Advances in genotyping microsatellite markers through sequencing and consequences of scoring methods for <i>Ceratonia siliqua</i> (Leguminosae)

Viruel, Juan; Haguenauer, Anne; Juin, Marianick; Mirleau, Fatma; Bouteiller, Delphine; Boudagher-Kharrat, Magda; Ouahmane, Lahcen; Malfa, Stefano La; Mèdail, Frédéric; Sanguin, Hervé; Feliner, Gonzalo Nieto; Baumel, Alex

doi:10.1002/aps3.1201

Cited by 25 publications

(42 citation statements)

References 41 publications

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“…To identify microsatellite markers, we employed the approach used by Viruel et al. (), in which contigs are mined for microsatellite loci after a de novo assembly. DNA extractions for seven L. bienne individuals from different locations (Appendix ) and corresponding whole genome shotgun libraries were prepared following the methods in Viruel et al.…”

Section: Methods and Resultsmentioning

confidence: 99%

Microsatellite marker development in the crop wild relative Linum bienne using genome skimming

et al. 2020

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Premise Nuclear microsatellite markers were developed for Linum bienne, the sister species of the crop L. usitatissimum, to provide molecular genetic tools for the investigation of L. bienne genetic diversity and structure. Methods and Results Fifty microsatellite loci were identified in L. bienne by means of genome skimming, and 44 loci successfully amplified. Of these, 16 loci evenly spread across the L. usitatissimum reference nuclear genome were used for genotyping six L. bienne populations. Excluding one monomorphic locus, the number of alleles per locus ranged from two to 12. Four out of six populations harbored private alleles. The levels of expected and observed heterozygosity were 0.076 to 0.667 and 0.000 to 1.000, respectively. All 16 loci successfully cross‐amplified in L. usitatissimum. Conclusions The 16 microsatellite loci developed here can be used for population genetic studies in L. bienne, and 28 additional loci that successfully amplified are available for further testing.

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Section: Methods and Resultsmentioning

confidence: 99%

Microsatellite marker development in the crop wild relative Linum bienne using genome skimming

et al. 2020

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“…Thus, we stress the importance to include a significant number of repeated individuals (at least 48) in the first analysis of a new SSRseq panel to (1) coarsely optimize analysis parameters for reliable loci, (2) quantify genotyping error rate and (3) identify and exclude unreliable loci. Such procedure has been implemented only in a limited number of previous studies describing SSRseq methods (5 out of 12 published studies thus far, (De Barba et al 2016;Zhan et al 2017;Bradbury et al 2018;Barbian et al 2018;Viruel et al 2018)) but should be generalized.…”

Section: )mentioning

confidence: 99%

“…Sequence data thus reduces allele homoplasy because alleles of the same size may contain molecular variation that does not translate into size variation such as SNP, indels masking variation in repeat number, or presence of two adjacent SSR motifs with complementary size variation (Darby et al 2016). As a result, SSRseq offers refined genetic diversity estimation and population structure inference (Darby et al 2016;Bradbury et al 2018;Neophytou et al 2018;Viruel et al 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Studies published so far have explored specific technical or analytical aspects of SSRseq. Several bioinformatics approaches have been developed (Hoogenboom et al 2016;Suez et al 2016;Zhan et al 2017; Barbian et al 2018), different laboratory protocols tested (Vartia et al 2016;Pimentel et al 2018) and means to account for molecular variation on population genetic inference compared (Neophytou et al 2018;Viruel et al 2018). Together, these studies explored numerous issues surrounding the technical and analytical advantages of SSRseq over traditional methods, each of them focusing on a given model species making it difficult to assess finding generalization to other biological models.…”

Section: Introductionmentioning

confidence: 99%

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Fast sequence-based microsatellite genotyping development workflow

Lepais

Chancerel

Boury

et al. 2019

Preprint

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AbstractApplication of high-throughput sequencing technologies to microsatellite genotyping (SSRseq) has been shown to remove many of the limitations of electrophoresis-based methods and to refine inference of population genetic diversity and structure. We present here a streamlined SSRseq development workflow that includes microsatellite development, multiplexed marker amplification and sequencing, and automated bioinformatics data analysis. We illustrate its application to five groups of species across phyla (fungi, plant, insect and fish) with different levels of genomic resource availability. We found that relying on previously developed microsatellite assay is not optimal and leads to a resulting low number of reliable locus being genotyped. In contrast, de novo ad hoc primer designs gives highly multiplexed microsatellite assays that can be sequenced to produce high quality genotypes for 20 to 40 loci. We highlight critical upfront development factors to consider for effective SSRseq setup in a wide range of situations. Sequence analysis accounting for all linked polymorphisms along the sequence, quickly generates a powerful multi-allelic haplotype-based genotypic dataset, calling to new theoretical and analytical frameworks to extract more information from multi-nucleotide polymorphism marker systems.

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“…Sequence data thus reduces allele homoplasy because alleles of the same size may contain molecular variation that does not translate into size variation such as SNP, indels masking variation in repeat number, or presence of two adjacent SSR motifs with complementary size variation (Darby et al, 2016). As a result, SSRseq offers refined genetic diversity estimation and population structure inference (Darby et al, 2016;Bradbury et al, 2018;Neophytou et al, 2018;Viruel et al, 2018;Layton et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Fast sequence-based microsatellite genotyping development workflow

Lepais

Chancerel

Boury

et al. 2020

PeerJ

View full text Add to dashboard Cite

Application of high-throughput sequencing technologies to microsatellite genotyping (SSRseq) has been shown to remove many of the limitations of electrophoresis-based methods and to refine inference of population genetic diversity and structure. We present here a streamlined SSRseq development workflow that includes microsatellite development, multiplexed marker amplification and sequencing, and automated bioinformatics data analysis. We illustrate its application to five groups of species across phyla (fungi, plant, insect and fish) with different levels of genomic resource availability. We found that relying on previously developed microsatellite assay is not optimal and leads to a resulting low number of reliable locus being genotyped. In contrast, de novo ad hoc primer designs gives highly multiplexed microsatellite assays that can be sequenced to produce high quality genotypes for 20–40 loci. We highlight critical upfront development factors to consider for effective SSRseq setup in a wide range of situations. Sequence analysis accounting for all linked polymorphisms along the sequence quickly generates a powerful multi-allelic haplotype-based genotypic dataset, calling to new theoretical and analytical frameworks to extract more information from multi-nucleotide polymorphism marker systems.

show abstract

Advances in genotyping microsatellite markers through sequencing and consequences of scoring methods for Ceratonia siliqua (Leguminosae)

Cited by 25 publications

References 41 publications

Microsatellite marker development in the crop wild relative Linum bienne using genome skimming

Microsatellite marker development in the crop wild relative Linum bienne using genome skimming

Fast sequence-based microsatellite genotyping development workflow

Fast sequence-based microsatellite genotyping development workflow

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