Literature DB >> 24277306

Integrated genomics approaches in evolutionary and ecological endocrinology.

Jun Kitano1, Asano Ishikawa, Sean C Lema.   

Abstract

Hormones can act on a variety of target tissues to regulate the expression of multiple phenotypic traits. Therefore, phenotypes regulated by the same hormones can be genetically correlated due to their common regulatory mechanism. Such genetic correlations may either facilitate or constrain adaptive evolution. In addition, hormone signaling pathways are regulated by external environmental factors, so hormones can mediate phenotypic plasticity and polyphenism. When different responses to environmental signals are favored, hormone signaling pathways can vary between populations and species exploiting dissimilar environments and thus mediate genotype-by-environment interactions. A complete understanding of the evolutionary causes and ecological implications of hormone signal variation requires examining several components of hormone signaling pathways across multiple individuals, populations, and species. Genomic technologies are excellent tools for undertaking genetic studies of naturally occurring variation in hormone signals. In this chapter, we review how genomic approaches can help to answer major questions in evolutionary endocrinology, including how environmental cues can be translated into phenotypic development through hormone pathways, how multiple hormone-mediated phenotypic traits are coupled and decoupled, how gene functions in hormone pathways influence the evolutionary rate of genes, and how divergence in hormone pathways can contribute to phenotypic diversification and speciation in non-model organisms. We also discuss how emerging analytical and experimental technologies in genomics and hormone measurement can provide valuable new insights into the roles of hormone signal variation in adaptive evolution and phenotypic diversification.

Mesh:

Substances:

Year:  2014        PMID: 24277306     DOI: 10.1007/978-94-007-7347-9_15

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  2 in total

1.  Biological factors and age-dependence of primary motor cortex experimental plasticity.

Authors:  Renato Polimanti; Ilaria Simonelli; Filippo Zappasodi; Mariacarla Ventriglia; Maria Concetta Pellicciari; Luisa Benussi; Rosanna Squitti; Paolo Maria Rossini; Franca Tecchio
Journal:  Neurol Sci       Date:  2015-10-07       Impact factor: 3.307

2.  Genomic legacy of migration in endangered caribou.

Authors:  Maria Cavedon; Bridgett vonHoldt; Mark Hebblewhite; Troy Hegel; Elizabeth Heppenheimer; Dave Hervieux; Stefano Mariani; Helen Schwantje; Robin Steenweg; Jessica Theoret; Megan Watters; Marco Musiani
Journal:  PLoS Genet       Date:  2022-02-10       Impact factor: 5.917

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.