-F1 PCR Clean-up Kit was used to purify the PCR product, subsequently the samples
were sent to 1st Base SdnBhd (Malaysia) for sequencing.
Sequence and Phylogenetic Analysis
Sequence results obtained from the 1st Base Laboratories Sdn Bhd were proofread and edited using BioEdit
Sequence Alignment Editor [7], and the Sequence Similarity searches were performed using GenBankBLASTn application to validate the DNA sequences obtained. ClustalW multiple alignment algorithm of BioEdit [7] was then used to align the sequences, and sequence and phylogenetic analyses were performed. PAUP 4.0b10 [8] and MEGA version 6[9]softwares were used for sequence analysis to determine genetic distance (using Kimura-2-parameter algorithm) and single nucleotide polymorphisms (SNPs) of the sequences/dataset respectively. Phylogenetic trees were constructed on three distinct criteria, distance-based (Neighbor Joining Tree), character-based (Maximum Parsimony Tree) and Bayesian Inference. Different softwares were used to construct the phylogenetic trees -Neighbor Joining (NJ) tree with MEGA 6, Maximum Parsimony (MP) tree with PAUP 4.0b10 and Bayesian Inference with MrBayes 3.1 [10]. Kimura-2-Parameter model was used in the NJ tree reconstruction tested with 1000 bootstrap replicates and Tree Bisection and Reconnection (TBR) algorithm was used for MP tree. Heuristic search method and 1000 random stepwise additions were applied to find the best tree with the application of 50% consensus majority rule. All the tree constructed were tested with bootstrap analysis (1000 replicates) to obtain the bootstrap confidence level. Modeltest version 3.7 software [11] was used to select the best substitution model for the Control Region sequences using Akaike Information Criterion (AIC). The best substitution model was applied in the Bayesian analysis using MrBayes 3.1.2. software. The most suitable model that fit the data was the HKY+G model with a gamma shape parameter of 0.5455 and base frequencies of 0.2866 for A, 0.3171 for C, 0.1266 for G and 0.2696 for T. We ran Metropolis-coupled Markov Chain Monte Carlo (MCMC) with 150000 generations, with 0.009861 Split Frequencies Probability (P) and tree was sampled every 10 generations. The first 10% of the trees obtained in the analysis was discarded as burn-in (1500 trees discarded from total 15000 trees), a majority-rule consensus of remaining trees was constructed and posterior probabilities (PP) were summarized for each branch.
RESULTS AND DISCUSSION
Genetic Distance and Nucleotide Diversity
A total of 21 DNA sequences in a size of 458bp of D-loop locus contained106 (23.14%) variable sites, among which 74 sites were parsimony informative characters (16.15%), and the remaining 32 sites were parsimony uninformative. The nucleotide composition for the entire 458 bp sequences was as follow: thymine = 26.9 %, cytosine = 29.6 %, adenosine = 30.3%, and guanine = 13.1 %. The sequences exhibited a total of 32 (7%) Single Nucleotide Polymorphisms, 23 transitional pairs and 4 transversional pairs. Samples originated from Borneo and Peninsula Malaysia showed a minimum genetic distance of 0.133 and a maximum value of0.153.Within Peninsular Malaysia, a significant pairwise genetic distances can be observed between Perak population on East Coast with the rest of Peninsular Malaysia population, with genetic distance as high as 0.074.
The NJ tree (FIGURE 1) portrays parallel result with genetic distance. Borneo population is separated from
Peninsular’s populations supported by 100% and 80% of bootstrap value respectively. Perak population also formed a distinctive clade within Peninsular Malaysia clade, supported by 100% bootstrap value. The MP tree reconstruction yielded a 50% consensus-rule tree summarized from the 9 most parsimonious trees (length = 140) is shown in FIGURE 2. The consistency index was 0.666667, the retention index was 0.848980, and the composite index was 0.624606 for all sites and parsimony-informative sites. The MP tree is consistent with NJ tree in which the Borneo population and Peninsula populations are separated supported with the bootstrap value of 100% and 84% respectively. Perak population is also separated in the MP tree, supported by 99% bootstrap value. Finally, The Bayesian Inference phylogenetic tree (FIGURE 3) generated conclude that the genetic distance, NJ and MP phylogenetic tree are unswerving with each other. Separation of Borneo population from Peninsula populations together with separation of Perak population from the remaining Peninsula population are supported by a perfect 1.0 Posterior Probabilities (PP).
FIGURE1. Neighbor-Joining tree generated using Kimura-2-Parameter with bootstrap (1000 replicates) statistical test.
ALMNK125 ALMNK126 ALMNK104
ALMNK103
Kedah
ALMNJ277 ALMNJ278 ALMNJ279
Johor
ALMND18 ALMND22 Kelantan ALMNC229
ALMNC230 Pahang ALMNA361
ALMNA367 ALMNA368 ALMNA351 ALMNA352 ALMNA354 ALMNA355
Perak
AAMNQ287
AAMNQ289 Sarawak M.fascicularis
100 98
24 70 50 27
100 80
76
99
41 98
43 74
80 65
FIGURE2. 50% majority rule consensus maximum parsimony treewith bootstrap (1000 replicates) statistical test.
FIGURE3. Bayesian Inference of the 50% majority rule consensus tree. Bayesian Posterior Probability (PP) is indicated on the nodes.
ALMNJ277 ALMNJ279 ALMNJ278
Johor
ALMND18 ALMND22 Kelantan ALMNK104 ALMNK103 ALMNK125 ALMNK126
Kedah
ALMNC229 ALMNC230 Pahang ALMNA361 ALMNA367 ALMNA368 ALMNA352 ALMNA354 ALMNA351 ALMNA355
Perak
AAMNQ287 AAMNQ289 Sarawak M.fascicularis
46
85 22 68
39 98 30
85
95
100 62
84
99 33
51 67
The separation of Borneo and Peninsular Malaysia populations of M. nemestrina is highly anticipated, considering the vicariance theory on population disjunction. In this scenario, Borneo and Peninsular Malaysia populations are separated by the South China Sea. This separation interrupted gene flow between both of the populations causing them to undergo speciation, thus distinguishing these two populations genetically. Although, these separations (in genetic analysis) may also occur due to differences at subspecies level. Unfortunately, there are no previous (morphological nor genetic) studies to suggest this assumption, thus more genetic studies (more samples, longer and more variable loci) are needed to support this assumption. The total separation of Perak population on the other hand is unpredicted as we assume the separation might only occur based on biogeographical reasoning such as Perak River, Pahang River etc. However, the results indicated that Perak population formed its on colony in the genetic analysis supported with a high bootstrap values. Previous studies [12] have proven that by exploiting genetic data, the genetic structure of a population can be unravelled and might give a new insight in pig-tailed macaque taxonomy. The findings in this research need a further attention on the note for future research as Perak population might be a different subspecies for all we know.
CONCLUSION
Macaca nemestrina in Malaysia is successfully defined into Peninsular Malaysia populations and Borneo population based on D-loop region of mtDNA. Perak populations is also appearing to be distinctive based on the analysis. D-loop region of mtDNA is proven to be effective in studying phylogenetic relationships of M. nemestrina at the population level. Future research isrecommended to use longer and more variable loci and include more samples from Perak population to define the phylogenetic position of this population.
ACKNOWLEDGEMENTS
We are deeply indebted to Department of Wildlife and National Parks and Sarawak Forestry Department that provided us with the necessary facilities and assistance for tissue sample collection. The authors acknowledge Universiti Kebangsaan Malaysia for providing necessary funding, facilities and assistance. This research was supported by grants FRGS/1/2012/STWN10/UKM/02/3, UKM-GUP-2011-168, KOMUNITI-2011-023, ERGS/1/2013/STWN10/UKM/02/1 and DLP-2013-006.
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