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1. Genetic, maternal, and environmental influences on sociality in a pedigreed primate population

   https://doi.org/10.1038/s41437-022-00558-6  

   Godoy, Irene ; Korsten, Peter ; Perry, Susan E. ( September 2022 , Heredity)

   Various aspects of sociality in mammals (e.g., dyadic connectedness) are linked with measures of biological fitness (e.g., longevity). How within- and between-individual variation in relevant social traits arises in uncontrolled wild populations is challenging to determine but is crucial for understanding constraints on the evolution of sociality. We use an advanced statistical method, known as the ‘animal model’, which incorporates pedigree information, to look at social, genetic, and environmental influences on sociality in a long-lived wild primate. We leverage a longitudinal database spanning 20 years of observation on individually recognized white-faced capuchin monkeys (Cebus capucinus imitator), with a multi-generational pedigree. We analyze two measures of spatial association, using repeat sampling of 376 individuals (mean: 53.5 months per subject, range: 6–185 months per subject). Conditioned on the effects of age, sex, group size, seasonality, and El Niño–Southern Oscillation phases, we show low to moderate long-term repeatability (across years) of the proportion of time spent social (posterior mode [95% Highest Posterior Density interval]: 0.207 [0.169, 0.265]) and of average number of partners (0.144 [0.113, 0.181]) (latent scale). Most of this long-term repeatability could be explained by modest heritability (h²_social: 0.152 [0.094, 0.207];h²_partners: 0.113 [0.076, 0.149]) with small long-term maternal effects (m²_social: 0.000 [0.000, 0.045];m²_partners: 0.000 [0.000, 0.041]). Our models capture the majority of variance in our behavioral traits, with much of the variance explained by temporally changing factors, such as group of residence, highlighting potential limits to the evolvability of our trait due to social and environmental constraints.

    

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2. Genetic and ecological drivers of molt in a migratory bird

   https://doi.org/10.1038/s41598-022-26973-7  

   Contina, Andrea ; Bossu, Christen M. ; Allen, Daniel ; Wunder, Michael B. ; Ruegg, Kristen C. ( January 2023 , Scientific Reports)

   The ability of animals to sync the timing and location of molting (the replacement of hair, skin, exoskeletons or feathers) with peaks in resource availability has important implications for their ecology and evolution. In migratory birds, the timing and location of pre-migratory feather molting, a period when feathers are shed and replaced with newer, more aerodynamic feathers, can vary within and between species. While hypotheses to explain the evolution of intraspecific variation in the timing and location of molt have been proposed, little is known about the genetic basis of this trait or the specific environmental drivers that may result in natural selection for distinct molting phenotypes. Here we take advantage of intraspecific variation in the timing and location of molt in the iconic songbird, the Painted Bunting (Passerina ciris) to investigate the genetic and ecological drivers of distinct molting phenotypes. Specifically, we use genome-wide genetic sequencing in combination with stable isotope analysis to determine population genetic structure and molting phenotype across thirteen breeding sites. We then use genome-wide association analysis (GWAS) to identify a suite of genes associated with molting and pair this with gene-environment association analysis (GEA) to investigate potential environmental drivers of genetic variation in this trait. Associations between genetic variation in molt-linked genes and the environment are further tested via targeted SNP genotyping in 25 additional breeding populations across the range. Together, our integrative analysis suggests that molting is in part regulated by genes linked to feather development and structure (GLI2andCSPG4) and that genetic variation in these genes is associated with seasonal variation in precipitation and aridity. Overall, this work provides important insights into the genetic basis and potential selective forces behind phenotypic variation in what is arguably one of the most important fitness-linked traits in a migratory bird.

    

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3. Patterns of reproduction and autozygosity distinguish the breeding from nonbreeding gray wolves of Yellowstone National Park

   https://doi.org/10.1093/jhered/esad062  

   vonHoldt, Bridgett M. ; DeCandia, Alexandra L. ; Cassidy, Kira A. ; Stahler, Erin E. ; Sinsheimer, Janet S. ; Smith, Douglas W. ; Stahler, Daniel R. ; Lohmueller, ed., Kirk ( October 2023 , Journal of Heredity)

   For species of management concern, accurate estimates of inbreeding and associated consequences on reproduction are crucial for predicting their future viability. However, few studies have partitioned this aspect of genetic viability with respect to reproduction in a group-living social mammal. We investigated the contributions of foundation stock lineages, putative fitness consequences of inbreeding, and genetic diversity of the breeding versus nonreproductive segment of the Yellowstone National Park gray wolf population. Our dataset spans 25 years and seven generations since reintroduction, encompassing 152 nuclear families and 329 litters. We found more than 87% of the pedigree foundation genomes persisted and report influxes of allelic diversity from two translocated wolves from a divergent source in Montana. As expected for group-living species, mean kinship significantly increased over time but with minimal loss of observed heterozygosity. Strikingly, the reproductive portion of the population carried a significantly lower genome-wide inbreeding coefficients, autozygosity, and more rapid decay for linkage disequilibrium relative to the nonbreeding population. Breeding wolves had significantly longer lifespans and lower inbreeding coefficients than nonbreeding wolves. Our model revealed that the number of litters was negatively significantly associated with heterozygosity (R = −0.11). Our findings highlight genetic contributions to fitness, and the importance of the reproductively active individuals in a population to counteract loss of genetic variation in a wild, free-ranging social carnivore. It is crucial for managers to mitigate factors that significantly reduce effective population size and genetic connectivity, which supports the dispersion of genetic variation that aids in rapid evolutionary responses to environmental challenges.

    

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4. Genomic association with pathogen carriage in bighorn sheep ( Ovis canadensis )

   https://doi.org/10.1002/ece3.7159  

   Martin, Alynn M. ; Cassirer, E. Frances ; Waits, Lisette P. ; Plowright, Raina K. ; Cross, Paul C. ; Andrews, Kimberly R. ( March 2021 , Ecology and Evolution)

   Genetic composition can influence host susceptibility to, and transmission of, pathogens, with potential population‐level consequences. In bighorn sheep (Ovis canadensis), pneumonia epidemics caused byMycoplasma ovipneumoniaehave been associated with severe population declines and limited recovery across North America. Adult survivors either clear the infection or act as carriers that continually shedM. ovipneumoniaeand expose their susceptible offspring, resulting in high rates of lamb mortality for years following the outbreak event. Here, we investigated the influence of genomic composition on persistent carriage ofM. ovipneumoniaein a well‐studied bighorn sheep herd in the Wallowa Mountains of Oregon, USA. Using 10,605 SNPs generated using RADseq technology for 25 female bighorn sheep, we assessed genomic diversity metrics and employed family‐based genome‐wide association methodologies to understand variant association and genetic architecture underlying chronic carriage. We observed no differences among genome‐wide diversity metrics (heterozygosity and allelic richness) between groups. However, we identified two variant loci of interest and seven associated candidate genes, which may influence carriage status. Further, we found that the SNP panel explained ~55% of the phenotypic variance (SNP‐based heritability) forM. ovipneumoniaecarriage, though there was considerable uncertainty in these estimates. While small sample sizes limit conclusions drawn here, our study represents one of the first to assess the genomic factors influencing chronic carriage of a pathogen in a wild population and lays a foundation for understanding genomic influence on pathogen persistence in bighorn sheep and other wildlife populations. Future research should incorporate additional individuals as well as distinct herds to further explore the genomic basis of chronic carriage.

    

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5. A scalable estimator of SNP heritability for biobank-scale data

   https://doi.org/10.1093/bioinformatics/bty253  

   Wu, Yue ; Sankararaman, Sriram ( June 2018 , Bioinformatics)

   Heritability, the proportion of variation in a trait that can be explained by genetic variation, is an important parameter in efforts to understand the genetic architecture of complex phenotypes as well as in the design and interpretation of genome-wide association studies. Attempts to understand the heritability of complex phenotypes attributable to genome-wide single nucleotide polymorphism (SNP) variation data has motivated the analysis of large datasets as well as the development of sophisticated tools to estimate heritability in these datasets. Linear mixed models (LMMs) have emerged as a key tool for heritability estimation where the parameters of the LMMs, i.e. the variance components, are related to the heritability attributable to the SNPs analyzed. Likelihood-based inference in LMMs, however, poses serious computational burdens.

   We propose a scalable randomized algorithm for estimating variance components in LMMs. Our method is based on a method-of-moment estimator that has a runtime complexity O(NMB) for N individuals and M SNPs (where B is a parameter that controls the number of random matrix-vector multiplications). Further, by leveraging the structure of the genotype matrix, we can reduce the time complexity to O(NMBmax( log⁡3N, log⁡3M)).

   We demonstrate the scalability and accuracy of our method on simulated as well as on empirical data. On standard hardware, our method computes heritability on a dataset of 500 000 individuals and 100 000 SNPs in 38 min.

   The RHE-reg software is made freely available to the research community at: https://github.com/sriramlab/RHE-reg.

    

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