Journal of Applied Genetics最新文献

tsRNAs (tRNA-derived small non-coding RNAs), including tRNA halves (tiRNAs) and tRNA fragments (tRFs), have been implicated in some viral infections, such as respiratory viral infections. However, their involvement in SARS-CoV infection is completely unknown. A comprehensive analysis was performed to determine tsRNA populations in a mouse model of SARS-CoV-infected samples containing the wild-type and attenuated viruses. Data from the Gene Expression Omnibus (GEO) dataset at NCBI (accession ID GSE90624 ) was used for this study. A count matrix was generated for the tRNAs. Differentially expressed tRNAs, followed by tsRNAs derived from each significant tRNAs at different conditions and time points between the two groups WT(SARS-CoV-MA15-WT) vs Mock and ΔE (SARS-CoV-MA15-ΔE) vs Mock were identified. Notably, significantly differentially expressed tRNAs at 2dpi but not at 4dpi. The tsRNAs originating from differentially expressed tRNAs across all the samples belonging to each condition (WT, ΔE, and Mock) were identified. Intriguingly, tRFs (tRNA-derived RNA fragments) exhibited higher levels compared to tiRNAs (tRNA-derived stress-induced RNAs) across all samples associated with WT SARS-CoV strain compared to ΔE and mock-infected samples. This discrepancy suggests a non-random formation of tsRNAs, hinting at a possible involvement of tsRNAs in SARS-CoV viral infection.

Atherosclerosis is a chronic inflammatory disease that affects arterial walls and is a leading cause of cardiovascular disease. Gene co-expression modules can provide insight into the molecular mechanisms underlying atherosclerosis progression. In this study, gene co-expression network analysis (WGCNA) was done to identify gene co-expression modules associated with atherosclerosis progression. Before conducting WGCNA, preprocessing and soft power selection were performed on the GSE28829, GSE100927, GSE43292, GSE10334, and GSE16134 datasets ( https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi ). Co-expression modules were identified using dynamic tree cuts, and their correlations and trait associations were visualized. Enrichment analysis was performed on the blue and magenta modules to identify biological processes (BP) and pathways related to atherosclerosis. The CIBERSORT algorithm was used to predict immune cell infiltration in early and advanced atherosclerotic plaques. We identified 12 co-expression modules, in which blue and magenta were most highly correlated with atherosclerosis progression. The blue module was enriched for inflammation- and immune-related BP and pathways, including phagosome, lysosome, osteoclast differentiation, chemokine signaling pathway, platelet activation, NF-kappa B signaling pathway, Fc gamma R-mediated phagocytosis, lipid and atherosclerosis, autophagy, and apoptosis. The magenta module was significantly enriched for vascular permeability regulation, positive and negative regulation of epithelial to mesenchymal transition, and lamellipodium. Additionally, the CIBERSORT algorithm predicted less abundance of T regulatory cells and monocytes in advanced compared to early atherosclerotic plaques. The enrichment analysis of BP, cellular components, molecular functions, and atherosclerosis-related pathways in the blue and magenta modules showed that inflammation and immune response played a key role in the progression of atherosclerosis. Our study provides insights into the molecular mechanisms underlying atherosclerosis progression and identifies potential therapeutic targets for the treatment of atherosclerosis. The identification of immune cell subtypes associated with atherosclerosis could lead to the development of immunomodulatory therapies to prevent or treat atherosclerosis.

Mineral composition in milk can affect its nutritional as well as physio-chemical properties of milk and is considered an important trait in the evaluation of milk quality. The composition and concentration of milk minerals could be altered with natural source of variation including nutrition and genetics. The effect of diet on milk minerals is well studied. However, genetic effects on the milk minerals have recently gained the attention. This review provides an overview of the genetic variation of milk minerals, and the genomic regions associated with mineral concentration in the milk are also discussed. The difference of milk minerals between breeds and the genetic parameters including heritability estimates and correlation among minerals indicates that milk minerals are under strong genetic control. Recently, the genome-wide association study (GWAS) has explored several regions associated with milk minerals and thus provides a new genetic source for improving the milk quality through genomics-assisted breeding. Hence, a combination of the qualitative and molecular approaches can be exploited to improving the nutritional quality of cattle milk in terms of its mineral composition.

Triticale (X Triticosecale Wittmack), a wheat-rye small grain crop hybrid, combines wheat and rye attributes in one hexaploid genome. It is characterized by high adaptability to adverse environmental conditions: drought, soil acidity, salinity and heavy metal ions, poorer soil quality, and waterlogging. So that its cultivation is prospective in a changing climate. Here, we describe RGB on-ground phenotyping of field-grown eighteen triticale market-available cultivars, made in naturally changing light conditions, in two consecutive winter cereals growing seasons: 2018-2019 and 2019-2020. The number of ears was counted on top-down images with an accuracy of 95% and mean average precision (mAP) of 0.71 using advanced object detection algorithm YOLOv4, with ensemble modeling of field imaging captured in two different illumination conditions. A correlation between the number of ears and yield was achieved at the statistical importance of 0.16 for data from 2019. Results are discussed from the perspective of modern breeding and phenotyping bottleneck.

Pigmentation in rice grains is an important quality parameter. Purple-coloured rice (Oryza sativa L.) indicates the presence of high anthocyanin with benefits of antioxidant properties. However, the genetic mechanism of grain colour is not fully understood. Therefore, the study focused on understanding pigmentation in grain pericarp and vegetative parts, and its relationship with blast resistance and enhanced grain yield. Three local cultivars from the northeastern region (NER) of India - Chakhao Poireiton (purple), Mang Meikri (light brown), and Kala Joha (white) - along with high-yielding varieties (HYVs) Shasharang (light brown) and Sahbhagi dhan (white) were used to develop biparental populations. The findings suggested that pigmentation in vegetative tissue was governed by the inter-allelic interaction of several genes. Haplotype analysis revealed that Kala3 complemented Kala4 in enhancing purple pigmentation and that Kala4 is not the only gene responsible for purple colour as evident by the presence of a desired allele for markers RID3 and RID4 (Kala4 locus) in Chakhao Poireiton and Kala Joha irrespective of their pericarp colour, implying the involvement of some other additional, unidentified genes/loci. RID3 and RID4 together with RM15191 (Kala3 locus) could be employed as a reliable marker set for marker-assisted selection (MAS). Pericarp colour was strongly correlated with colour in different vegetative parts, but showed a negative correlation with grain yield. Pb1, reported to be associated with panicle blast resistance, contributed to leaf blast resistance. Transgressive segregants for improved pigmentation and high yield were identified. The selection of lines exhibiting coloured pericarp, high anthocyanin content, aroma, blast resistance, and increased yield compared to their respective HYV parents will be valuable resources in the rice breeding programme.

Long non-coding RNAs (lncRNAs) have been implicated in carcinogenesis and progression of hepatocellular carcinoma (HCC). This study aimed to identify a robust lncRNA signature for predicting the survival of HCC patients. We performed an integrated analysis of the lncRNA expression profiling in The Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma database to identify the prognosis-related lncRNA for the HCC. The HCC cohort was randomly divided into a training set (n = 250) and a testing set (n = 113). Following a two-step screening, we identified an 18-lncRNA signature risk score. The high-risk subgroups had significantly shorter survival time than the low-risk group in both the training set (P < 0.0001) and the testing set (P = 0.005). Stratification analysis revealed that the prognostic value of the lncRNA-based signature was independent of the tumor stage and pathologic stage. The area under the receiver operating characteristic curve (AUROC) of the 18-lncRNA signature risk score was 0.826 (95%CI, 0.764-0.888), 0.817 (95%CI, 0.759-0.876), and 0.799 (95%CI, 0.731-0.867) for 1-year, 3-year, and 5-year follow-up, respectively. Bioinformatics analyses indicated that the 18 lncRNA might mediate cell cycle, DNA replication processes, and canonical cancer-related pathways, in which MCM3AP-AS1 was a potential target for HCC. In conclusion, the 18-lncRNA signature was a robust predictive biomarker for the prognosis and progression of HCC.

A 9-year-old Thoroughbred mare with normal external genitalia and regular oestrus symptoms was gynecologically examined prior to insemination. This primary examination revealed the presence of a hypoplastic uterus and the lack of normal ovaries, and the mare was therefore subjected to more detailed diagnostics, including endocrinological, genetic, and clinical tests. Diagnostic imaging with the use of ultrasonography and endoscopy confirmed the underdevelopment of internal genitalia. Analysis of circulating sex hormones revealed very low concentrations of progesterone and oestradiol. Finally, cytogenetic analysis showed the presence of non-mosaic X trisomy (65,XXX), an aneuploidy of sex chromosomes that is rarely detected in horses. This finding was also confirmed by molecular methods, including highly sensitive droplet digital PCR (ddPCR) and microsatellite markers genotyping. Our study reveals the need for gynaecological and genetic evaluation of broodmares, even if their phenotype (including developed external genitalia and oestrus symptoms) shows no signs of potential abnormalities.

Composite breeds, including Brangus, are widely utilized in subtropical and tropical regions to harness the advantages of both Bos t. taurus and Bos t. indicus breeds. The formation and subsequent selection of composite breeds may result in discernible signatures of selection and shifts in genomic population structure. The objectives of this study were to 1) assess genomic inbreeding, 2) identify signatures of selection, 3) assign functional roles to these signatures in a commercial Brangus herd, and 4) contrast signatures of selection between selected and non-selected cattle from the same year. A total of 4035 commercial Brangus cattle were genotyped using the GGP-F250K array. Runs of Homozygosity (ROH) were used to identify signatures of selection and calculate genomic inbreeding. Quantitative trait loci (QTL) enrichment analysis and literature search identified phenotypic traits linked to ROH islands. Genomic inbreeding averaged 5%, primarily stemming from ancestors five or more generations back. A total of nine ROH islands were identified, QTL enrichment analysis revealed traits related to growth, milk composition, carcass, reproductive, and meat quality traits. Notably, the ROH island on BTA14 encompasses the pleiomorphic adenoma (PLAG1) gene, which has been linked to growth, carcass, and reproductive traits. Moreover, ROH islands associated with milk yield and composition were more pronounced in selected replacement heifers of the population, underscoring the importance of milk traits in cow-calf production. In summary, our research sheds light on the changing genetic landscape of the Brangus breed due to selection pressures and reveals key genomic regions impacting production traits.

The coronavirus disease 2019 (COVID-19) was first found in Wuhan, China, in December 2019. Because the virus spreads quickly, it quickly became a global worry. Coronaviridae is the family that contains both SARS-CoV-2 and the viruses that came before (i.e., MERS-CoV and SARS-CoV). Recent sources portray that the COVID-19 virus has affected 344,710,576 people worldwide and killed about 5,598,511 people in the last 2 years. The B.1.1.529 strain, later called "Omicron," was named a Variant of Concern on November 24, 2021. The SARS-CoV-2 virus has gone through a never-ending chain of changes that have never happened before. As a result, it has many different traits. Most of these changes have occurred in the spike protein, where antibodies bind. Because of these changes, the Omicron type is very contagious and easy to pass on. There have been a lot of studies done to try to figure out this new challenge in the COVID-19 strains race, but there is still a lot that needs to be explained. This study focuses on virtual screening, docking, and molecular dynamic analysis; we aimed to identify therapeutic candidates for the SARS-CoV-2 variant Omicron based on their ability to inhibit non-structural proteins. We investigate the prediction of the properties of a substantial database of drug molecules obtained from the OliveNet™ database. Compounds that did not exhibit adequate gastrointestinal absorption and failed the Lipinski test are not considered for further research. The filtered compounds were coupled with our primary target, SARS-CoV-2 Omicron spike protein. We focused on SARS-CoV-2 Omicron spike protein and filtering potent olive compounds. Pinoresinol, the most likely candidate, is bound best (- 8.5 kcal/mol). Pinoresinol's strong interaction with the active site made the complex's dynamic structure more resilient. MD simulations explain the protein-ligand complex's stability and function. Pinoresinol may be a promising SARS-CoV-2 Omicron spike protein receptor lead drug, and additional research may assist the scientific community.