Supplementary Methods
The microarray and hybridization
The Lund-zfa array is a custom Affymetrix array produced for the zebra finch [1]. It
contains approximately 22600 ESTs, representing approximately 15800 non-redundant
genes, and each EST is represented by 11 (25 bases long) probes (except for 148 ESTs
that are represented by 8-10 probes). In total, there are 254430 probes on the array.
The array contains no Affymetrix mismatch probes. High-quality total-RNA samples
representing each individual (the 40 zebra finch samples) were delivered to the
Swegene Center for Integrative Biology at Lund University (SCIBLU genomics,
http://www.lth.se/sciblu), Lund, Sweden, where they were hybridized according to
standard Affymetrix protocols for RNA (see Naurin et al. [1,2] for a detailed description
of the hybridization procedures). Signal intensities were normalized and filtered as
previously described and to ensure high quality signal intensity measurements, we
excluded ESTs that had not retained all 11 probes in a previous comparative genome
hybridization analysis [cf. 1,2].
EST annotation and chromosome position
Estimations of redundancies amongst the ESTs on the array had previously been made
using the annotations produced for each sequence in the ESTIMA: songbird build 2
assembly [1,3]. Here, we used BLAST analyses against the 3.2.4-build of the zebra finch
genome (http://www.ncbi.nlm.nih.gov/genome/guide/finch/) to generate annotation
of chromosome and position, which in turn were used to remove redundancies and to
compare autosomal and Z-chromosome gene expression. We used a cut off E-value of
10-10 for significant hits, and included only single hits (when more than one significant
match occurred the best hit had to be <10-10 and the next nearest hit had to be more
than 10-10 weaker) and hits separated by at least 5 kbp in the zebra finch genome. Our
analyses are based on 10695 ESTs (10131 autosomal; 564 Z-linked). Data are available
from the Dryad Digital Repository: http://dx.doi.org/10.5061/dryad.ps515.
Linear mixed models
Gene expression (log2 signal intensity) was analysed with linear mixed models in the R
package nlme [4]. The model included three fixed factors (‘sex’: male or female;
‘chromosomal location’: autosomal or Z-linked; ‘inbreeding treatment’: inbred or
outbred) and their interactions. To account for array effects, ‘individual identity’ was
included as random factor. Significances of the fixed factors and their interactions were
calculated with F-tests using the anova option in R. The denominator degrees of freedom
as shown in Table 1 are upper bounds. There is no ‘correct’ denominator degrees of
freedom because the F-test is an approximation of the mixed model, but since the real
degrees of freedom should be lower than the upper bound the present test is
conservative [4, 5]. Note also that the fixed effect of main interest in the present study,
i.e. inbreeding treatment, was consistently associated with very low F-values (Table 1).
1.
Naurin S, Hansson B, Hasselquist D, Kim YH, Bensch S. 2011 The sex-biased brain:
sexual dimorphism in gene-expression in two species of songbirds. BMC Genomics 12,
37.
2.
Naurin S, Bensch S, Hansson B, Johansson T, Clayton DF, Albrekt AS, von Schantz T,
Hasselquist D. 2008 A microarray for large-scale genomic and transcriptional analyses of
the zebra finch (Taeniopygia guttata) and other passerines. Mol Ecol Res 8, 275-281.
3.
Replogle K, Arnold AP, Ball GF, Band M, Bensch S, Brenowitz EA, Dong S, Drnevich
J, Ferris M, George JM, et al. 2008 The Songbird Neurogenomics (SoNG) Initiative:
community-based tools and strategies for study of brain gene function and evolution.
BMC Genomics 9, 131.
4.
Pinheiro J, Bates D, DebRoy S, Sarkar D and R Core Team. 2014 nlme: Linear and
Nonlinear Mixed Effects Models. R package version 3.1-117, http://CRAN.Rproject.org/package=nlme.
5.
Bates DM. 2005 Fitting linear mixed models in R. R News 5, 27–30.