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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
agricultural and biological sciences
Social discrimination by quantitative assessment of immunogenetic similarity
Proceedings of the Royal Society B: Biological Sciences, Volume 279, No. 1746, Year 2012
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Description
Genes of the major histocompatibility complex (MHC) that underlie the adaptive immune system may allow vertebrates to recognize their kin. True kin-recognition genes should produce signalling products to which organisms can respond. Allelic variation in the peptide-binding region (PBR) of MHC molecules determines the pool of peptides that can be presented to trigger an immune response. To examine whether these MHC peptides also might underlie assessments of genetic similarity, we tested whether Xenopus laevis tadpoles socially discriminate between pairs of siblings with which they differed in PBR amino acid sequences. We found that tadpoles (four sibships, n 1/4 854) associated preferentially with siblings with which they were more similar in PBR amino acid sequence. Moreover, the strength of their preference for a conspecific was directly proportional to the sequence similarity between them. Discrimination was graded, and correlated more closely with functional sequence differences encoded by MHC class I and class II alleles than with numbers of shared haplotypes. Our results thus suggest that haplotype analyses may fail to reveal fine-scale behavioural responses to divergence in functionally expressed sequences. We conclude that MHC-PBR gene products mediate quantitative social assessment of immunogenetic similarity that may facilitate kin recognition in vertebrates. © 2012 The Royal Society.
Authors & Co-Authors
Villinger, Jandouwe
Kenya, Nairobi
International Centre of Insect Physiology and Ecology Nairobi
Waldman, Bruce
New Zealand, Lincoln
Lincoln University
South Korea, Seoul
School of Biological Sciences
Statistics
Citations: 18
Authors: 2
Affiliations: 3
Identifiers
Doi:
10.1098/rspb.2012.1279
ISSN:
09628452
e-ISSN:
14712954
Research Areas
Genetics And Genomics
Study Approach
Quantitative