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17 results for “mitochondrial DNA haplotype”
Fig. 3 in Variation In Cone And Seed Morphology Traits Among The Mitochondrial Dna Haplotypes Of Scots Pine (Pinus Sylvestris L.)
Fig. 3. Dependence of seed number per cone on cone length for the type A and type B mitotypes of Scots pine. Individual cone values are shown.
Figures 4–5. Mitochondrial D-loop 474 in Molecular confirmation of the occurrence of Anguilla interioris (Actinopterygii: Anguilliformes) in North Maluku of Indonesia and mitochondrial DNA haplotype diversity among existing specimens
Figures 4–5. Mitochondrial D-loop 474 bp sequence analyses. (4) Phylogenetic analysis based on maximum likelihood algorithm with the sample codes, GenBank accession numbers and sample sites shown. Bootstrap percentages are shown at the tree nodes. (5) Haplotype network with the haplotypes labelled as H1 to H9. The circle size is proportional to the number of samples, and different sample sites are represented by different colours. Small white circle represents median vector which is the hypothesized or missing haplotype. Each dash on the line symbolizes one mutational step.
Figure 1 in Molecular confirmation of the occurrence of Anguilla interioris (Actinopterygii: Anguilliformes) in North Maluku of Indonesia and mitochondrial DNA haplotype diversity among existing specimens
Figure 1. Sampling locations of Anguilla interioris in North Maluku of East Indonesia. Sampling locations are shown in red (circle: COI, triangle: D-loop). Locations of Bougainville of Papua New Guinea, Papua New Guinea mainland, Negros Oriental and Sibutad of Philippines, and Ambon and Bengkulu of Indonesia, which were used in molecular phylogenetic and haplotype network analyses, are shown in purple (circle: COI, triangle: D-loop). Specimen records are shown in square with growth stages; L [larval (leptocephalus); Kuroki et al. 2006, Wouthuyzen et al. 2009, Aoyama et al. 2018], J [juvenile (glass eel); Sugeha et al. 2008, Fahmi et al. 2012, Wibowo et al. 2021] and A (adult; Watanabe et al. 2004, Fahmi et al. 2012, Wibowo et al. 2021, this study). Base maps were downloaded from http://viewer. nationalmap.gov/viewer (USGS 2022) and from the OpenStreetMap at https://www.openstreetmap.org.
Fig. 2. Minimum spanning network for haemosporidian mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the YukonKuskokwim Delta, Alaska during 2006–2016 in Negligible evidence for detrimental effects of Leucocytozoon infections among Emperor Geese (Anser canagicus) breeding on the Yukon-Kuskokwim Delta, Alaska
Fig. 2. Minimum spanning network for haemosporidian mitochondrial DNA cytochrome b haplotypes identified from blood samples collected from Emperor Geese inhabiting the YukonKuskokwim Delta, Alaska during 2006–2016. Circles are drawn proportional to the frequency at which haplotypes were detected. Shading represented the assignment of representative sequences for haplotypes to L. simondi clade A (teal), L. simondi clade B (orange), or other Leucocytozoon (grey) in phylogenetic analyses (see Results and Fig. 5). Lines are drawn proportional to genetic distance and are labeled per the number of mutations represented (except single nucleotide polymorphisms which are unlabeled). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig 4. Median-joining haplotype network for M in Evolutionary relationships of Macaca fascicularis fascicularis (Raffles 1821) (Primates: Cercopithecidae) from Singapore revealed by Bayesian analysis of mitochondrial DNA sequences
Fig 4. Median-joining haplotype network for M. fascicularis. The size of the circular nodes representing haplotypes is proportional to the number of sequences comprising the haplotype. Shading of circular nodes corresponds to general geographic groupings including Sundaic islands (white), mainland Indochina (gray), Malay Peninsula and northern Sumatra (dark gray), and Singapore (black). Haplotype identifications are presented in Table 1.
Fig. 5 in Variation In Cone And Seed Morphology Traits Among The Mitochondrial Dna Haplotypes Of Scots Pine (Pinus Sylvestris L.)
Fig. 5. Distribution of the seed wing shape (%, units) between and within Scots pine mitotypes.
Haplotype analysis of the mitochondrial DNA d-loop region reveals the maternal origin and historical dynamics among the indigenous goat populations in east and west of the Democratic Republic of Congo (DRC)
<p><span>This study aimed at assessing haplotype diversity and population dynamics of three Congolese indigenous goat populations that included Kasai goat (KG), small goat (SG), and dwarf goat (DG) of the Democratic Republic of Congo (DRC). The 1,169 bp <em>d-loop</em> region of mitochondrial DNA (mtDNA) was sequenced for 339 Congolese indigenous goats. The total length of sequences was used to generate the haplotypes and evaluate their diversities, whereas the hypervariable region (HVI, 453 bp) was analyzed to define the maternal variation and the demographic dynamic. A total of 568 segregating sites that generated 192 haplotypes were observed from the entire <em>d-loop</em> region (1,169 bp <em>d-loop</em>). Phylogenetic analyses using reference haplotypes from the six globally defined goat mtDNA haplogroups showed that all the three Congolese indigenous goat populations studied clustered into the dominant haplogroup A, as revealed by the Neighbor-joining (NJ) tree and median-joining (MJ) network. Nine haplotypes were shared between the studied goats and goat populations from Pakistan (1 haplotype), Kenya, Ethiopia and Algeria (1 haplotype), Zimbabwe (1 haplotype), Cameroon (3 haplotypes), and Mozambique (3 haplotypes). The population pairwise analysis (<em>F<sub>ST</sub></em>) indicated a weak differentiation between the Congolese indigenous goat populations. Negative and significant (<em>p</em>-value < 0.05) values for <em>F</em>u's <em>F</em>s (-20.418) and Tajima's (-2.189) tests showed the expansion in the history of the three Congolese indigenous goat populations. These results suggest a weak differentiation and a single maternal origin for the studied goats. This information will contribute to the improvement of the management strategies and long-term conservation of indigenous goats in DRC</span><span>.</span></p>
FIGURE 3. TCS haplotype network obtained for 521 in Mitochondrial DNA-based reassessment of Antennablennius Fowler (Blenniidae: Salariini) from the north-western Indian Ocean, with resurrection of A. persicus (Regan)
FIGURE 3. TCS haplotype network obtained for 521 bp fragment of mitochondrial COI of the genus Antennablennius. Numbers between haplotypes represent mutational steps between them.
FIGURE 5. Haplotype network for Austroniscus brandtae n in Combining morphological and mitochondrial DNA data to describe a new species of Austroniscus Vanhöffen, 1914 (Isopoda, Janiroidea, Nannoniscidae) linking abyssal and hadal depths of the Puerto Rico Trench
FIGURE 5. Haplotype network for Austroniscus brandtae n. sp. for the mitochondrial ribosomal large subunit 16S. Sampled haplotypes are shown as solid circles with circle area proportional to the number of individuals possessing that haplotype; black circles represent unsampled haplotypes required to connect the network. The number of mutational steps between haplotypes are shown along connecting lines. The colours represent sampling locations as indicated in the legend.
FIGURE 4. Haplotype network for Austroniscus brandtae n in Combining morphological and mitochondrial DNA data to describe a new species of Austroniscus Vanhöffen, 1914 (Isopoda, Janiroidea, Nannoniscidae) linking abyssal and hadal depths of the Puerto Rico Trench
FIGURE 4. Haplotype network for Austroniscus brandtae n. sp. for COI (cytochrome c oxidase subunit I). Sampled haplotypes are shown as solid circles with circle area proportional to the number of individuals possessing that haplotype; black circles represent unsampled haplotypes required to connect the network. The number of mutational steps between haplotypes are shown along connecting lines. The colours represent sampling locations as indicated in the legend.
Haplotype analysis of the mitochondrial DNA d-loop region reveals the maternal origin and historical dynamics among the indigenous goat populations in east and west of the Democratic Republic of Congo (DRC)
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Fig. 4 in Variation In Cone And Seed Morphology Traits Among The Mitochondrial Dna Haplotypes Of Scots Pine (Pinus Sylvestris L.)
Fig. 4. Dependence of seed number per cone on cone width for the type A and type B mitotypes of Scots pine. Individual cone values are shown.
Figures 2–3. Mitochondrial cytochrome c oxidase subunit 1 in Molecular confirmation of the occurrence of Anguilla interioris (Actinopterygii: Anguilliformes) in North Maluku of Indonesia and mitochondrial DNA haplotype diversity among existing specimens
Figures 2–3. Mitochondrial cytochrome c oxidase subunit 1 (CO1) 551 bp sequence analyses. (2) Phylogenetic analysis based on maximum likelihood algorithm with the sample codes, GenBank or BOLD accession numbers and sample sites shown. Bootstrap percentages are shown at the tree nodes. (3) Haplotype network with the haplotypes labelled as H1 to H9. The circle size is proportional to the number of samples, and different sample sites are represented by different colours. Small white circle represents median vector which is the hypothesized or missing haplotype. Each dash on the line symbolizes one mutational step.
Figure 2. CAD haplotype network. TCS Network based off 814 in Low Variation in Nuclear and Mitochondrial DNA Inhibits Resolution of Invasion Pathways across the Pacific for the Coconut Rhinoceros Beetle (Scarabeidae: Oryctes rhinoceros)
Figure 2. CAD haplotype network. TCS Network based off 814 base pairs of the CAD gene region from a total of 117 samples (8 to 39 from any given location) representing 234 total haplotypes. Hash marks represent a single base pair change. A PHASE algorithm was used to generate haplotypes from ambiguities present in the sequence data of a multi-copy nuclear gene, resulting in twice as many haplotypes as samples.
Multiple mitochondrial haplotypes within individual specimens affect biodiversity estimation by DNA metabarcoding
<p>In the global action for biodiversity conservation, the most urgent need is to delimit and identify species. DNA barcoding and metabarcoding based on molecular markers have been increasingly used in species delimitation and species diversity assessment, respectively, owing to their advantages of standardization and high throughput. The molecular markers used in these methods for animals are mainly derived from mitochondrial DNA. The principle involved is that inter-specific genetic distances are greater than intra-specific genetic distances. However, if multiple mitochondrial haplotypes exist within individual specimens and the divergence between these haplotypes is greater than the assumed maximum intra-specific divergence, the species delimitation and species diversity assessment may be affected. In our recent studies, a widespread phenomenon of multiple mitochondrial haplotypes within individual specimens was discovered in fig wasps (Hymenoptera, Insecta), having negative impact on DNA barcoding and metabarcoding. In this study, we expanded the taxa to include up to 480 specimens from 82 species, 66 genera, 45 families, and 13 orders of Insecta and Arachnida. By high-throughput sequencing of mitochondrial <i>cox1</i> fragments within individual specimens, we studied the pattern of multiple mitochondrial haplotypes within individual specimens. Three DNA metabarcoding strategies, one of which was simulated, were applied. The results revealed that multiple mitochondrial haplotypes within individual specimens could lead to an overestimation of species diversity by metabarcoding. Simultaneously, we found that the infection with intracellular endosymbiotic bacteria <i>Wolbachia</i> was significantly negatively related with this effect. These results suggest that additional attention should be paid to the interference of multiple mitochondrial haplotypes within individual specimens on the results of DNA metabarcoding in species diversity assessment of animals.</p>
Multiple mitochondrial haplotypes within individual specimens affect biodiversity estimation by DNA metabarcoding
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Mitochondrial DNA haplotypes induce differential patterns of DNA methylation that result in differential chromosomal gene expression patterns
GEO Series GSE94918. Mus musculus. 12 samples. Type: Methylation profiling by array.
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