Candidate gene polymorphisms are linked to dispersive and migratory behaviour: searching for a mechanism behind the “paradox of the great speciators”
Data files
Jan 25, 2023 version files 789.87 MB
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0_divBasic.ods
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20200324_CandidateGenes.geneious
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BA3-SNP_aus.inp
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BA3-SNP_mel.inp
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brms_adcyap_null.rds
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brms_adcyap.rds
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brms_creb_null.RDS
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brms_creb.RDS
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curated_dataset.ods
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island_info.csv
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island_labels.csv
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mcp_creb_age.rds
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mcp_creb_disp.rds
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mcp_creb_null_age.rds
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mcp_creb_null_disp.rds
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migratory.rds
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mod_adcyap1_pop.RDS
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mod_clock_pop.RDS
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mod_creb1_pop.RDS
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mod_npas_pop.RDS
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ngsadmix_bestK_likelihoods.ods
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pcangsd_output_pop.ods
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pcangsd_output.cov
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pop_covariance_matrix.ods
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README.md
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snps_syn_nonsyn.ods
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subset-genotype-phenotype-genpop
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WGS_subset4cov_matrix.ods
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wholegenome_pruned_1million_melanesia_subset.beagle.gz
358.89 KB
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wholegenome_pruned_1million_subset_oz.beagle.gz
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wholegenome_pruned_1million_subset.beagle.gz
65.79 MB
May 16, 2023 version files 1.33 GB
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0_divBasic.ods
15.37 KB
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20200324_CandidateGenes.geneious
266.62 MB
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aus_wholegenome_10K_1.ba
20.59 MB
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aus_wholegenome_10K_2.ba
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aus_wholegenome_10K_3.ba
20.59 MB
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aus_wholegenome_10K_4.ba
20.59 MB
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aus_wholegenome_10K_5.ba
20.60 MB
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brms_adcyap_long.rds
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brms_adcyap_null_long.rds
23.45 MB
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brms_adcyap_null.rds
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brms_adcyap.rds
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brms_clock_migratory.rds
20.15 MB
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brms_creb_long.rds
23.80 MB
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brms_creb_null_long.rds
23.26 MB
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brms_creb_null.rds
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brms_creb.rds
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curated_dataset.ods
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geneflow_output.ods
36.98 KB
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island_info.csv
1.07 KB
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island_labels.csv
229 B
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mcp_creb_age_null.rds
13.65 MB
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mcp_creb_age.rds
50.80 MB
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mcp_creb_disp_null.rds
13.64 MB
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mcp_creb_disp.rds
50.80 MB
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mcp_creb_long_age.rds
50.36 MB
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mcp_creb_long_disp.rds
50.34 MB
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mcp_creb_null_long_age.rds
11.24 MB
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mcp_creb_null_long_disp.rds
11.23 MB
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mel_wholegenome_10K_1.ba
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mel_wholegenome_10K_2.ba
59.57 MB
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mel_wholegenome_10K_3.ba
59.56 MB
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mel_wholegenome_10K_4.ba
59.58 MB
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mel_wholegenome_10K_5.ba
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migrants.cov
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mod_adcyap1_pop.rds
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mod_clock_longallele.rds
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mod_clock_pop.rds
21.28 MB
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mod_creb1_pop.rds
21.22 MB
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mod_npas_pop.rds
21.28 MB
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ngsadmix_bestK_likelihoods.ods
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ngsadmix_bestK_likelihoods.xlsx
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pcangsd_output_pop.ods
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pcangsd_output.cov
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pop_covariance_matrix.csv
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pop_covariance_matrix.ods
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README.md
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snps_syn_nonsyn.ods
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subset-genotype-phenotype-genpop
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wholegenome_pruned_1million_melanesia_subset.beagle.gz
358.89 KB
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wholegenome_pruned_1million_subset_oz.beagle.gz
31.45 MB
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wholegenome_pruned_1million_subset.beagle.gz
65.79 MB
Aug 30, 2023 version files 1.33 GB
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20200324_CandidateGenes.geneious
266.62 MB
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aus_wholegenome_10K_1.ba
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aus_wholegenome_10K_2.ba
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aus_wholegenome_10K_3.ba
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aus_wholegenome_10K_4.ba
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aus_wholegenome_10K_5.ba
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brms_adcyap_long.rds
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brms_adcyap_null_long.rds
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brms_adcyap_null.rds
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brms_adcyap.rds
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brms_clock_migratory.rds
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brms_creb_long.rds
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brms_creb_null_long.rds
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brms_creb_null.rds
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brms_creb.rds
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curated_dataset.csv
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curated_dataset.ods
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island_info.csv
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island_labels.csv
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mcp_creb_age_null.rds
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mcp_creb_age.rds
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mcp_creb_disp_null.rds
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mcp_creb_disp.rds
50.80 MB
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mcp_creb_long_age.rds
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mcp_creb_long_disp.rds
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mcp_creb_null_long_age.rds
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mcp_creb_null_long_disp.rds
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mel_wholegenome_10K_1.ba
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mel_wholegenome_10K_2.ba
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mel_wholegenome_10K_3.ba
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mel_wholegenome_10K_4.ba
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mel_wholegenome_10K_5.ba
59.60 MB
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migrants.cov
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mod_adcyap1_pop.rds
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mod_clock_longallele.rds
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mod_clock_pop.rds
21.28 MB
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mod_creb1_pop.rds
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mod_npas_pop.rds
21.28 MB
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pcangsd_output.cov
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pop_covariance_matrix.csv
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README.md
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subset-genotype-phenotype-genpop
17.81 KB
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wholegenome_pruned_1million_melanesia_subset.beagle.gz
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wholegenome_pruned_1million_subset_oz.beagle.gz
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wholegenome_pruned_1million_subset.beagle.gz
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Abstract
The “paradox of the great speciators” has puzzled evolutionary biologists for over half a century. A great speciator requires excellent dispersal propensity to explain its occurrence on multiple islands, but reduced dispersal ability to explain its high number of subspecies. A rapid reduction in dispersal ability is often invoked to solve this apparent paradox, but a proximate mechanism has not been identified yet. Here, we explored the role of six genes linked to migration and animal personality differences (CREB1, CLOCK, ADCYAP1, NPAS2, DRD4, and SERT) in 20 South Pacific populations of silvereye (Zosterops lateralis) that range from highly sedentary to partially migratory, to determine if genetic variation is associated with dispersal propensity and migration. We detected genetic associations in three of the six genes: i) in a partial migrant population, migrant individuals had longer microsatellite alleles at the CLOCK gene compared to resident individuals from the same population; ii) CREB1 displayed longer average microsatellite allele lengths in recently colonised island populations (< 200 years), compared to evolutionarily older populations. Bayesian broken stick regression models supported a reduction in CREB1 length with time since colonisation; and iii) like CREB1, DRD4 showed differences in polymorphisms between recent and old colonisations but a larger sample is needed to confirm. ADCYAP1, SERT, and NPAS2 were variable but that variation was not associated with dispersal propensity. The association of genetic variants at three genes with migration and dispersal ability in silvereyes provides the impetus for further exploration of genetic mechanisms underlying dispersal shifts and the prospect of resolving a long-running evolutionary paradox through a genetic lens.
Estandía et al. 2023 is motivated by the concept of the “paradox of the great speciators”, that is those subspecies-rich birds distributed across multiple islands. The paradox lies in their wide distributions suggesting excellent dispersal ability, combined with, high subspecific diversity suggesting limits to dispersal. Could this paradox be resolved if there were genetic switches associated with dispersal? We examined if genetic variation at six genes linked to migration and animal personality differences was associated with variation in dispersal propensity in 422 individuals from 20 populations of silvereye (Zosterops lateralis) in Australia and the south-west Pacific. We found several genetic associations: in a partial migrant population, migrant individuals had longer microsatellite alleles at the CLOCK gene compared to residents; CREB1 displayed longer average microsatellite allele lengths in recently colonised island populations (< 200 years), compared to evolutionarily older populations and furthermore, modelling supported a reduction in CREB1 length with time since colonisation and decreasing dispersal propensity, potentially indicating selection against dispersal following island colonisation. Results from other genes were equivocal or showed no association with dispersal propensity. Nevertheless our results show that the paradox can be partly understood through a genetic lens.
Description of the data and file structure
Dryad
INPUT DATA
curated_dataset
: main curated dataset:- Order: order of the samples sorted alphabetically by population
- common_name: common name for the species
- species: scientific name for the species
- subspecies: scientific name for the subspecies
- country: country where the sample was collected
- state: state, if relevant, where the sample was collected
- population: population defined as island if no genetic substructure
- island: only relevant for island populations
- town_region: region where the sample was collected (e.g. Canberra)
- location: location where the sample was collected (e.g. Australian National Botanical Garden, in Canberra)
- site: particular site within location where the sample was collected
- migrant: migratory status as calculated in
1.0_model_migrants.Rmd
notebook athttps://github.com/andreaestandia/1.0_silvereye_candidate_genes
- name: field sample name, mostly the same as id expect for a few from Aotearoa New Zealand
- id: blood id
- measured_by: fieldworker who took measurements of the bird
- fieldtrip: which fieldtrip the sample was collected in
- date
- time
- latitude
- longitude
- disp_index: dispersal index as calculated by equation 1 available in materials and methods
- age_myr: age of the population in millions of years
- isolation_index: isolation index. distance between islands
- area: area of the island
- short_adcyap: for microsatellite candidate genes there are often two peaks,
short_gene
represents the shorter one,long_gene
the long one andmean_gene
the average between short and long - long_adcyap
- mean_adcyap
- short_creb1
- long_creb1
- mean_creb1
- short_clock
- long_clock
- mean_clock
- short_npas2
- long_npas2
- mean_npas2
- DRD4_snp1218: each of these columns represent SNPs for DRD4 and SERT . 0 and 1 represent each of the variants
- DRD5_snp1228
- DRD6_snp140
- DRD7_snp150
- DRD8_snp217
- DRD9_snp224
- DRD10_snp41
- DRD11_snp742
- DRD12_snp83
- DRD13_snp926
- SERT_indel195
- SERT_snp266
- SERT_snp311
- cluster: k1 represents the SM cluster and k2 the ANZO cluster
- locator_x: locators are used for the structure plots to get the right order of populations
- locator
- locator2
202000224_Candidategenes.geneious
: it contains the raw and processed geneious files for candidate genessubset-genotype-phenotype-genpop
: input for genpop to estimate HWE and allelic richnessaus_wholegenome_10K_* and mel_wholegenome_10K_*
: input files to estimate gene flow with BayesAss3-SNP (https://github.com/stevemussmann/BayesAss3-SNPs)wholegenome_pruned_1million
*: input files to estimate population structure with NGSAdmix (http://www.popgen.dk/software/index.php/NgsAdmix)- wholegenome_pruned_1million_melanesia_subset.beagle.gz: samples from the SM cluster
- wholegenome_pruned_1million_subset_oz.beagle.gz: samples for the ANZO cluster
- wholegenome_pruned_1million_subset.beagle.gz: all samples pooled together
island_labels
andislands_info
: they contain essential information to reproduce Figure 1pop_covariance_matrix
: population-level covariance matrix used to produce the heatmap in Figure S3
OUTPUT DATA
pcangsd_output.cov
: raw output from PCAngsdmigrants.cov
: raw output from PCAngsd for the migratory and resident Tasmanian samples*rds
: any file with RDS extension is the output of a model. Those models with the _long word before the rds extension, represent the same models with using the longer allele.mcp_creb_age.rds
: Broken stick regression output for CREB1 with population age as explanatory variablemcp_creb_age_null.rds
: Null model. Broken stick regression output for CREB1 with population age as explanatory variablemcp_creb_disp.rds
: Broken stick regression output for CREB1 with dispersal propensity as explanatory variablemcp_creb_disp_null.rds
: Null model. Broken stick regression output for CREB1 with dispersal propensity as explanatory variablemod_clock_pop.rds
: Model output. Differences among populations at CLOCKmod_adcyap_pop.rds
: Model output. Differences among populations at ADCYAP1mod_npas_pop.rds
: Model output. Differences among populations at NPAS2mod_creb1_pop.rds
: Model output. Differences among populations at CREB1brms_creb_null.rds
: Null model. Generalised linear mixed model output for CREB1 with pop age and dispersal propensity as explanatory variablesbrms_creb.rds
: Generalised linear mixed model output for CREB1 with pop age and dispersal propensity as explanatory variablesbrms_adcyap_null.rds
: Null model. Generalised linear mixed model output for ADCYAP1 with pop age and dispersal propensity as explanatory variablesbrms_adcyap.rds
: Generalised linear mixed model output for ADCYAP1 with pop age and dispersal propensity as explanatory variablesbrms_clock_migratory.rds
: Model output. Differences between migratory and resident birds at CLOCK
<br>Code/Software
Code to reproduce all analyses can be found here: https://github.com/andreaestandia/1.0_silvereye_candidate_genes