Literature DB >> 35051503

Triplication is the main evolutionary driving force of NLP transcription factor family in Chinese cabbage and related species.

Huilong Chen1, Kexin Ji2, Yuxian Li2, Yaliu Gao2, Fang Liu2, Yutong Cui3, Ying Liu2, Weina Ge4, Zhenyi Wang5.   

Abstract

The NODULE-INCEPTION-like protein (NLP) is a plant-specific transcription factor (TF) family that plays an important role in both signal transduction and nitrate assimilation. However, the NLP gene family in Chinese cabbage (Brassica rapa) has yet to be studied. Here we identified 17, 16, and 32 NLP genes in Chinese cabbage, Brassica oleracea, and Brassica napus, respectively. We found that duplication of those NLP genes almost always originated from genome-wide duplication events. Further analysis (using Arabidopsis as a reference) revealed that the NLP family in Chinese cabbage and B. oleracea was characterized by direct expansion caused by whole-genome duplication. By contrast, indirect expansion characterized B. napus, which arose from hybridization and fusion of the two species. In addition, phylogenetic and homology analyses showed that the Brassica NLP gene family has been highly conserved in evolution. Finally, we also identified optimal codons for four studied species. Altogether, through comparative genome analysis methods, we presented compelling evidence that triplication is the main driving force for the NLP TF family's evolution in Chinese cabbage and related Brassica plants, a process evidently highly conserved. This work will help in better understanding the impact of genome-wide duplication on gene families of plants.
Copyright © 2022. Published by Elsevier B.V.

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Keywords:  Chinese cabbage; Duplication and loss; Evolution; NLP; Polyploid

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Year:  2022        PMID: 35051503     DOI: 10.1016/j.ijbiomac.2022.01.082

Source DB:  PubMed          Journal:  Int J Biol Macromol        ISSN: 0141-8130            Impact factor:   6.953


  1 in total

1.  CFVisual: an interactive desktop platform for drawing gene structure and protein architecture.

Authors:  Huilong Chen; Xiaoming Song; Qian Shang; Shuyan Feng; Weina Ge
Journal:  BMC Bioinformatics       Date:  2022-05-13       Impact factor: 3.307

  1 in total

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