The rough‐toothed dolphin genome provides new insights into the genetic mechanism of its rough teeth

Huang, Xin; Fan, Huizhong; Zhou, Wen‐Liang; Yang, Guang; Wei, Fuwen

doi:10.1111/1749-4877.12723

Cited by 2 publications

(1 citation statement)

References 82 publications

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“…Branch-site model and branch model in the PAML package were used to identify positive selection. The preferred standard test for positive selection is the branch-site Model A [46]. Model A categorized sites into one of four categories: ω0 < 1 (purifying selection); ω1 = 1 (neutral evolution); ω2a > 1 (positive selection in the foreground, purifying in the background) and ω2b > 1 (positive selection in the foreground and neutral in the background).…”

Section: (I) Selection Analysismentioning

confidence: 99%

Comparative genomics sheds new light on the convergent evolution of infrared vision in snakes

Zou,

Huang,

Tian

et al. 2024

Proc. R. Soc. B.

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Infrared vision is a highly specialized sensory system that evolved independently in three clades of snakes. Apparently, convergent evolution occurred in the transient receptor potential ankyrin 1 ( TRPA1 ) proteins of infrared-sensing snakes. However, this gene can only explain how infrared signals are received, and not the transduction and processing of those signals. We sequenced the genome of Xenopeltis unicolor , a key outgroup species of pythons, and performed a genome-wide analysis of convergence between two clades of infrared-sensing snakes. Our results revealed pervasive molecular adaptation in pathways associated with neural development and other functions, with parallel selection on loci associated with trigeminal nerve structural organization. In addition, we found evidence of convergent amino acid substitutions in a set of genes, including TRPA1 and TRPM2 . The analysis also identified convergent accelerated evolution in non-coding elements near 12 genes involved in facial nerve structural organization and optic nerve development. Thus, convergent evolution occurred across multiple dimensions of infrared vision in vipers and pythons, as well as amino acid substitutions, non-coding elements, genes and functions. These changes enabled independent groups of snakes to develop and use infrared vision.

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Section: (I) Selection Analysismentioning

confidence: 99%

Comparative genomics sheds new light on the convergent evolution of infrared vision in snakes

Zou,

Huang,

Tian

et al. 2024

Proc. R. Soc. B.

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Crucial Role of microRNAs as New Targets for Amelogenesis Disorders Detection

Masunova,

Tereschenko,

Alexandrov

et al. 2023

CDT

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Introduction: Amelogenesis imperfecta (AI) refers to a heterogeneous group of conditions with multiple factors which contribute to the hypomineralisation of enamel. Preventive measures are necessary to predict this pathology. Prospects for preventive medicine are closely related to the search for new informative methods for diagnosing a human disease. MicroRNAs are prominent for the non-invasive diagnostic platform. The Aim of the Study: The aim of the review is to review the heterogeneous factors involved in amelogenesis and to select the microRNA panel associated with the AI type. Methods: We used DIANA Tools (algorithms, databases and software) for interpreting and archiving data in a systematic framework ranging from the analysis of expression regulation from deep sequencing data to the annotation of miRNA regulatory elements and targets (https://dianalab. e-ce.uth.gr/). In our study, based on a gene panel associated with the AI types, twenty-four miRNAs were identified for the hypoplastic type (supplement), thirty-five for hypocalcified and forty-- nine for hypomaturation AI. The selection strategy included the microRNA search with multiple targets using the AI type's gene panel. Results: Key proteins, calcium-dependent and genetic factors were analysed to reveal their role in amelogenesis. The role of extracellular non-coding RNA sequences with multiple regulatory functions seems to be the most attractive. We chose the list of microRNAs associated with the AI genes. We found four microRNAs (hsa-miR-27a-3p, hsa-miR-375, hsa-miR-16-5p and hsamiR- 146a-5p) for the gene panel, associated with the hypoplastic type of AI; five microRNAs (hsa- miR-29c-3p, hsa-miR-124-3p, hsa-miR-1343-3p, hsa-miR-335-5p, and hsa-miR-16-5p - for hypocalcified type of AI, and seven ones (hsa-miR-124-3p, hsa-miR-147a, hsa-miR-16-5p, hsamiR- 429, hsa-let-7b-5p, hsa-miR-146a-5p, hsa-miR-335-5p) - for hypomaturation. It was revealed that hsa-miR-16-5p is included in three panels specific for both hypoplastic, hypocalcified, and hypomaturation types. Hsa-miR-146a-5p is associated with hypoplastic and hypomaturation type of AI, which is associated with the peculiarities of the inflammatory response immune response. In turn, hsa-miR-335-5p associated with hypocalcified and hypomaturation type of AI. Conclusion: Liquid biopsy approaches are a promising way to reduce the economic cost of treatment for these patients in modern healthcare. Unique data exist about the role of microRNA in regulating amelogenesis. The list of microRNAs that are associated with AI genes and classified by AI types has been uncovered. The target gene analysis showed the variety of functions of selected microRNAs, which explains the multiple heterogeneous mechanisms in amelogenesis. Predisposition to mineralisation problems is a programmed event. Many factors determine the manifestation of this problem. Additionally, it is necessary to remember the variable nature of the changes, which reduces the prediction accuracy. Therefore, models based on liquid biopsy and microRNAs make it possible to take into account these factors and their influence on the mineralisation. The found data needs further investigation.

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The rough‐toothed dolphin genome provides new insights into the genetic mechanism of its rough teeth

Cited by 2 publications

References 82 publications

Comparative genomics sheds new light on the convergent evolution of infrared vision in snakes

Comparative genomics sheds new light on the convergent evolution of infrared vision in snakes

Crucial Role of microRNAs as New Targets for Amelogenesis Disorders Detection

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