Information content in genome-wide scans: concordance between patterns of genetic differentiation and linkage mapping associations.
BACKGROUND
Scanning the genome with high density SNP markers has become a standard approach for identifying regions of the genome showing substantial between-population genetic differentiation, and thus evidence of diversifying selection. Such regions may contain genes of large phenotypic effect. However, few studies have attempted to address the power or efficacy of such an approach.


RESULTS
In this study, the patterns of allele frequency differences between two cattle breeds based on the Bovine HapMap study were compared with statistical evidence for QTL based on a linkage mapping study of an experimental population formed by a cross between the same breeds. Concordance between the two datasets was seen for chromosomes carrying QTL with strong statistical support, such as BTA5 and BTA18, which carry genes associated with coat color. For these chromosomes, there was a correspondence between the strength of the QTL signal along the chromosome and the degree of genetic differentiation between breeds. However, such an association was not seen in a broader comparison that also included chromosomes carrying QTL with lower significance levels. In addition, other chromosomal regions with substantial QTL effects did not include markers showing extreme between-breed genetic differentiation. Furthermore, the overall consistency between the two studies was weak, with low genome-wide correlation between the statistical values obtained in the linkage mapping study and between-breed genetic differentiation from the HapMap study.


CONCLUSIONS
These results suggest that genomic diversity scans are capable of detecting regions associated with qualitative traits but may be limited in their power to detect regions associated with quantitative phenotypic differences between populations, which may depend on the marker resolution of the study and the level of LD in the populations under investigation.
The Roslin Institute and R(D)SVS, University of Edinburgh, Roslin, Midlothian EH25 9PS, UK. pam.wiener@roslin.ed.ac.uk
Pamela
P
Wiener
Mohammad A
MA
Edriss
John L
JL
Williams
David
D
Waddington
Andrew
A
Law
John A
JA
Woolliams
Beatriz
B
Gutiérrez-Gil
D000818:Animals; D002417:Cattle; D002874:Chromosome Mapping / Q000379:methods*; D005787:Gene Frequency / Q000235:genetics; D055106:Genome-Wide Association Study / Q000379:methods*; D040641:Quantitative Trait Loci / Q000235:genetics
Genetics. 2008 Sep;180(1):583-99
18723892
Nature. 1993 Apr 15;362(6421):587-8
8385273
Proc Natl Acad Sci U S A. 2010 Jan 19;107(3):1160-5
20080661
J Dairy Sci. 2005 Jul;88(7):2643-51
15956326
Anim Genet. 2008 Feb;39(1):51-61
18254735
Science. 2007 Apr 6;316(5821):112-5
17412960
Anim Genet. 2007 Apr;38(2):109-13
17302792
Genet Res. 1993 Dec;62(3):195-203
8157171
BMC Genet. 2007 Aug 16;8:56
17705851
J Comput Biol. 2000 Feb-Apr;7(1-2):203-14
10890397
Genetics. 2009 May;182(1):233-49
19255369
J Hered. 2008 Nov-Dec;99(6):629-38
18784067
Mamm Genome. 1995 Sep;6(9):636-9
8535072
BMC Genomics. 2009 Apr 24;10:178
19393047
Genetics. 2009 Nov;183(3):951-64
19720859
Bioinformatics. 2002 Feb;18(2):339-40
11847090
PLoS One. 2009 Aug 12;4(8):e6595
19672461
Science. 2009 Apr 24;324(5926):528-32
19390050
J Anim Sci. 2009 Jan;87(1):24-36
18791160
Genome Res. 2002 Dec;12(12):1805-14
12466284
Genetics. 2003 Jan;163(1):253-66
12586713
Genome Res. 2004 Oct;14(10A):1987-98
15466297
Heredity (Edinb). 2007 Sep;99(3):313-21
17593945
J Anim Sci. 2008 Jan;86(1):1-16
17785604
BMC Genomics. 2009 Apr 24;10:180
19393050
PLoS One. 2008 Sep 11;3(9):e3183
18784841
BMC Genet. 2009 Aug 04;10:43
19653884
Anim Genet. 2009 Dec;40(6):975-7
19531114
Genetics. 1994 Mar;136(3):1195-207
8005424
Mamm Genome. 1996 Apr;7(4):317-8
8661706
Am J Hum Genet. 2001 Nov;69(5):1080-94
11590548
Genetics. 2010 Aug;185(4):1451-61
20479146
Anim Genet. 2009 Apr;40(2):176-84
19067671
Evolution. 1984 Nov;38(6):1358-1370
28563791