Highlights
- •The SPInDel (Species Identification by Insertions/Deletions) was tested in plants.
- •Four variable-length cpDNA regions were suitable for the SPInDel.
- •A high level of species discrimination was achievable by combining three regions.
- •Low intra-species variability was observed in variable-length sequences.
- •The SPInDel approach can be used for the identification of plant species.
Abstract
The correct identification of species in the highly divergent group of plants is crucial
for several forensic investigations. Previous works had difficulties in the establishment
of a rapid and robust method for the identification of plants. For instance, DNA barcoding
requires the analysis of two or three different genomic regions to attain reasonable
levels of discrimination. Therefore, new methods for the molecular identification
of plants are clearly needed. Here we tested the utility of variable-length sequences
in the chloroplast DNA (cpDNA) as a way to identify plant species. The SPInDel (Species
Identification by Insertions/Deletions) approach targets hypervariable genomic regions
that contain multiple insertions/deletions (indels) and length variability, which
are found interspersed with highly conserved regions. The combination of fragment
lengths defines a unique numeric profile for each species, allowing its identification.
We analysed more than 44,000 sequences retrieved from public databases belonging to
206 different plant families. Four target regions were identified as suitable for
the SPInDel concept: atpF-atpH, psbA-trnH, trnL CD and trnL GH. When considered alone, the discrimination power of each region was low, varying
from 5.18% (trnL GH) to 42.54% (trnL CD). However, the discrimination power reached more than 90% when the length of some
of these regions is combined. We also observed low diversity in intraspecific data
sets for all target regions, suggesting they can be used for identification purposes.
Our results demonstrate the utility of the SPInDel concept for the identification
of plants.
Keywords
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Article info
Publication history
Published online: May 29, 2018
Accepted:
May 28,
2018
Received in revised form:
May 10,
2018
Received:
December 18,
2017
Identification
Copyright
© 2018 Elsevier B.V. All rights reserved.
