Aohan fine-wool sheep (AFWS) is a high-quality fine-wool sheep breed that supplies wool and meat. Research is needed on the molecular mechanism behind intramuscular fat (IMF) deposition that greatly improves mutton quality. The widely expressed non-coding RNA is physiologically used in roles such as competitive endogenous RNA (ceRNA) that includes circular RNAs (circRNAs). Although circRNAs were studied in many fields, little research was devoted to IMF in sheep. We used the longissimus dorsi muscle of 2 and 12-month-old AWFS as research material to identify circRNAs related to IMF deposition in these sheep by RNA-seq screening for differentially expressed circRNAs in the two age groups. A total of 11,565 candidate circRNAs were identified, of which the 104 differentially expressed circRNAs in the two age groups were analyzed. Enrichment analysis was performed using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes. The enriched pathways included lipid transport (GO:0006869), negative regulation of canonical Wnt signaling pathway (GO:0090090), fat digestion and absorption (ko04975), and sphingolipid metabolism (ko00600). The differentially expressed circRNAs included ciRNA455, circRNA9086, circRNA7445, circRNA4557, and others. The source genes involved in these pathways might regulate IMF deposition. We used the TargetScan and miRanda software for interaction analysis, and a network diagram of circRNA-miRNA interactions was created. CircRNA455-miR-127, circRNA455-miR-29a, circRNA455-miR-103, circRNA4557-mir149-5p, and circRNA2440-mir-23a might be involved in the IMF deposition process. The targeting relationship of circRNA4557-miR-149-5p was verified by a dual-luciferase reporter assay. The RT-qPCR results of seven randomly selected circRNAs were consistent with the sequencing results. This study provides additional information on circRNA regulation of IMF deposition in AFWS and is a useful resource for future research on this sheep breed.

The QTL-allele system underlying two spectral reflectance physiological traits, NDVI (normalized difference vegetation index) and CHL (chlorophyll index), related to plant growth and yield was studied in the Chinese soybean germplasm population (CSGP), which consisted of 341 wild accessions (WA), farmer landraces (LR), and released cultivars (RC). Samples were evaluated in the Photosynthetic System II imaging platform at Nanjing Agricultural University. The NDVI and CHL data were obtained from hyperspectral reflectance images in a randomized incomplete block design experiment with two replicates. The NDVI and CHL ranged from 0.05-0.18 and 1.20-4.78, had averages of 0.11 and 3.57, and had heritabilities of 78.3% and 69.2%, respectively; the values of NDVI and CHL were both significantly higher in LR and RC than in WA. Using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) method, 38 and 32 QTLs with 89 and 82 alleles and 2-4 and 2-6 alleles per locus were identified for NDVI and CHL, respectively, which explained 48.36% and 51.35% of the phenotypic variation for NDVI and CHL, respectively. The QTL-allele matrices were established and separated into WA, LR, and RC submatrices. From WA to LR + RC, 4 alleles and 2 new loci emerged, and 1 allele was excluded for NDVI, whereas 6 alleles emerged, and no alleles were excluded, in LR + RC for CHL. Recombination was the major motivation of evolutionary differences. For NDVI and CHL, 39 and 32 candidate genes were annotated and assigned to GO groups, respectively, indicating a complex gene network. The NDVI and CHL were upstream traits that were relatively conservative in their genetic changes compared with those of downstream agronomic traits. High-throughput phenotyping integrated with RTM-GWAS provides an efficient procedure for studying the population genetics of traits.

In recent years, many computational models have been designed to detect essential proteins based on protein-protein interaction (PPI) networks. However, due to the incompleteness of PPI networks, the prediction accuracy of these models is still not satisfactory. In this manuscript, a novel key target convergence sets based prediction model (KTCSPM) is proposed to identify essential proteins. In KTCSPM, a weighted PPI network and a weighted (Domain-Domain Interaction) network are constructed first based on known PPIs and PDIs downloaded from benchmark databases. And then, by integrating these two kinds of networks, a novel weighted PDI network is built. Next, through assigning a unique key target convergence set (KTCS) for each node in the weighted PDI network, an improved method based on the random walk with restart is designed to identify essential proteins. Finally, in order to evaluate the predictive effects of KTCSPM, it is compared with 12 competitive state-of-the-art models, and experimental results show that KTCSPM can achieve better prediction accuracy. Considering the satisfactory predictive performance achieved by KTCSPM, it indicates that KTCSPM might be a good supplement to the future research on prediction of essential proteins.

The sustainable development of aquaculture has been impeded by infectious diseases worldwide. However, the genomic architecture and the genetic basis underlying the disease resistance remain poorly understood, which severely hampers both the understanding of the evolution of fish disease resistance traits and the prevention of these diseases in the aquaculture community. Cynoglossus semilaevis is a representative and commercially-important flatfish species. Here we combined genome-wide association study and Fst and nucleotide diversity filtration to identify loci important for the disease resistance. Based on 1,016,774 single-nucleotide polymorphisms (SNPs) identified from 650 Gb genome resequencing data of 505 individuals, we detected 33 SNPs significantly associated with disease resistance and 79 candidate regions after filtration steps. Both the allele frequencies and genotype frequencies of the associated loci were significantly different between the resistant and susceptible fish, suggesting a role in the genetic basis of disease resistance. The SNP with strongest association with disease resistance was located in Chr 17, at 145 bp upstream of fblx19 gene, and overlapped with the major quantitative trait locus previously identified. Several genes, such as plekha7, nucb2, and fgfr2, were also identified to potentially play roles in the disease resistance. Furthermore, the expression of some associating genes were likely under epigenetic regulations between the bacterial resistant and susceptible families. These results provide insights into the mechanism that enable variation of disease resistance to bacterial pathogen infection. The identified polymorphisms and genes are valuable targets and molecular resources for disease resistance and other traits, and for advanced breeding practice for superior germplasm in fish aquaculture.

Intramuscular fat (IMF) is one of the most critical parameters affecting meat quality and mainly affected by genetic factors. MicroRNA as an important regulatory factor, which is still a lack of research in the development of sheep IMF deposition. We used RNA sequencing (RNA-seq) and cell-level validation to explore the role of miRNA in IMF deposition. As for this purpose, longissimus thoracis et lumborum (LTL) samples of 2 month-old (Mth-2) and 12 months-old (Mth-12) Aohan fine-wool sheep (AFWS) were used to identified miRNAs expression. We found 59 differentially expressed miRNAs (DE-miRNA) between these age groups and predicted their 1,796 target genes. KEGG functional enrichment analysis revealed eight pathways involved in lipid metabolism-related processes, including fatty acid elongation and the AMPK signaling pathway. A highly expressed DE-miRNA, miR-193a-5p, was found to serve a function in 3T3-L1 preadipocyte differentiation. Luciferase assay demonstrated that miR-193a-5p directly binds to the 3'-UTR region of ACAA2. By constructing mimics and inhibitor vector transfecting into 3T3-L1 cells to explore the effect of miR-193a-5p on cell proliferation and differentiation, we demonstrated that overexpression of miR-193a-5p inhibited 3T3-L1 preadipocyte proliferation, as evidenced by decreased mRNA and protein expression of CDK4 and CyclinB. CCK-8 assay showed that miR-193a-5p significantly inhibited cell proliferation. Similarly, the overexpression of miR-193a-5p inhibited 3T3-L1 preadipocyte differentiation and adipocyte-specific molecular markers' expression, leading to a decrease in PPARγ and C/EBPα and ACAA2. Inhibition of miR-193a-5p had the opposite effects. Our study lists the miRNAs associated with intramuscular lipid deposition in sheep and their potential targets, striving to improve sheep meat quality.

A single nucleotide polymorphism (SNP) within MIR137, the host gene for miR-137, has been identified repeatedly as a risk factor for schizophrenia. Previous genetic pathway analyses suggest that potential targets of this microRNA (miRNA) are also highly enriched in schizophrenia-relevant biological pathways, including those involved in nervous system development and function.

Recent studies have indicated that microRNAs (miRNAs) are closely related to sundry human sophisticated diseases. According to the surmise that functionally similar miRNAs are more likely associated with phenotypically similar diseases, researchers have proposed a variety of valid computational models through integrating known miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity to discover the potential miRNA-disease relationships in biomedical researches. Taking account of the limitations of previous computational models, a new computational model based on biased heat conduction for MiRNA-Disease Association prediction (BHCMDA) was proposed in this paper, which can achieve the AUC of 0.8890 in LOOCV (Leave-One-Out Cross Validation) and the mean AUC of 0.9060, 0.8931 under the framework of twofold cross validation, fivefold cross validation, respectively. In addition, BHCMDA was further implemented to the case studies of three vital human cancers, and simulation results illustrated that there were 88% (Esophageal Neoplasms), 92% (Colonic Neoplasms) and 92% (Lymphoma) out of top 50 predicted miRNAs having been confirmed by experimental literatures, separately, which demonstrated the good performance of BHCMDA as well. Thence, BHCMDA would be a useful calculative resource for potential miRNA-disease association prediction.

Alternative splicing (AS) is a process in eukaryotic gene expression, in which the primary transcript of a multi-exon gene is spliced into two or more different mature transcripts, thereby increasing proteome diversity. AS is often regulated differentially between different tissues or developmental stages. Recent studies suggested that up to 60% of intron-containing genes in Arabidopsis thaliana undergo AS. Yet little is known about this complicated and important process during floral development. To investigate the preferential expression of different isoforms of individual alternatively spliced genes, we used high throughput RNA-Seq technology to explore the transcriptomes of three floral development stages of Arabidopsis thaliana and obtained information of various AS events. We identified approximately 24,000 genes that were expressed at one or more of these stages, and found that nearly 25% of multi-exon genes had two or more spliced variants. This is less frequent than the previously reported 40-60% for multiple organs and stages of A. thaliana, indicating that many genes expressed in floral development function with a single predominant isoform. On the other hand, 1716 isoforms were differentially expressed between the three stages, suggesting that AS might still play important roles in stage transition during floral development. Moreover, 337 novel transcribed regions were identified and most of them have a single exon. Taken together, our analyses provide a comprehensive survey of AS in floral development and facilitate further genomic and genetic studies.

As one of the most malicious cancers, pancreatic cancer is difficult to treat due to the lack of effective early diagnosis. Therefore, it is urgent to find reliable diagnostic and predictive markers for the early detection of pancreatic cancer. In recent years, the detection of circulating cell-free DNA (cfDNA) methylation in plasma has attracted global attention for non-invasive and early cancer diagnosis. Here, we carried out a genome-wide cfDNA methylation profiling study of pancreatic ductal adenocarcinoma (PDAC) patients by methylated DNA immunoprecipitation coupled with high-throughput sequencing (MeDIP-seq). Compared with healthy individuals, 775 differentially methylated regions (DMRs) located in promoter regions were identified in PDAC patients with 761 hypermethylated and 14 hypomethylated regions; meanwhile, 761 DMRs in CpG islands (CGIs) were identified in PDAC patients with 734 hypermethylated and 27 hypomethylated regions (p-value < 0.0001). Then, 143 hypermethylated DMRs were further selected which were located in promoter regions and completely overlapped with CGIs. After performing the least absolute shrinkage and selection operator (LASSO) method, a total of eight markers were found to fairly distinguish PDAC patients from healthy individuals, including TRIM73, FAM150A, EPB41L3, SIX3, MIR663, MAPT, LOC100128977, and LOC100130148. In conclusion, this work identified a set of eight differentially methylated markers that may be potentially applied in non-invasive diagnosis of pancreatic cancer.

Background: Aging is a well-studied concept, but no studies have comprehensively analyzed the association between aging-related genes (AGs) and hepatocellular carcinoma (HCC) prognosis. Methods: Gene candidates were selected from differentially expressed genes and prognostic genes in The Cancer Genome Atlas (TCGA) database. A gene risk score for overall survival prediction was established using the least absolute shrinkage and selection operator (LASSO) regression analysis, and this was validated using data from the International Cancer Genome Consortium (ICGC) database. Functional analysis was conducted using gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes analysis, gene set enrichment analysis, and immune microenvironment and tumor stemness analyses. Results: Initially, 72 AGs from the TCGA database were screened as differentially expressed between normal and tumor tissues and as genes associated with HCC prognosis. Then, seven AGs (POLA1, CDK1, SOCS2, HDAC1, MAPT, RAE1, and EEF1E1) were identified using the LASSO regression analysis. The seven AGs were used to develop a risk score in the training set, and the risk was validated to have a significant prognostic value in the ICGC set (p < 0.05). Patients with high risk scores had lower tumor differentiation, higher stage, and worse prognosis (all p < 0.05). Multivariate Cox regression analyses also confirmed that the risk score was an independent prognostic factor for HCC in both the TCGA and ICGC sets (all p < 0.05). Further analysis showed that a high risk score was correlated with the downregulation of metabolism and tumor immunity. Conclusion: The risk score predicts HCC prognosis and could thus be used as a biomarker not only for predicting HCC prognosis but also for deciding on treatment.

The TEOSINTE BRANCHED 1/CYCLOIDEA/PROLIFERATING CELL FACTORS (TCP) protein, belonging to a plant-specific transcription factors (TFs) family, participates in the control of plant growth and development by regulating cell proliferation. Until now, a comprehensive study of concerning the TCP gene family and their roles in grapevine (Vitis vinifera L.) has not been completed. Using bioinformatics approaches, 17 VvTCP genes were identified and further classified into two classes, designated class I (PCF subclass) and class II (CIN and CYC/TB1 subclass), which was further supported by exon-intron organizations and conserved motif analysis. Promoter analysis demonstrated that VvTCPs have numerous cis-acting elements related to plant growth and development, phytohormone, and abiotic/biotic stress responses. The singleton duplication of grapevine TCP genes contributed to this gene family expansion. The syntenic analyses among Vitis vinifera, Arabidopsis, and Oryza sativa showed that these genes located in corresponding syntenic blocks arose before the divergence of V. vinifera, Arabidopsis, and O. sativa. The expression levels of 17 VvTCPs were determined in different tissues and fruit developmental stages, and abscisic acid (ABA) treatment. Seventeen VvTCPs exhibited distinct tissue-specific expression patterns, potentially illustrating the functional divergence of VvTCPs in all tested tissues. Eleven VvTCPs were down-regulated in five berry developmental stages, while three VvTCPs were up-regulated. Additionally, many members were strongly modulated by ABA treatment, suggesting these VvTCPs have important and diverse regulatory roles in ABA treatment. Our results provide valuable information on the evolution and functions of the VvTCPs, pave the way for further functional verification of these VvTCPs in grapevine.

Basic helix-loop-helix (bHLH) proteins are transcription factors (TFs) that have been shown to regulate anthocyanin biosynthesis in many plant species. However, the bHLH gene family in walnut (Juglans regia L.) has not yet been reported. In this study, 102 bHLH genes were identified in the walnut genome and were classified into 15 subfamilies according to sequence similarity and phylogenetic relationships. The gene structure, conserved domains, and chromosome location of the genes were analyzed by bioinformatic methods. Gene duplication analyses revealed that 42 JrbHLHs were involved in the expansion of the walnut bHLH gene family. We also characterized cis-regulatory elements of these genes and performed Gene Ontology enrichment analysis of gene functions, and examined protein-protein interactions. Four candidate genes (JrEGL1a, JrEGL1b, JrbHLHA1, and JrbHLHA2) were found to have high homology to genes encoding bHLH TFs involved in anthocyanin biosynthesis in other plants. RNA sequencing revealed tissue- and developmental stage-specific expression profiles and distinct expression patterns of JrbHLHs according to phenotype (red vs. green leaves) and developmental stage in red walnut hybrid progeny, which were confirmed by quantitative real-time PCR analysis. All four of the candidate JrbHLH proteins localized to the nucleus, consistent with a TF function. These results provide a basis for the functional characterization of bHLH genes and investigations on the molecular mechanisms of anthocyanin biosynthesis in red walnut.

Bloodstream infection is a major cause of morbidity and mortality worldwide. We explored whether MinION nanopore sequencing could accelerate diagnosis, resistance, and virulence profiling prediction in simulated blood samples and blood cultures. One milliliter of healthy blood samples each from direct spike (sample 1), anaerobic (sample 2), and aerobic (sample 3) blood cultures with initial inoculation of ∼30 CFU/ml of a clinically isolated Klebsiella pneumoniae strain was subjected to DNA extraction and nanopore sequencing. Hybrid assembly of Illumina and nanopore reads from pure colonies of the isolate (sample 4) was used as a reference for comparison. Hybrid assembly of the reference genome identified a total of 39 antibiotic resistance genes and 77 virulence genes through alignment with the CARD and VFDB databases. Nanopore correctly detected K. pneumoniae in all three blood samples. The fastest identification was achieved within 8 h from specimen to result in sample 1 without blood culture. However, direct sequencing in sample 1 only identified seven resistance genes (20.6%) but 28 genes in samples 2-4 (82.4%) compared to the reference within 2 h of sequencing time. Similarly, 11 (14.3%) and 74 (96.1%) of the virulence genes were detected in samples 1 and 2-4 within 2 h of sequencing time, respectively. Direct nanopore sequencing from positive blood cultures allowed comprehensive pathogen identification, resistance, and virulence genes prediction within 2 h, which shows its promising use in point-of-care clinical settings.