Organisms can adapt to variable environments by using environmental cues to modulate developmental gene expression. In principle, maternal influences can adaptively adjust offspring phenotype when early life and adult environments match, but they may be maladaptive when future environments are not predictable. One of the best-studied 'maternal effects' is through modification of the offspring's hypothalamic-pituitary-adrenal (HPA) axis, the neuroendocrine system that controls responses to stress. In addition to the direct transfer of glucocorticoids from mother to offspring, offspring HPA function and other phenotypes can also be affected by epigenetic modifications like DNA methylation of the glucocorticoid receptor promoter. Here we examine how among-year variation in rainfall is related to DNA methylation during development and fitness in adulthood in the superb starling (Lamprotornis superbus), which lives in a climatically unpredictable environment where early life and adult environments are unlikely to match. We found that DNA methylation in the putative promoter of the glucocorticoid receptor gene is reduced in chicks - particularly in males - born following drier prebreeding periods. Additionally, DNA methylation is lower in males that become breeders than those that never breed. However, there is no relationship in females between DNA methylation and the likelihood of dispersing from the natal group to breed elsewhere. These results suggest that early life conditions may positively affect fitness in a sex-specific manner through chemical modification of an HPA-associated gene. This study is the first to show that epigenetic modifications during early life may influence the fitness of free-living organisms adapted to unpredictable environments.

The development of genetic markers has revolutionized molecular studies within and among populations. Although poly-allelic microsatellites are the most commonly used genetic marker for within-population studies of free-living animals, biallelic single nucleotide polymorphisms, or SNPs, have also emerged as a viable option for use in nonmodel systems. We describe a robust method of SNP discovery from the transcriptome of a nonmodel organism that resulted in more than 99% of the markers working successfully during genotyping. We then compare the use of 102 novel SNPs with 15 previously developed microsatellites for studies of parentage and kinship in cooperatively breeding superb starlings (Lamprotornis superbus) that live in highly kin-structured groups. For 95% of the offspring surveyed, SNPs and microsatellites identified the same genetic father, but only when behavioural information about the likely parents at a nest was included to aid in assignment. Moreover, when such behavioural information was available, the number of SNPs necessary for successful parentage assignment was reduced by half. However, in a few cases where candidate fathers were highly related, SNPs did a better job at assigning fathers than microsatellites. Despite high variation between individual pairwise relatedness values, microsatellites and SNPs performed equally well in kinship analyses. This study is the first to compare SNPs and microsatellites for analyses of parentage and relatedness in a species that lives in groups with a complex social and kin structure. It should also prove informative for those interested in developing SNP loci from transcriptome data when published genomes are unavailable.

Iridescence is widespread in the living world, occurring in organisms as diverse as bacteria, plants, and animals. Yet, compared to pigment-based forms of coloration, we know surprisingly little about the developmental and molecular bases of the structural colors that give rise to iridescence. Birds display a rich diversity of iridescent structural colors that are produced in feathers by the arrangement of melanin-containing organelles called melanosomes into nanoscale configurations, but how these often unusually shaped melanosomes form, or how they are arranged into highly organized nanostructures, remains largely unknown. Here, we use functional genomics to explore the developmental basis of iridescent plumage using superb starlings (Lamprotornis superbus), which produce both iridescent blue and non-iridescent red feathers. Through morphological and chemical analyses, we confirm that hollow, flattened melanosomes in iridescent feathers are eumelanin-based, whereas melanosomes in non-iridescent feathers are solid and amorphous, suggesting that high pheomelanin content underlies red coloration. Intriguingly, the nanoscale arrangement of melanosomes within the barbules was surprisingly similar between feather types. After creating a new genome assembly, we use transcriptomics to show that non-iridescent feather development is associated with genes related to pigmentation, metabolism, and mitochondrial function, suggesting non-iridescent feathers are more energetically expensive to produce than iridescent feathers. However, iridescent feather development is associated with genes related to structural and cellular organization, suggesting that, while nanostructures themselves may passively assemble, barbules and melanosomes may require active organization to give them their shape. Together, our analyses suggest that iridescent feathers form through a combination of passive self-assembly and active processes.

No abstract

The increasing interest in studying DNA methylation to understand how traits or diseases develop requires new and flexible approaches for quantifying DNA methylation in a diversity of organisms. In particular, we need efficient yet cost-effective ways to measure CpG methylation states over large and complete regions of the genome. Here, we develop TEEM-Seq (target-enriched enzymatic methyl sequencing), a method that combines enzymatic methyl sequencing with a custom-designed hybridization capture bait set that can be scaled to reactions including large numbers of samples in any species for which a reference genome is available. Using DNA from a passerine bird, the superb starling (Lamprotornis superbus), we show that TEEM-Seq is able to quantify DNA methylation states similarly well to the more traditional approaches of whole-genome and reduced-representation sequencing. Moreover, we demonstrate its reliability and repeatability, as duplicate libraries from the same samples were highly correlated. Importantly, the downstream bioinformatic analysis for TEEM-Seq is the same as for any sequence-based approach to studying DNA methylation, making it simple to incorporate into a variety of workflows. We believe that TEEM-Seq could replace traditional approaches for studying DNA methylation in candidate genes and pathways, and be effectively paired with other whole-genome or reduced-representation sequencing approaches to increase project sample sizes. In addition, TEEM-Seq can be combined with mRNA sequencing to examine how DNA methylation in promoters or other regulatory regions is related to the expression of individual genes or gene networks. By maximizing the number of samples in the hybridization reaction, TEEM-Seq is an inexpensive and flexible sequence-based approach for quantifying DNA methylation in species where other capture-based methods are unavailable or too expensive, particularly for non-model organisms.