- •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.
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.
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Published online: May 29, 2018
Accepted: May 28, 2018
Received in revised form: May 10, 2018
Received: December 18, 2017
© 2018 Elsevier B.V. All rights reserved.