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New insights into the genetic variability of Fasciola hepatica (Trematoda) in Algeria and relationships with other geographic regions revealed by mitochondrial DNA Cover

New insights into the genetic variability of Fasciola hepatica (Trematoda) in Algeria and relationships with other geographic regions revealed by mitochondrial DNA

Helminthologia
Volume 59 (2022): Issue 2 (June 2022)
By:
Open Access
|Sep 2022

Figures & Tables

Fig. 1

Map of the Algerian sample collection sites. The map shows the geographical origin of the sequences from Algeria isolated in the present study and those from GenBank and BOLD.
Map of the Algerian sample collection sites. The map shows the geographical origin of the sequences from Algeria isolated in the present study and those from GenBank and BOLD.

Fig. 2

Median-joining network analysis. The network includes COI sequences from Algeria obtained in the present study along with those from GenBank. The small red plot on one node shows a median vector representing the hypothetical connecting sequence that was calculated using the maximum parsimony method. The number of mutations between sequences that are greater than 1 are reported on network branches. As well, the number of individuals showing the same haplotype that is greater than 1 is reported inside the spot.
Median-joining network analysis. The network includes COI sequences from Algeria obtained in the present study along with those from GenBank. The small red plot on one node shows a median vector representing the hypothetical connecting sequence that was calculated using the maximum parsimony method. The number of mutations between sequences that are greater than 1 are reported on network branches. As well, the number of individuals showing the same haplotype that is greater than 1 is reported inside the spot.

Fig. 3

Median-joining network analysis. The network includes all COI sequences from the present study along with those from GenBank. The small red plots on one node show a median vector representing the hypothetical connecting sequence that was calculated using the maximum parsimony method. The number of mutations between sequences that are greater than 1 are reported on network branches. As well, the number of individuals showing the same haplotype that is greater than 1 isreported inside the spot. The MP calculation post-processing option, that uses only the shortest trees sufficient to generate the graphic output, has been applied for drawing the network. This option allows to obtain a network without showing the reticulations. All Sardinian sequences in the network are form the present study.
Median-joining network analysis. The network includes all COI sequences from the present study along with those from GenBank. The small red plots on one node show a median vector representing the hypothetical connecting sequence that was calculated using the maximum parsimony method. The number of mutations between sequences that are greater than 1 are reported on network branches. As well, the number of individuals showing the same haplotype that is greater than 1 isreported inside the spot. The MP calculation post-processing option, that uses only the shortest trees sufficient to generate the graphic output, has been applied for drawing the network. This option allows to obtain a network without showing the reticulations. All Sardinian sequences in the network are form the present study.

Fig. 4

Principal coordinates analysis performed on the COI gene dataset. Bi-dimensional plots show the genetic differentiation among populations due to the base differences per site found in the dataset. Percentage of variation explained by the first three axes for the COI dataset: 1st = 40.96, 2nd = 13.80, 3rd=9.31.
Principal coordinates analysis performed on the COI gene dataset. Bi-dimensional plots show the genetic differentiation among populations due to the base differences per site found in the dataset. Percentage of variation explained by the first three axes for the COI dataset: 1st = 40.96, 2nd = 13.80, 3rd=9.31.

Fig. 5

Principal coordinates analysis performed on the ITS fragment dataset. Bi-dimensional plots show the genetic differentiation among populations due to the base differences per site found in the dataset. Percentage of variation explained by the first three axes for the ITS dataset: 1st = 36.71, 2nd = 23.37, 3rd=11.22.
Principal coordinates analysis performed on the ITS fragment dataset. Bi-dimensional plots show the genetic differentiation among populations due to the base differences per site found in the dataset. Percentage of variation explained by the first three axes for the ITS dataset: 1st = 36.71, 2nd = 23.37, 3rd=11.22.

Indices of genetic variation_ The table reports the estimates of genetic variation for the mitochondrial COI gene dataset_ N: sample sizes; bp: fragment size; S: number of polymorphic sites; H: number of haplotypes; hd: haplotype diversity; π: nucleotide diversity_

NbpSHhdπ
Samples from Algeria – present study24441120.1590.00036
Samples from Algeria – whole dataset32441770.3930.00271
Total COI dataset18744142320.7530.00664

Sampling plan_ The table reports data on the sampling collection, the GenBank accession numbers of the sequences obtained in the present study, and the haplotypes (Hap_ type) found among individuals_ The unique allelic variant isolated for the ITS fragment in all the samples analysed in the present study was deposited in GenBank under the accession number MZ292402_ The presence of an identical host code for different samples indicates that flukes were isolated from the same host_

Sample codeHost codeAreaSiteHostSampling dateGenBank COI #Hap. type
C1_142142AlgeriaTipazaCattle03-29-2016MT9209652
C2_142142AlgeriaTipazaCattle03-29-2016MT9209661
C1_170170AlgeriaTipazaCattle04-06-2016MT9209801
C1_858858AlgeriaBlidaCattle10-03-2016MT9209691
C2_858858AlgeriaBlidaCattle10-03-2016MT9209701
C1_903903AlgeriaBoumerdesCattle10-10-2016MT9209781
C1_995995AlgeriaAlgiersCattle11-02-2016MT9209671
C2_995995AlgeriaAlgiersCattle11-02-2016MT9209682
C1_10001000AlgeriaAlgiersCattle11-02-2016MT9209741
C2_10001000AlgeriaAlgiersCattle11-02-2016MT9209751
C1_11101110AlgeriaBoumerdesCattle11-26-2016MT9209821
C1_12111211AlgeriaAlgiersCattle12-31-2016MT9209761
C2_12111211AlgeriaAlgiersCattle12-31-2016MT9209771
C1_12151215AlgeriaAlgiersCattle12-31-2016MT9209811
C1_12301230AlgeriaAlgiersCattle12-31-2016MT9209831
C2_12301230AlgeriaAlgiersCattle12-31-2016MT9209841
C3_12301230AlgeriaAlgiersCattle12-31-2016MT9209851
C4_12301230AlgeriaAlgiersCattle12-31-2016MT9209861
C5_12301230AlgeriaAlgiersCattle12-31-2016MT9209871
C6_12301230AlgeriaAlgiersCattle12-31-2016MT9209881
C1_12791279AlgeriaAlgiersCattle01-18-2017MT9209791
C1_13421342AlgeriaAlgiersCattle02-04-2017MT9209711
C2_13421342AlgeriaAlgiersCattle02-04-2017MT9209721
C4_13421342AlgeriaAlgiersCattle02-04-2017MT9209731
FHLAC1LACItalyLaconiCattle12-09-2013MT9209891
FHLAC2LACItalyLaconiCattle12-09-2013MT9209901
FHLAC3LACItalyLaconiCattle12-09-2013MT9209911
FHLAC4LACItalyLaconiCattle12-09-2013MT9209921
FHLAC5LACItalyLaconiCattle12-09-2013MT9209931
FHLAC6LACItalyLaconiCattle12-09-2013MT9209941
FHLAC7LACItalyLaconiCattle12-09-2013MT9209951
FHLAC8LACItalyLaconiCattle12-09-2013MT9209961
FHGIA1GIAItalyGiara di GenoniGoat11-28-2013MT9209971
FHGIA2GIAItalyGiara di GenoniGoat11-28-2013MT9209981
FHGIA3GIAItalyGiara di GenoniGoat11-28-2013MT9209991
FHGIA4GIAItalyGiara di GenoniGoat11-28-2013MT9210001
FHGIA5GIAItalyGiara di GenoniGoat11-28-2013MT9210011
FHGIA6GIAItalyGiara di GenoniGoat11-28-2013MT9210021
FHGIA7GIAItalyGiara di GenoniGoat11-28-2013MT9210031
FHGIA8GIAItalyGiara di GenoniGoat11-28-2013MT9210041
DOI: https://doi.org/10.2478/helm-2022-0021 | Journal eISSN: 1336-9083 | Journal ISSN: 0440-6605
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Language: English
Page range: 152 - 164
Submitted on: Jan 19, 2022
Accepted on: Jul 14, 2022
Published on: Sep 3, 2022
Published by: Slovak Academy of Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 4 times per year
Keywords:
molecular characterization,
COI,
ITS,
phylogeography
Related subjects:
Life sciences,
Zoology,
Ecology,
Life sciences, other,
Medicine,
Clinical medicine,
Microbiology, virology and infection epidemiology

© 2022 M. Chaouadi, F. Scarpa, I. Azzena, P. Cossu, K. Harhoura, M. Aissi, F. Tazerouti, G. Garippa, P. Merella, M. Casu, D. Sanna, published by Slovak Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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