Behavioral Genetics and Animal Domestication - Genetics and the Behavior of Domestic Animals - page 59

extremely high, increasing the likelihood of such sweeps occurring, though
this is also dependent on the genetic architecture of the trait ( Pritchard
and Di Rienzo, 2010 ). Such sweeps have been seen in the chicken, where
around 50 40-kb regions were putatively identified as being under selection
in domestic layer and broiler populations ( Rubin et al., 2010 ), the dog (with
blocks of around 106 kb in length ( Goldstein et al., 2006 )), and even the
stickleback (sweep sizes between 20 kb and 90 kb in size ( Makinen et al.,
2008 )). This approach is particularly powerful when multiple domestic popu-
lations are analyzed, with shared regions of identity-by-descent identified,
and has been used to locate both discrete mutations (for example the pea
comb ( Wright et al., 2009 ) and yellow skin ( Eriksson et al., 2008 ) mutations
in chickens) and mutations affecting quantitative traits (QTNs), for example
pig fatness ( Van Laere et al., 2003 ), cattle twinning rate ( Meuwissen et al.,
2002 ) and milk production ( Riquet et al., 1999 ), and comb size in chickens
(Johnson et al., 2012).
MAPPING GENES FOR BEHAVIOR—BOTTOM-UP
APPROACHES
With this approach, research starts at the gene level and is built-up to the behav-
ioral phenotype. At its purest form, gene knock-outs, knock-downs (whereby
the expression of a gene is reduced using a variety of different techniques), and
transgenics (the insertion of a novel gene into a genome) ( Flint and Mott, 2001 )
can be used to directly study the effects of individual genes, though one must
still find which genes should be perturbed prior to analysis. Often such research
therefore starts with a mutagenesis screen, whereby large numbers of mutant
individuals are generated and then bulk screened for alterations to the behavior
of interest ( Nadeau and Frankel, 2000 ).
Such an approach has produced many of the early successes with behavioral
gene identification, though these were restricted to circadian rhythm in
Drosophila ( Sawyer et al., 1997; Tully, 1996 ), social aggregation in C. elegans
( Coates and de Bono, 2002; de Bono et al., 2002 ) and larval foraging in
Drosophila ( de Belle and Sokolowksi, 1989; Sokolowski, 1998 ), so the rele-
vance to domesticated animals may be lower, especially considering the size
and generation times of many of the domestic animals under investigation.
Moving up, global gene expression analysis, traditionally through microar-
ray analysis though more recently through RNA-sequencing (whole-genome
sequencing of the transcriptome) gives more precise measures of transcription
( Wang et al., 2009 ). The issue with this approach is the amount of data gener-
ated and interpreting it. For instance, what tissue does one look in and at what
time point? A particular gene may be limited in its expression to a very narrow
window and even then relatively modest differences in expression may cause
the phenotypic change. Additionally, if you find differentially expressed genes
between populations for example, many hundreds or even thousands can be