The mitochondrial genomes of Atlas Geckos (<i>Quedenfeldtia</i>): mitogenome assembly from transcriptomes and anchored hybrid enrichment datasets

Lyra, Mariana L.; Joger, Ulrich; Schulte, Ulrich; Slimani, Tahar; Mouden, El Hassan El; Bouazza, Abdellah; Künzel, Sven; Lemmon, Alan R.; Lemmon, Emily Moriarty; Vences, Miguel

doi:10.1080/23802359.2017.1339212

Cited by 6 publications

(3 citation statements)

References 18 publications

(26 reference statements)

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“…The remaining portion of the sequence data, that is off‐target sequences, is often ignored in many sequence capture studies, but several recent studies have exploited this by‐catch to extract legacy loci used in past phylogenetic studies (e.g. Barrow et al., 2017; Branstetter et al., 2021; Caparroz et al., 2018; Gasc et al., 2016; Guo et al., 2012; Łukasik et al., 2019; Lyra et al., 2017; Matsuura et al., 2018; Percy et al., 2018; Simon et al., 2019; Taucce et al., 2018). Our study sought to recover legacy loci from off‐target sequences in a sequence capture data set using published legacy data, explore approaches to improve legacy locus recovery, and perform a phylogenetic analysis on a concatenated data set comprised of legacy loci and UCE data.…”

Section: Discussionmentioning

confidence: 99%

Extracting ‘legacy loci’ from an invertebrate sequence capture data set

et al. 2021

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Sequence capture studies result in rich data sets comprising hundreds to thousands of targeted genomic regions that are superseding Sanger‐based data sets comprised of a few well‐known loci with historical uses in phylogenetics (‘legacy loci’). However, integrating sequence capture and Sanger‐based data sets is of interest as legacy loci can include different types of loci (e.g. mitochondrial and nuclear) across a potentially larger sample of species from past studies. Sequence capture data sets include nontargeted sequences, and there has been recent interest in extracting legacy loci from invertebrate data sets. Here, we use published legacy data from leaf‐footed bugs (Hemiptera: Coreoidea) to recover 15 mitochondrial and seven nuclear legacy loci from off‐target sequences in a sequence capture data set, explore approaches to improve legacy locus recovery, and combine these loci with sequence capture data for phylogenetic analysis. Two nuclear loci were determined to already be targeted by sequence capture baits. Most of the remaining loci were successfully recovered from off‐target sequences, but this recovery varied greatly. Additionally, complementing complete mitogenomes with additional reference mitochondrial sequences from a genetic depository did not offer improvement for most of our taxa; however, supplementing these reference sequences with extracted legacy loci offered ≥6% improvement across taxa for a given mitochondrial locus (negligible improvement for nuclear loci). Phylogenetic analysis of legacy and sequence capture data produced a topology generally congruent with recent studies, but support was lower. Thus, future studies may employ the approaches used in this study to integrate legacy data with newly generated sequence capture data sets without added expenses.

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Section: Discussionmentioning

confidence: 99%

Extracting ‘legacy loci’ from an invertebrate sequence capture data set

et al. 2021

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“…Whole genome sequencing (WGS) will inherently capture the organellar genome in addition to nuclear sequences, and researchers should make full use of these data by assembling and annotating these genomes. Perhaps more surprisingly, targeted sequence capture methods like UCEs and AHEs also tend to return organellar sequences, which should be fully utilized in subsequent evolutionary analyses (Caparroz et al, 2018; Derkarabetian et al, 2019; Lemmon et al, 2012; Lyra et al, 2017; Miller et al, 2022; Raposo do Amaral et al, 2015; Simon et al, 2019; Zarza et al, 2018). Finally, several RADseq/GBS studies have isolated and analysed organellar markers to provide a more comprehensive perspective on evolutionary history (Du et al, 2020; Meger et al, 2019; Stobie et al, 2019).…”

Section: Figurementioning

confidence: 99%

Organellar DNA continues to provide a rich source of information in the genomics era

Blair

2023

Molecular Ecology

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Next-generation sequencing (NGS) and genomics continue to transform how biologists address fundamental questions in ecology and evolution. The quantity of data that can be generated quickly and cheaply enable researchers to interrogate genomes for hundreds or thousands of loci that can be used for evolutionary inference. This phenomenon had led to an important paradigm shift in how phylogenetic, phylogeographic, and population genomic studies are designed.Historically, mitochondrial DNA (mtDNA) was the primary molecular marker used to estimate evolutionary history and demographic parameters in animals (Avise, 2000;Avise et al., 1987), whereas chloroplast markers were used extensively in plant phylogenetics and phylogeography (Bonatelli et al., 2013;Hickerson et al., 2010;Soltis et al., 1997). Subsequently, microsatellites became a popular multilocus, fragment-based method used to investigate population structure in the nuclear genome. More recently, methods and markers such as RADseq and its derivatives (Baird et al., 2008;Elshire et al., 2011;Peterson et al., 2012), ultraconserved elements (UCEs; Faircloth et al., 2012), anchored hybrid enrichment (AHEs;Lemmon et al., 2012), transcriptomes, and whole genomes have emerged to take full advantage of the power of NGS technologies. The potential resolution provided by thousands of loci is impressive, but not without challenges. Issues with assembly, paralogy, variant calling, phasing, and sequencing errors can all impact subsequent evolutionary inference. Another major issue that can impact these genomic

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“… 2020 ), even in the gecko family Sphaerodactylidae (Lyra et al. 2017 ; Tarroso et al. 2017 ), with the latter being the second most diverse family within Gekkota.…”

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confidence: 99%

A complete mitogenome of the Przewalski’s Wonder Gecko (Teratoscincus przewalskii) from the Junggar Basin in Northwest China with its phylogenetic implications

Guo

2023

Mitochondrial DNA Part B

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A complete mitogenome of the Przewalski’s Wonder Gecko ( Teratoscincus przewalskii ) from the Junggar Basin in Northwest China was determined by using polymerase chain reaction and directly sequenced with the primer walking method. The total length was 17,184 bp, containing 13 protein-coding genes (PCGs), 22 transfer RNA genes (tRNAs), two ribosomal RNA genes (rRNAs) and a control region (CR). The order and structure of the genes were identical to those of congeners. The 13 PCGs contain four start codons (ATG, GTG, ATA, and ATC), three complete stop codons (TAA, TAG, and AGG), and two incomplete stop codons (T–, TA-). The concatenated PCGs were used to perform Bayesian phylogenetic analyses together with mitogenome data of the family Sphaerodactylidae and related representative taxa available in GenBank. The resulting tree recovered the monophyly of Sphaerodactylidae, and confirmed the sister relationship between T. przewalskii and T. roborowskii with strong support. The newly determined mitogenome will provide fundamental data for understanding the population genetic structure of T. pzrewalskii in particular, and the mitochondrial DNA evolution in Sphaerodactylidae in general.

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The mitochondrial genomes of Atlas Geckos (Quedenfeldtia): mitogenome assembly from transcriptomes and anchored hybrid enrichment datasets

Cited by 6 publications

References 18 publications

Extracting ‘legacy loci’ from an invertebrate sequence capture data set

Extracting ‘legacy loci’ from an invertebrate sequence capture data set

Organellar DNA continues to provide a rich source of information in the genomics era

A complete mitogenome of the Przewalski’s Wonder Gecko (Teratoscincus przewalskii) from the Junggar Basin in Northwest China with its phylogenetic implications

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