The golden jackal of Africa (Canis aureus) has long been considered a conspecific of jackals distributed throughout Eurasia, with the nearest source populations in the Middle East. However, two recent reports found that mitochondrial haplotypes of some African golden jackals aligned more closely to gray wolves (Canis lupus), which is surprising given the absence of gray wolves in Africa and the phenotypic divergence between the two species. Moreover, these results imply the existence of a previously unrecognized phylogenetically distinct species despite a long history of taxonomic work on African canids. To test the distinct-species hypothesis and understand the evolutionary history that would account for this puzzling result, we analyzed extensive genomic data including mitochondrial genome sequences, sequences from 20 autosomal loci (17 introns and 3 exon segments), microsatellite loci, X- and Y-linked zinc-finger protein gene (ZFX and ZFY) sequences, and whole-genome nuclear sequences in African and Eurasian golden jackals and gray wolves. Our results provide consistent and robust evidence that populations of golden jackals from Africa and Eurasia represent distinct monophyletic lineages separated for more than one million years, sufficient to merit formal recognition as different species: C. anthus (African golden wolf) and C. aureus (Eurasian golden jackal). Using morphologic data, we demonstrate a striking morphologic similarity between East African and Eurasian golden jackals, suggesting parallelism, which may have misled taxonomists and likely reflects uniquely intense interspecific competition in the East African carnivore guild. Our study shows how ecology can confound taxonomy if interspecific competition constrains size diversification.

Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.

Early-life experiences can dramatically affect adult traits. However, the evolutionary origins of such early-life effects are debated. The predictive adaptive response hypothesis argues that adverse early environments prompt adaptive phenotypic adjustments that prepare animals for similar challenges in adulthood. In contrast, the developmental constraints hypothesis argues that early adversity is generally costly. To differentiate between these hypotheses, we studied two sets of wild female baboons: those born during low-rainfall, low-quality years and those born during normal-rainfall, high-quality years. For each female, we measured fertility-related fitness components during years in adulthood that matched and mismatched her early conditions. We found support for the developmental constraints hypothesis: females born in low-quality environments showed greater decreases in fertility during drought years than females born in high-quality environments, even though drought years matched the early conditions of females born in low-quality environments. Additionally, we found that females born in low-quality years to high-status mothers did not experience reduced fertility during drought years. These results indicate that early ecological adversity did not prepare individuals to cope with ecological challenges in later life. Instead, individuals that experienced at least one high-quality early environment—either ecological or social—were more resilient to ecological stress in later life. Together, these data suggest that early adversity carries lifelong costs, which is consistent with the developmental constraints hypothesis.

SignificanceSocial status can predict health, reproduction, and survival in social animals. To understand why, we investigated social status and immune gene expression in wild baboons, where kinship determines status in females but fighting ability determines status in males. We identified a much stronger relationship between status and gene expression in males than females. Further, inflammation-related genes were more active in high-status than low-status males; the opposite effect has been reported in status hierarchies that are not determined by fighting ability. Our results suggest that males who compete successfully for high status are already immunologically distinct. They therefore emphasize that how social hierarchies are formed shapes their relationship to immune function and health.

Here, we present estimates of heritability and selection on network traits in a single population, allowing us to address the evolutionary potential of social behavior and the poorly understood link between sociality and fitness. To evolve, sociality must have some heritable basis, yet the heritability of social relationships is largely unknown. Recent advances in both social network analyses and quantitative genetics allow us to quantify attributes of social relationships and estimate their heritability in free-living populations. Our analyses addressed a variety of measures (in-degree, out-degree, attractiveness, expansiveness, embeddedness, and betweenness), and we hypothesized that traits reflecting relationships controlled by an individual (i.e., those that the individual initiated or were directly involved in) would be more heritable than those based largely on the behavior of conspecifics. Identifying patterns of heritability and selection among related traits may provide insight into which types of relationships are important in animal societies. As expected, we found that variation in indirect measures was largely explained by nongenetic variation. Yet, surprisingly, traits capturing initiated interactions do not possess significant additive genetic variation, whereas measures of received interactions are heritable. Measures describing initiated aggression and position in an agonistic network are under selection (0.3 < |S| < 0.4), although advantageous trait values are not inherited by offspring. It appears that agonistic relationships positively influence fitness and seemingly costly or harmful ties may, in fact, be beneficial. Our study highlights the importance of studying agonistic as well as affiliative relationships to understand fully the connections between sociality and fitness.animal model | animal social networks | yellow-bellied marmots B ehavioral ecologists have long viewed sociality and social relationships as adaptive traits shaped by evolution (1, 2). However, if we are to study the evolution of sociality and social relationships, there must be heritable variation in traits describing individual social behavior. Numerous studies have identified heritable variation in animal dispositions (3, 4), morphological characteristics, and behavioral traits (5) that may affect how individuals interact with conspecifics, yet the role of genetics in social interactions themselves is poorly understood. If traits affecting social interactions are heritable, we may expect measures of social relationships to be explained somewhat by additive genetic factors.There has been a recent upsurge in using animal social networks as tools for studying the ecology, evolution, and adaptive significance of sociality (6-8). Networks are based on interactions between individuals, and a variety of measures have been developed to quantify how connected individuals are with others in the group (9). Although studies of nonhuman species have explored the development of social networks (10) as well as the causes (11-13) and...