All submissions of the EM system will be redirected to Online Manuscript Submission System. Authors are requested to submit articles directly to Online Manuscript Submission System of respective journal.
Research Article

Characterization of 33 microsatellite markers and development of multiplex PCR for yellow-throated marten (Martes flavigula)

Received: October 14, 2017
Accepted: November 08, 2017
Published: December 29, 2017
Genet.Mol.Res. 17(1): gmr16039854
DOI: 10.4238/gmr16039854

Abstract

The yellow-throated marten (Martes flavigula Boddaert 1785) is a medium-sized carnivore and a top predator in South Korea that is distributed throughout Western and Southeast Asia and Siberia in a wide range of habitats. In this study, we developed a panel of polymorphic microsatellite markers for M. flavigula by Illumina next-generation sequencing for investigation of population genetics. A total of 887 candidate microsatellite markers were identified and characterized from genomic sequences. By testing the markers in three individuals, we found 73 satisfactory microsatellite loci consisting of tri- or tetranucleotide repeats. We designed four multiplex panels of 33 microsatellite loci and applied them to 35 individuals from South Korea. The number of alleles and polymorphism information content per locus varied from 2 to 9 and from 0.164 to 0.841, respectively. The observed and expected heterozygosity per locus ranged from 0.143 (MF233) to 0.800 (MF339) and from 0.183 (MF233) to 0.871 (MF327) respectively. Nine of the 33 loci deviated significantly from Hardy-Weinberg equilibrium. We also found that at least 10 of the loci were transferrable to two other species of Mustelidae (Meles and Mustela sibirica). These markers can be applied to studies of genetic variation and population structure and can be useful for ex situ conservation and ecological monitoring by non-invasive sampling of M. flavigula populations.

Introduction

The yellow-throated marten (Martes flavigula) is a medium-sized carnivore that is distributed in a wide geographical range from eastern Afghanistan to the Russian Far East, extending south to the Malaysian peninsula, Sumatra, Java, and Borneo (Corbert, 1978; Corbet and Hill, 1992). In South Korea, this species inhabits forest zones in small groups of one to six individuals (mean=2.9 ± 1.6), and helps to control the population size of herbivores such as Chinese water deer (Hydropotes inermis) (Woo et al., 2015). Given the extinction of large carnivores (Panthera tigris, Canis lupus, and Panthera pardus) in South Korea, the yellow-throated marten is expected to become a top predator in ecosystems (Woo et al., 2015). Although the population size of M. flavigula has been relatively stable in South Korea, it is classified as a Class II endangered species by the Ministry of Environment of South Korea and as Least Concern on the International Union for Conservation of Nature red list (Chutipong et al., 2016).

Despite its wide distribution and ecological importance, there have been few genetic studies on M. flavigula. Previous studies on the complete mitochondrial genome (Jang and Hwang, 2014; Xu et al., 2013) and phylogenetic relationships between species (Hosoda et al., 2011; Koepfli et al., 2008; Sato et al., 2003) have shown that M. flavigula is distantly related to the other species in genus Martes, but no population-level study has been carried out to clarify genetic diversity and population structure in M. flavigula.

Microsatellites, also known as simple sequence repeats or short tandem repeats, are distributed throughout the nuclear genome and exhibit codominance, Mendelian inheritance, high polymorphism, and a rapid mutation rate, and are therefore suitable tools for population genetics, fingerprinting, parentage identification, genetic mapping, and ecological and evolutionary analyses (Buschiazzo et al., 2006; Goldstein and Schlötterer 1999; Guichoux et al., 2011). In the present study, we attempted to identify and characterize novel polymorphic microsatellite markers for M. flavigula by next-generation sequencing (NGS) and developed multiplex panels that will reduce the time and cost of genotyping. The utility of the panels was evaluated by the cross-amplification tests in other Mustelidae species i.e., Meles meles and Mustela sibirica. Our results may provide a basis for future genetic studies of M. flavigula.

Material and Methods

Samples, DNA isolation, genomic library construction, and NGS

Samples used in this study were collected in compliance with the relevant regulations. Individuals of M. flavigula (n=35), Meles meles (n=8), and Mustela sibirica (n=12) were collected from several regions of South Korea and tissue samples (muscle, blood, and hair) were preserved at −70°C. Total genomic DNA was extracted using the DNeasy Blood and Tissue kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s protocol. Of 35 individuals, two (IN590 and IN592) were used for NGS. A genomic DNA library was constructed using the NEXTflex Rapid DNA-seq kit (Bioo Scientific, Austin, TX, USA), and DNA was sheared into 500-bp fragments with Q-Sonica 800 (QSonica, Newtown, CT, USA) according to the manufacturer’s instructions. The fragmented DNA was blunt-end repaired, 3′ adenylated, and ligated with multiplex-compatible adapters to construct an Illumina-compatible DNA library. Fragments 300–600 bp in size were selected with Agencourt AMPure XP SPRI beads (Beckman Coulter, Beverly, MA, USA). DNA with adapters on both ends was selectively enriched by PCR. The quality of the constructed DNA libraries was verified on an Agilent 2100 BioAnalyzer (Agilent Technologies, Santa Clara, CA, USA) and the DNA was quantified using a Quant-iT Picogreen dsDNA HS Assay kit (Invitrogen, CA, USA) and the KAPA SYBR FAST qPCR kit (KAPA Biosystems, Woburn, MA, USA). Equimolar amounts of each library were pooled at 10 nM for sequencing, which was carried out on the high-throughput Illumina HiSeq 2500 platform (Illumina, San Diego, CA, USA) at the Genome Analysis Center of the National Instrumentation Center for Environmental Management, Seoul, South Korea in Rapid Paired End mode (250 cycles).

Data analysis and primer design

NGS generated approximately 42 and 21 Gb of DNA sequence data from everyone. All paired-end sequences were evaluated using PEAR v.0.9.6 (Zhang et al., 2014) to obtain a single read. De novo assembly was performed using CLC Genomics Workbench v.10.0.0.1 (CLCBio, Cambridge, MA, USA). Singleton reads that were not assembled were used for microsatellite identification in the case of tandem repeats of 2–4 bp with a minimum of four repeats. Primers targeting the flanking regions of candidate microsatellite loci were designed using Primer 3 (Rozen and Skaletsky, 2000).

Microsatellite validation and characterization

A total of 179 candidate microsatellite loci were selected for initial screening of polymorphisms in three individual yellow-throated martens. Forward primers were tagged at the 5′ end with either 6-carboxyfluorescein (6-FAM)-labelled M13 (5′-GGATAACAATTTCACACAGG-3′) or VIC-labelled Hill (5′-TGACCGGCAGCAAAATTG-3′). For this screen, simplex PCR reactions were carried out in a 20-μL reaction mixture containing 10× PCR buffer, 2.5 mM MgCl2, 100 μM each dNTP, 0.04 μM forward primer tagged with M13 or Hill at their 5’ ends, 0.2 μM reverse primer, 0.2 μM each fluorescent dye, 1 U i-start Taq DNA polymerase, and ~20 ng genomic DNA. The thermal cycling profile was as follows: 95°C for 5 min; 10 cycles of 95°C for 1 min, 60°C to 51°C for 1 min (decreasing by 1°C per cycle), and 72°C for 1 min; and 72°C for 5 min. The annealing temperature for the last 25 cycles was 50°C with denaturation. All primer sets were genotyped using GeneScan-LIZ500 (Applied Biosystems, Foster City, CA, USA) as a size standard and analyzed with Generous Pro v.8.1.9 (Biomatters, Auckland, New Zealand; Kearse et al., 2012). When necessary, PCR products were sequenced to confirm the repeat motif. Direct sequencing was performed using the Big Dye Terminator v.3.1 Cycle sequencing kit (Applied Biosystems) and ABI 3730xl DNA Analyzer (Applied Biosystems). Sequences were analyzed for the presence of repeat motifs and/or primer site mutations using Geneious Pro v.8.1.9.

Fragment analysis and population genetics

After preliminary screening, 28 individuals were genotyped for the candidate loci using fluorescently labeled forward primers, which were connected to one of the 5′ universal primer sequence tails (6-FAM: M13, 5′-GGATAACAATTTCACACAGG-3′, VIC: Hill, 5′-TGACCGGCAGCAAAATTG-3′; NED: T3, 5′-AATTAACCCTCACTAAAGGG-3′, or PET: Neomycin, 5′-AGGTGAGATGACAGGAGATC-3′; Applied Biosystems). We designed four multiplex panels for 33 microsatellite loci. PCR amplification was performed using the Multiplex PCR Master Mix (Qiagen) in a 50-μL reaction volume containing 25 μL Multiplex PCR Master Mix (2×) (including HotStarTaq Plus DNA Polymerase and Multiplex PCR Buffer with 3 mM MgCl2), 0.05–0.4 mM primer (Table 1), ~20 ng genomic DNA, and 19 μL RNase-free water. Touchdown PCR parameters were as follows: 95°C for 15 min; 10 cycles of 95°C for 30 s, 60°C for 90 s (decreasing by 1°C per cycle), and 72°C for 60 s; 25 cycles of 95°C for 30 s, 55°C for 90 s, and 72°C for 60 s; and 60°C for 30 min. Each panel was run on an ABI 3730xl DNA Analyzer and sized with GeneScan-LIZ500.

Locus Primer sequence (5′-3′) Fluorophore Size range Repeat motif Ta (°C) Gen Bank accession no.
PCR multiplex set A          
MF305 F: TTTGTGCTCTCTCACTCTCTGA 6-FAM 211–227 (AAAT)n 60–50 MG254740
  R: CATATGGCAAAACAATCAAATG          
MF304 F: AAAAAGAATCAAGCTGGGC VIC 169–181 (AAAT)n 60–50 MG254739
  R: ATCAAACTCTTTTCATTCAAGTACA          
MF380 F: TTCACCTTAATGCTTCCCTTTA VIC 193–213 (TATG)n 60–50 MG254749
  R: TTTATGGTAGCTACACTTGGGG          
MF385 F: AGTAACCCAGCATACCTCAAAA VIC 264–280 (GAAA)n
…(AAG)n
60–50 MG254750
  R: TGTCTCATGTAAGCTGAATTGG        
MF360 F: CTGTATTTCCCACAGTCTCCAT NED 260–306 (AGAA)n(AG)n 60–50 MG254748
  R: TCATCTTCCATTAGCTGGACTT        
MF392 F: ATGCCAGCATCTAGAAGAGTGT NED 189–197 (TGGA)n 60–50 MG254753
  R: ATCCATCATCCATCCATTTATC          
MF337 F: GGGAAAGAAAGAGGTAGGAAAA PET 183–191 (AATA)n 60–50 MG254744
  R: CAGCACTCTGAGCTTCTAGATTT          
MF326 F: TCTTGACCCTGTGAAATCTTCT PET 231–239 (AAAG)n 60–50 MG254741
  R: CCATGTCTGTCTCTGTCTGTCT          
MF389 F: CCAAGTTCCTCTTTGATGAGTC PET 286–314 (GGAA)n 60–50 MG254752
  R: ATGGAAACAGTTGCTAATTTGG          
PCR multiplex set B          
MF341 F: TGTGTAAGACTGATGAATCCCA 6-FAM 176–192 (ATAA)n 60–50 MG254746
  R: CTCTTGAACATCCCCACATATT          
MF334 F: GAAACCAAAAGGTGTTTCTTGA 6-FAM 200–212 (AAAC)n 60–50 MG254743
  R: ATCCATTGGGTCTGTAGTGATG          
MF339 F: AGTCTGCTTATCCTTCTCCCTC 6-FAM 230–250 (AAGA)n 60–50 MG254745
  R: ATGCGAACTATTTGGATAGGAA          
MF394 F: TATTTTGGCAGAAACTCAAAGG VIC 229–253 (GAAG)n 60–50 MG254755
  R: CAGTATGCATCCCTAACCAATC          
MF303 F: TTCAGTGGGTTAAATATCTGCC VIC 289–301 (AAAT)n 60–50 MG254738
  R: AAGAGTCACAGGCTCTATCGAA          
MF388 F: ACAGCATGTGAAGACATTGAAC NED 189–213 (GGAA)n 60–50 MG254751
  R: CCCCTTCTTTCTCTTGTCTTTC          
MF393* F: ACAATGCATATGACTGACAGGA NED 257–304 (GAAG)n(AG)n…
(AGAA)n
60–50 MG254754
  R: TCCAGTTTTTCCAGTACCATTC        
MF327 F: TCTAGAAAACAAAAGTCCAGCC PET 230–270 (AAAG)n 60–50 MG254742
  R: TTGGGGTTTTACTGTTTTATGG          
MF358 F: TAAACGGTAAGACCAGAAGGAA PET 312–358 (AGAA)n 60–50 MG254747
  R: TGGAGGTTTATGGATTCAGTTC          
PCR multiplex set C          
MF227 F: CAAAAATTGAAGAGAACCTCCTT 6-FAM 229–232 (AAG)n 60–50 MG254726
  R: GTTTTCCTTACCACTGGCAATA          
MF237 F: CTTGCTAAGTAGACATTTGGGG 6-FAM 268–283 (AAC)n 60–50 MG254729
  R: GAAAGCAAGCTTCAGAGATTGT          
MF264 F: AGGGAACAAGCTTCCAGTATTT VIC 211–223 (AGG)n 60–50 MG254737
  R: CCATGTTACCCCTTCTAACTCA          
MF233 F: CATATAATAACTGGGGTGCCTG VIC 277–286 (AAC)n 60–50 MG254727
  R: CCATTGCAAATAGTTACTTCCC          
MF241 F: AAACACTAAACAAACCAGACCC VIC 296–314 (AAC)n 60–50 MG254732
  R: TCCTTTTCCAACCAACTTCTTA     …(AT)n    
MF259* F: ACAGTCTGAGAAAAGGACTCCA NED 183–210 (AG)n(AGA)n 60–50 MG254736
  R: CCCTTTTGGTAATAGGAAGGAC          
MF239 F: GGTGAGTGCTTTGAATTGTGTA NED 291–303 (AAC)n 60–50 MG254731
  R: AGTAAAGGATGGTTTTCACTGG          
PCR multiplex set D          
MF238 F: GGGAATTGAGTATAAAGAGGAAGA 6-FAM 186–198 (AAC)n 60–50 MG254730
  R: ACCGTTGATCTTCTAAGGTTGA          
MF225 F: TGGTGAGGTACGTGCTATAGTG 6-FAM 251–281 (AAG)n 60–50 MG254725
  R: GGGTACTTTGCTGGACATAGAA          
MF258 F: CCCTGAATACACTAAAAGCCAA 6-FAM 300–312 (AGA)n 60–50 MG254735
  R: CTAAGCCTGAGAGCTGTGAGTT          
MF242 F: CATACTTTTGGAGAAAGGCAAC VIC 186–192 (AAC)n 60–50 MG254733
  R: CCCACTATTGTCTTTTGTGCTT          
MF243 F: ATCTGCAAAACAACATGAACTG VIC 279–293 (AAC)n…(CT)n
TTTT(CA)n
60–50 MG254734
  R: TTTCCTTGGCTTAATTCTTTGA        
MF236 F: TGTGCTAGGATTCCTTTCATTC NED 210–222 (AAC)n 60–50 MG254728
  R: TAGGACCATCTAGCTCCACAGT          
MF224 F: TCATATAAATTGGTTAAGCGGC NED 291–306 (AAG)n 60–50 MG254724
  R: TAACTACCCATAGCTTGCCATT          
MF223 F: CCCACCTTGCAAAATAAAATAA PET 200–218 (AAG)n 60–50 MG254723
  R: TGTCTCATGTAAGCTGAATTGG          

Table 1: Characteristics of 33 newly developed microsatellite loci in M. flavigula in the four PCR multiplexes

Allele sizes were verified and scored using Geneious Pro v.8.1.9. The occurrence of null alleles, large allele dropout, and stutters interfering with scoring accuracy was evaluated for each microsatellite locus using Micro-Checker v.2.2.3 (Van Oosterhout et al., 2004). Gene pop v.4.2 on the web (Rousset, 2008) was used to detect deviation from Hardy-Weinberg equilibrium (HWE) at each locus and linkage disequilibrium between pairs of loci. To estimate microsatellite variation, the number of alleles (NA), polymorphism information content (PIC), fixation index (FIS), observed heterozygosity (HO), and expected heterozygosity (HE) were calculated for a population using FSTAT (Goudet, 1995) and the Excel Microsatellite Toolkit (Park, 2001).

Results and Discussion

A total of 887 contigs (di: 451, tri: 156, tetra: 280) containing candidate microsatellite motifs were obtained using bioinformatics tools. Of these, 179 primer pairs consisting of tri- and tetranucleotide motifs were randomly evaluated in simplex PCR reactions using samples from the three individuals, yielding PCR products of the expected size from 73 primer pairs; 45 polymorphic and 28 monomorphic loci were excluded from further characterization. We ultimately selected a set of 33 novel microsatellite loci that were used to generate four multiplex panels (Table 1) based on the degree of polymorphism. The strength and consistency of the loci were verified by comparing the results from the initial and multiplexing reactions. Detailed information on the loci is provided in Table 1.

The 33 polymorphic microsatellites were characterized (Table 2). The estimated fragment size at each locus was between 169 and 358 bp, including the tailed primer sequences. The average number of alleles was 4.3, ranging from 2 (MF337, MF326, MF264, MF242, MF233, and MF227) to 9 (MF327 and MF259). PIC per locus ranged from 0.164 to 0.841, with an average value of 0.541. HO ranged from 0.143 (MF233) to 0.800 (MF339), and HE ranged from 0.183 (MF233) to 0.871 (MF327). The inbreeding coefficient (FIS) ranged from −0.200 to 0.706. Significant deviations from HWE were detected for nine of the 33 loci (MF380, MFR360, MF334, MF303, MF243, MF241, MF238, MF236, and MF224); six of these (MF360, MF334, MF327, MF303, MF259, and MF241) exhibited significant homozygote excess, which was likely due to null alleles or stutter issues, as suggested by the Micro-Checker results. Alternatively, it may reflect the Wahlund effect (Wahlund 1928) or non-random mating since the samples collected in this study were from patchy regions. There were 39 cases of linkage disequilibrium between loci in 528 paired comparisons.

No. Locus N NA FIS HO HE PIC pHWD
1 MF394 35 5 0.009 0.714 0.720 0.663 0.724
2 MF393 35 8 0.052 0.714 0.753 0.715 0.172
3 MF392 35 3 0.336 0.257 0.386 0.326 0.063
4 MF389 35 6 −0.053 0.735 0.699 0.639 0.571
5 MF388 35 5 −0.082 0.743 0.687 0.626 0.715
6 MF385 35 4 −0.178 0.743 0.632 0.579 0.490
7 MF380 35 4 0.183 0.600 0.732 0.670 0.033
8 MF360 33 8 0.268 0.636 0.865 0.835 0.021
9 MF358 33 8 0.052 0.727 0.766 0.728 0.183
10 MF341 35 4 0.222 0.457 0.586 0.505 0.336
11 MF339 35 6 −0.028 0.800 0.779 0.732 0.614
12 MF337 35 2 0.081 0.457 0.497 0.370 0.736
13 MF334 35 4 0.631 0.257 0.690 0.618 0.000
14 MF327 32 9 0.177 0.719 0.871 0.841 0.232
15 MF326 35 2 −0.086 0.543 0.501 0.372 0.734
16 MF305 35 3 0.219 0.486 0.620 0.539 0.071

Table 2: Estimates of genetic diversity in M. flavigula in South Korea based on 33 microsatellite loci

We examined cross-amplification of M. flavigula microsatellite markers to determine their transferability to two species of Mustelidae, i.e., Meles meles and Mustela sibirica. Not all loci were transferable, with a greater number of alleles and loci recovered in more closely related species: for example, 19 loci were successfully amplified in M. sibirica as compared to 10 in M. meles (Table 3), with eight (MF394, MF388, MF341, MF337, MF305, MF264, MF236, and MF233) amplified in both species. MF394 exhibited greater polymorphism in M. sibirica (NA=9) and M. meles (NA=7) than in M. flavigula (NA=5). These results indicate that the polymorphic marker panel developed for M. flavigula can be useful for investigating population genetics and genetic diversity in other Mustelidae species.

Locus Mustela sibirica (n=12) Meles meles (n=8)
MF394 9 [280–314] 7 [306–334]
       
MF393 6 [326–374]
MF392  
MF389  
MF388 2 [188, 220] 1 [174]
MF385  
MF380 1 [204]
MF360  
MF358 3 [216–328]
MF341 1 [163] 2 [158–162]
MF339   6 [210–250]
MF337 1 [186] 2 [183–187]
MF334   1 [204]
MF327  
MF326  
MF305 4 [205–225] 1 [194]
MF304  
MF303 1 [260]
MF264 1 [215] 1 [230]
MF259 2 [186–192]
MF258  
MF243 1 [281]
MF242  
MF241 1 [300]

Table 3: Cross-species transferability of 33 microsatellite loci identified in M. flavigula to two other Mustelidae

Conclusion

In summary, we report 33 novel microsatellite markers in M. flavigula identified by NGS and demonstrate their transferability to two other Mustelidae species. These results provide a non-invasive analytical tool for ex situ conservation and ecological monitoring of this important predator.

Acknowledgments

Genetic samples for this study were collected under permits obtained from the Ministry of Environment, Republic of Korea. This work was supported by grants from the National Institute of Biological Resources (NIBR201703102) and National Institute of Ecology (NIE-Fundamental Research-2017-07) funded by the Ministry of Environment, Republic of Korea.

About the Authors

Corresponding Author

Junghwa An

National Institute of Biological Resources, 42 Hwangyeong-ro, Seo-gu, Incheon 22689, Republic of Korea

Email:
safety@korea.kr

References

  • Buschiazzo E, Gemmell NJ (2006). The rise, fall and renaissance of microsatellites in eukaryotic genomes. BioEssays. 28: 1040-1050. https://doi.org/10.1002/bies.20470
  • Chutipong W, Duckworth JW, Timmins RJ, Choudhury A, et al. (2016). Martes flavigula. The IUCN Red List of Threatened Species. 2016: e.T41649A45212973.
  • Corbet GB (1978). The Mammals of the Palaearctic Region: A Taxonomic Review. British Museum (Natural History) and Cornell University Press, London, U.K., and Ithaca, USA. 314.
  • Corbet GB, Hill JE (1992). The Mammals of the Indomalayan Region: a Systematic Review. Natural History Museum Publications and Oxford University Press, Oxford, U.K. 488.
  • Chunzhu X, Honghai Z, Jianzhang M (2013). The complete mitochondrial genome of Martes flavigula. Mitochondrial DNA. 24: 240-242. https://doi.org/10.3109/19401736.2012.752479
  • Goudet J (2001). FSTAT: A Program to Estimate and Test Gene Diversities and Fixation Indices, Version 2.9.3 Lausanne University: Lausanne, Switzerland.
  • Hosoda T, Sato JJ, Lin LK, Chen YJ, et al. (2011). Phylogenetic history of mustelid fauna in Taiwan inferred from mitochondrial genetic loci. Can. J. Zool. 89: 559-569. https://doi.org/10.1139/z11-029
  • Kearse M, Moir R, Wilson A, Stones-Havas S, et al. (2012). Geneious basic: an integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics. 28: 1647-1649. https://doi.org/10.1093/bioinformatics/bts199
  • Koepfli KP, Deere KA, Slater GJ, Begg C, et al. (2008). Multigene phylogeny of the Mustelidae: resolving relationships, tempo and biogeographic history of a mammalian adaptive radiation. BMC Biol. 6: 10. https://doi.org/10.1186/1741-7007-6-10
  • Kuem HJ, Hwang UW (2016). Complete mitochondrial genome of Korean yellow-throated marten, Martes flavigula (Carnivora, Mustelidae). Mitochondrial DNA A DNA Mapp. Seq. Anal. 27: 1785-1786. https://doi.org/10.3109/19401736.2014.963812
  • Goldstein DB, Schlotterer C (1999). Microsatellites. Evolution and application. Oxford University Press, New York.
  • Guichoux E, Lagache L, Wagner S, Chaumeil P, et al. (2011). Current trends in microsatellite genotyping. Mol. Ecol. Resour. 11: 591-611. https://doi.org/10.1111/j.1755-0998.2011.03014.x
  • Park SDE (2001). The Excel microsatellite toolkit. Trypan tolerance in west African cattle and the population genetic effects of selection. Ph. D thesis, University of Dublin, Dublin, Ireland.
  • Peakall R, Smouse PE (2006). GenAlEx 6: genetic analysis in excel. Population genetic of software for teaching and research. Mol. Ecol Notes. 6: 288-295.https://doi.org/10.1111/j.1471-8286.2005.01155.x
  • Rousset F (2008). GENEPOP’007: a complete re-implementation of the gene pop software for Windows and Linux. Mol. Ecol. Resour. 8: 103-106. https://doi.org/10.1111/j.1471-8286.2007.01931.x
  • Sato JJ, Hosoda T, Wolsan M, Tsuchiya K, et al. (2003). Phylogenetic relationships and divergence times among mustelids (Mammalia: Carnivora) based on nucleotide sequences of the nuclear interphotoreceptor retinoid binding protein and mitochondrial cytochrome b genes.Zool. Sci. 20: 243-264.https://doi.org/10.2108/zsj.20.243
  • Schuelke M (2000). An economic method for the fluorescent labelling of PCR fragments. Nat. Biotechnol. 18: 233-234. https://doi.org/10.1038/72708
  • Van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004). MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol. Ecol. Notes. 4: 535-538. https://doi.org/10.1111/j.1471-8286.2004.00684.x
  • Wahlund S (1928). Composition of populations from the perspective of the theory of heredity. Hereditas. 11: 65-105. https://doi.org/10.1111/j.1601-5223.1928.tb02483.x
  • Woo DG, Choi TY, Kwon HS, Lee SG, et al. (2015). The food habits and habitat use of yellow-throated martens (Martes flavigula) by snow tracking in Korean temperate forest during the winter. J. Environ. Impact Assess. 24: 532-548. https://doi.org/10.14249/eia.2015.24.5.532
  • Zhang J, Kobert K, Flouri T, Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-end reAd mergeR. Bioinformatics 30: 614-620. https://doi.org/10.1093/bioinformatics/btt593

Keywords:
Download:
Full PDF