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Background DNA methylation is an important epigenetic modification that is known to regulate gene expression. Whole-genome bisulfite sequencing (WGBS) is a powerful method for studying cytosine methylation in a whole genome. However, it is difficult to obtain methylation profiles using the WGBS raw reads and is necessary to be proficient in all types of bioinformatic tools for the study of DNA methylation. In addition, recent end-to-end pipelines for DNA methylation analyses are not sufficient for addressing those difficulties. Results Here we present msPIPE, a pipeline for DNA methylation analyses with WGBS data seamlessly connecting all the required tasks ranging from data pre-processing to multiple downstream DNA methylation analyses. The msPIPE can generate various methylation profiles to analyze methylation patterns in the given sample, including statistical summaries and methylation levels. Also, the methylation levels in the functional regions of a genome are computed with proper annotation. The results of methylation profiles, hypomethylation, and differential methylation analysis are plotted in publication-quality figures. The msPIPE can be easily and conveniently used with a Docker image, which includes all dependent packages and software related to DNA methylation analyses. Conclusion msPIPE is a new end-to-end pipeline designed for methylation calling, profiling, and various types of downstream DNA methylation analyses, leading to the creation of publication-quality figures. msPIPE allows researchers to process and analyze the WGBS data in an easy and convenient way. It is available at https://github.com/jkimlab/msPIPE and https://hub.docker.com/r/jkimlab/mspipe .

Background Currently, diverse minipigs have acquired a common dwarfism phenotype through independent artificial selections. Characterizing the population and genetic diversity in minipigs is important to unveil genetic mechanisms regulating their body sizes and effects of independent artificial selections on those genetic mechanisms. However, full understanding for the genetic mechanisms and phenotypic consequences in minipigs still lag behind. Results Here, using whole genome sequencing data of 41 pig breeds, including eight minipigs, we identified a large genomic diversity in a minipig population compared to other pig populations in terms of population structure, demographic signatures, and selective signatures. Selective signatures reveal diverse biological mechanisms related to body size in minipigs. We also found evidence for neural development mechanism as a minipig-specific body size regulator. Interestingly, selection signatures within those mechanisms containing neural development are also highly different among minipig breeds. Despite those large genetic variances, PLAG1 , CHM , and ESR1 are candidate key genes regulating body size which experience different differentiation directions in different pig populations. Conclusions These findings present large variances of genetic structures, demographic signatures, and selective signatures in the minipig population. They also highlight how different artificial selections with large genomic diversity have shaped the convergent dwarfism.

Minipigs are widely used as animal models in biomedical research because they have distinctive advantages, including small body size. However, the regulatory roles of long non-coding RNAs (lncRNAs) in shaping their distinct characteristics remain unexplored. In this study, we performed a comparative transcriptomic analysis of five tissues (heart, kidney, liver, lung, and spleen) from three breeds of minipig (ET-type, L-type, and Bama minipigs) and two breeds of pig (Duroc and Landrace). We identified 5,288 lncRNAs and found that their expression patterns distinguished breeds more prominently than protein-coding genes, suggesting the existence of different evolutionary constraints between them. Based on differential expression analyses, we identified tissue-common lncRNAs (tcDELs) that exhibited consistent expression differences between minipigs and pigs, as well as tissue-specific lncRNAs (tsDELs) with unique expression patterns in individual minipig tissues. Expression correlation analysis and functional enrichment of associated protein-coding genes revealed that these lncRNAs are involved in a wide range of biological processes. Notably, tcDELs were linked to pathways related to organ size and gene regulation across tissues, while tsDELs were associated with physiological functions specific to each tissue. These findings demonstrate that lncRNAs may contribute to both tissue-common and tissue-specific traits in minipigs, reinforcing their utility as animal models.

Eukaryotic cells use guided search to coordinately control dispersed genetic elements. Argonaute proteins and their small RNA cofactors engage nascent RNAs and chromatin-associated proteins to direct transcriptional silencing. The small ubiquitin-like modifier (SUMO) has been shown to promote the formation and maintenance of silent chromatin (called heterochromatin) in yeast, plants, and animals. Here, we show that Argonaute-directed transcriptional silencing in Caenorhabditis elegans requires SUMOylation of the type 1 histone deacetylase HDA-1. Our findings suggest how SUMOylation promotes the association of HDAC1 with chromatin remodeling factors and with a nuclear Argonaute to initiate de novo heterochromatin silencing.

Background Many studies have been performed to identify various genomic loci and genes associated with the meat quality in pigs. However, the full genetic architecture of the trait still remains unclear in part because of the lack of accurate identification of related structural variations (SVs) which resulted from the shortage of target breeds, the limitations of sequencing data, and the incompleteness of genome assemblies. The recent generation of a new pig breed with superior meat quality, called Nanchukmacdon, and its chromosome-level genome assembly (the NCMD assembly) has provided new opportunities. Results By applying assembly-based SV calling approaches to various genome assemblies of pigs including Nanchukmacdon, the impact of SVs on meat quality was investigated. Especially, by checking the commonality of SVs with other pig breeds, a total of 13,819 Nanchukmacdon-specific SVs (NSVs) were identified, which have a potential effect on the unique meat quality of Nanchukmacdon. The regulatory potentials of NSVs for the expression of nearby genes were further examined using transcriptome- and epigenome-based analyses in different tissues. Conclusions Whole-genome comparisons based on chromosome-level genome assemblies have led to the discovery of SVs affecting meat quality in pigs, and their regulatory potentials were analyzed. The identified NSVs will provide new insights regarding genetic architectures underlying the meat quality in pigs. Finally, this study confirms the utility of chromosome-level genome assemblies and multi-omics analysis to enhance the understanding of unique phenotypes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused devastation to human society through its high virulence, infectivity, and genomic mutations, which reduced the efficacy of vaccines. Here, we report the development of aptamers that effectively interfere with SARS-CoV-2 infection by targeting its spike protein, which plays a pivotal role in host cell entry of the virus through interaction with the viral receptor angiotensin-converting enzyme 2 (ACE2). To develop highly effective aptamers and to understand their mechanism in inhibiting viral infection, we determined the three-dimensional (3D) structures of aptamer/receptor-binding domain (RBD) complexes using cryogenic electron microscopy (cryo-EM). Moreover, we developed bivalent aptamers targeting two distinct regions of the RBD in the spike protein that directly interact with ACE2. One aptamer interferes with the binding of ACE2 by blocking the ACE2-binding site in RBD, and the other aptamer allosterically inhibits ACE2 by binding to a distinct face of RBD. Using the 3D structures of aptamer–RBD complexes, we minimized and optimized these aptamers. By combining the optimized aptamers, we developed a bivalent aptamer that showed a stronger inhibitory effect on virus infection than the component aptamers. This study confirms that the structure-based aptamer-design approach has a high potential in developing antiviral drugs against SARS-CoV-2 and other viruses.

The purpose of this study was to investigate the thermal and cyclic behaviors of fire-damaged walls designed with different failure modes, aspect ratios and heated areas. These cyclic behaviors include temperature distribution, maximum lateral load, stiffness, ductility, and energy dissipations, etc. Toward this goal, the concrete wall specimens were exposed to heat following an ISO 834 standard time–temperature curve and the cyclic loading was applied to the fire-damaged walls. The test results showed that exposure to fire significantly reduced the cyclic performance of the RC walls. Especially, it was observed that heated area, designed failure mode, and aspect ratio have influences on maximum lateral loads, stiffness, and ductility of the fire-damaged walls, while almost no effects of the heated area, designed failure mode, and aspect ratio on temperature distribution and energy dissipation were found.

Germlines shape and balance heredity, integrating and regulating information from both parental and foreign sources. Insights into how germlines handle information have come from the study of factors that specify or maintain the germline fate. In early Caenorhabditis elegans embryos, the CCCH zinc finger protein PIE-1 localizes to the germline where it prevents somatic differentiation programs. Here, we show that PIE-1 also functions in the meiotic ovary where it becomes SUMOylated and engages the small ubiquitin-like modifier (SUMO)-conjugating machinery. Using whole-SUMO-proteome mass spectrometry, we identify HDAC SUMOylation as a target of PIE-1. Our analyses of genetic interactions between pie-1 and SUMO pathway mutants suggest that PIE-1 engages the SUMO machinery both to preserve the germline fate in the embryo and to promote Argonaute-mediated surveillance in the adult germline.

Performance-based fire resistance design needs consideration of various influencing parameters of structures such as load levels and cross-sectional size. Therefore, the studies of fire damaged reinforced concrete (RC) structures are performed experimentally and analytically. Twelve RC beams with different load levels and cross sections are exposed to high temperatures following the ISO 834 standard time temperature. After the fire test, the fire-damaged beams are loaded using four-point loading to obtain its residual strength. In addition, ABAQUS 6.10-3 is used to preform structural analyses of the ductility of the fire-damaged beams. The results indicate that the temperature, stiffness and ductility of the fire-damaged beams are significantly influenced by the load level, cross-sectional size and time exposed to fire. Also, the ductility of the fire-damaged beam can be predicted using an analytical method, which is not easy to otherwise determine experimentally.

There are two specific aims in this study; first is to develop and validate an automated crack detection technique for the fire damaged beam. Second is to investigate whether the detected crack information and thermal-structural behaviors can be numerically related. To fulfill the aims, fire tests and residual strength tests are conducted on RC beams having different fire exposure time periods and sustained load levels. To detect the automated cracks, surface images of the fire damaged beam surfaces are taken with digital cameras and an automatic crack detection method is developed using a convolutional neural network (CNN) which is a deep learning technique primarily used for analyzing intricate structures of high-dimensional data [such as high definition (HD) images and videos]. The quantity of cracks detected using the proposed CNN changes depending on the test variables, and the changing trends are similar to those of the crack lengths obtained from the optical observation. Additionally, it is found that the quantity of the automatically detected cracks is numerically related to the temperatures inside the beams as well as the stiffnesses obtained from the residual strength tests.