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通过氨基酸重新编码解决生命之树中棘手的节点问题。

Resolving tricky nodes in the tree of life through amino acid recoding.

作者信息

Giacomelli Mattia, Rossi Maria Eleonora, Lozano-Fernandez Jesus, Feuda Roberto, Pisani Davide

机构信息

Bristol Palaeobiology Group, School of Biological Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, BS8 1TQ, UK.

Bristol Palaeobiology Group, School of Earth Sciences, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol BS8 1TQ, UK.

出版信息

iScience. 2022 Nov 15;25(12):105594. doi: 10.1016/j.isci.2022.105594. eCollection 2022 Dec 22.

DOI:10.1016/j.isci.2022.105594
PMID:36458253
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9706708/
Abstract

Genomic data allowed a detailed resolution of the Tree of Life, but "tricky nodes" such as the root of the animals remain unresolved. Genome-scale datasets are heterogeneous as genes and species are exposed to different pressures, and this can negatively impacts phylogenetic accuracy. We use simulated genomic-scale datasets and show that recoding amino acid data improves accuracy when the model does not account for the compositional heterogeneity of the amino acid alignment. We apply our findings to three datasets addressing the root of the animal tree, where the debate centers on whether sponges (Porifera) or comb jellies (Ctenophora) represent the sister of all other animals. We show that results from empirical data follow predictions from simulations and suggest that, at the least in phylogenies inferred from amino acid sequences, a placement of the ctenophores as sister to all the other animals is best explained as a tree reconstruction artifact.

摘要

基因组数据使生命之树得到了详细解析,但诸如动物起源等“棘手节点”仍未得到解决。基因组规模的数据集具有异质性,因为基因和物种受到不同压力的影响,这可能会对系统发育准确性产生负面影响。我们使用模拟的基因组规模数据集表明,当模型未考虑氨基酸序列比对的组成异质性时,对氨基酸数据进行重新编码可提高准确性。我们将研究结果应用于三个关于动物树起源的数据集,其中争论的焦点在于海绵动物(多孔动物门)还是栉水母动物(栉水母纲)是所有其他动物的姐妹群。我们表明,实证数据的结果符合模拟预测,并表明,至少在从氨基酸序列推断的系统发育中,栉水母动物作为所有其他动物的姐妹群的定位最好解释为树重建假象。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/b842602a5351/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/487ebe1428e9/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/393541cbb25d/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/d41c34ec66d6/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/7c74239c861a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/0c1520304c78/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/8d37774df4bf/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/b842602a5351/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/487ebe1428e9/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/393541cbb25d/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/d41c34ec66d6/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/7c74239c861a/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/0c1520304c78/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/8d37774df4bf/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/df22/9706708/b842602a5351/gr6.jpg

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