安吉莫拉,在Squamata命令中,代表蜥蜴在不同生态位具有不同形态和行为特征的群体。在安吉莫拉,有一个以肢体缺失为特征的群体,占据较低的生态位,集中在Anguinae亚科。有四肢的蜥蜴和没有四肢的蜥蜴在适应其栖息地时表现出明显的运动能力,这反过来又需要不同程度的能量消耗。线粒体,被称为细胞的代谢动力,在提供大约95%的生物体能量方面发挥着至关重要的作用。功能上,有丝分裂基因组(线粒体基因组)可以作为研究爬行动物肢体缺失背后潜在的适应性进化选择的有价值的工具。由于每个物种之间有丝分裂基因组结构的变化,以及其简单的遗传结构,母性继承,和高进化率,有丝分裂基因组越来越多地用于重建鳞类动物的系统发育关系。在这项研究中,我们对Anguimorpha中两个物种的有丝分裂基因组以及Gekkota中两个物种和Scincoidea中四个物种的有丝分裂基因组进行了测序。我们将这些数据与相关物种的有丝分裂基因组含量和进化史进行了比较。在安吉莫拉,在无肢蜥蜴和有肢蜥蜴的有丝分裂基因组之间,分支位点模型分析支持存在10个阳性选择位点:Cytb蛋白(位于位点183和187),ND2蛋白(位于位点90、155和198),ND3蛋白(在位点21),ND5蛋白(位于位点12和267),和ND6蛋白(在位点72和119)。这些发现表明,无肢蜥蜴中有丝分裂体的阳性选择可能与其运动所需的能量有关。此外,我们从NCBI数据库中获得了205个有丝分裂基因组的数据.使用来自213个有丝分裂基因组的13个线粒体蛋白质编码基因(PCG)和两个rRNA(12SrRNA和16SrRNA)构建贝叶斯推断(BI)和最大似然(ML)树。我们的系统发育树和基于有丝分裂基因组数据的Squamata的发散时间估计与先前研究的结果一致。Gekkota被放置在BI和ML树中的Squamata的根部。然而,在毒物进化枝内,由于长分支的吸引,Anguimorpha和(Pleurodonta(蛇纹石Acrodonta))是密切相关的群体,这可能表明错误,也表明基于有丝分裂基因组的系统发育树可能无法有效解决长枝吸引问题。此外,我们回顾了中生代鳞茎的起源和多样化,表明鳞茎起源于三叠纪晚期(206.05Mya),随着白垩纪时期各种超家族的多样化。使用有丝分裂基因组构建鳞茎系统发育关系的未来改进将依赖于识别进化速率较慢的蛇和杂种,确保全面的鳞类多样性分类覆盖,增加被分析基因的数量.
Anguimorpha, within the order
Squamata, represents a group with distinct morphological and behavioral characteristics in different ecological niches among lizards. Within Anguimorpha, there is a group characterized by limb loss, occupying lower ecological niches, concentrated within the subfamily Anguinae. Lizards with limbs and those without exhibit distinct locomotor abilities when adapting to their habitats, which in turn necessitate varying degrees of energy expenditure. Mitochondria, known as the metabolic powerhouses of cells, play a crucial role in providing approximately 95% of an organism\'s energy. Functionally, mitogenomes (mitochondrial genomes) can serve as a valuable tool for investigating potential adaptive evolutionary selection behind limb loss in reptiles. Due to the variation of mitogenome structures among each species, as well as its simple genetic structure, maternal inheritance, and high evolutionary rate, the mitogenome is increasingly utilized to reconstruct phylogenetic relationships of squamate animals. In this study, we sequenced the mitogenomes of two species within Anguimorpha as well as the mitogenomes of two species in Gekkota and four species in Scincoidea. We compared these data with the mitogenome content and evolutionary history of related species. Within Anguimorpha, between the mitogenomes of limbless and limbed lizards, a branch-site model analysis supported the presence of 10 positively selected sites: Cytb protein (at sites 183 and 187), ND2 protein (at sites 90, 155, and 198), ND3 protein (at site 21), ND5 protein (at sites 12 and 267), and ND6 protein (at sites 72 and 119). These findings suggested that positive selection of mitogenome in limbless lizards may be associated with the energy requirements for their locomotion. Additionally, we acquired data from 205 mitogenomes from the NCBI database. Bayesian inference (BI) and Maximum Likelihood (ML) trees were constructed using the 13 mitochondrial protein-coding genes (PCGs) and two rRNAs (12S rRNA and 16S rRNA) from 213 mitogenomes. Our phylogenetic tree and the divergence time estimates for
Squamata based on mitogenome data are consistent with results from previous studies. Gekkota was placed at the root of
Squamata in both BI and ML trees. However, within the Toxicofera clade, due to long-branch attraction, Anguimorpha and (Pleurodonta + (Serpentes + Acrodonta)) were closely related groupings, which might indicate errors and also demonstrate that mitogenome-based phylogenetic trees may not effectively resolve long-branch attraction issues. Additionally, we reviewed the origin and diversification of
Squamata throughout the Mesozoic era, suggesting that
Squamata originated in the Late Triassic (206.05 Mya), with the diversification of various superfamilies occurring during the Cretaceous period. Future improvements in constructing squamate phylogenetic relationships using mitogenomes will rely on identifying snake and acrodont species with slower evolutionary rates, ensuring comprehensive taxonomic coverage of squamate diversity, and increasing the number of genes analyzed.