Animals make a diverse array of architectures including nests, bowers, roosts, traps, and tools. Much of the research into animal architecture has focused on the analysis of physical properties such as the dimensions and material of the architectures, rather than the behavior responsible for creating these architectures. However, the relationship between the architecture itself and the construction behavior that built it is not straightforward, and overlooking behavior risks obtaining an incomplete or even misleading picture of how animal architecture evolves. Here we review data about animal architectures broadly, with a particular focus on building by birds and social insects. We then highlight three ways in which a better understanding of building behavior could benefit the study of animal architecture: by clarifying how behavior leads to physical properties; by examining the costs and benefits of building behavior; and by determining the role of learning and how this interacts with selection on behavior. To integrate questions about building behavior alongside those about architectures, we propose a framework inspired by Niko Tinbergen's four questions, examining the mechanistic, ontogenetic, phylogenetic, and functional basis of animal building. By integrating the study of behavior and architecture across levels of analysis, we can gain a more holistic view of the behavior-architecture interactions, and a better understanding of how behavior, cognition, and evolution interact to produce the diversity seen in animal architecture.
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http://dx.doi.org/10.1111/1440-1703.12309 | DOI Listing |
Mol Biol (Mosk)
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Institute of Functional Genomics, Moscow State University, Moscow, 119991 Russia.
The CRISPR/Cas technology of targeted genome editing made it possible to carry out genetic engineering manipulations with eukaryotic genomes with a high efficiency. Targeted induction of site-specific DNA breaks is one of the key stages of the technology. The cell repairs the breaks via one of the two pathways, nonhomologous end joining (NHEJ) and homology-driven repair (HDR).
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Institute of Functional Genomics, Moscow State University, Moscow, 119991 Russia.
Modern genetic engineering technologies, such as base editing and prime editing (PE), have proven to provide the efficient and reliable genome editing tools that obviate the need for donor templates and double-strand breaks (DSBs) introduced in DNA. Relatively new, they quickly gained recognition for their accuracy, simplicity, and multiplexing capabilities. The review summarizes the new literature on the technologies and considers their architecture, methods to create editors, specificity, efficiency, and versatility.
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Agricultural Bioinformatics Key Laboratory of Hubei Province, Huazhong Agricultural University, No. 1 Shizishan Street, Hongshan District, Wuhan 430070, China.
Advances in three-dimensional (3D) genomics have revealed the spatial characteristics of chromatin interactions in gene expression regulation, which is crucial for understanding molecular mechanisms in biological processes. High-throughput technologies like ChIA-PET, Hi-C, and their derivatives methods have greatly enhanced our knowledge of 3D chromatin architecture. However, the chromatin interaction mechanisms remain largely unexplored.
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Biology Department, College of Education for Pure Sciences, University of Anbar, Iraq.
This study aimed to evaluate the therapeutic effects of B6 in rats experimentally intoxicated by benzopyrene. Twenty-eight Male Sprague Dawley (white Swiss) rats weighing 170-210 g and 3-4 months old were utilized in this examination. Rats were divided into 4 control groups (G1), B[a]P 2 pmol/μL (G2), B6 only once per 2 days for a full month at 1000 mcg (15 dose per month) (G3), B6 + B[a]P (G4).
View Article and Find Full Text PDFGenet Sel Evol
December 2024
State Key Laboratory of Animal Biotech Breeding, College of Biological Sciences, China Agricultural University, Beijing, China.
Background: The genome-wide association study (GWAS) is a powerful method for mapping quantitative trait loci (QTL). However, standard GWAS can detect only QTL that segregate in the mapping population. Crossing populations with different characteristics increases genetic variability but F2 or back-crosses lack mapping resolution due to the limited number of recombination events.
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