dataesr/scientific-paragraphs-categorization huggingface dataset:
Transgene integration in hairy roots The presence and expression of transgenes in the tomato hairy roots genome were confirmed by genomic PCR, Southern blot, and RT-PCR. PCR amplification confirmed the presence of KanR gene by amplification of PCR product of 662 bp with the primer set KanR genomics (Fig. S3A , see Supporting Information). Southern blotting to confirm T-DNA integration into the tomato roots genome was performed using DIG-labeled probes according to the manufacturer's protocols (Roche Molecular Biochemicals, Mannheim, Germany) (Fig. S3B , see Supporting Information). Genomic DNA of transformed roots was digested with EcoRI, which does not cut within the T-DNA, and hybridized with a labelled 380 bp KanR amplicon using the primer set KanR-F (CCGGTTCTTTTTGTCAAGAC) and KanR-R (AGAAGAACTCGTCAAGAAGG).
STATISTICS All statistical analyses were carried out with R software (version 2. 14. 0; R Core Team, 2011). Effect of treatment (D. radicum infestation or phytohormone application) on herbivore abundance was assessed using a Wald chi square test on a Generalized Linear Mixed Model, with a Poisson distribution (function "glmer" in package "lme4";  Bates et al. , 2011). Data considered were the number of individuals/eggs per plant. Since the two control treatments (AC and C) were conducted differently, two models were built: one to test for an effect of phytohormone application, a second one to test for an effect of D. radicum infestation. In both models, treatment was specified as a fixed factor, date was specified as a random factor and block was specified as a random factor nested into date.
The same procedure was used to test for an effect of treatment on abundance of D. radicum adults, without the date factor. When needed, pairwise comparisons were computed by using an analysis of contrasts [function "esticon" in package "doBy"  (Højsgaard et al. , 2011) ] with a Benjamini-and-Hochberg correction. Effect of treatment on plant quality (height, total weight, head weight and visual quality) was assessed by using a Wald chi square test on a Linear Mixed Model (function "lmer" in package "lme4"). Treatment was considered as a fixed factor and block as a random factor. When needed, pairwise comparisons were computed by an analysis of contrasts with a Benjamini-and-Hochberg correction. Effect of treatment on GLS profile was assessed by using an Analysis Of Variance (ANOVA). Different ANOVAs were conducted to test for an effect on (i) total GLS, (ii) GLS classes (aliphatic and indole), and (iii) individual GLS content.
ACKNOWLEDGMENTS The authors thank the staff of the  "Domaine de la Motte" experimental station (INRA Center, Le Rheu, France) , the staff of  APBV (INRA, Center Le Rheu, France)  and the following people for their excellent assistance with field experiment set up, surveys and harvest of broccoli plants:  G. Nedelec ,  P. Leconte ,  C. Paillusson ,  A. Dechatre ,  S. Bouchebti ,  V. Chaminade ,  C. Paty ,  S. Dourlot ,  F. Kohandani-Tafresh ,  C. Josso ,  Y. Fournis ,  D. Poinsot , and  D. Webb  at  Rennes University (France ). The authors are also grateful to  C. E. Raaijmakers  at  NIOO-KNAW (Netherlands ) for glucosinolate analysis,  Y. Outreman  at  INRA Center (Le Rheu, France ) and  D. Poinsot  at  Rennes University (France ) for precious advice in statistics. This work was funded by a PhD grant from  Région Bretagne  to  P.
Statistical Analysis Data from cone bioassays were compared between each net using a Chi square test. Significance between treatments was set at 5% level. Data were analyzed using the Minitab Software Version 12. 2. The number of mosquitoes of each species entering the huts was compared and analysed using the non-parametric Kruskal-Wallis test. The proportion of mosquitoes that exited early (induced exophily), the proportion that was killed within the hut (mortality) and the proportion that successfully blood-fed (bloodfeeding rate) were compared and analysed using the logistic regression (XLSTAT Software version 2011).
The automated base-calling in CodonCode Aligner software detected SNPs in many clones from single individuals. In order to verify their authenticity, we visually inspected all SNPs in the corresponding chromatograms from both forward and reverse reads. All ambiguous SNPs were excluded from the final data set. Confirmed SNPs were then divided into two groups: recurrent SNPs and true singletons. Recurrent SNPs refer to nucleotide positions that were detected in independent clones in either different lines of new hosts, in R. cerasi clones only, or in both systems. Unique SNPs that were found in single clones only, but appeared reliable in the sequence chromatogram, were classified as singletons. Anticipating that PCR accuracy was strongly impacted by the performance of the enzyme polymerase, we first determined the error base line of the Taq DNA polymerase used for all assays.
Statistical analysis For statistical analysis SPSS 16. 0 and GraphPad Software (www. graphpad. com) were used. SNP frequencies were analyzed using x 2 with Yates Correction (262 contingency table); two tailed P-values indicated significant differences between values when ,0. 05. To detect potential traits of positive or negative selection, synonymous to non-synonymous substitutions per site were calculated using SNAP (Synonymous and Non-synonymous Analysis Program) provided at http://www. hiv. lanl. gov. This program uses the Nei-Gojobori corrected path counting method that adjusts for counts via Jukes-Cantor plus the weighting of pathways from one codon to another according to an equiprobable model for each possible codon-to-codon path (  [61] ).
In order to determine when this shift from wCer2 to wCer1 took place, we analyzed RC20 DNA extracts from seven, randomly picked, non-consecutive generations between G140 (beginning of this study) and G168 (see time course in Figure  1A ). We found a switch from wCer2 to wCer1 during a transition period between generations F150 and F167, followed by replacement of wCer2 by wCer1 in F168. However, to directly prove the correlation between wCer2 and host fecundity, and to rule out that the microinjection-caused bottleneck did not just lead to accumulation of negative effects, further experiments are needed. Re-evaluation of our data in a homogenized host nuclear background obtained through outcrossing the RC20 line will allow for better analysis of wCer-triggered fitness costs in the host.
singleton singleton singleton singleton singleton singleton singleton singleton singleton singleton singleton variable amino acid positions in GATB of Position 1 in the presented 404 bp fragment corresponds to position 981 of the full gatB locus of wRi infecting Drosophila simulans Riverside (GenBank accession number CP001391). Aa position 1 in (B) corresponds to aa position 148 of the full GATB protein of wRi (protein ID:ACN94961. 1). Frequency of SNP indicates which SNPs are singletons or occur recurrently in what host system. Nonsense mutations leading to a stop codon are indicated by asterisks. Abbreviations: aa amino acid. doi:10. 1371/journal. pone. 0082402. t001.
Acknowledgments We are thankful to  Lisa Klasson  ( Sweden ) for critically reading the manuscript. We thank  Kostas Bourtzis  ( Greece ) for kindly providing DNA from C. capitata strain WolMed88. 6,and  Kirsten Ko ¨ppler (Germany)  for technical assistance with antibiotic treatment of R. cerasi. We are obliged to  Traude Kehrer  ( Austria ) for excellent fly care.
The BLV transcriptional promoter is located in the 5′ long terminal repeat (5′-LTR) and is composed of the U3, R and U5 regions. Gene expression is induced at the transcriptional level by the virus-encoded transactivator Tax  [16]. Few complete genomic sequences of BLV strains are available in the databases. These sequences are from different sources: peripheral blood mononuclear cells (PBMC)  [17] , tumor cells, experimentally infected sheep, and cell lines (FLK). The degree of genetic variation among these strains and those directly isolated from bovine B-cell lymphosarcomas remains unknown. For this reason, and in order to contribute to the understanding of the mechanisms of leukemogenesis induced by BLV, we performed a detailed characterization of the complete genome of three BLV isolates from B-cell lymphosarcomas of three cows from different farms, and we compared them with all available and corresponding full length sequences from BLV isolates from other sources.
Sequencing Both strands of purified plasmids were sequenced in order to avoid discrepancies by using specific and universal T7 or SP6 primers and the Big Dye DNA sequencing kit (Perkin-Elmer) on a 373 DNA sequencer apparatus (Perkin-Elmer). Complete genome sequences were obtained from B-cell lymphosarcomas and deposited in the EMBL database under accession numbers EMBL:HE967301 to EMBL: HE967303 (LS1to LS3). Complete genome sequences were obtained for all available and comparable BLV strains by using All-round Retrieval of Sequence and Annotation (ARSA) at the DNA Data Bank of Japan (DDBJ)  [18].
T. AF033818. T. FJ914764. T. K02120. T. AF257515. V. TF. C. LS3. K. EF600696. AF033818. E. L. FJ914764. E. L. K02120. AF257515. V. E. L. LS2. EF600696. N. S. V. AF033818. S. FJ914764. S. K02120. V. S. AF257515. V. S. V. LS3. EF600696. R. AF033818 R. FJ914764. R. A. K02120. T. AF257515. R. A. LS3. EF600696. AF033818. I. FJ914764. I. K02120. D. L. AF257515. I.
FJ914764. L. I. K K02120. S. AF257515. L. A. I. V. F. G. GFF. S. LS3. EF600696. AF033818. FJ914764. K02120. AF257515. S. LS3. EF600696. AF033818. FP. FJ914764. G. ES. FA. R K02120. LR. AF257515. G. ES. A. R 501 LS1 LSPVKPDYINLRPCP LS2. LS3. EF600696. AF033818. T. FJ914764. T. K02120. AF257515. T.
LS3. EF600696. AF033818. R. A. K. E. FJ914764. Y. S. T. K02120. E. AF257515. Y. S. T. LS3. EF600696. AF033818. I. FJ914764. K02120. I. -. AF257515. V. LS3. EF600696. V. AF033818. V. M. FJ914764. VP. K02120. S. V. AF257515. I. S. L. I. V.
LS3. EF600696. K. AF033818. Q. T. PR. F. FJ914764. Q. T. F. K02120. AF257515. Q. F. F. H. S. LS3. H. S. EF600696. D. AF033818. H. D. FJ914764. D. D. G. K02120. D. AF257515. D. D. LS3. EF600696. AF033818. G. L. V.
LS3. EF600696. AF033818. T. F. FJ914764. P. T. F. A. K02120. AF257515. H. T. F. A. RDPAPRA. Q. LS2. Q. EF600696. R. Q. AF033818. Q. Q. P. V. FJ914764. V. Q. P. K02120. Q. AF257515. V. Q. P. N. LS3. EF600696. AF033818. TS. Y. G. L. FJ914764. L. K02120. P. AF257515. L. LS3. EF600696. K. AF033818. N. P. L. H. FJ914764. T. P. P. S. K02120. AF257515. T. T. P. S. LS3. EF600696. AF033818. S. S. FJ914764. S. K02120. AF257515. G. S.
LS3. EF600696. LS3. EF600696. G. FJ914764. G. K02120. G. AF257515. G. 1 5 0 CRE E Box CRE E Box 100 LS1 TGTATGAAAGATCATGCCGACCTAGGCGCCGCCACCGCCCCGTAAACCAGACAGAGACGTCAGCTGCCAGAAAAGCTGGTGACGGCAGCTGGTGGCTAG LS2. CAT Box PU. 1/Spi-B GRE 150 CRE E Box PROMT PAS 200 LS1 AATCCCCGTACCTCCCCAACTTCCCCTTTCCCGAAAAATCCACACCCTAAGCTGCTGACCTCACCTGCTGATAAATTAATAAAATGCCGGCCCTGTCGA LS2. CAP SITE U3| R 250 300 LS1 GTTAGCGGCACCAGAAGCGTTCTTCTCCTGAGACCCTCGTGCTCAGCTCTCGGTCCTGAGCTCTCTTGCTCCCGAGACCTTCTGGTCGGCTATCCGGCA LS2. FJ914764. G. T. A. K02120. A. AF257515. G. T. A. LS3. EF600696. FJ914764. T. C. K02120. AF257515. T. C.
tRNA Pro Bind site 600. T. 550 U5| LS1 CGGCGCCCTCTAGCGGCCAGGAGAGACCGGCAAACAATTGGGGGCTCGTCCGGGATTGATCACCCCGGAACCCTAACAACTCTCTGGACCCACCCCCTC LS2. LS3. EF600696. T. FJ914764. T. K02120. AF257515. TC. T. LS1 GGCGGCATTTTGGGTCTCTCCTTCAAATTATATC LS2. LS3. EF600696. FJ914764. G. T. K02120. AF257515. G. T. CT.
LS3. EF600696. AF033818. R. A. K. E. FJ914764. Y. S. T. K02120. E. AF257515. Y. S. T. LS3. EF600696. AF033818. I. FJ914764. K02120. I. -. AF257515. V. LS3. EF600696. V. AF033818. V. M. FJ914764. VP. K02120. S. V. AF257515. I. S. L. I. V. (A) gag 1 P15-MA 50 100 LS1 MGNSPSYNPPAGISPSDWLNLLQSAQRLNPRPSPSDFTDLKNYIHWFHKTQKKPWTFTSGGPTSCPPGRFGRVPLVLATLNEVLSNDGGAPGASAPEEQP LS2. 101 P24-CA 150 200 LS1 PPYDPPAVLPIISEGNRNRHRAWALRELQDIKKEIENKAPGSQVWIQTLRLAILQADPTPADLEQLCQYIASPVDQTAHMTSLTAAIAAAEAANTLQGFN LS2. 201 250 300 LS1 PQNGTLTQQSAQPNAGDLRSQYQNLWLQAWKNLPTRPSVQPWSTIVQGPAESYVEFVNRLQISLADNLPDGVPKEPIIDSLSYANANKECQQILQGRGLV LS2. 301 P12-NC 350Zn finger Zn finger LS1 AAPVGQKLQACAHWAPKMKQPAILVHTPGPKMPGPRQPASKRPPPGPCYRCLKEGHWARDCPTKATGPPPGPCPICKDPSHWKRDCPTLKSKN LS2. 1 5 0 1 0 0 LS1 RSFPLETRLSNPQIKKLIEGGLSAPQTITPITDSLSGTELECLLSIPLARSRPSVAVYLSGPWLQPSQNQALMLVDTGAENTVLPQNWLVRDYPRIPAAV LS2.
101 150 LS1 LGAGGVSRNRYNWLQGPLTLALKPEGPFITIPKILVDTFDKWQILGRDVLSRLQASISIPEEIRPPVVG LS2. LS3. EF600696. AF033818. FJ914764. S. K02120. -. S. -. R. -. AF257515. LS3. EF600696. V. V. P. AF033818. V. P. T. FJ914764. I. P. T. L. K02120. --. L. P. AF257525. I. P. T. L. (B) pro. EA. LS3. EA. EF600696. EA. AF033818. V. P. EA. FJ914764. T. EA. R. T. K02120. EA. AF257525. T. EA. E. T.
K02120. F. LS. S. Y. S. AF257515. T. LS3. EF600696. AF033818. N. FJ914764. L. AF257515. L. 201 250 300 LS1 TPSPVPFLGQMVHEQIVTYQSLPTLQISSPISLHQLQAVLGDLQWVSRGTPTTRRPLQLLYSSLKGIDDPRAIIQLSPEQLQGIAELRQALSHNARSRYN LS2. 301 350 400 LS1 EQEPLLAYVHLTRAGSTLVLFQKGAQFPLAYFQTPLTDNQASPWGLLLLLGCQYLQTQALSSYAKPILKYYHNLPKASLDNWIQSSEDPRVQELLQLWPQ LS2. K02120. LS3. EF600696.
LS3. EF600696. K. AF033818. Q. T. PR. F. FJ914764. Q. T. F. K02120. AF257515. Q. F. F. H. S. LS3. H. S. EF600696. D. AF033818. H. D. FJ914764. D. D. G. K02120. D. AF257515. D. D. LS3. EF600696. AF033818. G. L. V. LS1 LS2 LS1 LS2 LS1 LS2 LS1 LS2 801 RWLGPLPALVEASGGALLATDPPVWVPWRLLKAFKCLKNDGPEDAHNRSSDG 850 1 Leader peptide | gp51 50 MPKERRSRRRPQPIIRWVSLTLTLLALCRPIQTWRCSLSLGNQQWMTAYNQEAKFSISIDQILEAHNQSPFCAKSPRYTLDSVNGYPKIYWPPPQGRRRF ND 100. Conformational epitopes F,G,H | 101 ND 150CD8 + -T Cell epitope epitope E 200 GARAMVTYDCEPRCPYVGADRFDCPHWDNASQANQGSFYVNHQILFLHLKQCHGIFTLTWEIWGYDPLITFSLHKIPDPPQPDFPQLNSDWVPSVRSWAL. 201 epitope B epitope B' 250 epitopes D D' TMHR epitope A 300 LLNQTARAFPDCAICWEPSPPWAPEILVYNKTISSSGPGLALPDAQIFWVNTSSFNTTQGWHHPSQRLLFNVSQGNALLLPPISLVNLSTASSAPPTRVR. | conformational epitopes F,G,H.
LS2. EF600696. AF033818. N. P. FJ914764. I. P. K02120. AF257515. I. P. Figure 3 Alignment of amino acid sequences of Polymerase (Pol) proteins of BLV isolates. The reverse transcriptase (RT) region is shown in green and the endonuclease region is shown in light blue. The rest is the same as Figure 1.
LS3. EF600696. AF033818. T. F. FJ914764. P. T. F. A. K02120. AF257515. H. T. F. A. RDPAPRA. Q. LS2. Q. EF600696. R. Q. AF033818. Q. Q. P. V. FJ914764. V. Q. P. K02120. Q. AF257515. V. Q. P. N. LS3. EF600696. AF033818. TS. Y. G. L. FJ914764. L. K02120. P. AF257515. L. LS3. EF600696. K. AF033818. N. P. L. H. FJ914764. T. P. P. S. K02120. AF257515. T. T. P. S. LS3. EF600696. AF033818. S. S. FJ914764. S. K02120. AF257515. G. S. Zn finger LS1 MASVVGWGPHSLHACPALVLSNDVTIDAWCPLCGPHERLQFERIDTTLTCETHRINWTADGRPCGLNGTLFPRLHVSETRPQGPRRLWINCPLPAVRAQP LS2. 157 Leucine-rich activation domain LS1 GPVSLSPFERSPFQPYQCQLPSASSDGCPIIGHGLLPWNNLVTHPVLGKVLILNHMANFSLLPSFDTLLVDPLRLSVFAPDTRGAIRYLSTLLTLCPATC LS2. 261 240 247 251 258| 265 287 297 LS1 ILPLGEPFSPNVPICRFPRDSNEPPLSEFELPLIQTPGLSWSVPAIDLFLTGPPSPCDRLHVWSSPQALQRFLHDPTLTWSELVASRKIRLDSPLKLQLL LS2.
303 LS1 ENEWLSRLF LS2. LS3. EF600696. AF033818. FJ914764. K02120. AF257515. (B) Rex NES LS1 MPKERRSRRRPQPIIRWRQNYFLSFKQVLLVGGPTLYMPARPWFCPMMSPSMPGAPSAGPMSDSNSKGSTPRSPARPTVSTGPPMDDLAASMERCSLDCM LS2. NLS LS1 SPRPAPKGPDDSGSTAPFRPFALSPARFHFPPSSGPPSSPTNANCPRPLATVAPLSGTAFFPGTT LS2.
QQS Is a Novel Gene Embedded within a TE-Rich Region of the A. thaliana Genome and Is Negatively Regulated by DNA Methylation The A. thaliana Qua-Quine Starch (QQS, At3g30720) was first described as a gene involved in starch metabolism in leaves  [19, 20]. Despite being functional and presumably already under purifying selection (dN/dS = 0. 5868; p-value,0. 045), QQS is likely a recent gene that emerged de novo. Indeed, QQS has no significant similarity to any other sequence present in GenBank  [18, 19] , suggesting that it originated from scratch since A. thaliana diverged from its closest sequenced relative A. lyrata around 5-10 million years ago. Furthermore, QQS encodes a short protein (59 amino acids) and it is differentially expressed under various abiotic stresses  [18] , which are also hallmarks of de novo originated genes  [21] [22] [23].
Overall codon-based Z-test of purifying selection Available QQS coding-sequences (464 different accessions) were downloaded from the ''Salk Arabidopsis 1001 Genomes'' database (http://signal. salk. edu/atg1001/index. php). A. suecica QQS sequence (coming from the A. thaliana genome of this allotetraploid  [49] ) was also included in the analysis. The aligned sequences were used to calculate the probability of rejecting the null hypothesis (H 0 ) of strict-neutrality (dN = dS; where dN = number of nonsynonymous and dS = number of synonymous substitutions per site) in favor of the alternative hypothesis of purifying selection (H A ; dS. dN). The analysis was done using the MEGA5 software under the Nei-Gojobori method  [50]  with the variance of the difference calculated by the bootstrap method with 100 replicates.
Here, we present a combined analysis of mtDNA and microsatellite data from A. m. cypria, which provides information on the genetic structure of the Cyprian honey bee population. These data, as well as those obtained from analogous studies using different approaches, can contribute to the conservation of the local honey bee populations in Cyprus. '25. 65''N, 38°18'30. 94''E), and Troulloi (35°02'06. 68''N, 33°37'17. 69 ''E) (Fig. 1 ). The sampling in Flassou was performed in 2001, sampling in Alabra, Alassa, Katydata, and Kyrenia was conducted in 2003, and sampling in Troulloi was performed in 2005. Fifty colonies each were sampled from Flassou, Alabra, Alassa, Katydata, and Kyrenia, which is considered sufficient to characterize a "population" within an area  (Nei, 1987). The apiary at Troulloi contained only 18 colonies; therefore, a maximum of only 18 colonies was sampled at this location.
microsatellite analysis Fourteen polymorphic microsatellite loci -A7, A8, A28, A88, A113, B124  (Estoup et al. , 1995) , A43, Ap33, Ap36, Ap43, Ap55, Ap66, Ap81, and B24  (Solignac et al. , 2003)  -were amplified in two multiplex reactions and sequenced. The resulting sequences were analyzed using GeneMapper Software (Applied Biosystems).
Data analysis The data were statistically analyzed using the TREEMAKER package. Phylogenic analyses were performed based on the method described by  Cavalli-Sforza and Edwards (1967). An exact test of sample differentiation based on haplotype frequencies was calculated according to the method of  Raymond and Rousset (1995)  using the GENEPOP v. 3. 1 package. Principal coordinate analysis (PCA) was performed using the NUEES v. 0. 8. package  (Langella, 2001).
Zebra finch and chicken lineages diverged between 75 and 150 Ma, thus bracketing all of avian diversity with the exception of the palaeognathes  [18 -20]. Comparisons of zebra finch and chicken therefore necessarily average evolutionary signatures across much of avian diversity. In doing so, the signal of recent adaptation in songbirds has been obscured  [17]. Next-generation sequencing studies are driving a rapid increase in the genome-scale data available for birds  [21, 22] , but these datasets too have targeted divergent taxa. Transcriptome datasets, however, offer the potential to rapidly fill in the avian tree of life  [21,23 -27] , allowing comparisons of closely related taxa towards the understanding of molecular evolution on more recent time scales. Birds in general display striking variation in social behaviour  [28] , and the estrildid finches (family Estrildidae, 143 species) in particular have been cited as important model systems for studying the behavioural, endocrinological and neural substrates of sociality  [29] [30] [31].
We then normalized the cDNA library using the Trimmer Direct kit (Evrogen) and manufacturer's protocols. End repair, 3 0 addition of A bases and ligation of adaptors were done following Illumina library preparation guidelines but using Roche 454 adaptors. We then ran the library in agarose and gel purified the 400-800 bp band. Sequences were assembled using GSASSEMBLER software (v. 2. 3) from Roche. Reads that contained homopolymers (60% over the entire length of the read represented by one nucleotide) and reads that were shorter than 100 bp were filtered. The parameters used for the assembly were overlap-MinMatchLength of 40 and overlapMinMatchIdentity of 90%. The resulting isotigs and singlets that were more than 100 bp were annotated using BLAST against non-redundant protein database from NCBI (http://www.
Sequence alignment and molecular rate analyses To align sequences from the new violet-eared waxbill transcriptome, we compared assembled transcripts with annotated zebra finch cDNAs and with another recently published songbird transcriptome-that of the great tit  [23] -using BLASTþ2. 2. 25. The whole set of waxbill and great tit transcripts were compared with the zebra finch database using the following parameters: expected e-value ¼ 1 Â 10 25 and minimum length of the BLAST hit ¼ 300 bp. For each waxbill and great tit transcript, we kept the zebra finch hit satisfying these criteria and with the best e-value. In order to conduct downstream molecular rate analyses, we refined alignments to match homologous codons across species and remove any non-coding regions. To refine alignments, we used MUSCLE  [44, 45]  with the -diags parameter invoked to improve alignment speed given the similarity of the species in question.
05) using Q-value  [50]. To examine molecular rates at different time scales, we also compared rates from zebra finch/waxbill codeml comparisons with those from zebra finch/chicken comparisons. Estimates of v from zebra finch relative to chicken were made using Ensembl Biomart (ensemble. org). To estimate the overall rate of protein evolution (v) across the genome, we generated bootstrap datasets based on our previous alignment following Heger & Ponting  [5]. For each species pair, we generated 1000 bootstrap datasets by concatenating 150 randomly chosen alignments. These longer alignments generate more robust and reliable estimates of genome-wide v  [5]. Across each of the 1000 alignments, we compared average v between pairwise analyses of zebra finch -great tit and waxbill-great tit to test for rate variation between these two species, as might be expected if the two species had different demographic histories.
Assembly and annotation Two plates of 454 sequencing yielded 975 606 and 1 055 860, reads with average read lengths of 323. 5 bp and 380. 5 bp, respectively. Raw sequence data have been deposited at the NCBI short read archive under accession no. SRX337999. The total waxbill brain transcriptome dataset therefore consisted of 2 031 466 reads, and 2 013 275 after filtering. Transcriptome assembly yielded 32 938 isogroups (genes) and 43 137 isotigs (transcripts) with an average size of 1555 bp and an N50 value of 2486 bp. This compares favourably with recent de novo transcriptome assemblies of the zebra finch (mean contig length ¼ 150 bp  [53] ), great tit (mean contig length ¼ 871 bp  [23] ) kiwi (mean contig length ¼ 162 bp  [26] ) and other bird species  [21]. The transcript set described here closely matches the transcript length profile for the full Ensembl transcript set for zebra finch (figure  1 ).
The longest assembled isotig in our assembly spanned 17 589 bp, covering the primary transcript of the mitochondrial genome. Four hundred and seventy nine contigs could not be placed in isotigs, but were included in subsequent analyses, yielding 43 616 putative transcripts. A total of 233 903 singleton reads were not included in the assembly. BLAST analysis of assembled transcripts found significant matches to 7817 Ensembl genes out of 17 475 total zebra finch Ensembl genes (44. 7%). Including singletons in our count of detected transcripts expands our transcriptome coverage to 11 084 Ensembl genes (63. 4%).