Is the order in which proteins assemble into complexes important for biological function? Here, we seek to address this by searching for evidence of evolutionary selection for ordered protein complex assembly. First, we experimentally characterize the assembly pathways of several heteromeric complexes and show that they can be simply predicted from their three-dimensional structures. Then, by mapping gene fusion events identified from fully sequenced genomes onto protein complex assembly pathways, we demonstrate evolutionary selection for conservation of assembly order. Furthermore, using structural and high-throughput interaction data, we show that fusion tends to optimize assembly by simplifying protein complex topologies. Finally, we observe protein structural constraints on the gene order of fusion that impact the potential for fusion to affect assembly. Together, these results reveal the intimate relationships among protein assembly, quaternary structure, and evolution and demonstrate on a genome-wide scale the biological importance of ordered assembly pathways.
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http://dx.doi.org/10.1016/j.cell.2013.02.044 | DOI Listing |
Biol Direct
December 2024
Key Laboratory of Animal Genetics Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Background: Integrating multi-layered information can enhance the accuracy of genomic prediction for complex traits. However, the improvement and application of effective strategies for genomic prediction (GP) using multi-omics data remains challenging.
Methods: We generated 11 feature sets for sequencing variants from genomics, transcriptomics, metabolomics, and epigenetics data in beef cattle, then we assessed the contribution of functional variants using genomic restricted maximum likelihood (GREML).
PLoS One
December 2024
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China.
The existing landslide monitoring methods are unable to accurately reflect the true deformation of the landslide body, and the use of a single SAR satellite, affected by its revisit cycle, still suffers from the limitation of insufficient temporal resolution for landslide monitoring. Therefore, this paper proposes a method for the dynamic reconstruction and evolutionary characteristic analysis of the Gaojiawan landslide's along-slope deformation based on ascending and descending orbit time-series InSAR observations using Kalman filtering. Initially, the method employs a gridded selection approach during the InSAR time-series processing, filtering coherent points based on the standard deviation of residual phases, thereby ensuring the density and quality of the extracted coherent points.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Department of Computer Science, University of Haifa, Haifa 3303221, Israel.
Selective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained AI models to predict codons given their amino acid sequence in the eukaryotes and and the bacteria and to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels.
View Article and Find Full Text PDFPLoS One
December 2024
Division of Medical Information Sciences, Geneva University Hospitals, Geneva, Switzerland.
The essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting principles of adaptation to evolutionary selection pressure, we attempt to identify the major determinants of language emergence specific to this context.
View Article and Find Full Text PDFPLoS One
December 2024
Organismal and Evolutionary Biology Research Programme, University of Helsinki, Helsinki, Finland.
As the technology for mass identification of species is advancing rapidly, we developed a field sampling method that takes advantage of the emerging possibilities of combining sensor-based data with automated high-throughput data processing. This article describes the five field sampling methods used by the LIFEPLAN project to collect biodiversity data in a systematic manner, all over the world. These methods are designed for use by anyone with basic biology or ecology knowledge from the higher education or university level.
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