Fine mapping of a quantitative trait locus on chromosome 9 affecting non‐return rate in Swedish dairy cattle

Abstract

We previously mapped a quantitative trait locus (QTL) affecting the trait non-return rate at 56 days in heifers to bovine chromosome 9. The purpose of this study was to confirm and refine the position of the QTL by using a denser marker map and fine mapping methods. Five families that previously showed segregation for the QTL were included in the study. The mapping population consisted of 139 bulls in a granddaughter design. All bulls were genotyped for 25 microsatellite markers surrounding the QTL on chromosome 9. We also analysed the correlated trait number of inseminations per service period in heifers. Both traits describe the heifer's ability to become pregnant after insemination. Linkage analysis, linkage disequilibrium and combined linkage and linkage disequilibrium analysis were used to analyse the data. Analysis of the families jointly by linkage analysis resulted in a significant but broad QTL peak for non-return rate. Results from the combined analysis gave a sharp QTL peak with a well-defined maximum in between markers BMS1724 and BM7209, at the same position as where the highest peak from the linkage disequilibrium analysis was found. One of the sire families segregated clearly at this position and the difference in effects between the two sire haplotypes was 2.9 percentage units in non-return rate. No significant results were found for the number of inseminations in the combined analysis.

Validation of associations for female fertility traits in Nordic Holstein, Nordic Red and Jersey dairy cattle

“…Two separate studies [20,21] detected a QTL for non-return rate near the marker TGLA73 (76.7 Mb), which coincides with the BTA9 region containing SNPs detected for AISC, FTI, IFLC and NRRC in the present study. Combined linkage and linkage disequilibrium analysis were used to fine-map this QTL to 27 cM [22], and a QTL for heat intensity was detected near the marker BMS817 (39.3 Mb) [21], which coincides with the QTLs we detected for AISH, AISC, FTI, ICF, IFLC, IFLH, NRRC, and NRRH.…”

Excited State Properties and Energy Transfer within Dipyrrin‐Based Binuclear Iridium/Platinum Dyads: The Effect of ortho‐Methylation on the Spacer

“…The BLUP, REML and Bayesian analysis methods incorporate common fixed effects for particular loci and ‘residual’ random effects of remaining polygenes to provide more exact results 7, 43, 45. Another approach for obtaining more exact results is also to use particular loci as random effects with IBD to account for their variability 8, 55…”

“…IBD describes the probable positional relationships between each marker/QTL pair and the probability of inheriting the paternal or maternal QTL allele. The construction of IBD depends on whether linkage analysis (LA), linkage disequilibrium (LD) or a combination of both methods (LDLA) was used to determine linkage status 8. In this context, several teams have developed algorithms for the construction of an IBD matrix 41, 44, 55.…”

“…Recently, the evaluation of animal performance based on molecular‐genetic information has become more widespread. Dairy cattle populations evaluated for several groups of traits of moderate and low heritability (production, conformation, reproduction) using genetic markers have been presented by several authors2–8 as well as in Interbull Bulletin No. 39 9.…”

Mouse models for identifying genes modulating fertility parameters

“…Several recent studies taking into account fertility parameters alongside other production traits illustrate this point (Kirkpatrick et al, 2000;Lien et al, 2000;Boichard et al, 2003;Ashwell et al, 2004;Schnabel et al, 2005). To the best of our knowledge, only four studies in cattle focused exclusively on fertility traits (Holmberg and Andersson-Eklund, 2006;Guillaume et al, 2007;Holmberg et al, 2007;Schulman et al, 2008), while the other studies involve the phenotyping of other production traits. Loci involved mainly in female fertility were identified (see Table 1).…”