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Putative secondary structures of mitochondrial tRNAs determined in A. urmiana. Nucleotides in red color indicate anticodon sequences.

Putative secondary structures of mitochondrial tRNAs determined in A. urmiana. Nucleotides in red color indicate anticodon sequences.

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Article
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In the previously published mitochondrial genome sequence of Artemia urmiana (NC_021382 [JQ975176]), the taxonomic status of the examined Artemia had not been determined, due to parthenogenetic populations coexisting with A. urmiana in Urmia Lake. Additionally, NC_021382 [JQ975176] has been obtained with pooled cysts of Artemia (0.25 g cysts consis...

Contexts in source publication

Context 1
... The shortest and longest tRNAs were tRNA-Ala, tRNA-Ley (59 bp), and tRNA-Ser 2 (67 bp), respectively (Figure 3). Diversity ...
Context 2
... highest and lowest values of AT percentage in tRNAs were detected in tRNA-Glu (80.3%) and tRNA-Ser1 (47.7%), respectively. The shortest and longest tRNAs were tRNA-Ala, tRNA-Ley (59 bp), and tRNA-Ser2 (67 bp), respectively (Figure 3). ...
Context 3
... genes start with ATC (ATP8 and ND4L), GTG (ATP6 and ND6), or ATT (ND3) and ATA (ND4). Stop codons are TAA (ND2, ATP8, ATP6, COX3, ND4L, CYTB, and ND1), TAG Figure 3. Putative secondary structures of mitochondrial tRNAs determined in A. urmiana. ...

Citations

Article
We document morphology and genetic relatedness of morphotypes within the Artemia franciscana that has colonized Covelong saltern in Kelambakkam (South India). They exhibits high phenotypic plasticity and intra-population variation in a supposedly panmictic population. Morphometric analysis was carried out on 18 traits in males and 15 in females and subjected to multivariate analysis. Three types each in males (M1, M3 and M4) and females (F1, F2 and F3) were singled out. The axes in the plot explain 77.9% in males and 73.9% in females of the variation through discriminant function analysis. The sequence divergence of the population was evaluated through mtDNA (16S rRNA) and nDNA (p26 gene) markers. The substantial sequence divergence was observed between the morphotypes through nDNA and appearing sequence divergence was recognized by mtDNA. Likewise, phylogenetic analyses of maximum likelihood and Bayesian analysis through nDNA revealed a maximum similarities between M1, M4 with F1 & F2 and M3 with F3. Further, haplotype distribution of nDNA revealed unique haplotype between M1 and M4 with F1 and F2 morphotypes. This study thus confirms the occurrence of morphotypes with specific characteristics inside a seemingly homogeneous population.
Article
Full-text available
Online repositories of DNA sequences are a rich and indispensable source of comparative data for biodiversity research and taxonomic studies. Despite increasingly high data quality of published sequences and associated metadata, particular attention should be paid to taxonomic assignment of DNA sequences, in particular if voucher specimens were not available or could not be examined. In this study, two nearly identical mitogenomes of two distinctive plover species (Charadrius alexandrinus and C. placidus) were re‐analysed and compared to a comprehensive data set of DNA‐barcode sequences (cytochrome‐oxidase subunit 1, COI) for 55 shorebird species. Phylogenetic analysis separated the two plover species in two reciprocally monophyletic clades that differed by mean p‐distances of 11.5–14.7%, however the COI sequence from the C. placidus mitogenome was nested in the Kentish Plover clade (C. alexandrinus). A similar mismatch was found for another DNA‐barcode sequence from a C. mongolus mitogenome that clustered with one of two clades of C. leschenaultii in the COI tree. These results strongly suggest that to date two out of seven mitogenomes published for Charadriidae are not representative of the taxon names the respective Genbank entries were assigned to. Only a few DNA‐barcode sequences were associated with outdated taxonomy, others were suspected to be chimeric sequences. Thus, free access to digital sequence information is a key factor for steady improvement of data quality in online repositories via swarm intelligence of the scientific community.