2018
DOI: 10.1002/aps3.1196
|View full text |Cite
|
Sign up to set email alerts
|

In silico detection of polymorphic microsatellites in the endangered Isis tamarind, Alectryon ramiflorus (Sapindaceae)

Abstract: Premise of the Study Alectryon ramiflorus (Sapindaceae) is an endangered rainforest tree known from only two populations. In this study, we identified polymorphic microsatellites, in silico, improving the effectiveness and efficiency of microsatellite development of nonmodel species. The development of genetic markers will support future conservation management of the species.Methods and ResultsWe used next‐generation sequencing and bioinformatics to detect polymorphic microsatellites, in silico, reducing both… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2019
2019
2019
2019

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 10 publications
0
1
0
Order By: Relevance
“…The application of a microsatellite‐picking tool such as pal_finder typically results in tens of thousands of potential loci, and therefore it makes logical sense to attempt to apply in silico marker optimisation methods over laboratory optimisation, to increase the efficiency in identifying informative loci. MiMi is the first tool, to our knowledge, that allows this range of important characteristics to be observed at the marker design stage (but see Nichols, Conroy, Kasinadhuni, Lamont, & Ogbourne, ). In a direct comparison between the traditional and MiMi methods, we show that the application of MiMi resulted in a 58% increase in the rate of identification of informative microsatellite markers, facilitating a 16% reduction in costs associated with the development of a microsatellite marker panel.…”
Section: Discussionmentioning
confidence: 99%
“…The application of a microsatellite‐picking tool such as pal_finder typically results in tens of thousands of potential loci, and therefore it makes logical sense to attempt to apply in silico marker optimisation methods over laboratory optimisation, to increase the efficiency in identifying informative loci. MiMi is the first tool, to our knowledge, that allows this range of important characteristics to be observed at the marker design stage (but see Nichols, Conroy, Kasinadhuni, Lamont, & Ogbourne, ). In a direct comparison between the traditional and MiMi methods, we show that the application of MiMi resulted in a 58% increase in the rate of identification of informative microsatellite markers, facilitating a 16% reduction in costs associated with the development of a microsatellite marker panel.…”
Section: Discussionmentioning
confidence: 99%