Conserved G-matrices of morphological and life-history traits among continental and island blue tit populations.
Conserved G-matrices of morphological and life-history traits among continental and island blue tit populations.
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DOI：
10.1038/hdy.2017.15
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发表时间：
2017-08
期刊：
影响因子：
3.8
通讯作者：
Teplitsky C
中科院分区：
文献类型：
--
作者：
Delahaie B;Charmantier A;Chantepie S;Garant D;Porlier M;Teplitsky C
遗传方差-协方差矩阵(G-矩阵)概括了多个性状的遗传结构。它在理解表型差异和量化种群的进化潜力方面发挥着核心作用。实验室实验表明，在不同的选择压力下，G矩阵可以快速变化。然而，由于野生种群中G矩阵估计和比较的苛刻性质，其空间变异的程度在很大程度上仍然是未知的。在这项研究中，我们使用一个大陆种群和三个岛屿种群的长期数据集，研究了形态和生活史特征在G矩阵中的空间变异。我们没有发现G矩阵在人群中存在差异的证据。有趣的是，表型方差-协方差矩阵(P)在不同种群之间是不同的，这表明用P作为G的替代品可能是不够的。这些分析还首次在野生种群中提供了所有四个种群在潜伏期(即从最后产卵到孵化之间的时期)存在加性遗传变异的证据。总之，我们的结果表明，G-矩阵在居住在不同环境中的人群中可能是稳定的，因此挑战了以前的模拟研究和实验室实验的结果。
The genetic variance-covariance matrix (G-matrix) summarizes the genetic architecture of multiple traits. It has a central role in the understanding of phenotypic divergence and the quantification of the evolutionary potential of populations. Laboratory experiments have shown that G-matrices can vary rapidly under divergent selective pressures. However, due to the demanding nature of G-matrix estimation and comparison in wild populations, the extent of its spatial variability remains largely unknown. In this study, we investigate spatial variation in G-matrices for morphological and life-history traits using long-term data sets from one continental and three island populations of Blue tit (Cyanistes caeruleus), which have experienced contrasting population history and selective environment. We found no evidence for differences in G-matrices among populations. Interestingly, the phenotypic variance-covariance matrices (P) were divergent across populations, suggesting that using P as a substitute for G may be inadequate. These analyses also provide the first evidence in wild populations for additive genetic variation in the incubation period (i.e. the period between last egg laid and hatching) in all four populations. Altogether, our results suggest that G-matrices may be stable across populations inhabiting contrasted environments therefore challenging the results of previous simulation studies and laboratory experiments.
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DOI：
10.1098/rspb.2015.1119
发表时间：
2015-11-22
影响因子：
4.7
作者：
Careau, Vincent;Wolak, Matthew E.;Garland, Theodore, Jr.
通讯作者：
Garland, Theodore, Jr.
影响因子：
4.4
作者：
Basser, Peter J.;Pajevic, Sinisa
通讯作者：
Pajevic, Sinisa
影响因子：
1.7
作者：
Charmantier, A;Blondel, J;Lambrechts, MM
通讯作者：
Lambrechts, MM
影响因子：
2.9
作者：
ARNOLD, SJ
通讯作者：
ARNOLD, SJ
DOI：
10.1073/pnas.1505357112
发表时间：
2015-10-27
影响因子：
11.1
作者：
Bolstad, Geir H.;Cassara, Jason A.;Pelabon, Christophe
通讯作者：
Pelabon, Christophe