Transcriptomics

Dataset Information

0

Conservation genomics of Atlantic salmon (Year Two)


ABSTRACT: Due to difficulties inherent in designating conservation units for effective species management and conservation, the use of multiple complementary sources of information is required to identify and assess the designation of conservation units based on the degree of variation among populations within a species. In this study, we combined estimates of microsatellite and transcriptomic variation to assess the population structure and potential for adaptive variation of threatened Atlantic salmon, Salmo salar, among rivers in the Bay of Fundy. In general, population structure identified by genetic differentiation was consistent with the patterns of variation in gene expression. Both data sets provided clear indication of strong regional differentiation between rivers located within the inner Bay of Fundy relative to rivers located within the outer Bay of Fundy or the Southern Uplands region. There was also support for more refined population structure; there was some differentiation in both microsatellite and gene expression patterns between salmon from rivers in the two regions of the inner Bay of Fundy: Chignecto Bay and Minas Basin. Consistent patterns apparent in the genetic and transcriptomic dataset indicate that Atlantic salmon populations from the inner and outer Bay of Fundy reflect unique genetic lineages, with some evidence of unique genetic legacies between regions of the inner Bay of Fundy, and even between individual rivers within a region. Consistency of the microarray data across two years helps to validate the use of this technique as a useful tool in assessment of variation among wild populations for species conservation.

ORGANISM(S): Osmerus mordax Salmo salar Oncorhynchus tshawytscha Oncorhynchus mykiss Coregonus clupeaformis

PROVIDER: GSE19119 | GEO | 2009/11/25

SECONDARY ACCESSION(S): PRJNA123759

REPOSITORIES: GEO

Dataset's files

Source:
Action DRS
Other
Items per page:
1 - 1 of 1

Similar Datasets

2009-11-25 | GSE19111 | GEO
2010-05-19 | E-GEOD-19111 | biostudies-arrayexpress
2010-05-19 | E-GEOD-19119 | biostudies-arrayexpress
2010-05-19 | E-GEOD-19170 | biostudies-arrayexpress
2021-04-23 | GSE173119 | GEO
2011-08-20 | E-TABM-1065 | biostudies-arrayexpress
| PRJNA120581 | ENA
2024-01-12 | GSE253087 | GEO
2023-01-11 | MODEL2207070001 | BioModels
| PRJNA123737 | ENA