Social evolution. Genomic signatures of evolutionary transitions from solitary to group living.
Social evolution. Genomic signatures of evolutionary transitions from solitary to group living.
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DOI：
10.1126/science.aaa4788
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发表时间：
2015-06-05
期刊：
影响因子：
--
通讯作者：
Zhang G
中科院分区：
文献类型：
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作者：
Kapheim KM;Pan H;Li C;Salzberg SL;Puiu D;Magoc T;Robertson HM;Hudson ME;Venkat A;Fischman BJ;Hernandez A;Yandell M;Ence D;Holt C;Yocum GD;Kemp WP;Bosch J;Waterhouse RM;Zdobnov EM;Stolle E;Kraus FB;Helbing S;Moritz RF;Glastad KM;Hunt BG;Goodisman MA;Hauser F;Grimmelikhuijzen CJ;Pinheiro DG;Nunes FM;Soares MP;Tanaka ÉD;Simões ZL;Hartfelder K;Evans JD;Barribeau SM;Johnson RM;Massey JH;Southey BR;Hasselmann M;Hamacher D;Biewer M;Kent CF;Zayed A;Blatti C 3rd;Sinha S;Johnston JS;Hanrahan SJ;Kocher SD;Wang J;Robinson GE;Zhang G
真社会性的进化是进化过程中的主要转变之一，但潜在的基因组变化是未知的。我们比较了10种蜜蜂的基因组，这些蜜蜂的社会复杂性各不相同，代表了社会进化中的多个独立过渡，并报告了三个主要发现。首先，许多重要的基因显示出中性进化的证据，这是随着社会复杂性的增加而放松选择的结果。第二，没有单一的路线图，以真社会性;独立的进化过渡的社会性有独立的遗传基础。第三，虽然在细节上明显独立，但这些转变确实具有相似的一般特征，包括限制蛋白质进化的增加，伴随着基因调控潜力的增加和转座因子多样性和丰度的减少。真社会性可能每次都通过不同的机制产生，但可能总是涉及基因网络复杂性的增加。
The evolution of eusociality is one of the major transitions in evolution, but the underlying genomic changes are unknown. We compared the genomes of 10 bee species that vary in social complexity, representing multiple independent transitions in social evolution, and report three major findings. First, many important genes show evidence of neutral evolution as a consequence of relaxed selection with increasing social complexity. Second, there is no single road map to eusociality; independent evolutionary transitions in sociality have independent genetic underpinnings. Third, though clearly independent in detail, these transitions do have similar general features, including an increase in constrained protein evolution accompanied by increases in the potential for gene regulation and decreases in diversity and abundance of transposable elements. Eusociality may arise through different mechanisms each time, but would likely always involve an increase in the complexity of gene networks.