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EGP Mitochondrial Genome Analysis on Simons Genome Diversity Project Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the SGDP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Simons Genome Diversity Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <table> <tbody> <tr> <th>Public Dataset</th> <th>EGP Result File Type</th> <th>MD5</th> </tr> </tbody> <tbody> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>86b09553f80926c1c29c57000ec1a88f</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>010026d77bee81e7b8daf5836bd12da3</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>f1ea3edf4a82b42f2028467fb3544dc4</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Copy Number</td> <td>4872eeb792c214ad49662e98e4b14620</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p>

EGP Mitochondrial Genome Analysis on 1000 Genomes Project 2504 Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 2504 Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 2504 Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_2504_high_coverage.sequence.index</code>. Please note that the index files are there as well. You just have to append a <code>.crai</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>dbf39d6ff0e4389b900f9d985f2e6c64</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>4d53ef60ec16f3e4b566c45fdf0fb977</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Variant Tables</td> <td>16925b546051d37cce27df8ec57ccc5e</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Copy Number</td> <td>365c1b360ea327795d981356064658a6</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>

EGP Mitochondrial Genome Analysis on 1000 Genomes Project 698 Related Whole-Genome Sequencing Data

<div> <p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 698 Related Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 698 Related Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp-trace.ncbi.nlm.nih.gov/1000genomes/ftp/1000G_2504_high_coverage/additional_698_related/1000G_698_related_high_coverage.sequence.index</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>322038d61b4da2e937b32410613c3532</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>36c782c12245100478903f7fa191a402</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Variant Tables</td> <td>68b2a51361ffae4e7ad9d420b8becd38</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Copy Number</td> <td>1e83c8ae132b0a7ef33b090757b29063</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div> <p> </p> </div> <h2> </h2>

EGP Mitochondrial Genome Analysis on Gambian Genome Variation Project Whole-Genome Sequencing Data

<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the GGVP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Gambian Genome Variation Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>d21e1e91e8b4c00627171fae79a1f54d</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>b359d1068d4f84f7746d1ebde82df29a</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>ee2b93aa93d2177d92ec0f8f308b43ed</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Copy Number</td> <td>fda509ba1d2bf33fd2d6b77b92e76c03</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>

EGP Mitochondrial Genome Analysis on GIAB Whole-Genome Sequencing Data

<div> <p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the GIAB. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on GIAB</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/refs/heads/master/AshkenazimTrio/alignment.index.AJtrio_Illumina300X_wgs_novoalign_GRCh37_GRCh38_NHGRI_07282015</code></p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>5eac6ec7d36307aa401fd5441b38a506</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>1151ae74c8e515f4f39bef816bb55d6a</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Variant Tables</td> <td>b3e342fe9827df2e399f5685f84cd4dc</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Copy Number</td> <td>3c45c19f76f71b3ccaad155565ead5e4</td> </tr> </tbody> </table> </div> <div>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</div> <p> </p> <p> </p> </div> <h2> </h2>

opencc-by-4.0Oct 2023View details →

Table 2 in The Complete Mitochondrial Genome of Glischropus bucephalus (Vespertilionidae; Chiroptera) Provides New Evidence for Pipistrellus Paraphyly

<p><b>Table 2.</b> GenBank accession numbers for mitochondrion and <i>cytb</i> sequences used in analysis.</p><table><tbody><tr><th>Species</th><th>Mitochondrion</th><th>cytb</th></tr></tbody><tbody><tr><th><i>Glischropus aquilus</i></th><td></td><td>KR612333.1</td></tr><tr><th><i>G. bucephalus</i></th><td>OR667258</td><td>KR612331.1, KR612332.1, OR667259, OR667260, OR667261</td></tr><tr><th><i>G. tylopus</i></th><td></td><td>JX570898.1, EU521632.1, OR667262, OR667263</td></tr><tr><th><i>“</i> <i>Pipistrellus coromandra”</i></th><td>NC_029191.1</td><td>NC_029191.1</td></tr><tr><th><i>Nyctalus aviator</i></th><td>NC_060309.1</td><td>NC_060309.1, MK167360.1</td></tr><tr><th><i>N. labiata</i></th><td>NC_027237.1, NC_041160.1</td><td>NC_027237.1, NC_041160.1, KX467596.1</td></tr><tr><th><i>N. lasiopterus</i></th><td></td><td>DQ120867.1, EU360680.1, JX570900.1</td></tr><tr><th><i>N. leisleri</i></th><td></td><td>DQ120877.1, JX570901.1, EU360690.1</td></tr><tr><th><i>N. noctula</i></th><td>MN122876.1, MN122907.1</td><td>MN122907.1, MN122876.1, DQ120872.1</td></tr><tr><th><i>Pipistrellus abramus</i></th><td>KX355640.1, NC_005436.1</td><td>GQ332529.1, KX355640.1, NC_005436.1</td></tr><tr><th><i>P. deserti</i></th><td></td><td>KM252759.1</td></tr><tr><th><i>P. coromandra</i></th><td></td><td>OR667264, OR667265, OR667266, OR667267</td></tr><tr><th><i>P. dhofarensis</i></th><td></td><td>KX375145.1, KX375148.1</td></tr><tr><th><i>P. hesperidus</i></th><td></td><td>MN790830.1, MT778037.1, MN790820.1</td></tr><tr><th><i>P. javanicus</i></th><td></td><td>KX496357.1</td></tr><tr><th><i>P. kuhlii</i></th><td>KU058655.1</td><td>KU058655.1, DQ120845.1, EU360657.1</td></tr><tr><th><i>P. maderensis</i></th><td></td><td>KC520771.1, KC520774.1, MT374272.1</td></tr><tr><th><i>P. nanulus</i></th><td></td><td>MK188530.1</td></tr><tr><th><i>P. nathusii</i></th><td>MN122914.1</td><td>MN122914.1, AJ504446.1, DQ120849.1</td></tr><tr><th><i>P. paterculus</i></th><td></td><td>OR667268, OR667269, OR667270</td></tr><tr><th><i>P. pipistrellus</i></th><td>LR862378.1</td><td>KF874520.1, DQ120853.1, LR862378.1</td></tr><tr><th><i>P. pygmaeus</i></th><td>MN122927.1, OX465325.1</td><td>MN122927.1, OX465325.1, EU084882.1</td></tr><tr><th><i>P. raceyi</i></th><td></td><td>KM886094.1, KM886088.1</td></tr><tr><th><i>P. rusticus</i></th><td></td><td>KX375166.1, KX375167.1</td></tr><tr><th><i>P. stenopterus</i></th><td></td><td>MH540194.1</td></tr><tr><th><i>Plecotus auritus</i></th><td>MN122881.1, MT410875.1</td><td></td></tr><tr><th><i>P. macrobullaris</i></th><td>KR134372.1, KR134385.1</td><td></td></tr><tr><th><i>Hypsugo alaschanicus</i></th><td>MF459671.1, MK135784.1, NC_029939.1</td><td></td></tr><tr><th><i>Lasionycteris noctivagans</i></th><td>MT774150.1, MT774151.1, NC_050995.1</td><td></td></tr><tr><th><i>Chalinolobus tuberculatus</i></th><td>NC 002626.1</td><td></td></tr><tr><th><i>Eptesicus bottae</i></th><td>NC_070014.1, OP328299.1, OP328300.1</td><td></td></tr><tr><th><i>E. nilssonii</i></th><td>OX621305.1</td><td></td></tr><tr><th><i>Vespertilio murinus</i></th><td>NC_033347.1</td><td>NC_033347.1</td></tr><tr><th><i>V. sinensis</i></th><td>KJ081440.1, KM092493.1.</td><td>KJ081440.1, KM092493.1.</td></tr><tr><th><i>Myotis brandtii</i></th><td>NC_025308.1</td><td></td></tr><tr><th><i>M. horsfieldii</i></th><td>MF143494.1</td><td></td></tr><tr><th><i>M. muricola</i></th><td>KT213444.1</td><td></td></tr></tbody></table>

opencc-by-4.0Oct 2023View details →

Table 3 in The Complete Mitochondrial Genome of Glischropus bucephalus (Vespertilionidae; Chiroptera) Provides New Evidence for Pipistrellus Paraphyly

<p><b>Table 3.</b> Gene organization and characterization of the <i>G. bucephalus</i> mitogenome.</p><table><tbody><tr><th></th><th><b>Start Position</b></th><th><b>Stop Position</b></th><th><b>Length (bp)</b></th><th><b>Anticodon</b></th><th><b>Start Codon</b></th><th><b>Stop Codon</b></th><th><b>Strand</b></th></tr></tbody><tbody><tr><th>tRNAPhe</th><td>1</td><td>73</td><td>73</td><td>GAA</td><td></td><td></td><td>+</td></tr><tr><th>12S rRNA</th><td>74</td><td>1010</td><td>937</td><td></td><td></td><td></td><td>+</td></tr><tr><th>tRNAVal</th><td>1011</td><td>1078</td><td>68</td><td>TAC</td><td></td><td></td><td>+</td></tr><tr><th>16S rRNA</th><td>1079</td><td>2644</td><td>1566</td><td></td><td></td><td></td><td>+</td></tr><tr><th>tRNALeu</th><td>2650</td><td>2725</td><td>76</td><td>TAA</td><td></td><td></td><td>+</td></tr><tr><th>Nd1</th><td>2731</td><td>3684</td><td>954</td><td></td><td>ATG</td><td>TA-</td><td>+</td></tr><tr><th>tRNAIle</th><td>3687</td><td>3755</td><td>69</td><td>GAT</td><td></td><td></td><td>+</td></tr><tr><th>tRNAGln</th><td>3753</td><td>3827</td><td>75</td><td>TTG</td><td></td><td></td><td>-</td></tr><tr><th>tRNAMet</th><td>3828</td><td>3896</td><td>69</td><td>CAT</td><td></td><td></td><td>+</td></tr><tr><th>Nd2</th><td>3897</td><td>4937</td><td>1041</td><td></td><td>ATT</td><td>T-</td><td>+</td></tr><tr><th>tRNATrp</th><td>4939</td><td>5005</td><td>67</td><td>TCA</td><td></td><td></td><td>+</td></tr><tr><th>tRNAAla</th><td>5013</td><td>5081</td><td>69</td><td>TGC</td><td></td><td></td><td>-</td></tr><tr><th>tRNAAsn</th><td>5082</td><td>5154</td><td>73</td><td>GTT</td><td></td><td></td><td>-</td></tr><tr><th>OR</th><td>5155</td><td>5189</td><td>35</td><td></td><td></td><td></td><td></td></tr><tr><th>tRNACys</th><td>5187</td><td>5252</td><td>66</td><td>GCA</td><td></td><td></td><td>-</td></tr><tr><th>tRNATyr</th><td>5253</td><td>5319</td><td>67</td><td>GTA</td><td></td><td></td><td>-</td></tr><tr><th>Cox1</th><td>5321</td><td>6862</td><td>1542</td><td></td><td>ATG</td><td>TAA</td><td>+</td></tr><tr><th>tRNASer</th><td>6869</td><td>6937</td><td>69</td><td>TGA</td><td></td><td></td><td>-</td></tr><tr><th>tRNAAsp</th><td>6945</td><td>7011</td><td>67</td><td>GTC</td><td></td><td></td><td>+</td></tr><tr><th>Cox2</th><td>7012</td><td>7692</td><td>681</td><td></td><td>ATG</td><td>TAA</td><td>+</td></tr><tr><th>tRNALys</th><td>7699</td><td>7765</td><td>67</td><td>TTT</td><td></td><td></td><td>+</td></tr><tr><th>ATP8</th><td>7767</td><td>7967</td><td>201</td><td></td><td>ATG</td><td>TAA</td><td>+</td></tr><tr><th>ATP6</th><td>7928</td><td>8605</td><td>678</td><td></td><td>ATG</td><td>TAA</td><td>+</td></tr><tr><th>Cox3</th><td>8608</td><td>9390</td><td>783</td><td></td><td>ATG</td><td>TA-</td><td>+</td></tr><tr><th>tRNAGly</th><td>9392</td><td>9460</td><td>69</td><td>TCC</td><td></td><td></td><td>+</td></tr><tr><th>Nd3</th><td>9461</td><td>9805</td><td>345</td><td></td><td>ATT</td><td>TA-</td><td>+</td></tr><tr><th>tRNAArg</th><td>9809</td><td>9878</td><td>70</td><td>TCG</td><td></td><td></td><td>+</td></tr><tr><th>Nd4L</th><td>9880</td><td>10,173</td><td>294</td><td></td><td>ATG</td><td>TAA</td><td>+</td></tr><tr><th>Nd4</th><td>10,170</td><td>11,546</td><td>1377</td><td></td><td>ATG</td><td>T-</td><td>+</td></tr><tr><th>tRNAHis</th><td>11,548</td><td>11,616</td><td>69</td><td>GTG</td><td></td><td></td><td>+</td></tr><tr><th>tRNASer</th><td>11,617</td><td>11,675</td><td>59</td><td>GCT</td><td></td><td></td><td>+</td></tr><tr><th>tRNALeu</th><td>11,676</td><td>11,745</td><td>70</td><td>TAG</td><td></td><td></td><td>+</td></tr><tr><th>Nd5</th><td>11,764</td><td>13,552</td><td>1789</td><td></td><td>ATA</td><td>TAA</td><td>+</td></tr><tr><th>Nd6</th><td>13,544</td><td>14,062</td><td>519</td><td></td><td>ATG</td><td>TAA</td><td>-</td></tr><tr><th>tRNAGlu</th><td>14,066</td><td>14,133</td><td>68</td><td>TTC</td><td></td><td></td><td>-</td></tr><tr><th>CytB</th><td>14,139</td><td>15,275</td><td>1137</td><td></td><td>ATG</td><td>AGA</td><td>+</td></tr><tr><th>tRNAThr</th><td>15,279</td><td>15,348</td><td>70</td><td>TGT</td><td></td><td></td><td>+</td></tr><tr><th>tRNAPro</th><td>15,348</td><td>15,416</td><td>69</td><td>TGG</td><td></td><td></td><td>-</td></tr><tr><th>D-loop</th><td>15,416</td><td>17,023</td><td>1608</td><td></td><td></td><td></td><td></td></tr></tbody></table>

opencc-by-4.0Oct 2023View details →

Table 1 in The Complete Mitochondrial Genome of Glischropus bucephalus (Vespertilionidae; Chiroptera) Provides New Evidence for Pipistrellus Paraphyly

<p><b>Table 1.</b> Model types for protein-coding gene analysis configured by IQtree ModelFinder through ultrafast bootstrap (10,000 replicates) for the phylogenetic tree with 3 codons.</p><table><tbody><tr><th>Model Type</th><th></th><th></th><th></th><th></th><th></th><th></th><th>Gene</th><th></th><th></th><th></th><th></th><th></th><th></th></tr></tbody><tbody><tr><th></th><td>ND1</td><td>ND2</td><td>COX1</td><td>COX2</td><td>ATP8</td><td>ATP6</td><td>COX3</td><td>ND3</td><td>ND4L</td><td>ND4</td><td>ND5</td><td>ND6</td><td>CYTB</td></tr><tr><th>GTR+F+G4</th><td>1st pos</td><td></td><td></td><td>1st pos</td><td></td><td>1st pos</td><td></td><td>1st pos</td><td></td><td></td><td></td><td></td><td>1st pos</td></tr><tr><th>TPM3u+F+I+G4</th><td>2nd pos</td><td></td><td>2nd pos</td><td>2nd pos</td><td></td><td>2nd pos</td><td>2nd pos</td><td></td><td></td><td></td><td></td><td></td><td>2rd pos</td></tr><tr><th>TIM+F+I+G4</th><td>3rd pos</td><td>3rd pos</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3rd pos</td></tr><tr><th>TIM2+F+I+G4</th><td></td><td>1st pos</td><td></td><td></td><td>1st pos, 2nd pos</td><td></td><td></td><td></td><td>1st pos</td><td>1st pos</td><td>1st pos</td><td></td><td></td></tr><tr><th>TPM3u+F+I+G4</th><td></td><td>2nd pos</td><td></td><td></td><td></td><td></td><td></td><td>2nd pos</td><td>2nd pos</td><td>2nd pos</td><td>2nd pos</td><td></td><td></td></tr><tr><th>TIM2e+I+G4</th><td></td><td></td><td>1st pos</td><td></td><td></td><td></td><td>1st pos</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>TIM2+F+I+G4</th><td></td><td></td><td>3rd pos</td><td>3rd pos</td><td>3rd pos</td><td>3rd pos</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>TN+F+I+G4</th><td></td><td></td><td></td><td></td><td></td><td></td><td>3rd pos</td><td>3rd pos</td><td>3rd pos</td><td>3rd pos</td><td>3rd pos</td><td></td><td></td></tr><tr><th>HKY+F+I+G4</th><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1st pos, 2nd pos</td><td></td></tr><tr><th>HKY+F+G4</th><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3rd pos</td><td></td></tr></tbody></table>

opencc-zeroDec 2018View details →

Data from: Genomics overrules mitochondrial DNA, siding with morphology on a controversial case of species delimitation

Species delimitation is a major quest in biology and is essential for adequate management of the organismal diversity. A challenging example comprises the fish species of red snappers in the Western Atlantic. Red snappers have been traditionally recognized as two separate species based on morphology: Lutjanus campechanus (northern red snapper) and L. purpureus (southern red snappers). Recent genetic studies using mitochondrial markers, however, failed to delineate these nominal species, leading to the current lumping of the northern and southern populations into a single species (L. campechanus). This decision carries broad implications for conservation and management as red snappers have been commercially over-exploited across the Western Atlantic and are currently listed as vulnerable. To address this conflict, we examine genome-wide data collected throughout the range of the two species. Population genomics, phylogenetic and coalescent analyses favor the existence of two independent evolutionary lineages, a result that confirms the morphology-based delimitation scenario in agreement with conventional taxonomy. While we find evidence of introgression in geographically neighboring populations in northern South America, the genetic differences strongly support isolation and differentiation of these species, suggesting that the northern and southern red snappers should be treated as distinct taxonomic entities.

opencc-by-4.0Dec 2016View details →

Figure 5 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea

Figure 5. The potential stem-loop structure with "GAAT" and "TATA" in the flanking region.

opencc-by-4.0Dec 2016View details →

Figure 2 in General methods to obtain and analyze the complete mitochondrial genome of aphid species: Eriosoma lanigerum (Hemiptera: Aphididae) as an example

Figure 2. Steps of annotation one complete mt genome of aphid species.

opencc-by-4.0Dec 2016View details →

Figure 1 in General methods to obtain and analyze the complete mitochondrial genome of aphid species: Eriosoma lanigerum (Hemiptera: Aphididae) as an example

Figure 1. Procedures of sequencing one complete mt genome of aphid species.

opencc-zeroSep 2021View details →

Highly diversified mitochondrial genomes provide new evidence for inter-ordinal relationships in the Arachnida

<p>Arachnida is an exceptionally diverse class in the Arthropoda, comprising of 20 orders and playing essential roles in the terrestrial ecosystems. However, their inter-ordinal relationships have been debated for over a century. Rearranged or highly rearranged mitochondrial (mt) genomes were consistently found in this class, but their various extent in different lineages and efficiency for resolving arachnid phylogenies are unclear. Here, we reconstructed phylogenetic trees using mt genome sequences of 290 arachnid species to decipher inter-ordinal relationships as well as diversification through time. Our results recovered monophyly of 10 orders (i.e., Amblypygi, Araneae, Ixodida, Mesostigmata, Opiliones, Pseudoscorpiones, Ricinulei, Sarcoptiformes, Scorpiones, and Solifugae), while rejected monophyly of the Trombidiformes due to unstable position of the Eriohyoidea. The monophyly of Acari (subclass) was rejected possibly due to long-branch attraction of the Pseudoscorpiones. Basal inter-ordinal relationships were partially resolved by sharing conserved mt gene arrangements. Highly rearranged mt genomes in mites while less rearranged or conserved in the remaining lineages point to their exceptionally diversification in mite orders; however, shared derived mt gene clusters were found within superfamilies rather than inter-orders, confusing phylogenetic signals in arachnid inter-ordinal relationships. Molecular dating results show that arachnid orders have ancient origins ranged from the Silurian to the Carboniferous, followed by a huge gap, crossing the Permian, Triassic, and Jurassic, then especially diversified after the Cretaceous in orders Araneae, Mesostigmata, Sarcoptiformes, and Trombidiformes. By summarizing previously resolved key positions of some orders, we propose a plausible inter-ordinal phylogeny: ((Solifugae, Palpigradi) (Phalangiotarbida (Trigonotarbida ((Uraraneida, Araneae) (Haptopoda (Amblypygi (Thelyphonida, Schizomida)))) (Opiliones (Ricinulei ((Opilioacarida (Mesostigmata (Holothyrida, Ixodida))) (Trombidiformes, Sarcoptiformes)))))) (Scorpiones, Pseudoscorpiones))). Our results underline a more precise framework for inter-ordinal phylogeny in the Arachnida and provide insights into their ancient evolution.</p>

opencc-zeroDec 2022View details →

Supplementary information for: NUMT PARSER: Automated identification and removal of nuclear mitochondrial pseudogenes (numts) for accurate mitochondrial genome reconstruction in Panthera

<p>Nuclear mitochondrial pseudogenes (numts) may hinder the reconstruction of mtDNA genomes and affect the reliability of mtDNA datasets for phylogenetic and population genetic comparisons. Here, we present the program Numt Parser, which allows for the identification of DNA sequences that likely originate from numt pseudogene DNA. Sequencing reads are classified as originating from either numt or true cytoplasmic mitochondrial (cymt) DNA by direct comparison against cymt and numt reference sequences. Classified reads can then be parsed into cymt or numt datasets. We tested this program using whole genome shotgun-sequenced data from two ancient Cape lions (<em>Panthera</em> <em>leo</em>) because mtDNA is often the marker of choice for ancient DNA studies, and the genus <em>Panthera</em> is known to have numt pseudogenes. Numt Parser decreased sequence disagreements that were likely due to numt pseudogene contamination and equalized read coverage across the mitogenome by removing reads that likely originated from numts. We compared the efficacy of Numt Parser to two other bioinformatic approaches that can be used to account for numt contamination. We found that Numt Parser outperformed approaches that rely only on read alignment or Basic Local Alignment Search Tool (BLAST) properties, and was effective at identifying sequences that likely originated from numts while having minimal impacts on the recovery of cymt reads. Numt Parser therefore improves the reconstruction of true mitogenomes, allowing for more accurate and robust biological inferences.</p>

opencc-zeroJan 2023View details →

Genome-scale angiosperm phylogenies based on nuclear, plastome, and mitochondrial datasets

<p>Angiosperms dominate the Earth's ecosystems and provide most of the basic necessities for human life. The major angiosperm clades comprise 64 orders, as recognized by the APG IV classification. However, the phylogenetic relationships of angiosperms remain unclear, as phylogenetic trees with different topologies have been reconstructed depending on the sequence datasets utilized, from targeted genes to transcriptomes. Here, we used currently available <em>de novo</em> genome data to reconstruct the phylogenies of 366 angiosperm species from 241 genera belonging to 97 families across 43 of the 64 orders based on orthologous genes from the nuclear, plastid, and mitochondrial genomes of the same species with compatible datasets. The phylogenetic relationships were largely consistent with previously constructed phylogenies based on sequence variations in each genome type. However, there were major inconsistencies in the phylogenetic relationships of the five Mesangiospermae lineages when different genomes were examined. We discuss ways to address these inconsistencies, which could ultimately lead to the reconstruction of a comprehensive angiosperm tree of life. The angiosperm phylogenies presented here provide a basic framework for further updates and comparisons. These phylogenies can also be used as guides to examine the evolutionary trajectories among the three genome types during lineage radiation. </p>

opencc-by-4.0Feb 2023View details →

Comparative Mitochondrial Genomics of selected Noctuoid Moths (Lepidoptera: Noctuoidea) with implications for their Phylogeny

<p>In this study, I sequenced and annotated the complete mitochondrial genome sequences of 19 species that belong to the superfamily Noctuoidea viz. <em>Actinotia polyodon, Episparis tortuosalis, Ercheia cyllaria, Eudocima salaminia, Hulodes caranea, Hypospila bolinoides, Ischyja manlia, Lygephila dorsigera, Mecodina praecipua, Mocis undata, Odontodes seranensis, Ophiusa tirhaca, Oraesia emarginata, Pandesma quenavadi, Polydesma boarmoides, Psimada quadripennis, Rusicada privata, Trigonodes hyppasia </em>and<em> Xanthodes albago</em>. In addition to this, I performed the analysis of their genetic compositions as well as their molecular characterization in order to provide molecular insights into their taxonomic and phylogenetic implications. Based on the data and those obtained from the NCBI database, I examined the phylogenetic relationships among the species of the superfamily Noctuoidea.</p>

opencc-zeroApr 2023View details →

Palaeoloxodon mitochondrial genome

<p>My dataset includes the mitogenomes sequence (bam format file) of two Chinese straight-tusked elephants (genus: <em>Palaeoloxodon</em>, sample number: CADG1074 and CADG841).</p>

opencc-zeroApr 2023View details →

Mitochondrial genome evolution in Annelida: A systematic study on conservative and variable gene orders and the factors influencing its evolution

<p><span>The mitochondrial genomes of Bilateria are relatively conserved in their protein-coding, rRNA and tRNA gene complement, but the order of these genes can range from very conserved to very variable depending on the taxon. The supposedly conserved gene order of Annelida has been used to support the placement of some taxa within Annelida. Recently, authors have cast doubts on the conserved nature of the annelid gene order. Various factors may influence gene-order variability including, among others, increased substitution rates, base composition differences, structure of non-coding regions, parasitism, living in extreme habitats, short generation times and biomineralization. However, these analyses were neither done systematically, nor based on well-established reference trees. Several focused on only a few of these factors and biological factors were usually explored ad-hoc without rigorous testing or correlation analyses. Herein, we investigated the variability and evolution of the annelid gene order and the factors that potentially influenced its evolution, using a comprehensive and systematic approach. The analyses were based on 170 genomes, including 33 previously unrepresented species. Our analyses included 706 different molecular properties, 20 life-history and ecological traits and a reference tree corresponding to recent improvements concerning the annelid tree. The results showed that the gene order with and without tRNAs is generally conserved. However, individual taxa exhibit higher degrees of variability. None of the analyzed life-history and ecological traits explained the observed variability across mitochondrial gene orders. In contrast, the combination and interaction of the best predicting factors for substitution rate and base composition explained up to 30% of the observed variability. Accordingly, correlation analyses of different molecular properties of the mitochondrial genomes showed an intricate network of direct and indirect correlations between the different molecular factors. Hence, gene order evolution seems to be driven by molecular evolutionary aspects rather than by life history or ecology. On the other hand, gene order variability does not predict difficulty in placing certain taxa within molecular phylogenetic studies. We also discuss the molecular properties of annelid mitochondrial genomes considering canonical views on gene evolution and potential reasons why they do not always fit to the observed patterns without nuisance.</span></p>

opencc-zeroMay 2023View details →

Origin of minicircular mitochondrial genomes in red algae

<p><span>Eukaryotic organelle genomes are generally of conserved size and gene content within phylogenetic groups. However, significant variation in genome structure may occur. Here, we report that the Stylonematophyceae red algae contain multipartite circular mitochondrial genomes (i.e., minicircles) which encode one or two genes bounded by a specific cassette and a conserved constant region. These minicircles are visualized using Fluorescence Microscope and Scanning Electron Microscope, proving the circularity. Mitochondrial gene sets are reduced in these highly divergent mitogenomes. Newly generated chromosome-level nuclear genome assembly of </span><em><span>Rhodosorus marinus</span></em><span> reveals that most mitochondrial ribosomal subunit genes are transferred to the nuclear genome. </span><span>Hetero-concatemers that resulted from recombination between minicircles and unique gene inventory that is responsible for mitochondrial genome stability may explain how the transition</span><span> from typical mitochondrial genome to minicircles occurs. </span><span>Our results offer inspiration on minicircular organelle genome formation and highlight an extreme case of mitochondrial gene inventory reduction.</span></p>