Predicting genotype environmental range from genome–environment associations. Issue 13 (6th June 2018)
- Record Type:
- Journal Article
- Title:
- Predicting genotype environmental range from genome–environment associations. Issue 13 (6th June 2018)
- Main Title:
- Predicting genotype environmental range from genome–environment associations
- Authors:
- Manel, Stéphanie
Andrello, Marco
Henry, Karine
Verdelet, Daphné
Darracq, Aude
Guerin, Pierre‐Edouard
Desprez, Bruno
Devaux, Pierre - Abstract:
- Abstract: Genome–environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single‐locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14, 409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction ( I ) of aridity‐associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress‐aridity conditions and could be used to improve the resistance of cultivatedAbstract: Genome–environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single‐locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14, 409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction ( I ) of aridity‐associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress‐aridity conditions and could be used to improve the resistance of cultivated varieties to aridity. … (more)
- Is Part Of:
- Molecular ecology. Volume 27:Issue 13(2018)
- Journal:
- Molecular ecology
- Issue:
- Volume 27:Issue 13(2018)
- Issue Display:
- Volume 27, Issue 13 (2018)
- Year:
- 2018
- Volume:
- 27
- Issue:
- 13
- Issue Sort Value:
- 2018-0027-0013-0000
- Page Start:
- 2823
- Page End:
- 2833
- Publication Date:
- 2018-06-06
- Subjects:
- genome scan -- genome–environment association -- landscape genomics -- predictive landscape genetics
Molecular ecology -- Periodicals
Molecular population biology -- Periodicals
576 - Journal URLs:
- http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code=mec&close=1999#C1999 ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-294X ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/mec.14723 ↗
- Languages:
- English
- ISSNs:
- 0962-1083
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5900.817360
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7000.xml