3 resultados para Pair bond

em Duke University


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© 2013 The Association for the Study of Animal Behaviour.Social complexity, often estimated by group size, is seen as driving the complexity of vocal signals, but its relation to olfactory signals, which arguably arose to function in nonsocial realms, remains underappreciated. That olfactory signals also may mediate within-group interaction, vary with social complexity and promote social cohesion underscores a potentially crucial link with sociality. To examine that link, we integrated chemical and behavioural analyses to ask whether olfactory signals facilitate reproductive coordination in a strepsirrhine primate, the Coquerel's sifaka, Propithecus coquereli. Belonging to a clade comprising primarily solitary, nocturnal species, the diurnal, group-living sifaka represents an interesting test case. Convergent with diurnal, group-living lemurids, sifakas expressed chemically rich scent signals, consistent with the social complexity hypothesis for communication. These signals minimally encoded the sex of the signaller and varied with female reproductive state. Likewise, sex and female fertility were reflected in within-group scent investigation, scent marking and overmarking. We further asked whether, within breeding pairs, the stability or quality of the pair's bond influences the composition of glandular signals and patterns of investigatory or scent-marking behaviour. Indeed, reproductively successful pairs tended to show greater similarity in their scent signals than did reproductively unsuccessful pairs, potentially through chemical convergence. Moreover, scent marking was temporally coordinated within breeding pairs and was influenced by past reproductive success. That olfactory signalling reflects social bondedness or reproductive history lends support to recent suggestions that the quality of relationships may be a more valuable proxy than group size for estimating social complexity. We suggest that olfactory signalling in sifakas is more complex than previously recognized and, as in other socially integrated species, can be a crucial mechanism for promoting group cohesion and maintaining social bonds. Thus, the evolution of sociality may well be reflected in the complexity of olfactory signalling.

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The direct addition of enolizable aldehydes and a-halo thioesters to produce beta-hydroxy thioesters enabled by reductive soft enolization is reported. The transformation is operationally simple and efficient and has the unusual feature of giving high syn-selectivity, which is the opposite of that produced for (thio)esters under conventional conditions. Moreover, excellent diastereoselectivity results when a chiral nonracemic alpha-hydroxy aldehyde derivative is used.

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The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.