Annual Report 2019
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ST. KILDA SOAY SHEEP PROJECT: ANNUAL REPORT 2019 J.G. Pilkington5,1, C. Bérénos1, X. Bal1, D. Childs2, Y. Corripio-Miyar3, A. Fenton11, M. Fraser8, A. Free12, H. Froy9, A. Hayward3, H. Hipperson2, W. Huang1, D. Hunter2,5, S.E. Johnston1, F. Kenyon3, H. Lemon1, D. McBean3, L. McNally1, T. McNeilly3, R.J. Mellanby4, M. Morrissey5, D. Nussey1, R. J. Pakeman7, A. Pedersen1, J.M. Pemberton1, J. Slate2, A.M. Sparks10, I.R. Stevenson6, M.A. Stoffel1, A. Sweeny1, H. Vallin8, K. Watt1. 1Institute of Evolutionary Biology, University of Edinburgh. 2Department of Animal and Plant Sciences, University of Sheffield. 3Moredun Research Institute, Edinburgh. 4Royal (Dick) School of Veterinary Studies, University of Edinburgh. 5School of Biology, University of St. Andrews. 6Sunadal Data Solutions, Penicuik. 7James Hutton Institute, Craigiebuckler, Aberdeen. 8Institute of Biological, Environmental & Rural Sciences, Aberystwyth University. 9Norwegian University of Science and Technology, Trondheim. 10School of Biology, University of Leeds. 11Institute of Integrative Biology, University of Liverpool. 12Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh. POPULATION OVERVIEW ......................................................................................................... 2 REPORTS ON COMPONENT STUDIES ........................................................................................ 4 Determination of Pregnancy in Soay sheep ................................................................................... 4 The Ecology Within: The impact of gut ecosystem dynamics on host fitness in the wild ............... 8 Inbreeding depression on survival: A genomic perspective ......................................................... 10 Finding the genes that underlie interesting traits in Soay sheep ................................................. 14 Association between MHC haplotypes and phenotypic traits in Soay sheep ............................... 18 PUBLICATIONS. ..................................................................................................................... 20 ACKNOWLEDGEMENTS.. ........................................................................................................ 21 APPENDIX A: PERSONNEL NEWS & SCHEDULE OF WORK ..................................................... 21 1 Population Overview The sheep population on Hirta entered 2019 at a moderate level and there was relatively low mortality over winter with 46 tagged animals being found dead with in the study area. Lambing began on the 25th of March with 79.92% of lambs born surviving (Fig. 1). Figure 1. The temporal distribution of lamb births during 2019. In December 2019, 634 tagged sheep were believed to be alive on Hirta, of which 508 regularly used the study area, an increase of 34.4% using the study area since the previous year. The age distribution of the population is shown in Figure 2 and changes in sheep numbers in the study area over time are shown in Figure 3. Figure 2. Age distribution of tagged Soay sheep presumed to be alive at the end of 2019. 2 Figure 3. The number of sheep counted on the whole island and the number of tagged sheep regularly using the study area since 1985. One whole-island count yielded 1810 tagged and untagged sheep, with the details displayed in Table 1. The total population had increased by 29.2% since summer 2018 when it was estimated as 1401. This gives a delta (calculated as ln (Nt+1/Nt)) of +0.256. The whole island count is also shown in Figure 3. Table 1. Demographic and geographic distribution of sheep observed during the count of Hirta on August 13th 2019. Coat colours are DW = dark wild, DS = dark self, LW = light wild, and LS = light self. Location Females Males Lambs Total DW DS LW LS DW DS LW LS Conachair/Oiseval 171 12 40 3 59 1 11 0 155 452 Mullach Bi / Cambir 265 12 69 4 53 2 20 0 258 683 Ruaival/Village 234 9 73 5 67 2 18 0 267 675 Total 670 33 182 12 179 5 49 0 680 1810 3 Determination of Pregnancy in Soay sheep. Michael Morrissey, Jill Pilkington and Josephine Pemberton. Background The main reason why the St Kilda Soay sheep project can support such a broad range of studies is the extensive individual-based data on life histories. Essentially, the remarkably complete record of births and deaths in this wild population is the backbone of the study. Despite the scope of the data there are inevitably areas where further information could support even more detailed and extensive studies. In particular, the NERC grant “Resolving the paradox of stasis: addressing the missing fraction problem”, held by Michael Morrissey and Josephine Pemberton has identified more complete determination of pregnancy status, particularly of ewe lambs, as an area where further efforts could support better understanding of how natural selection acts throughout the entire life cycle. This report describes our progress on developing a more comprehensive, non-invasive assay of pregnancy using hormones measured in faecal samples. We focus on the determination of pregnancy status in ewe lambs (ewes that get pregnant at approximately seven months of age), as they appear to be pregnant at lower rates than older ewes. Furthermore, we suspect that the scope for uncertainty in our current data on pregnancy is greatest for ewe lambs, since they may be most likely to abort a foetus during gestation, and if born their lambs might suffer the greatest neonatal mortality and be missed during field work. Sample collection In each of December of 2017 and January of 2018, Jill Pilkington collected two faecal samples from all ewe lambs and yearlings, and from a sample of older individuals. Subsequently, pregnancy status was determined with high certainty for a subset of these. In some cases, certain determinations that an individual was, or was not, pregnant was possible from post mortem. In other cases, positive determination of pregnancy was possible from observations of live births. Here, we focus on only those cases of with highly certain pregnancy status, for the purpose of developing and testing our approach. Replicate faecal samples from the focal set of ewe lambs were assayed for progesterone concentration by Helen Evans (Nationwide Specialist Laboratories, Cambridge). Timing of sampling In December of 2017, Jill Pilkington formed the opinion that faecal samples from that time were unlikely to be representative of pregnancy status for that winter, because the rut was ongoing at the time of sample collection. Progesterone assay results supported this, with overlap between individuals subsequently determined to have been pregnant or not pregnant in December, but this was not the case in January (Fig. 4). Subsequent analyses consider only samples from January. 4 Figure 4. The distributions of faecal progesterone assay results (umol/L/g) in samples from Soay lambs in December of 2017 and January of 2018, in relation to their pregnancy status, as subsequently determined from field observations. Ascertainment of pregnancy status We constructed a probabilistic model that estimated: (a) The variability of progesterone concentration from one replicate sample to the next, within an individual (b) The means and variances of progesterone concentration for pregnant and non-pregnant ewes, and (c) Individual probabilities of being pregnant The model estimates indicate substantial repeatability of replicate samples (taken min. 3 days apart in January) on the same individual, with a within-individual variance of progesterone concentration (log umol/L/g) of 0.15. The variances among pregnant and non-pregnant individuals are 0.77 and 0.13, respectively. As such, the progesterone concentrations in our samples provide substantial information on individual variation in progesterone concentration, i.e., they have appreciable repeatability. 5 We estimate that there is substantial separation of the distributions of progesterone concentration, with pregnant ewe lambs having a mean concentration of 5.44 (log umol/L/g) and non-pregnant individuals having a mean concentration of 3.4. As such, most pregnant and non-pregnant individuals fall in distinct ranges of progesterone concentration, but there is a small intermediate range in which pregnancy status is ambiguous (Fig. 5). Figure 5. Model-based inference of the distribution of faecal progesterone concentration among pregnant and non-pregnant ewe lambs, using data from the winter of 2017/18. Most individuals can thus have their pregnancy status confirmed by the model with reasonably high certainty (Table 2). Interestingly, two individuals that were determined not to have been pregnant on the basis of post-mortem (CG029 and CG030; Table 2) appear most likely to have been pregnant, on the basis of progesterone concentrations. This probably reflects a low rate of loss of embryos or possibly pseudo pregnancy, but should not interfere with our ability to study trade-offs between survival and reproduction that occur in early the lives of ewes. 6 Table 2. Individual model-based posterior probabilities of having been pregnant, using data from field observations and faecal progesterone assays simultaneously. Tag numbers refer to the green tags assigned to the 2017 birth cohort. Pregnancy status based on field data is coded as zero for non-pregnant ewe lambs and one for pregnant individuals. tag pregnancy status model-based probability of CG015 from field0 data bhaving 0.194been pregnant CG019 1 1.000 CG020 1 1.000 CG029 0 0.994 CG030 0 0.716 CG039 1 1.000 CG047 1 1.000 CG048