Effects of nest-box environment on fledgling success rate and pathogen load.

Nest boxes have been used for many decades as tools for conservation and to study avian population dynamics. Plastic is increasingly used as a material for nest boxes, but no studies have investigated effects of this different material. Two consecutive studies were conducted to investigate effects of nest-box environment on nidicolous parasites, bacteria and fungi, as well as nest success, in blue tits Cyanistes caeruleus and great tits Parus major. The first compared microclimate and parasite and pathogen load in plastic and wooden nest boxes. The second tested the nest protection hypothesis ­ that birds naturally incorporate aromatic herbs into nests to decrease nest parasites and pathogens ­ by comparing parasite and pathogen load in plastic nest boxes to which aromatic or non-aromatic plant material was added. No significant difference in nest-box temperature or relative humidity was found between plastic and wooden boxes. Wooden boxes, however, contained 30-fold higher numbers of fleas and a higher total bacterial load on chicks. Fledging success for blue tit broods was significantly higher in wooden boxes. Parasites and bacteria did not decrease by the inclusion of aromatic herbs. The results increase the evidence base for nest-box design in support of plastic, which can provide an appropriate alternative nest-box material to wood, with apparently no difference in microclimate and no increase in the load of measured parasites and pathogens.

No evidence for MHC class I-based disassortative mating in a wild population of great tits.

Genes of the major histocompatibility complex (MHC) are regarded as a potentially important target of mate choice due to the fitness benefits that may be conferred to the offspring. According to the complementary genes hypothesis, females mate with MHC dissimilar males to enhance the immunocompetence of their offspring or to avoid inbreeding depression. Here, we investigate whether selection favours a preference for maximally dissimilar or optimally dissimilar MHC class I types, based on MHC genotypes, average amino acid distances and the functional properties of the antigen-binding sites (MHC supertypes); and whether MHC type dissimilarity predicts relatedness between mates in a wild great tit population. In particular, we explore the role that MHC class I plays in female mate choice decisions while controlling for relatedness and spatial population structure, and examine the reproductive fitness consequences of MHC compatibility between mates. We find no evidence for the hypotheses that females select mates on the basis of either maximal or optimal MHC class I dissimilarity. A weak correlation between MHC supertype sharing and relatedness suggests that MHC dissimilarity at functional variants may not provide an effective index of relatedness. Moreover, the reproductive success of pairs did not vary with MHC dissimilarity. Our results provide no support for the suggestion that selection favours, or that mate choice realizes, a preference for complimentary MHC types.

Performance of methods to detect genetic variants from bisulphite sequencing data in a non-model species.

The profiling of epigenetic marks like DNA methylation has become a central aspect of studies in evolution and ecology. Bisulphite sequencing is commonly used for assessing genome-wide DNA methylation at single nucleotide resolution but these data can also provide information on genetic variants like single nucleotide polymorphisms (SNPs). However, bisulphite conversion causes unmethylated cytosines to appear as thymines, complicating the alignment and subsequent SNP calling. Several tools have been developed to overcome this challenge, but there is no independent evaluation of such tools for non-model species, which often lack genomic references. Here, we used whole-genome bisulphite sequencing (WGBS) data from four female great tits (Parus major) to evaluate the performance of seven tools for SNP calling from bisulphite sequencing data. We used SNPs from whole-genome resequencing data of the same samples as baseline SNPs to assess common performance metrics like sensitivity, precision, and the number of true positive, false positive, and false negative SNPs for the full range of variant and genotype quality values. We found clear differences between the tools in either optimizing precision (Bis-SNP), sensitivity (biscuit), or a compromise between both (all other tools). Overall, the choice of SNP caller strongly depends on which performance parameter should be maximized and whether ascertainment bias should be minimized to optimize downstream analysis, highlighting the need for studies that assess such differences.