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Supplemental informationMitochondrial genome of a 22,000-year-old giant panda from southern China reveals a new panda lineageAlbert Min-Shan Ko, Yingqi Zhang, Melinda A. Yang, Yibo Hu, Peng Cao, Xiaotian Feng, Lizhao Zhang, Fuwen Wei and Qiaomei FuSupplemental DataFigure S1. Authenticity of the Cizhutuo mtDNA and select analyses comparing to present-day panda mtDNA. Related to Figure 1.A. Length distribution of mtDNA fragments of the Cizhutuo panda, B. Pattern of substitutions along sequences; Frequency of C > T (red), G > A (black) and other differences from the mtDNA reference sequence (gray) was shown as a function of the position at 5’ and 3’ ends of the sequences. Increased frequencies of C > T substitutions close to the fragment ends indicated the presence of cytosine deamination in the single strand library, C. General agreement between the consensus call of mtDNA sequences for the Cizhutuo panda (upper plot) and a present-day giant panda from Chengdu, Sichuan province, China (lower plot), D. Bayesian Skyline Plot of population size changes in giant pandas within past 20 ka (Neτ is the product of female effective population size and the generation length in years), E. Pairwise nucleotide differences within present-day pandas (blue, green, black), and between present-day pandas and the Cizhutuo panda (red). There are more genetic differences between the Cizhutuo panda and present-day pandas than within present-day pandas, F. Boxplot comparisons of Ka/Ks ratios between the Cizhutuo and present-day pandas (red) and within present-day pandas (blue) for each set of complexes in the mtDNA coding region. Black circles indicate outliers.Table S1. Summary of select phylogenetic results for different mtDNA partitions and list of mitochondrial amino acid changes distinguishing between the Cizhutuo and present-day pandas. Related to Figure 1.(A) Time to the Most Recent Common Ancestor (TMRCA) for giant pandas and mutation rate estimates for different mtDNA partitionsmtDNA PartitionTMRCA (Units in thousands years, ka)μ / Site / Year (Units in 10-8)Cizhutuo + Present-dayPresent-day OnlyMean95% HPDMean95% HPDMean95% HPDComplete mtDNA183(227 – 144)72(94 – 55)2.22(1.83– 2.60)Coding region204(258 – 151)74(99 – 53)1.94(1.54 – 2.34)1st-2nd Codon204(295 – 124)95(145 – 48)1.06(0.74 – 1.37)3rd Codon171(229 – 122)65(92 – 43)5.29(4.13 – 6.53)rRNA113(205 – 37)50(96 – 14)1.16(0.69 – 1.69)(B) 64 diagnostic sites in the mtDNA coding region that differentiate the 49 present-day pandas from the Cizhutuo pandaPositionRespiratoryComplexGeneAmino acid changeChange*Present-day PandaCizhutuo5863IND2GTA (V) → ATA (Met)Non-SynGA5935IND2TTC (F) → CTC (L)Non-SynTC5978IND2ACA (T) → ATA (Met)Non-SynCT10942IND3GTA (V) → GCA (A)Non-SynTC11181IND3GCC (A) → ACC (T)Non-SynGA11265IND4LGTG (V) → GCG (A)Non-SynTC11633IND4ACC (T) → ATC (I)Non-SynCT11711IND4ACA (T) → ATA (Met)Non-SynCT11845IND4ATT (I) → GTT (V)Non-SynAG13143IND5TTC (F) → TCC (S)Non-SynTC13199IND5GCA (A) → ACA (T)Non-SynGA13256IND5ACA (T) → GCA (A)Non-SynAG13985IND5ACA (T) → GCA (A)Non-SynAG14535IND5AAC (N) → AGC (S)Non-SynAG14934IND5TTC (F) → TCC (S)Non-SynTC16180IIICytbATC (I) → GTC (V)Non-SynAG16235IIICytbGTC (V) → GCC (A)Non-SynTC16432IIICytbACT (T) → GCT (A)Non-SynAG4460IND1TCT (S) → TCC (S)SynTC4892IND1TTT (F) → TTC (F)SynTC4976IND1CAC (H) → CAT (H)SynCT5493IND2ATG (Met) → ATA (Met)SynGA5607IND2TCA (S) → TCG (S)SynAG5634IND2GTT (V) → GTC (V)SynTC5679IND2TGA (W) → TGG (W)SynAG6845IVCOIGCT (A) → GCC (A)SynTC7091IVCOIGTA (V) → GTC (V)SynAC7454IVCOICCT (P) → CCC (P)SynTC7670IVCOITTC (F) → TTT (F)SynCT7991IVCOICAG (Q) → CAA (Q)SynGA8195IVCOICAC (H) → CAT (H)SynCT8868IVCOIIGTG (V) → GTA (V)SynGA9039IVCOIICTG (L) → CTA (L)SynGA9045IVCOIITAC (Y) → TAT (Y)SynCT9371VATP6GTT (V) → GTC (V)SynTC9386VATP6TTC (F) → TTT (F)SynCT9650VATP6GTT (V) → GTC (V)SynTC9755VATP6CTG (L) → CTA (L)SynGA10462IVCOIIICAT (H) → CAC (H)SynTC10678IVCOIIIAAC (N) → AAT (N)SynCT11333IND4LTTA (L) → CTA (L)SynTC11622IND4ATT (I) → ATC (I)SynTC11649IND4ATC (I) → ATT (I)SynCT11946IND4ATT (I) → ATC (I)SynTC12273IND4GGT (G) → GGC (G)SynTC12297IND4CTC (L) → CTT (L)SynCT12624IND4TGA (W) → TGG (W)SynAG12636IND4GGC (G) → GGA (G)SynCA12714IND4TCC (S) → TCT (S)SynCT12867IND4CAT (H) → CAC (H)SynTC12894IND4CTT (L) → CTC (L)SynTC13483IND5TAT (Y) → TAC (Y)SynTC13579IND5TTT (F) → TTC (F)SynTC13645IND5TAC (Y) → TAT (Y)SynCT13867IND5CAC (H) → CAT (H)SynCT14176IND5AAC (N) → AAT (N)SynCT14440IND5CCC (P) → CCT (P)SynCT14554IND5GTC (V) → GTT (V)SynCT14680IND5ACG (T) → ACA (T)SynGA14701IND5CTA (L) → CTG (L)SynAG15606IIICytbAAC (N) → AAT (N)SynCT15867IIICytbTGG (W) → TGA (W)SynGA16284IIICytbGAC (D) → GAT (D)SynCT16522IIICytbCTA (L) → TTA (L)SynCT*Non-Syn, non-synonymous; Syn, synonymous; all sites are biallelic.Supplemental Experimental Procedures.1. DNA extraction and enrichment. Permission to use the Cizhutuo specimen was granted by the Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences. The extraction and library preparation steps prior to amplification were carried out in the specialized ancient DNA clean-room facilities at the same institute. The petrous bone of the giant panda skull was irradiated on the sampling area. Using a dental drill, 163.7 mg of bone powder was collected from petrous bone and used in DNA extraction following the protocol described by Dabney et al ADDIN EN.CITE <EndNote><Cite><Author>Dabney</Author><Year>2013</Year><RecNum>14</RecNum><Prefix>S</Prefix><DisplayText>[S1]</DisplayText><record><rec-number>14</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507533040">14</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Dabney, J.</author><author>Knapp, M.</author><author>Glocke, I.</author><author>Gansauge, M. T.</author><author>Weihmann, A.</author><author>Nickel, B.</author><author>Valdiosera, C.</author><author>Garcia, N.</author><author>Paabo, S.</author><author>Arsuaga, J. L.</author><author>Meyer, M.</author></authors></contributors><auth-address>Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, 04103 Leipzig, Germany.</auth-address><titles><title>Complete mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from ultrashort DNA fragments</title><secondary-title>Proc Natl Acad Sci U S A</secondary-title></titles><periodical><full-title>Proc Natl Acad Sci U S A</full-title><abbr-1>Proceedings of the National Academy of Sciences of the United States of America</abbr-1></periodical><pages>15758-63</pages><volume>110</volume><number>39</number><edition>2013/09/11</edition><keywords><keyword>Animals</keyword><keyword>Base Sequence</keyword><keyword>Caves</keyword><keyword>DNA/*genetics/isolation &amp; purification</keyword><keyword>Genome, Mitochondrial/*genetics</keyword><keyword>Molecular Sequence Data</keyword><keyword>Phylogeny</keyword><keyword>Time Factors</keyword><keyword>Ursidae/*genetics</keyword></keywords><dates><year>2013</year><pub-dates><date>Sep 24</date></pub-dates></dates><isbn>1091-6490 (Electronic)&#xD;0027-8424 (Linking)</isbn><accession-num>24019490</accession-num><urls><related-urls><url>;[S1]. 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ADDIN EN.CITE.DATA [S2, S3]. The resulting library was PCR amplified for 35 cycles once using AccuPrime Pfx DNA polymerase (Life Technologies) ADDIN EN.CITE <EndNote><Cite><Author>Dabney</Author><Year>2012</Year><RecNum>2</RecNum><Prefix>S</Prefix><DisplayText>[S2]</DisplayText><record><rec-number>2</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507529540">2</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Dabney, J.</author><author>Meyer, M.</author></authors></contributors><auth-address>Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany. jesse_dabney@eva.mpg.de</auth-address><titles><title>Length and GC-biases during sequencing library amplification: a comparison of various polymerase-buffer systems with ancient and modern DNA sequencing libraries</title><secondary-title>Biotechniques</secondary-title><alt-title>BioTechniques</alt-title></titles><periodical><full-title>Biotechniques</full-title><abbr-1>BioTechniques</abbr-1></periodical><alt-periodical><full-title>Biotechniques</full-title><abbr-1>BioTechniques</abbr-1></alt-periodical><pages>87-94</pages><volume>52</volume><number>2</number><edition>2012/02/09</edition><dates><year>2012</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1940-9818 (Electronic)&#xD;0736-6205 (Linking)</isbn><accession-num>22313406</accession-num><work-type>Research Support, Non-U.S. Gov&apos;t</work-type><urls><related-urls><url>;[S2]. Sample-specific indexes were introduced into the P5 and P7 adaptors during the library amplification step to identify the contaminating sequences that derived from present-day DNA contamination ADDIN EN.CITE <EndNote><Cite><Author>Kircher</Author><Year>2012</Year><RecNum>5</RecNum><Prefix>S</Prefix><DisplayText>[S4]</DisplayText><record><rec-number>5</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507529540">5</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Kircher, M.</author><author>Sawyer, S.</author><author>Meyer, M.</author></authors></contributors><auth-address>Max Planck Institute for Evolutionary Anthropology, Department of Evolutionary Genetics, 04103 Leipzig, Germany. martin.kircher@eva.mpg.de</auth-address><titles><title>Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform</title><secondary-title>Nucleic Acids Res</secondary-title><alt-title>Nucleic acids research</alt-title></titles><periodical><full-title>Nucleic Acids Res</full-title></periodical><alt-periodical><full-title>Nucleic Acids Res</full-title><abbr-1>Nucleic acids research</abbr-1></alt-periodical><pages>e3</pages><volume>40</volume><number>1</number><edition>2011/10/25</edition><keywords><keyword>Gene Library</keyword><keyword>High-Throughput Nucleotide Sequencing/*methods</keyword><keyword>Reproducibility of Results</keyword><keyword>Sequence Analysis, DNA/*methods</keyword></keywords><dates><year>2012</year><pub-dates><date>Jan</date></pub-dates></dates><isbn>1362-4962 (Electronic)&#xD;0305-1048 (Linking)</isbn><accession-num>22021376</accession-num><work-type>Evaluation Studies&#xD;Research Support, Non-U.S. Gov&apos;t</work-type><urls><related-urls><url>;[S4]. After preparing the Cizhutuo library, its concentration was determined to be 325.1 ng/ul using a NanoDrop 2000 spectrophotometer. To enrich the library for giant panda mtDNA and subsequently capture the complete mitochondrial genome, we generated biotinylated enrichment probes, for which a detailed description of the methodology can be found in?SI 3.2.3 of Fu et?al PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5GdTwvQXV0aG9yPjxZZWFyPjIwMTM8L1llYXI+PFJlY051

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ADDIN EN.CITE.DATA [S5]. The giant panda mtDNA probes were designed using the giant panda mtDNA reference (GenBank: EF212882), with a tiling density of 1 base and length of 60 bases, comprising a unique 52-base sequence and a universal linker sequence of 8 bases (5’-CACTGCGG-3’). To exclude the repetitive sequences, those probes containing 2 to 8-mer sequences that spanned 24 bases or more were removed. The resulting 60-base probes were printed onto a custom-designed one million-feature microarray (Agilent Technologies). Sequence submission: The complete mtDNA genome for the Cizhutuo giant panda (MH102403) is deposited in GenBank. 2. Illumina sequencing and analysis. High-throughput DNA sequencing for the enriched library pools was carried out on a Miseq platform using 2 × 76 + 7 cycles, per manufacturer’s instructions for multiplex sequencing (MiSeq Reagent Kit v3, 150-cycles). An indexed control library of ?X 174 was spiked into the library prior to sequencing, contributing to 0.5% of the sequences. The program leeHom () ADDIN EN.CITE <EndNote><Cite><Author>Renaud</Author><Year>2014</Year><RecNum>8</RecNum><Prefix>S</Prefix><DisplayText>[S6]</DisplayText><record><rec-number>8</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507529540">8</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Renaud, G.</author><author>Stenzel, U.</author><author>Kelso, J.</author></authors></contributors><auth-address>Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.&#xD;Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany kelso@eva.mpg.de.</auth-address><titles><title>leeHom: adaptor trimming and merging for Illumina sequencing reads</title><secondary-title>Nucleic Acids Res</secondary-title></titles><periodical><full-title>Nucleic Acids Res</full-title></periodical><pages>e141</pages><volume>42</volume><number>18</number><keywords><keyword>*Algorithms</keyword><keyword>Bayes Theorem</keyword><keyword>Likelihood Functions</keyword><keyword>Sequence Analysis, DNA/*methods</keyword><keyword>Software</keyword></keywords><dates><year>2014</year><pub-dates><date>Oct</date></pub-dates></dates><isbn>1362-4962 (Electronic)&#xD;0305-1048 (Linking)</isbn><accession-num>25100869</accession-num><urls><related-urls><url>;[S6] was used to merge overlapping mate-pairs with the parameter “--ancientdna” and to trim adapter sequences. After merging, the sequences were assigned to the library by matching the index sequences using deML () ADDIN EN.CITE <EndNote><Cite><Author>Renaud</Author><Year>2015</Year><RecNum>9</RecNum><Prefix>S</Prefix><DisplayText>[S7]</DisplayText><record><rec-number>9</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507529540">9</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Renaud, G.</author><author>Stenzel, U.</author><author>Maricic, T.</author><author>Wiebe, V.</author><author>Kelso, J.</author></authors></contributors><auth-address>Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony D-04103, Germany.</auth-address><titles><title>deML: robust demultiplexing of Illumina sequences using a likelihood-based approach</title><secondary-title>Bioinformatics</secondary-title></titles><periodical><full-title>Bioinformatics</full-title></periodical><pages>770-2</pages><volume>31</volume><number>5</number><keywords><keyword>*Algorithms</keyword><keyword>Humans</keyword><keyword>Likelihood Functions</keyword><keyword>Sequence Analysis, DNA/*instrumentation/*methods</keyword><keyword>*Software</keyword></keywords><dates><year>2015</year><pub-dates><date>Mar 01</date></pub-dates></dates><isbn>1367-4811 (Electronic)&#xD;1367-4803 (Linking)</isbn><accession-num>25359895</accession-num><urls><related-urls><url>;[S7] with default parameters. All non-matching sequences were discarded. All fragments were aligned to the giant panda mtDNA reference (GenBank: EF212882) using bwa (version: 0.5.10-evan.9-1-g44db244 ) ADDIN EN.CITE <EndNote><Cite><Author>Li</Author><Year>2009</Year><RecNum>6</RecNum><Prefix>S</Prefix><DisplayText>[S8]</DisplayText><record><rec-number>6</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1507529540">6</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Li, H.</author><author>Durbin, R.</author></authors></contributors><auth-address>Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK.</auth-address><titles><title>Fast and accurate short read alignment with Burrows-Wheeler transform</title><secondary-title>Bioinformatics</secondary-title></titles><periodical><full-title>Bioinformatics</full-title></periodical><pages>1754-60</pages><volume>25</volume><number>14</number><edition>2009/05/20</edition><keywords><keyword>*Algorithms</keyword><keyword>Genomics/*methods</keyword><keyword>Sequence Alignment/*methods</keyword><keyword>Sequence Analysis, DNA/methods</keyword><keyword>*Software</keyword></keywords><dates><year>2009</year><pub-dates><date>Jul 15</date></pub-dates></dates><isbn>1367-4811 (Electronic)&#xD;1367-4803 (Linking)</isbn><accession-num>19451168</accession-num><work-type>Research Support, Non-U.S. Gov&apos;t</work-type><urls><related-urls><url>;[S8] with parameters: –n 0.01 –o 2 –l 16500 to increase sensitivity. Sequences shorter than 30 base pairs were removed and duplicates were merged into one sequence using bam-rmdup (version: 0.6.3, ). The estimated mtDNA coverage of this giant panda library was 282-fold after duplicate removal.3. BEAST analyses. We used BEAST v1.8.2 ADDIN EN.CITE <EndNote><Cite><Author>Drummond</Author><Year>2012</Year><RecNum>49</RecNum><Prefix>S</Prefix><DisplayText>[S9]</DisplayText><record><rec-number>49</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1514982419">49</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Drummond, A. J.</author><author>Suchard, M. A.</author><author>Xie, D.</author><author>Rambaut, A.</author></authors></contributors><auth-address>Department of Computer Science, University of Auckland, Auckland, New Zealand. alexei@cs.auckland.ac.nz</auth-address><titles><title>Bayesian phylogenetics with BEAUti and the BEAST 1.7</title><secondary-title>Mol Biol Evol</secondary-title></titles><periodical><full-title>Mol Biol Evol</full-title></periodical><pages>1969-73</pages><volume>29</volume><number>8</number><edition>2012/03/01</edition><keywords><keyword>Animals</keyword><keyword>Base Sequence</keyword><keyword>Bayes Theorem</keyword><keyword>Computational Biology/*methods</keyword><keyword>DNA, Mitochondrial/genetics</keyword><keyword>Finches/genetics</keyword><keyword>Molecular Sequence Data</keyword><keyword>Phenotype</keyword><keyword>*Phylogeny</keyword><keyword>*Software</keyword><keyword>User-Computer Interface</keyword></keywords><dates><year>2012</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>1537-1719 (Electronic)&#xD;0737-4038 (Linking)</isbn><accession-num>22367748</accession-num><urls><related-urls><url>;[S9] to reconstruct the phylogeny of the family Ursidae (Figure 1B). 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ADDIN EN.CITE.DATA [S1, S11, S18, S19, S20, S21, S22] whose radiocarbon dates acted as calibration points. We produced a multiple genome alignment of the 170 complete mtDNA sequences using MUSCLE v3.8.31 ADDIN EN.CITE <EndNote><Cite><Author>Edgar</Author><Year>2004</Year><RecNum>108</RecNum><Prefix>S</Prefix><DisplayText>[S23]</DisplayText><record><rec-number>108</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1519457940">108</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Edgar, R. C.</author></authors></contributors><auth-address>bob@</auth-address><titles><title>MUSCLE: multiple sequence alignment with high accuracy and high throughput</title><secondary-title>Nucleic Acids Res</secondary-title></titles><periodical><full-title>Nucleic Acids Res</full-title></periodical><pages>1792-7</pages><volume>32</volume><number>5</number><edition>2004/03/23</edition><keywords><keyword>Algorithms</keyword><keyword>Amino Acid Motifs</keyword><keyword>Amino Acid Sequence</keyword><keyword>Internet</keyword><keyword>Molecular Sequence Data</keyword><keyword>Reproducibility of Results</keyword><keyword>Sequence Alignment/*methods</keyword><keyword>Sequence Analysis, Protein/*methods</keyword><keyword>*Software</keyword><keyword>Time Factors</keyword></keywords><dates><year>2004</year></dates><isbn>1362-4962 (Electronic)&#xD;0305-1048 (Linking)</isbn><accession-num>15034147</accession-num><urls><related-urls><url>;[S23] and determined the best-fit nucleotide substitution model to be GTR+Γ4+I under Bayesian Information Criterion using jModeltest v2.1.10 PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EYXJyaWJhPC9BdXRob3I+PFllYXI+MjAxMjwvWWVhcj48

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ADDIN EN.CITE.DATA [S24, S25].We next tested whether a strict or relaxed molecular clock was more suitable for our phylogenetic analysis. Using the likelihood ratio test in baseml v4.9f ADDIN EN.CITE <EndNote><Cite><Author>Yang</Author><Year>2007</Year><RecNum>51</RecNum><Prefix>S</Prefix><DisplayText>[S26]</DisplayText><record><rec-number>51</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1515030654">51</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Yang, Z.</author></authors></contributors><auth-address>Department of Biology, Galton Laboratory, University College London, London, UK. z.yang@ucl.ac.uk</auth-address><titles><title>PAML 4: phylogenetic analysis by maximum likelihood</title><secondary-title>Mol Biol Evol</secondary-title></titles><periodical><full-title>Mol Biol Evol</full-title></periodical><pages>1586-91</pages><volume>24</volume><number>8</number><edition>2007/05/08</edition><keywords><keyword>Animals</keyword><keyword>Computer Simulation</keyword><keyword>Genetic Variation</keyword><keyword>*Likelihood Functions</keyword><keyword>Models, Genetic</keyword><keyword>*Phylogeny</keyword><keyword>Selection, Genetic</keyword><keyword>Software</keyword><keyword>Species Specificity</keyword></keywords><dates><year>2007</year><pub-dates><date>Aug</date></pub-dates></dates><isbn>0737-4038 (Print)&#xD;0737-4038 (Linking)</isbn><accession-num>17483113</accession-num><urls><related-urls><url>;[S26], we showed that an assumption of a strict molecular clock could not be rejected for the Ursidae family (-2δL=83.1, P=0.17), so we used a strict clock for further analysis. We further tested molecular clock for giant pandas by comparing the strict and relaxed clock models in BEAST, and did not find strong support for using a relaxed clock; log Bayes Factor (BF)=1.4 < log BF=2 PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5LYXNzPC9BdXRob3I+PFllYXI+MTk5NTwvWWVhcj48UmVj

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ADDIN EN.CITE.DATA [S27]. Thus, we assumed a strict molecular clock, requiring a single mutation rate across the phylogeny.For the choice of tree prior, three models (constant size, Skyline piecewise-constant, and Skyline piecewise-linear) were tested. We used log marginal likelihoods estimated by Path-Sampling (PS) and Stepping-Stone (SS) methods ADDIN EN.CITE <EndNote><Cite><Author>Baele</Author><Year>2012</Year><RecNum>46</RecNum><Prefix>S</Prefix><DisplayText>[S28]</DisplayText><record><rec-number>46</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1514442198">46</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Baele, G.</author><author>Lemey, P.</author><author>Bedford, T.</author><author>Rambaut, A.</author><author>Suchard, M. A.</author><author>Alekseyenko, A. V.</author></authors></contributors><auth-address>Department of Microbiology and Immunology, KU Leuven, Leuven, Belgium. guy.baele@rega.kuleuven.be</auth-address><titles><title>Improving the accuracy of demographic and molecular clock model comparison while accommodating phylogenetic uncertainty</title><secondary-title>Mol Biol Evol</secondary-title></titles><periodical><full-title>Mol Biol Evol</full-title></periodical><pages>2157-67</pages><volume>29</volume><number>9</number><edition>2012/03/10</edition><keywords><keyword>Algorithms</keyword><keyword>Computer Simulation</keyword><keyword>DNA Viruses/genetics</keyword><keyword>*Evolution, Molecular</keyword><keyword>HIV Infections/epidemiology</keyword><keyword>HIV-1/classification/genetics</keyword><keyword>Humans</keyword><keyword>Likelihood Functions</keyword><keyword>Methicillin-Resistant Staphylococcus aureus/genetics</keyword><keyword>*Models, Genetic</keyword><keyword>Models, Statistical</keyword><keyword>*Phylogeny</keyword><keyword>Software</keyword></keywords><dates><year>2012</year><pub-dates><date>Sep</date></pub-dates></dates><isbn>1537-1719 (Electronic)&#xD;0737-4038 (Linking)</isbn><accession-num>22403239</accession-num><urls><related-urls><url>;[S28] to determine the best model. For each model, we ran a total of 200 million MCMC chains, sampling every 2×105 steps, and ensured that the effective sample size (ESS) values were greater than 300. The best model was the Skyline piecewise-constant (PS and SS values: -73431.6 and -73251.1) followed by Skyline piecewise-linear (-73440.7 and -73558.4) and constant size (-73510.4 and -73618.3). Thus, we used the Skyline piecewise-constant prior in subsequent phylogenetic analyses.Using tip-calibration ADDIN EN.CITE <EndNote><Cite><Author>Shapiro</Author><Year>2011</Year><RecNum>360</RecNum><Prefix>S</Prefix><DisplayText>[S29]</DisplayText><record><rec-number>360</rec-number><foreign-keys><key app="EN" db-id="9x05p2wtax5fvlerz2lp2dr9tapffvw5swaf">360</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Shapiro, B.</author><author>Ho, S. Y.</author><author>Drummond, A. J.</author><author>Suchard, M. A.</author><author>Pybus, O. G.</author><author>Rambaut, A.</author></authors></contributors><auth-address>Department of Biology, The Pennsylvania State University, PA, USA. beth.shapiro@psu.edu</auth-address><titles><title>A Bayesian phylogenetic method to estimate unknown sequence ages</title><secondary-title>Mol Biol Evol</secondary-title><alt-title>Molecular biology and evolution</alt-title></titles><periodical><full-title>Mol Biol Evol</full-title></periodical><alt-periodical><full-title>Molecular Biology and Evolution</full-title></alt-periodical><pages>879-87</pages><volume>28</volume><number>2</number><edition>2010/10/05</edition><keywords><keyword>Animals</keyword><keyword>Bayes Theorem</keyword><keyword>Bison/genetics</keyword><keyword>Computer Simulation</keyword><keyword>DNA, Mitochondrial/genetics</keyword><keyword>Dengue Virus/genetics</keyword><keyword>*Models, Genetic</keyword><keyword>*Phylogeny</keyword><keyword>Time</keyword></keywords><dates><year>2011</year><pub-dates><date>Feb</date></pub-dates></dates><isbn>1537-1719 (Electronic)&#xD;0737-4038 (Linking)</isbn><accession-num>20889726</accession-num><work-type>Research Support, N.I.H., Extramural&#xD;Research Support, U.S. Gov&apos;t, Non-P.H.S.</work-type><urls><related-urls><url>;[S29] of 32 ancient samples and 138 present-day samples, we estimated a mutation rate of 2.22×10-8 (95% HPD, 1.83–2.60×10-8) substitutions/site/year across the complete mtDNA genome for the Ursidae family. We confirmed that all chains converged in Tracer v1.6 and a total of 10% of the trees were discarded as burn-in using TreeAnnotator v1.8.2. The phylogeny and coalescence times were visualized in FigTree v1.40 (Figure 1B, Table S1A). Furthermore, we tested the effect that different mtDNA partitions could have on our estimates of the time to the most recent common ancestor (TMRCA) for giant pandas. We extracted the two rRNA and twelve protein-encoding genes (excluding stop codons, and ND6 since its nucleotide composition is heterogeneous and encoded on the light strand, opposite in direction from the other twelve coding genes). As variable number tandem repeats (VNTRs) are not found in giant pandas but are found in other present-day bears, we did not analyse the control region. 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ADDIN EN.CITE.DATA [S24, S25]. Table S1A shows that TMRCA were mostly similarly estimated. However, a lower estimate and a wide 95% HPD was observed for the rRNA partition, which could be due to it having the fewest sites compared to other partitions. The 3rd Codon partition showed the fastest evolving sites compared to other partitions, consistent with previous observations for the third codon ADDIN EN.CITE <EndNote><Cite><Author>K?lersj?</Author><Year>1999</Year><RecNum>134</RecNum><DisplayText>[30]</DisplayText><record><rec-number>134</rec-number><foreign-keys><key app="EN" db-id="9aa55ax9w9aft6edx5apewsz2exdtxprxe5s" timestamp="1522734947">134</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Mari K?lersj?</author><author>Victor A. Albert</author><author>James S. Farris</author></authors></contributors><titles><title>Homoplasy Increases Phylogenetic Structure</title><secondary-title>Cladistics</secondary-title></titles><periodical><full-title>Cladistics</full-title></periodical><pages>91-93</pages><volume>15</volume><number>1</number><dates><year>1999</year></dates><urls><related-urls><url>;[S30], and the TMRCA estimated from this partition was similar with those obtained for the complete mtDNA, Coding region, and 1st-2nd Codon partitions (Table S1A).The Bayesian Skyline Plot to estimate the female effective population size was constructed for the Cizhutuo and 49 present-day pandas, and we found that the addition of a single ancient sample is not enough to affect estimates of population size change from the Bayesian Skyline Plot using multiple present-day panda samples (Figure S1D). The best-fit nucleotide substitution model was determined to be HKY by jModeltest v2.1.10 PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5EYXJyaWJhPC9BdXRob3I+PFllYXI+MjAxMjwvWWVhcj48

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ADDIN EN.CITE.DATA [S24, S25], and the Skyline piecewise-constant was the best tree prior. Resulting trees were read into Tracer v1.6, where the default settings were used to produce the Bayesian Skyline Plot.4. Pairwise nucleotide difference analysis and estimating Ka/Ks ratio. We calculated pairwise difference using the 50 giant panda complete mtDNA sequences from the BEAST analysis as another way of visualizing the distinction between the mtDNA of the Cizhutuo and present-day pandas. For each pair of sequences, we calculated the total sites that were different. The following four combinations were considered: (1) Cizhutuo vs. present-day (Qinling and non-Qinling); (2) within Qinling; (3) within non-Qinling; and (4) Qinling vs. non-Qinling (Figure S1E).We analysed the mutational differences in the coding region between the Cizhutuo and present-day mtDNA (Table S1B). For each pair of sequences for each mitochondrial gene, we also calculated Ka/Ks, i.e. the ratio of the number of non-synonymous mutations (Ka) divided by the number of synonymous mutations (Ks). Ratios of genes that made up a respiratory complex were pooled (e.g. complex I: ND1, ND2, ND3, ND4, ND4L, ND5; complex III: cytb; complex IV: COI, COII, COIII; and complex V: ATP6, ATP8). We used the Wilcoxon rank sum test to test for significant differences in the complexes between the two groups (present-day–ancient pairs vs. present-day–present-day pairs) and found that the Cizhutuo mtDNA has higher Ka/Ks ratios than present-day giant pandas (mean ratio=0.24 vs. 0.09, Wilcoxon P<1×10-15), whereas the reverse was true in respiratory complexes IV and V (mean ratio=0.01 vs. 0.08, Wilcoxon P<1×10-6, Figure S1F). Most importantly, we find that there are 18 non-synonymous mutations in the Cizhutuo mtDNA, which are concentrated in the genes of complexes I and III.Supplemental References.S ADDIN EN.REFLIST 1.Dabney, J., Knapp, M., Glocke, I., Gansauge, M.T., Weihmann, A., Nickel, B., Valdiosera, C., Garcia, N., Paabo, S., Arsuaga, J.L., et al. (2013). Complete mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from ultrashort DNA fragments. Proceedings of the National Academy of Sciences of the United States of America 110, 15758-15763.S2.Dabney, J., and Meyer, M. (2012). Length and GC-biases during sequencing library amplification: a comparison of various polymerase-buffer systems with ancient and modern DNA sequencing libraries. BioTechniques 52, 87-94.S3.Gansauge, M.T., and Meyer, M. (2013). Single-stranded DNA library preparation for the sequencing of ancient or damaged DNA. Nature protocols 8, 737-748.S4.Kircher, M., Sawyer, S., and Meyer, M. (2012). Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res 40, e3.S5.Fu, Q., Meyer, M., Gao, X., Stenzel, U., Burbano, H.A., Kelso, J., and Paabo, S. (2013). DNA analysis of an early modern human from Tianyuan Cave, China. Proceedings of the National Academy of Sciences of the United States of America 110, 2223-2227.S6.Renaud, G., Stenzel, U., and Kelso, J. (2014). leeHom: adaptor trimming and merging for Illumina sequencing reads. Nucleic Acids Res 42, e141.S7.Renaud, G., Stenzel, U., Maricic, T., Wiebe, V., and Kelso, J. (2015). deML: robust demultiplexing of Illumina sequences using a likelihood-based approach. Bioinformatics 31, 770-772.S8.Li, H., and Durbin, R. (2009). Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754-1760.S9.Drummond, A.J., Suchard, M.A., Xie, D., and Rambaut, A. (2012). Bayesian phylogenetics with BEAUti and the BEAST 1.7. 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