Ecological Research

, Volume 26, Issue 2, pp 265–276 | Cite as

New insights on diet variability revealed by DNA barcoding and high-throughput pyrosequencing: chamois diet in autumn as a case study

  • Gilles Rayé
  • Christian Miquel
  • Eric Coissac
  • Claire Redjadj
  • Anne Loison
  • Pierre Taberlet
Original Article


Characterizing the diet of large herbivores and the determinants of its variation remains a difficult task in wild species. DNA-based techniques have the potential to complement traditional time-consuming methods based on the microhistology of plant cuticle fragments in fecal or rumen samples. Recently, it has been shown that a short chloroplast DNA fragment, the P6 loop of the trnL (UAA) intron, can act as a minimalist barcode. Here, we used the trnL approach with high-throughput pyrosequencing to study diet from feces in a wild herbivore, the alpine chamois (Rupicapra rupicapra) and showed that the fine resolution in plant determination obtained with this method allows exploring subtle temporal shifts and inter-individual variability in diet composition. First, we built a DNA barcoding database of 475 plants species. Seventy-two percent of plant species can be unambiguously identified to species level, 79% to genus level and 100% to family level using the P6 loop. Second, we analysed 74 feces collected from October to November. Based on 47,896 P6 loop sequences, we identified a total of 110 taxa, 96 in October and 76 in November, with a clear diet shift between October and November. We recognized four and two clusters of feces composition in October and November, respectively, revealing different diet categories among individuals within each month. DNA-based diet analysis is faster and more taxonomically precise than studies based on microhistology, and opens new possibilities for analysing plant-herbivore interactions in the wild.


Diet DNA-barcoding Temporal and inter-individual variability Plant-herbivore Alpine chamois 


  1. Anthony RG, Smith NS (1974) Comparison of rumen and fecal analysis to describe deer diets. J Wildl Manag 38:729–746Google Scholar
  2. Auvray F (1983) Recherche sur l’éco-éthologie du mouflon (Ovis musimon musimon Schreber 1782) dans le massif de Caroux-Espinousse (Hérault). PhD thesis, Montpellier University, FranceGoogle Scholar
  3. Babad G (1997) Etude des relations entre un peuplement animal et la végétation: impacts du chamois, du chevreuil et du mouflon sur les peuplements forestiers dans la Réserve Nationale de Faune Sauvage et de Chasse des Bauges (Savoie). PhD thesis, Chambery University, FranceGoogle Scholar
  4. Berducou C (1974) Contribution à l’étude d’un problème éco-physiologique pyrénéen: l’alimentation hivernale de l’isard. PhD thesis, Toulouse University, FranceGoogle Scholar
  5. Bertolino S, di Montezemolo NC, Bassano B (2009) Food-niche relationships within a guild of alpine ungulates including an introduced species. J Zool 277:63–69CrossRefGoogle Scholar
  6. Bjelland T, Ekman S (2005) Fungal diversity in rock beneath a crustose lichen as revealed by molecular markers. Microb Ecol 49:598–603PubMedCrossRefGoogle Scholar
  7. Brownstein MJ, Carpten JD, Smith JR (1996) Modulation of non-templated nucleotide addition by Taq DNA polymerase: primer modifications that facilitate genotyping. BioTechniques 20:1008–1010Google Scholar
  8. Calenge C, Darmon G, Basille M, Loison A, Jullien JM (2007) The factorial decomposition of the Mahalanobis distances in habitat selection studies. Ecology 89:555–566CrossRefGoogle Scholar
  9. Castle EJ (1956) The rate of passage of foodstuffs through the alimentary tract of the goat. 3. The intestines. Br J Nutr 10:338–346PubMedCrossRefGoogle Scholar
  10. Chapuis JL, Bousses P, Pisanu B, Reale D (2001) Comparative rumen and fecal diet microhistological determinations of European mouflon. J Range Manag 54:239–242CrossRefGoogle Scholar
  11. Clarke KR (1993) Non-parametric multivariate analyses of changes in community structure. Aust J Ecol 18:117–143CrossRefGoogle Scholar
  12. Couturier MAJ (1938) Le Chamois. Arthaud, GrenobleGoogle Scholar
  13. Crawley MJ (2007) The R book. Wiley, New YorkCrossRefGoogle Scholar
  14. Darmon G, Calenge C, Loison A, Maillard D, Jullien J-M (2007) Social and spatial patterns determine the population structure and colonisation processes in mouflon. Can J Zool 85:634–643CrossRefGoogle Scholar
  15. De Jong CB, Gill RMA, van Wieren SE, Burlton FWE (1995) Diet selection by roe deer Capreolus capreolus in Kielder forest in relation to plant cover. For Ecol Manag 79:91–97CrossRefGoogle Scholar
  16. Deagle BE, Tollit DJ, Jarman SN, Hindell MA, Trites AW, Gales NJ (2005) Molecular scatology as a tool to study diet: analysis of prey DNA in scats from captive Steller sea lions. Mol Ecol 14:1831–1842PubMedCrossRefGoogle Scholar
  17. Deagle BE, Eveson JP, Jarman SN (2006) Quantification of damage in DNA recovered from highly degraded samples—a case study on DNA in faeces. Front Zool 3:11PubMedCrossRefGoogle Scholar
  18. Deagle BE, Gales NJ, Evans K, Jarman SN, Robinson S, Trebilco R, Hindell MA (2007) Studying seabird diet through genetic analysis of faeces: a case study on macaroni penguins (Eudyptes chrysolophus). PLoS ONE 2:e831PubMedCrossRefGoogle Scholar
  19. Dixon P (2003) VEGAN, a package of R functions for community ecology. J Veg Sci 14:927–930CrossRefGoogle Scholar
  20. Dove H, Mayes RW (1996) Plant wax components: a new approach to estimating intake and diet composition in herbivores. J Nutr 126:13–26PubMedGoogle Scholar
  21. Ferrari C, Rossi G, Cavani C (1988) Summer food-habits and quality of female, kid and subadult Apennine chamois, Rupicapra pyrenaica ornata Neumann, 1899 (Artiodactyla, Bovidae). J Mamm Biol 53(3):170–177Google Scholar
  22. Foley WJ, McIlwee A, Lawler I, Aragones L, Wollnough AP, Berding N (1998) Ecological applications of near infrared reflectance spectroscopy—a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia 116:293–305CrossRefGoogle Scholar
  23. Garcia Gonzalez R, Cuartas P (1995) Trophic utilization of a montane/subalpine forest by chamois (Rupicapra pyrenaica) in the Central Pyrenees. In: Conference on ungulates in temperate forest ecosystems, 23–27 April. Elsevier Science, Wageningen, pp 15–23Google Scholar
  24. Garel M, Loison A, Jullien JM, Dubray D, Maillard D, Gaillard JM (2009) Sex-specific growth in mass in Alpine chamois. J Mammal 90:954–960CrossRefGoogle Scholar
  25. Hall TA (1999) BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp 41:95–98Google Scholar
  26. Hofmann RR (1989) Evolutionary steps of ecophysiological adaptation and diversification of ruminants: a comparative view of their digestive system. Oecologia 78:443–457CrossRefGoogle Scholar
  27. Holechek JL, Vavra M, Pieper RD (1982) Botanical composition determination of range herbivore diets—a review. J Range Manag 35:309–315CrossRefGoogle Scholar
  28. Höss M, Kohn M, Pääbo S, Knauer F, Schröder W (1992) Excrement analysis by PCR. Nature 359:199PubMedCrossRefGoogle Scholar
  29. Howe HF (1988) Ecological relationships of plants and animals. Oxford University Press, OxfordGoogle Scholar
  30. Kohn MH, Wayne RK (1997) Facts from faeces revisited. TREE 12:223–227PubMedGoogle Scholar
  31. Kozena I (1986) Further data on the winter diet of the chamois, Rupicapra rupicapra rupicapra, in the Jeseniky. Folia Zool 35:207–214Google Scholar
  32. La Morgia V, Bassano B (2009) Feeding habits, forage selection, and diet overlap in Alpine chamois (Rupicapra rupicapra L.) and domestic sheep. Ecol Res 24:1043–1050CrossRefGoogle Scholar
  33. Lembke M (2005) L’habitat alimentaire du bouquetin des Alpes (Capra i. ibex) au cours de la saison de végétation sur le massif de Belledonne—Sept Laux (Isère, France). Variations spatio-temporelles, effets du dimorphisme sexuel et implications pour sa gestion. PhD thesis, Chambery University, FranceGoogle Scholar
  34. Loison A, Appolinaire J, Jullien JM (2006) How reliable are population counts to detect trends in population size in chamois? Wildl Biol 12:77–88CrossRefGoogle Scholar
  35. Loison A, Darmon G, Cassar S, Jullien J-M, Maillard D (2008) Age- and sex-specific settlement patterns of chamois (Rupicapra rupicapra) offspring. Can J Zool 86:588–593Google Scholar
  36. Magnuson VL, Ally DS, Nylund SJ et al (1996) Substrate nucleotide-determined non-templated addition of adenine by Taq DNA polymerase: implications for PCR-based genotyping and cloning. BioTechniques 21:700–709Google Scholar
  37. Noris JJ (1943) Botanical analyses of stomach contents as a method for determining forage consumption of range sheep. Ecology 24:244–251CrossRefGoogle Scholar
  38. Obrtel R, Holisova V, Kozena I (1984) The winter diet of the chamois Rupicapra rupicapra rupicapra, in the Jeseniky Mts. Folia Zool 33:327–338Google Scholar
  39. Pegard A, Miquel C, Valentini A, Coissac E, Bouvier F, Francois D, Taberlet P, Engel E, Pompanon F (2009) Universal DNA-based methods for assessing the diet of grazing livestock and wildlife from feces. J Agric Food Chem 57:5700–5706PubMedCrossRefGoogle Scholar
  40. Poinar HN, Hofreiter M, Spaulding WG, Martin PS, Stankiewicz BA, Bland H, Evershed RP, Possnert G, Pääbo S (1998) Molecular coproscopy: dung and diet of the extinct ground sloth Nothrotheriops shastensis. Science 281:402–406PubMedCrossRefGoogle Scholar
  41. Shipley LA (2007) The influence of bite size on foraging at larger spatial and temporal scales by mammalian herbivores. Oïkos 116:1964–1974Google Scholar
  42. Soininen EM, Valentini A, Coissac E, Miquel C, Gielly L, Brochmann C, Brysting AK, Sønstebø JH, Ims RA, Yoccoz NG, Taberlet P (2009) Analysing diet of small herbivores: the efficiency of DNA barcoding coupled with high-throughput pyrosequencing for deciphering the composition of complex plant mixture. Front Zool 6:16PubMedCrossRefGoogle Scholar
  43. Stewart DRM (1967) Analysis of plant epidermis in faeces: a feeding experiment with penned sika deer. J Mamm Soc Jpn 7:167–180Google Scholar
  44. Taberlet P, Gielly L, Pautou G, Bouvet J (1991) Universal primers for amplification of three non-coding regions of chloroplast DNA. Plant Mol Biol 17:1105–1109PubMedCrossRefGoogle Scholar
  45. Taberlet P, Coissac E, Pompanon F, Gielly L, Miquel C, Valentini A, Vermat T, Corthier G, Brochmann C, Willerslev E (2007) Power and limitations of the chloroplast trnL(UAA) intron for plant DNA barcoding. Nucleic Acid Res 35:e14PubMedCrossRefGoogle Scholar
  46. Team RDC (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
  47. Thioulouse J, Chessel D, Doledee S, Olivier JM (1997) ADE-4A multivariate analysis and graphical display software. Stat Comput 7:75–83CrossRefGoogle Scholar
  48. Valentini A, Miquel C, Nawaz MA, Bellemain E, Coissac E, Pompanon F, Gielly L, Cruaud C, Nascetti G, Wincker P et al (2009a) New perspectives in diet analysis based on DNA barcoding and parallel pyrosequencing: the trnL approach. Mol Ecol Res 9:51–60CrossRefGoogle Scholar
  49. Valentini A, Pompanon F, Taberlet P (2009b) DNA barcoding for ecologists. Trends Ecol Evol 9:51–60Google Scholar
  50. Vaucher CA (1988) Contribution à l’étude éco-éthologique du chamois (Rupicapra rupicapra) au Mont Salève (Haute Savoie). PhD thesis, Univ Nancy 1Google Scholar
  51. Yockney IJ, Hickling GJ (2000) Distribution and diet of chamois (Rupicapra rupicapra) in Westland forests, South Island, New Zealand. N Z J Ecol 24:31–38Google Scholar

Copyright information

© The Ecological Society of Japan 2010

Authors and Affiliations

  • Gilles Rayé
    • 1
  • Christian Miquel
    • 1
  • Eric Coissac
    • 1
  • Claire Redjadj
    • 1
    • 2
  • Anne Loison
    • 2
  • Pierre Taberlet
    • 1
  1. 1.Laboratoire d′Ecologie Alpine, CNRS UMR 5553Université Joseph FourierGrenobleFrance
  2. 2.Laboratoire d′Ecologie Alpine, CNRS UMR 5553Université de SavoieLe Bourget du LacFrance

Personalised recommendations