The design and cross-population application of a genome-wide SNP chip for the great tit Parus major

Fine-scale genetic structure and phenotypic divergence of a passerine bird population inhabiting a continuous Mediterranean woodland

Genetic differentiation between populations inhabiting ecologically different habitats might appear because of limited dispersal and gene flow, which may lead to patterns of phenotypic divergence and local adaptation. In this study, we use dispersal, genotypic (24 microsatellite loci) and phenotypic (body size and clutch size) data to analyse patterns of genetic structuring and phenotypic divergence in a blue tit (Cyanistes caeruleus) population inhabiting a continuous and heterogeneous woodland along a valley. The two slopes of the valley differ in their forest formations and environmental conditions. Findings showed that most blue tits reproduced within their natal slope. Accordingly, microsatellite analyses revealed that populations of blue tits established in the two slopes show subtle genetic differentiation. The two genetic populations diverged in clutch size, exceeding the level of differentiation expected based on genetic drift, hence suggesting divergent selection (or other processes promoting divergence) on this life-history trait. Our findings reveal that restricted dispersal and spatial heterogeneity may lead to genetic differentiation among bird populations at a surprisingly small scale. In this respect, it is worth highlighting that such differentiation occurs for an organism with high dispersal capacity and within a continuous woodland. Moreover, we show that small-scale ecological differences, together with limited gene flow, can result in selection favouring different phenotypes even within the same continuum population.

Application potential of chicken DNA chip in domestic pigeon species - Preliminary results

Introducing the SNP technology to pigeon breeding will enhance the competitiveness of a sector that produces one of the healthiest and best quality meats. The present study aimed to test the applicability of the Illumina Chicken_50K_CobbCons array on 24 domestic pigeon individuals from the Mirthys hybrids and Racing pigeon breeds. A total of 53,313 SNPs were genotyped. Principal component analysis shows a significant overlap between the two groups. The chip performed poorly in this data set, with a call rate per sample of 0.474 (49%). The low call rate was likely due to an increase in the evolutionary distance. A total of 356 SNPs were retained after a relatively strict quality control. We have demonstrated that it is technically feasible to use a chicken microarray chip on pigeon samples. Presumably, with a larger sample size and by assigning phenotypic data, efficiency would be improved, allowing more thorough analyses, such as genome-wide association studies.

The design and application of a 50 K SNP chip for a threatened Aotearoa New Zealand passerine, the hihi

Next-generation sequencing has transformed the fields of ecological and evolutionary genetics by allowing for cost-effective identification of genome-wide variation. Single nucleotide polymorphism (SNP) arrays, or "SNP chips", enable very large numbers of individuals to be consistently genotyped at a selected set of these identified markers, and also offer the advantage of being able to analyse samples of variable DNA quality. We used reduced representation restriction-aided digest sequencing (RAD-seq) of 31 birds of the threatened hihi (Notiomystis cincta; stitchbird) and low-coverage whole genome sequencing (WGS) of 10 of these birds to develop an Affymetrix 50 K SNP chip. We overcame the limitations of having no hihi reference genome and a low quantity of sequence data by separate and pooled de novo assembly of each of the 10 WGS birds. Reads from all individuals were mapped back to these de novo assemblies to identify SNPs. A subset of RAD-seq and WGS SNPs were selected for inclusion on the chip, prioritising SNPs with the highest quality scores whose flanking sequence uniquely aligned to the zebra finch (Taeniopygia guttata) genome. Of the 58,466 SNPs manufactured on the chip, 72% passed filtering metrics and were polymorphic. By genotyping 1,536 hihi on the array, we found that SNPs detected in multiple assemblies were more likely to successfully genotype, representing a cost-effective approach to identify SNPs for genotyping. Here, we demonstrate the utility of the SNP chip by describing the high rates of linkage disequilibrium in the hihi genome, reflecting the history of population bottlenecks in the species.

An 85K SNP Array Uncovers Inbreeding and Cryptic Relatedness in an Antarctic Fur Seal Breeding Colony

High density single nucleotide polymorphism (SNP) arrays allow large numbers of individuals to be rapidly and cost-effectively genotyped at large numbers of genetic markers. However, despite being widely used in studies of humans and domesticated plants and animals, SNP arrays are lacking for most wild organisms. We developed a custom 85K Affymetrix Axiom array for an intensively studied pinniped, the Antarctic fur seal (Arctocephalus gazella). SNPs were discovered from a combination of genomic and transcriptomic resources and filtered according to strict criteria. Out of a total of 85,359 SNPs tiled on the array, 75,601 (88.6%) successfully converted and were polymorphic in 270 animals from a breeding colony at Bird Island in South Georgia. Evidence was found for inbreeding, with three genomic inbreeding coefficients being strongly intercorrelated and the proportion of the genome in runs of homozygosity being non-zero in all individuals. Furthermore, analysis of genomic relatedness coefficients identified previously unknown first-degree relatives and multiple second-degree relatives among a sample of ostensibly unrelated individuals. Such “cryptic relatedness” within fur seal breeding colonies may increase the likelihood of consanguineous matings and could therefore have implications for understanding fitness variation and mate choice. Finally, we demonstrate the cross-amplification potential of the array in three related pinniped species. Overall, our SNP array will facilitate future studies of Antarctic fur seals and has the potential to serve as a more general resource for the wider pinniped research community.

Exploration of tissue-specific gene expression patterns underlying timing of breeding in contrasting temperature environments in a song bird

BACKGROUND

Seasonal timing of breeding is a life history trait with major fitness consequences but the genetic basis of the physiological mechanism underlying it, and how gene expression is affected by date and temperature, is not well known. In order to study this, we measured patterns of gene expression over different time points in three different tissues of the hypothalamic-pituitary-gonadal-liver axis, and investigated specifically how temperature affects this axis during breeding. We studied female great tits (Parus major) from lines artificially selected for early and late timing of breeding that were housed in two contrasting temperature environments in climate-controlled aviaries. We collected hypothalamus, liver and ovary samples at three different time points (before and after onset of egg-laying). For each tissue, we sequenced whole transcriptomes of 12 pools (n = 3 females) to analyse gene expression.

RESULTS

Birds from the selection lines differed in expression especially for one gene with clear reproductive functions, zona pellucida glycoprotein 4 (ZP4), which has also been shown to be under selection in these lines. Genes were differentially expressed at different time points in all tissues and most of the differentially expressed genes between the two temperature treatments were found in the liver. We identified a set of hub genes from all the tissues which showed high association to hormonal functions, suggesting that they have a core function in timing of breeding. We also found ample differentially expressed genes with largely unknown functions in birds.

CONCLUSIONS

We found differentially expressed genes associated with selection line and temperature treatment. Interestingly, the latter mainly in the liver suggesting that temperature effects on egg-laying date may happen down-stream in the physiological pathway. These findings, as well as our datasets, will further the knowledge of the mechanisms of tissue-specific avian seasonality in the future.

Evaluation of a Chicken 600K SNP genotyping array in non-model species of grouse

The use of single nucleotide polymorphism (SNP) arrays to generate large SNP datasets for comparison purposes have recently become an attractive alternative to other genotyping methods. Although most SNP arrays were originally developed for domestic organisms, they can be effectively applied to wild relatives to obtain large panels of SNPs. In this study, we tested the cross-species application of the Affymetrix 600K Chicken SNP array in five species of North American prairie grouse (Centrocercus and Tympanuchus genera). Two individuals were genotyped per species for a total of ten samples. A high proportion (91%) of the total 580 961 SNPs were genotyped in at least one individual (73–76% SNPs genotyped per species). Principal component analysis with autosomal SNPs separated the two genera, but failed to clearly distinguish species within genera. Gene ontology analysis identified a set of genes related to morphogenesis and development (including genes involved in feather development), which may be primarily responsible for large phenotypic differences between Centrocercus and Tympanuchus grouse. Our study provided evidence for successful cross-species application of the chicken SNP array in grouse which diverged ca. 37 mya from the chicken lineage. As far as we are aware, this is the first reported application of a SNP array in non-passerine birds, and it demonstrates the feasibility of using commercial SNP arrays in research on non-model bird species.

Great tits and the city: Distribution of genomic diversity and gene-environment associations along an urbanization gradient

Urbanization is a growing concern challenging the evolutionary potential of wild populations by reducing genetic diversity and imposing new selection regimes affecting many key fitness traits. However, genomic footprints of urbanization have received little attention so far. Using RAD sequencing, we investigated the genomewide effects of urbanization on neutral and adaptive genomic diversity in 140 adult great tits Parus major collected in locations with contrasted urbanization levels (from a natural forest to highly urbanized areas of a city; Montpellier, France). Heterozygosity was slightly lower in the more urbanized sites compared to the more rural ones. Low but significant effect of urbanization on genetic differentiation was found, at the site level but not at the nest level, indicative of the geographic scale of urbanization impact and of the potential for local adaptation despite gene flow. Gene-environment association tests identified numerous SNPs with small association scores to urbanization, distributed across the genome, from which a subset of 97 SNPs explained up to 81% of the variance in urbanization, overall suggesting a polygenic response to selection in the urban environment. These findings open stimulating perspectives for broader applications of high-resolution genomic tools on other cities and larger sample sizes to investigate the consistency of the effects of urbanization on the spatial distribution of genetic diversity and the polygenic nature of gene-urbanization association.

Success and failure in replication of genotype-phenotype associations: How does replication help in understanding the genetic basis of phenotypic variation in outbred populations?

Recent developments in sequencing technologies have facilitated genomewide mapping of phenotypic variation in natural populations. Such mapping efforts face a number of challenges potentially leading to low reproducibility. However, reproducible research forms the basis of scientific progress. We here discuss the options for replication and the reasons for potential nonreproducibility. We then review the evidence for reproducible quantitative trait loci (QTL) with a focus on natural animal populations. Existing case studies of replication fall into three categories: (i) traits that have been mapped to major effect loci (including chromosomal inversion and supergenes) by independent research teams; (ii) QTL fine-mapped in discovery populations; and (iii) attempts to replicate QTL across multiple populations. Major effect loci, in particular those associated with inversions, have been successfully replicated in several cases within and across populations. Beyond such major effect variants, replication has been more successful within than across populations, suggesting that QTL discovered in natural populations may often be population-specific. This suggests that biological causes (differences in linkage patterns, allele frequencies or context-dependencies of QTL) contribute to nonreproducibility. Evidence from other fields, notably animal breeding and QTL mapping in humans, suggests that a significant fraction of QTL is indeed reproducible in direction and magnitude at least within populations. However, there is also a large number of QTL that cannot be easily reproduced. We put forward that more studies should explicitly address the causes and context-dependencies of QTL signals, in particular to disentangle linkage differences, allele frequency differences and gene-by-environment interactions as biological causes of nonreproducibility of QTL, especially between populations.

A high-density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour

High-density SNP microarrays ("SNP chips") are a rapid, accurate and efficient method for genotyping several hundred thousand polymorphisms in large numbers of individuals. While SNP chips are routinely used in human genetics and in animal and plant breeding, they are less widely used in evolutionary and ecological research. In this article, we describe the development and application of a high-density Affymetrix Axiom chip with around 500,000 SNPs, designed to perform genomics studies of great tit (Parus major) populations. We demonstrate that the per-SNP genotype error rate is well below 1% and that the chip can also be used to identify structural or copy number variation. The chip is used to explore the genetic architecture of exploration behaviour (EB), a personality trait that has been widely studied in great tits and other species. No SNPs reached genomewide significance, including at DRD4, a candidate gene. However, EB is heritable and appears to have a polygenic architecture. Researchers developing similar SNP chips may note: (i) SNPs previously typed on alternative platforms are more likely to be converted to working assays; (ii) detecting SNPs by more than one pipeline, and in independent data sets, ensures a high proportion of working assays; (iii) allele frequency ascertainment bias is minimized by performing SNP discovery in individuals from multiple populations; and (iv) samples with the lowest call rates tend to also have the greatest genotyping error rates.

Recent natural selection causes adaptive evolution of an avian polygenic trait

We used extensive data from a long-term study of great tits (Parus major) in the United Kingdom and Netherlands to better understand how genetic signatures of selection translate into variation in fitness and phenotypes. We found that genomic regions under differential selection contained candidate genes for bill morphology and used genetic architecture analyses to confirm that these genes, especially the collagen gene COL4A5, explained variation in bill length. COL4A5 variation was associated with reproductive success, which, combined with spatiotemporal patterns of bill length, suggested ongoing selection for longer bills in the United Kingdom. Last, bill length and COL4A5 variation were associated with usage of feeders, suggesting that longer bills may have evolved in the United Kingdom as a response to supplementary feeding.

Phylogeography of a migratory songbird across its Canadian breeding range: Implications for conservation units

The objectives of this study were to describe and evaluate potential drivers of genetic structure in Canadian breeding populations of the Ovenbird, Seiurus aurocapilla. We performed genetic analyses on feather samples of individuals from six study sites using nuclear microsatellites. We also assessed species identity and population genetic structure of quill mites (Acariformes, Syringophilidae). For male Ovenbirds breeding in three study sites, we collected light-level geolocator data to document migratory paths and identify the wintering grounds. We also generated paleohindcast projections from bioclimatic models of Ovenbird distribution to identify potential refugia during the last glacial maximum (LGM, 21,000 years before present) as a factor explaining population genetic structure. Birds breeding in the Cypress Hills (Alberta/Saskatchewan) may be considered a distinct genetic unit, but there was no evidence for genetic differentiation among any other populations. We found relatively strong migratory connectivity in both western and eastern populations, but some evidence of mixing among populations on the wintering grounds. There was also little genetic variation among syringophilid mites from the different Ovenbird populations. These results are consistent with paleohindcast distribution predictions derived from two different global climate models indicating a continuous single LGM refugium, with the possibility of two refugia. Our results suggest that Ovenbird populations breeding in boreal and hemiboreal regions are panmictic, whereas the population breeding in Cypress Hills should be considered a distinct management unit.

Passerines may be sufficiently plastic to track temperature-mediated shifts in optimum lay date

Projecting the fates of populations under climate change is one of global change biology's foremost challenges. Here, we seek to identify the contributions that temperature-mediated local adaptation and plasticity make to spatial variation in nesting phenology, a phenotypic trait showing strong responses to warming. We apply a mixed modeling framework to a Britain-wide spatiotemporal dataset comprising >100 000 records of first egg dates from four single-brooded passerine bird species. The average temperature during a specific time period (sliding window) strongly predicts spatiotemporal variation in lay date. All four species exhibit phenological plasticity, advancing lay date by 2-5 days °C(-1) . The initiation of this sliding window is delayed further north, which may be a response to a photoperiod threshold. Using clinal trends in phenology and temperature, we are able to estimate the temperature sensitivity of selection on lay date (B), but our estimates are highly sensitive to the temporal position of the sliding window. If the sliding window is of fixed duration with a start date determined by photoperiod, we find B is tracked by phenotypic plasticity. If, instead, we allow the start and duration of the sliding window to change with latitude, we find plasticity does not track B, although in this case, at odds with theoretical expectations, our estimates of B differ across latitude vs. longitude. We argue that a model combining photoperiod and mean temperature is most consistent with current understanding of phenological cues in passerines, the results from which suggest that each species could respond to projected increases in spring temperatures through plasticity alone. However, our estimates of B require further validation.

Transcriptomic SNP discovery for custom genotyping arrays: impacts of sequence data, SNP calling method and genotyping technology on the probability of validation success

BACKGROUND

Single nucleotide polymorphism (SNP) discovery is an important goal of many studies. However, the number of 'putative' SNPs discovered from a sequence resource may not provide a reliable indication of the number that will successfully validate with a given genotyping technology. For this it may be necessary to account for factors such as the method used for SNP discovery and the type of sequence data from which it originates, suitability of the SNP flanking sequences for probe design, and genomic context. To explore the relative importance of these and other factors, we used Illumina sequencing to augment an existing Roche 454 transcriptome assembly for the Antarctic fur seal (Arctocephalus gazella). We then mapped the raw Illumina reads to the new hybrid transcriptome using BWA and BOWTIE2 before calling SNPs with GATK. The resulting markers were pooled with two existing sets of SNPs called from the original 454 assembly using NEWBLER and SWAP454. Finally, we explored the extent to which SNPs discovered using these four methods overlapped and predicted the corresponding validation outcomes for both Illumina Infinium iSelect HD and Affymetrix Axiom arrays.

RESULTS

Collating markers across all discovery methods resulted in a global list of 34,718 SNPs. However, concordance between the methods was surprisingly poor, with only 51.0 % of SNPs being discovered by more than one method and 13.5 % being called from both the 454 and Illumina datasets. Using a predictive modeling approach, we could also show that SNPs called from the Illumina data were on average more likely to successfully validate, as were SNPs called by more than one method. Above and beyond this pattern, predicted validation outcomes were also consistently better for Affymetrix Axiom arrays.

CONCLUSIONS

Our results suggest that focusing on SNPs called by more than one method could potentially improve validation outcomes. They also highlight possible differences between alternative genotyping technologies that could be explored in future studies of non-model organisms.

Population genomic footprints of fine-scale differentiation between habitats in Mediterranean blue tits

Linking population genetic variation to the spatial heterogeneity of the environment is of fundamental interest to evolutionary biology and ecology, in particular when phenotypic differences between populations are observed at biologically small spatial scales. Here, we applied restriction-site associated DNA sequencing (RAD-Seq) to test whether phenotypically differentiated populations of wild blue tits (Cyanistes caeruleus) breeding in a highly heterogeneous environment exhibit genetic structure related to habitat type. Using 12 106 SNPs in 197 individuals from deciduous and evergreen oak woodlands, we applied complementary population genomic analyses, which revealed that genetic variation is influenced by both geographical distance and habitat type. A fine-scale genetic differentiation supported by genome- and transcriptome-wide analyses was found within Corsica, between two adjacent habitats where blue tits exhibit marked differences in breeding time while nesting < 6 km apart. Using redundancy analysis (RDA), we show that genomic variation remains associated with habitat type when controlling for spatial and temporal effects. Finally, our results suggest that the observed patterns of genomic differentiation were not driven by a small proportion of highly differentiated loci, but rather emerged through a process such as habitat choice, which reduces gene flow between habitats across the entire genome. The pattern of genomic isolation-by-environment closely matches differentiation observed at the phenotypic level, thereby offering significant potential for future inference of phenotype-genotype associations in a heterogeneous environment.

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic variation in different populations? Great tits (Parus major) have been studied extensively in long‐term studies across Europe and consequently are considered an ecological ‘model organism’. Recently, genomic resources have been developed for the great tit, including a custom SNP chip and genetic linkage map. In this study, we used a suite of approaches to investigate the genetic architecture of eight quantitative traits in two long‐term study populations of great tits—one in the Netherlands and the other in the United Kingdom. Overall, we found little evidence for the presence of genes of large effects in either population. Instead, traits appeared to be influenced by many genes of small effect, with conservative estimates of the number of contributing loci ranging from 31 to 310. Despite concordance between population‐specific heritabilities, we found no evidence for the presence of loci having similar effects in both populations. While population‐specific genetic architectures are possible, an undetected shared architecture cannot be rejected because of limited power to map loci of small and moderate effects. This study is one of few examples of genetic architecture analysis in replicated wild populations and highlights some of the challenges and limitations researchers will face when attempting similar molecular quantitative genetic studies in free‐living populations.

Genetic-geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping

Publically available SNP array increases the marker density for genotyping of forage crop, Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic-geographic correlation. Grassland ecosystems are ubiquitous across temperate and tropical regions, totalling 37% of the terrestrial land cover of the planet, and thus represent a global resource for understanding local adaptations to environment. However, genomic resources for grass species (outside cereals) are relatively poor. The advent of next-generation DNA sequencing and high-density SNP genotyping platforms enables the development of dense marker assays for population genetics analyses and genome-wide association studies. A high-density SNP marker resource (Illumina Infinium assay) for perennial ryegrass (Lolium perenne) was created and validated in a broad ecotype collection of 716 individuals sampled from 90 sites across Europe. Genetic diversity within and between populations was assessed. A strong correlation of geographic origin to genetic structure was found using principal component analysis, with significant correlation to longitude and latitude (P < 0.001). The potential of this array as a resource for studies of germplasm diversity and identifying traits underpinning adaptive variation is highlighted.

The influence of nonrandom extra-pair paternity on heritability estimates derived from wild pedigrees

Quantitative genetic analysis is often fundamental for understanding evolutionary processes in wild populations. Avian populations provide a model system due to the relative ease of inferring relatedness among individuals through observation. However, extra-pair paternity (EPP) creates erroneous links within the social pedigree. Previous work has suggested this causes minor underestimation of heritability if paternal misassignment is random and hence not influenced by the trait being studied. Nevertheless, much literature suggests numerous traits are associated with EPP and the accuracy of heritability estimates for such traits remains unexplored. We show analytically how nonrandom pedigree errors can influence heritability estimates. Then, combining empirical data from a large great tit (Parus major) pedigree with simulations, we assess how heritability estimates derived from social pedigrees change depending on the mode of the relationship between EPP and the focal trait. We show that the magnitude of the underestimation is typically small (<15%). Hence, our analyses suggest that quantitative genetic inference from pedigrees derived from observations of social relationships is relatively robust; our approach also provides a widely applicable method for assessing the consequences of nonrandom EPP.

In vitro selection of DNA-cleaving deoxyribozyme with site-specific thymidine excision activity

Single-nucleotide polymorphisms, either inherited or due to spontaneous DNA damage, are associated with numerous diseases. Developing tools for site-specific nucleotide modification may one day provide a way to alter disease polymorphisms. Here, we describe the in vitro selection and characterization of a new deoxyribozyme called F-8, which catalyzes nucleotide excision specifically at thymidine. Cleavage by F-8 generates 3'- and 5'-phosphate ends recognized by DNA modifying enzymes, which repair the targeted deoxyribonucleotide while maintaining the integrity of the rest of the sequence. These results illustrate the potential of DNAzymes as tools for DNA manipulation.

Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long-term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation-derived maternal links and microsatellite-derived paternal links; (ii) Pedigree 2, using SNP-derived assignment of both maternity and paternity; and (iii) whole-genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.

Reference genes for quantitative gene expression studies in multiple avian species

Quantitative real-time PCR (qPCR) rapidly and reliably quantifies gene expression levels across different experimental conditions. Selection of suitable reference genes is essential for meaningful normalization and thus correct interpretation of data. In recent years, an increasing number of avian species other than the chicken has been investigated molecularly, highlighting the need for an experimentally validated pan-avian primer set for reference genes. Here we report testing a set for 14 candidate reference genes (18S, ABL, GAPDH, GUSB, HMBS, HPRT, PGK1, RPL13, RPL19, RPS7, SDHA, TFRC, VIM, YWHAZ) on different tissues of the mallard (Anas platyrhynchos), domestic chicken (Gallus gallus domesticus), common crane (Grus grus), white-tailed eagle (Haliaeetus albicilla), domestic turkey (Meleagris gallopavo f. domestica), cockatiel (Nymphicus hollandicus), Humboldt penguin (Sphenicus humboldti), ostrich (Struthio camelus) and zebra finch (Taeniopygia guttata), spanning a broad range of the phylogenetic tree of birds. Primer pairs for six to 11 genes were successfully established for each of the nine species. As a proof of principle, we analyzed expression levels of 10 candidate reference genes as well as FOXP2 and the immediate early genes, EGR1 and CFOS, known to be rapidly induced by singing in the avian basal ganglia. We extracted RNA from microbiopsies of the striatal song nucleus Area X of adult male zebra finches after they had sang or remained silent. Using three different statistical algorithms, we identified five genes (18S, PGK1, RPS7, TFRC, YWHAZ) that were stably expressed within each group and also between the singing and silent conditions, establishing them as suitable reference genes. In conclusion, the newly developed pan-avian primer set allows accurate normalization and quantification of gene expression levels in multiple avian species.

Estimation of linkage disequilibrium and interspecific gene flow in Ficedula flycatchers by a newly developed 50k single-nucleotide polymorphism array

With the access to draft genome sequence assemblies and whole-genome resequencing data from population samples, molecular ecology studies will be able to take truly genome-wide approaches. This now applies to an avian model system in ecological and evolutionary research: Old World flycatchers of the genus Ficedula, for which we recently obtained a 1.1 Gb collared flycatcher genome assembly and identified 13 million single-nucleotide polymorphism (SNP)s in population resequencing of this species and its sister species, pied flycatcher. Here, we developed a custom 50K Illumina iSelect flycatcher SNP array with markers covering 30 autosomes and the Z chromosome. Using a number of selection criteria for inclusion in the array, both genotyping success rate and polymorphism information content (mean marker heterozygosity = 0.41) were high. We used the array to assess linkage disequilibrium (LD) and hybridization in flycatchers. Linkage disequilibrium declined quickly to the background level at an average distance of 17 kb, but the extent of LD varied markedly within the genome and was more than 10-fold higher in ‘genomic islands’ of differentiation than in the rest of the genome. Genetic ancestry analysis identified 33 F₁ hybrids but no later-generation hybrids from sympatric populations of collared flycatchers and pied flycatchers, contradicting earlier reports of backcrosses identified from much fewer number of markers. With an estimated divergence time as recently as <1 Ma, this suggests strong selection against F₁ hybrids and unusually rapid evolution of reproductive incompatibility in an avian system.

Challenges and prospects in genome-wide quantitative trait loci mapping of standing genetic variation in natural populations

A considerable challenge in evolutionary genetics is to understand the genetic mechanisms that facilitate or impede evolutionary adaptation in natural populations. For this, we must understand the genetic loci contributing to trait variation and the selective forces acting on them. The decreased costs and increased feasibility of obtaining genotypic data on a large number of individuals have greatly facilitated gene mapping in natural populations, particularly because organisms whose genetics have been historically difficult to study are now within reach. Here we review the methods available to evolutionary ecologists interested in dissecting the genetic basis of traits in natural populations. Our focus lies on standing genetic variation in outbred populations. We present an overview of the current state of research in the field, covering studies on both plants and animals. We also draw attention to particular challenges associated with the discovery of quantitative trait loci and discuss parallels to studies on crops, livestock, and humans. Finally, we point to some likely future developments in genetic mapping studies.

Genomic dissection of variation in clutch size and egg mass in a wild great tit (Parus major) population

Clutch size and egg mass are life history traits that have been extensively studied in wild bird populations, as life history theory predicts a negative trade-off between them, either at the phenotypic or at the genetic level. Here, we analyse the genomic architecture of these heritable traits in a wild great tit (Parus major) population, using three marker-based approaches - chromosome partitioning, quantitative trait locus (QTL) mapping and a genome-wide association study (GWAS). The variance explained by each great tit chromosome scales with predicted chromosome size, no location in the genome contains genome-wide significant QTL, and no individual SNPs are associated with a large proportion of phenotypic variation, all of which may suggest that variation in both traits is due to many loci of small effect, located across the genome. There is no evidence that any regions of the genome contribute significantly to both traits, which combined with a small, nonsignificant negative genetic covariance between the traits, suggests the absence of genetic constraints on the independent evolution of these traits. Our findings support the hypothesis that variation in life history traits in natural populations is likely to be determined by many loci of small effect spread throughout the genome, which are subject to continued input of variation by mutation and migration, although we cannot exclude the possibility of an additional input of major effect genes influencing either trait.

Next-generation QTL mapping: crowdsourcing SNPs, without pedigrees

For many molecular ecologists, the mantra and mission of the field of ecological genomics could be encapsulated by the phrase 'to find the genes that matter' (Mitchell-Olds ; Rockman ). This phrase of course refers to the early hope and current increasing success in the search for genes whose variation underlies phenotypic variation and fitness in natural populations. In the years since the modern incarnation of the field of ecological genomics, many would agree that the low-hanging fruit has, at least in principle, been plucked: we now have several elegant examples of genes whose variation influences key adaptive traits in natural populations, and these examples have revealed important insights into the architecture of adaptive variation (Hoekstra et al. ; Shapiro et al. ; Chan et al. ). But how well will these early examples, often involving single genes of large effect on discrete or near-discrete phenotypes, represent the dynamics of adaptive change for the totality of phenotypes in nature? Will traits exhibiting continuous rather than discrete variation in natural populations have as simple a genetic basis as these early examples suggest (Prasad et al. ; Rockman )? Two papers in this issue (Robinson et al. ; Santure et al. ) not only suggest answers to these questions but also provide useful extensions of statistical approaches for ecological geneticists to study the genetics of continuous variation in nature. Together these papers, by the same research groups studying evolution in a natural population of Great Tits (Parus major), provide a glimpse of what we should expect as the field begins to dissect the genetic basis of what is arguably the most common type of variation in nature, and how genome-wide surveys of variation can be applied to natural populations without pedigrees.

Replicated high-density genetic maps of two great tit populations reveal fine-scale genomic departures from sex-equal recombination rates

Linking variation in quantitative traits to variation in the genome is an important, but challenging task in the study of life-history evolution. Linkage maps provide a valuable tool for the unravelling of such trait-gene associations. Moreover, they give insight into recombination landscapes and between-species karyotype evolution. Here we used genotype data, generated from a 10k single-nucleotide polymorphism (SNP) chip, of over 2000 individuals to produce high-density linkage maps of the great tit (Parus major), a passerine bird that serves as a model species for ecological and evolutionary questions. We created independent maps from two distinct populations: a captive F2-cross from The Netherlands (NL) and a wild population from the United Kingdom (UK). The two maps contained 6554 SNPs in 32 linkage groups, spanning 2010 cM and 1917 cM for the NL and UK populations, respectively, and were similar in size and marker order. Subtle levels of heterochiasmy within and between chromosomes were remarkably consistent between the populations, suggesting that the local departures from sex-equal recombination rates have evolved. This key and surprising result would have been impossible to detect if only one population was mapped. A comparison with zebra finch Taeniopygia guttata, chicken Gallus gallus and the green anole lizard Anolis carolinensis genomes provided further insight into the evolution of avian karyotypes.

Partitioning of genetic variation across the genome using multimarker methods in a wild bird population

The underlying basis of genetic variation in quantitative traits, in terms of the number of causal variants and the size of their effects, is largely unknown in natural populations. The expectation is that complex quantitative trait variation is attributable to many, possibly interacting, causal variants, whose effects may depend upon the sex, age and the environment in which they are expressed. A recently developed methodology in animal breeding derives a value of relatedness among individuals from high-density genomic marker data, to estimate additive genetic variance within livestock populations. Here, we adapt and test the effectiveness of these methods to partition genetic variation for complex traits across genomic regions within ecological study populations where individuals have varying degrees of relatedness. We then apply this approach for the first time to a natural population and demonstrate that genetic variation in wing length in the great tit (Parus major) reflects contributions from multiple genomic regions. We show that a polygenic additive mode of gene action best describes the patterns observed, and we find no evidence of dosage compensation for the sex chromosome. Our results suggest that most of the genomic regions that influence wing length have the same effects in both sexes. We found a limited amount of genetic variance in males that is attributed to regions that have no effects in females, which could facilitate the sexual dimorphism observed for this trait. Although this exploratory work focuses on one complex trait, the methodology is generally applicable to any trait for any laboratory or wild population, paving the way for investigating sex-, age- and environment-specific genetic effects and thus the underlying genetic architecture of phenotype in biological study systems.

Fish scales and SNP chips: SNP genotyping and allele frequency estimation in individual and pooled DNA from historical samples of Atlantic salmon (Salmo salar)

Background

DNA extracted from historical samples is an important resource for understanding genetic consequences of anthropogenic influences and long-term environmental change. However, such samples generally yield DNA of a lower amount and quality, and the extent to which DNA degradation affects SNP genotyping success and allele frequency estimation is not well understood. We conducted high density SNP genotyping and allele frequency estimation in both individual DNA samples and pooled DNA samples extracted from dried Atlantic salmon (Salmo salar) scales stored at room temperature for up to 35 years, and assessed genotyping success, repeatability and accuracy of allele frequency estimation using a high density SNP genotyping array.

Results

In individual DNA samples, genotyping success and repeatability was very high (> 0.973 and > 0.998, respectively) in samples stored for up to 35 years; both increased with the proportion of DNA of fragment size > 1000 bp. In pooled DNA samples, allele frequency estimation was highly repeatable (Repeatability = 0.986) and highly correlated with empirical allele frequency measures (Mean Adjusted R² = 0.991); allele frequency could be accurately estimated in > 95% of pooled DNA samples with a reference group of at least 30 individuals. SNPs located in polyploid regions of the genome were more sensitive to DNA degradation: older samples had lower genotyping success at these loci, and a larger reference panel of individuals was required to accurately estimate allele frequencies.

Conclusions

SNP genotyping was highly successful in degraded DNA samples, paving the way for the use of degraded samples in SNP genotyping projects. DNA pooling provides the potential for large scale population genetic studies with fewer assays, provided enough reference individuals are also genotyped and DNA quality is properly assessed beforehand. We provide recommendations for future studies intending to conduct high-throughput SNP genotyping and allele frequency estimation in historical samples.

DNAzyme based gap-LCR detection of single-nucleotide polymorphism

Fast and accurate detection of single-nucleotide polymorphism (SNP) is thought more and more important for understanding of human physiology and elucidating the molecular based diseases. A great deal of effort has been devoted to developing accurate, rapid, and cost-effective technologies for SNP analysis. However most of those methods developed to date incorporate complicated probe labeling and depend on advanced equipment. The DNAzyme based Gap-LCR detection method averts any chemical modification on probes and circumvents those problems by incorporating a short functional DNA sequence into one of LCR primers. Two kinds of exonuclease are utilized in our strategy to digest all the unreacted probes and release the DNAzymes embedded in the LCR product. The DNAzyme applied in our method is a versatile tool to report the result of SNP detection in colorimetric or fluorometric ways for different detection purposes.

SNP marker detection and genotyping in tilapia

We have generated a unique resource consisting of nearly 175 000 short contig sequences and 3569 SNP markers from the widely cultured GIFT (Genetically Improved Farmed Tilapia) strain of Nile tilapia (Oreochromis niloticus). In total, 384 SNPs were selected to monitor the wider applicability of the SNPs by genotyping tilapia individuals from different strains and different geographical locations. In all strains and species tested (O. niloticus, O. aureus and O. mossambicus), the genotyping assay was working for a similar number of SNPs (288-305 SNPs). The actual number of polymorphic SNPs was, as expected, highest for individuals from the GIFT population (255 SNPs). In the individuals from an Egyptian strain and in individuals caught in the wild in the basin of the river Volta, 197 and 163 SNPs were polymorphic, respectively. A pairwise calculation of Nei's genetic distance allowed the discrimination of the individual strains and species based on the genotypes determined with the SNP set. We expect that this set will be widely applicable for use in tilapia aquaculture, e.g. for pedigree reconstruction. In addition, this set is currently used for assaying the genetic diversity of native Nile tilapia in areas where tilapia is, or will be, introduced in aquaculture projects. This allows the tracing of escapees from aquaculture and the monitoring of effects of introgression and hybridization.