NDLI: Using joint multivariate analyses of leaf morphology and molecular-genetic markers for taxon identification in three hybridizing European white oak species (Quercus spp.)

Content Provider	Springer Nature Link
Author	Rellstab, Christian Bühler, Andreas Graf, René Folly, Catherine Gugerli, Felix
Copyright Year	2016
Abstract	We show that joint multivariate analyses of leaf morphological characters and molecular-genetic markers improve the taxonomic assignment in hybridizing European white oaks. However, model-based approaches using genetic data alone represent straightforward alternatives to laborious, detailed morphological assessments.In European white oaks, species delimitation is debated because of large overlap of morphological characteristics likely due to hybridization.We tested whether joint multivariate analyses of leaf morphology and molecular markers improve the identification of three oak species (Quercus petraea, Quercus pubescens, Quercus robur) compared to approaches using morphological or genetic variables only.We assessed 13 leaf morphological characters and applied eight nuclear microsatellite markers in almost 1400 trees of 71 oak populations across Switzerland. We performed two multivariate approaches with three variable sets (morphology, genetics, combined) and assessed their performance in separating the taxa. We also compared the taxon assignment to a model-based clustering approach (Structure) based on genetic data alone.A joint use of morphological and genetic variables led to an improved taxon assignment. Whereas Q. robur could clearly be separated from the two other taxa, there was a certain overlap between Q. petraea and Q. pubescens. The Structure clustering led to the same taxon assignment in 85 % of the individuals.It is important to consider both morphological and genetic properties in morphologically similar and hybridizing species. However, it might be more efficient to concentrate only on genetic markers than on time-consuming morphological assessments.
Starting Page	669
Ending Page	679
Page Count	11
File Format	PDF
ISSN	12864560
Journal	Annals of Forest Science
Volume Number	73
Issue Number	3
e-ISSN	1297966X
Language	English
Publisher	Springer Paris
Publisher Date	2016-05-02
Publisher Institution	Institut National de la Recherche Agronomique (INRA)
Publisher Place	Paris
Access Restriction	Subscribed
Subject Keyword	Factor analysis of mixed data Introgression Linear discriminant analysis Nuclear microsatellite markers Species assignment Forestry Wood Science & Technology Forestry Management Tree Biology Environment
Content Type	Text
Resource Type	Article
Subject	Ecology Forestry

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in