2026-04-17T13:15:22Zhttps://recercat.cat/oai/requestoai:recercat.cat:20.500.12327/29282025-10-22T11:28:41Zcom_2072_4428com_2072_4427col_2072_487898
RECERCAT
author
Fernández, Ana I.
author
Pérez-Montarelo, Dafne
author
Barragán, Carmen
author
Ramayo-Caldas, Yuliaxis
author
Ibanez-Escriche, Noelia
author
Castelló, Anna
author
Noguera, José Luis
author
Silió, Luis
author
Folch, Josep María
author
Rodríguez, M Carmen
other
Producció Animal
group
Genètica i Millora Animal
2025-10-22T11:28:41Z
2025-10-22T11:28:41Z
2012-05-20
Fernández, Ana, Dafne Pérez-Montarelo, C. Barragán, Yuliaxis Ramayo-Caldas, Noelia Ibáñez‐Escriche, Anna Castelló, J. L. Noguera, L. Silió, Josep María Folch, and M. C. Rodríguez. 2012. “Genome-wide Linkage Analysis of QTL for Growth and Body Composition Employing the PorcineSNP60 BeadChip.” BMC Genomic Data 13 (1): 41. doi:10.1186/1471-2156-13-41.
1471-2156
http://hdl.handle.net/20.500.12327/2928
https://doi.org/10.1186/1471-2156-13-41
Background: The traditional strategy to map QTL is to use linkage analysis employing a limited number of markers.
These analyses report wide QTL confidence intervals, making very difficult to identify the gene and polymorphisms
underlying the QTL effects. The arrival of genome-wide panels of SNPs makes available thousands of markers
increasing the information content and therefore the likelihood of detecting and fine mapping QTL regions. The
aims of the current study are to confirm previous QTL regions for growth and body composition traits in different
generations of an Iberian x Landrace intercross (IBMAP) and especially identify new ones with narrow confidence
intervals by employing the PorcineSNP60 BeadChip in linkage analyses.
Results: Three generations (F3, Backcross 1 and Backcross 2) of the IBMAP and their related animals were
genotyped with PorcineSNP60 BeadChip. A total of 8,417 SNPs equidistantly distributed across autosomes were
selected after filtering by quality, position and frequency to perform the QTL scan. The joint and separate analyses
of the different IBMAP generations allowed confirming QTL regions previously identified in chromosomes 4 and 6
as well as new ones mainly for backfat thickness in chromosomes 4, 5, 11, 14 and 17 and shoulder weight in
chromosomes 1, 2, 9 and 13; and many other to the chromosome-wide signification level. In addition, most of the
detected QTLs displayed narrow confidence intervals, making easier the selection of positional candidate genes.
Conclusions: The use of higher density of markers has allowed to confirm results obtained in previous QTL scans
carried out with microsatellites. Moreover several new QTL regions have been now identified in regions probably
not covered by markers in previous scans, most of these QTLs displayed narrow confidence intervals. Finally,
prominent putative biological and positional candidate genes underlying those QTL effects are listed based on
recent porcine genome annotation.
eng
Attribution 4.0 International
Genome-wide linkage analysis of QTL for growth and body composition employing the PorcineSNP60 BeadChip
info:eu-repo/semantics/article