Genome-Wide CRISPR/Cas9 Screening Identifies That Mitochondrial Solute Carrier SLC25A23 Attenuates Type I IFN Antiviral Immunity via Interfering with MAVS Aggregation.

Activation of the mitochondrial antiviral signaling (MAVS) adaptor, also known as IPS-1, VISA, or Cardif, is crucial for antiviral immunity in retinoic acid-inducible gene I (RIG-I)-like receptor signaling. Upon interacting with RIG-I, MAVS undergoes K63-linked polyubiquitination by the E3 ligase Trim31, and subsequently aggregates to activate downstream signaling effectors. However, the molecular mechanisms that modulate MAVS activation are not yet fully understood. In this study, the mitochondrial solute carrier SLC25A23 was found to attenuate type I IFN antiviral immunity using genome-wide CRISPR/Cas9 screening. SLC25A23 interacts with Trim31, interfering with its binding of Trim31 to MAVS. Indeed, SLC25A23 downregulation was found to increase K63-linked polyubiquitination and subsequent aggregation of MAVS, which promoted type I IFN production upon RNA virus infection. Consistently, mice with SLC25A23 knockdown were more resistant to RNA virus infection in vivo. These findings establish SLC25A23 as a novel regulator of MAVS posttranslational modifications and of type I antiviral immunity.

Landscapes of gut bacterial and fecal metabolic signatures and their relationship in severe preeclampsia.

BACKGROUND: Preeclampsia is a pregnancy-specific disease leading to maternal and perinatal morbidity. Hypertension and inflammation are the main characteristics of preeclampsia. Many factors can lead to hypertension and inflammation, including gut microbiota which plays an important role in hypertension and inflammation in humans. However, alterations to the gut microbiome and fecal metabolome, and their relationships in severe preeclampsia are not well known. This study aims to identify biomarkers significantly associated with severe preeclampsia and provide a knowledge base for treatments regulating the gut microbiome. METHODS: In this study, fecal samples were collected from individuals with severe preeclampsia and healthy controls for shotgun metagenomic sequencing to evaluate changes in gut microbiota composition. Quantitative polymerase chain reaction analysis was used to validate the reliability of our shotgun metagenomic sequencing results. Additionally, untargeted metabolomics analysis was performed to measure fecal metabolome concentrations. RESULTS: We identified several Lactobacillaceae that were significantly enriched in the gut of healthy controls, including Limosilactobacillus fermentum, the key biomarker distinguishing severe preeclampsia from healthy controls. Limosilactobacillus fermentum was significantly associated with shifts in KEGG Orthology (KO) genes and KEGG pathways of the gut microbiome in severe preeclampsia, such as flagellar assembly. Untargeted fecal metabolome analysis found that severe preeclampsia had higher concentrations of Phenylpropanoate and Agmatine. Increased concentrations of Phenylpropanoate and Agmatine were associated with the abundance of Limosilactobacillus fermentum. Furthermore, all metabolites with higher abundances in healthy controls were enriched in the arginine and proline metabolism pathway. CONCLUSION: Our research indicates that changes in metabolites, possibly due to the gut microbe Limosilactobacillus fermentum, can contribute to the development of severe preeclampsia. This study provides insights into the interaction between gut microbiome and fecal metabolites and offers a basis for improving severe preeclampsia by modulating the gut microbiome.

Mutational analysis of minichromosome maintenance complex component (MCM) family genes in Chinese Han women with polycystic ovarian syndrome.

PURPOSE: To investigate whether mutations in the minichromosome maintenance complex component (MCM) family genes were present in patients with polycystic ovary syndrome (PCOS) of Chinese descent. METHODS: A total of 365 Chinese patients with PCOS and 860 women without PCOS as control who underwent with assisted reproductive technology were enrolled. Genomic DNA was extracted from the peripheral blood of these patients for PCR and Sanger sequencing. The potential damage of these mutations/rare variants was analyzed through evolutionary conservation analysis and bioinformatic programs. RESULTS: Twenty-nine missense or nonsense mutations/rare variants in the MCM genes were identified in 365 patients with PCOS (7.9%, 29/365), all these mutations/rare variants were predicted to be 'disease causing' by SIFT and PolyPhen2 programs. Among those, four mutations were reported here for the first time, p.S7C (c.20C > G) in MCM2 (NM_004526.3), p.K350R (c.1049A > G) in MCM5 (NM_006739.3), p.K283N (c.849G > T) in MCM10 (NM_182751.2), and p.S1708F (c.5123C > T) in MCM3AP (NM_003906.4). All of these novel mutations were not found in our 860 control women, or also absent in public databases. In addition, the evolutionary conservation analysis results suggested that these novel mutations caused highly conserved amino acid substitutions among 10 vertebrate species. CONCLUSION: This study identified a high frequency of potential pathogenic rare variants/mutations in MCM family genes in Chinese women with PCOS, which further expands the genotype spectrum in PCOS.

DIA-based proteomics analysis of serum-derived exosomal proteins as potential candidate biomarkers for intrahepatic cholestasis in pregnancy.

BACKGROUND: Data-independent acquisition (DIA) is one of the most powerful and reproducible proteomic technologies for large-scale digital qualitative and quantitative research. The aim of this study was to use proteomic methodologies for the identification of biomarkers that are over or underexpressed in women with intrahepatic cholestasis of pregnancy (ICP) compared with controls and discover a potential biomarker panel for ICP detection. METHODS: The participants included 11 ICP patients and 11 healthy pregnant women as controls. The clinical characteristic data and the laboratory biochemical data were collected at the time of recruitment. Then, a data-independent acquisition (DIA)-based proteomics approach was used to identify differentially expressed proteins (DEPs) in serum exosomes between ICP patients and controls. Finally, bioinformatics analysis was used to identify the relevant processes in which these DEPs were involved. RESULTS: The proteomics results showed that there were 162 DEPs in serum exosomes between pregnant women with ICP and healthy pregnant women, of which 106 were upregulated and 56 were downregulated in ICP. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the identified proteins were functionally related to specific cell processes including apoptosis, lipid metabolism, immune response and cell proliferation, and metabolic disorders, suggesting that these may be primary causative factors in ICP pathogenesis. Meanwhile, complement and coagulation cascades may be closely related to the development of ICP. Receiver operating characteristic curve (ROC) analysis showed that the area under the curve values of Elongation factor 1-alpha 1, Beta-2-glycoprotein I, Zinc finger protein 238, CP protein and Ficolin-3 were all approximately 0.9, indicating the promising diagnostic value of these proteins. CONCLUSIONS: This preliminary work provides a better understanding of the proteomic alterations in the serum exosomes of pregnant women with ICP.

Identifying biomarkers of the gut bacteria, bacteriophages and serum metabolites associated with three weaning periods in piglets.

BACKGROUND: The establishment of the piglet gut microbiome has a prolonged influence on host health, as it sets the stage for establishment of the adult swine microbiome. Substantial changes in host metabolism and immunity around the time of weaning may be accompanied by alterations in the gut microbiome. In this study, we systematically evaluated differences in the gut microbiome and host metabolites among three weaning periods using shotgun metagenomic sequencing and untargeted metabolomic profiling in piglets. RESULTS: We identified that P. copri was the most significantly different species among three weaning periods, and was the key bacterial species for mitigating piglet adaptation during the weaning transition, while Bacillus_phage_BCD7, the only differential bacteriophages, was significantly and positively correlated with P. copri enriched in day 28 group. Additionally, P. copri and Bacillus_phage_BCD7 was significantly correlated with the shifts of functional capacities of the gut microbiome and several CAZymes in day 28 group. Furthermore, the altered metabolites we observed were enriched in pathways matched to the functional capacity of the gut microbiome e.g., aminoacyl-tRNA biosynthesis. CONCLUSION: The results from this study indicate that the bacteria-phage interactions and host-microbial interactions during the weaning transition impact host metabolism, leading to beneficial host changes among three weaning periods.

Gut archaea associated with bacteria colonization and succession during piglet weaning transitions.

BACKGROUND: Host-associated gut microbial communities are key players in shaping the fitness and health of animals. However, most current studies have focused on the gut bacteria, neglecting important gut fungal and archaeal components of these communities. Here, we investigated the gut fungi and archaea community composition in Large White piglets using shotgun metagenomic sequencing, and systematically evaluated how community composition association with gut microbiome, functional capacity, and serum metabolites varied across three weaning periods. RESULTS: We found that Mucoromycota, Ascomycota and Basidiomycota were the most common fungi phyla and Euryarchaeota was the most common archaea phyla across individuals. We identified that Methanosarcina siciliae was the most significantly different archaea species among three weaning periods, while Parasitella parasitica, the only differential fungi species, was significantly and positively correlated with Methanosarcina siciliae enriched in day 28 group. The random forest analysis also identified Methanosarcina siciliae and Parasitella parasitica as weaning-biased archaea and fungi at the species level. Additionally, Methanosarcina siciliae was significantly correlated with P. copri and the shifts of functional capacities of the gut microbiome and several CAZymes in day 28 group. Furthermore, characteristic successional alterations in gut archaea, fungi, bacteria, and serum metabolites with each weaning step revealed a weaning transition coexpression network, e.g., Methanosarcina siciliae and P. copri were positively and significantly correlated with 15-HEPE, 8-O-Methyloblongine, and Troxilin B3. CONCLUSION: Our findings provide a deep insight into the interactions among gut archaea, fungi, bacteria, and serum metabolites and will present a theoretical framework for understanding gut bacterial colonization and succession association with archaea during piglet weaning transitions.

Alternatones A and B, two polyketides possessing novel skeletons from entophyte Alternaria alternate L-10.

On our ongoing searching for bioactive natural products derived from entophytes, two polyketides possessing novel skeletons, alternatones A-B (1-2), were identified from the culture of Alternaria alternate L-10. Their structures were established by a combination of spectroscopic and single-crystal X-ray diffraction with Cu Ka radiation. Alternatone A (1) exhibited cytotoxic activity against human hepatoma carcinoma HepG-2 cell line. The putative biosynthetic pathways for compounds 1-2 were also proposed.

Modelling dynamics of coronavirus disease 2019 spread for pandemic forecasting based on Simulink.

In this paper, we demonstrate the application of MATLAB to develop a pandemic prediction system based on Simulink. The susceptible-exposed-asymptomatic but infectious-symptomatic and infectious (severe infected population + mild infected population)-recovered-deceased (SEAI(I1+I2)RD) physical model for unsupervised learning and two types of supervised learning, namely, fuzzy proportional-integral-derivative (PID) and wavelet neural-network PID learning, are used to build a predictive-control system model that enables self-learning artificial intelligence (AI)-based control. After parameter setting, the data entering the model are predicted, and the value of the data set at a future moment is calculated. PID controllers are added to ensure that the system does not diverge at the beginning of iterative learning. To adapt to complex system conditions and afford excellent control, a wavelet neural-network PID control strategy is developed that can be adjusted and corrected in real time, according to the output error.

Whole-exome sequencing identifies novel mutations in ABC transporter genes associated with intrahepatic cholestasis of pregnancy disease: a case-control study.

BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) can cause premature delivery and stillbirth. Previous studies have reported that mutations in ABC transporter genes strongly influence the transport of bile salts. However, to date, their effects are still largely elusive. METHODS: A whole-exome sequencing (WES) approach was used to detect novel variants. Rare novel exonic variants (minor allele frequencies: MAF < 1%) were analyzed. Three web-available tools, namely, SIFT, Mutation Taster and FATHMM, were used to predict protein damage. Protein structure modeling and comparisons between reference and modified protein structures were performed by SWISS-MODEL and Chimera 1.14rc, respectively. RESULTS: We detected a total of 2953 mutations in 44 ABC family transporter genes. When the MAF of loci was controlled in all databases at less than 0.01, 320 mutations were reserved for further analysis. Among these mutations, 42 were novel. We classified these loci into four groups (the damaging, probably damaging, possibly damaging, and neutral groups) according to the prediction results, of which 7 novel possible pathogenic mutations were identified that were located in known functional genes, including ABCB4 (Trp708Ter, Gly527Glu and Lys386Glu), ABCB11 (Gln1194Ter, Gln605Pro and Leu589Met) and ABCC2 (Ser1342Tyr), in the damaging group. New mutations in the first two genes were reported in our recent article. In addition, compared to the wild-type protein structure, the ABCC2 Ser1342Tyr-modified protein structure showed a slight change in the chemical bond lengths of ATP ligand-binding amino acid side chains. In placental tissue, the expression level of the ABCC2 gene in patients with ICP was significantly higher (P < 0.05) than that in healthy pregnant women. In particular, the patients with two mutations in ABC family genes had higher average values of total bile acids (TBA), aspartate transaminase (AST), direct bilirubin (DBIL), total cholesterol (CHOL), triglycerides (TG) and high-density lipoprotein (HDL) than the patients who had one mutation, no mutation in ABC genes and local controls. CONCLUSIONS: Our present study provide new insight into the genetic architecture of ICP and will benefit the final identification of the underlying mutations.

A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak.

Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 that hits the world death tolls and economy loss very hard, is more complex and contagious than its precedent diseases. The complexity comes mostly from the emergence of asymptomatic patients and relapse of the recovered patients which were not commonly seen during SARS outbreaks. These new characteristics pertaining to COVID-19 were only discovered lately, adding a level of uncertainty to the traditional SEIR models. The contribution of this paper is that for the COVID-19 epidemic, which is infectious in both the incubation period and the onset period, we use neural networks to learn from the actual data of the epidemic to obtain optimal parameters, thereby establishing a nonlinear, self-adaptive dynamic coefficient infectious disease prediction model. On the basis of prediction, we considered control measures and simulated the effects of different control measures and different strengths of the control measures. The epidemic control is predicted as a continuous change process, and the epidemic development and control are integrated to simulate and forecast. Decision-making departments make optimal choices. The improved model is applied to simulate the COVID-19 epidemic in the United States, and by comparing the prediction results with the traditional SEIR model, SEAIRD model and adaptive SEAIRD model, it is found that the adaptive SEAIRD model's prediction results of the U.S. COVID-19 epidemic data are in good agreement with the actual epidemic curve. For example, from the prediction effect of these 3 different models on accumulative confirmed cases, in terms of goodness of fit, adaptive SEAIRD model (0.99997) ≈ SEAIRD model (0.98548) > Classical SEIR model (0.66837); in terms of error value: adaptive SEAIRD model (198.6563) < < SEAIRD model(4739.8577) < < Classical SEIR model (22,652.796); The objective of this contribution is mainly on extending the current spread prediction model. It incorporates extra compartments accounting for the new features of COVID-19, and fine-tunes the new model with neural network, in a bid of achieving a higher level of prediction accuracy. Based on the SEIR model of disease transmission, an adaptive model called SEAIRD with internal source and isolation intervention is proposed. It simulates the effects of the changing behaviour of the SARS-CoV-2 in U.S. Neural network is applied to achieve a better fit in SEAIRD. Unlike the SEIR model, the adaptive SEAIRD model embraces multi-group dynamics which lead to different evolutionary trends during the epidemic. Through the risk assessment indicators of the adaptive SEAIRD model, it is convenient to measure the severity of the epidemic situation for consideration of different preventive measures. Future scenarios are projected from the trends of various indicators by running the adaptive SEAIRD model.

Whole-exome sequencing reveals ANO8 as a genetic risk factor for intrahepatic cholestasis of pregnancy.

BACKGROUND: Intrahepatic cholestasis of pregnancy (ICP) is characterized by pruritus and cholestasis in late pregnancy and results in adverse pregnancy outcomes, including preterm delivery and birth weight, which are affected by the genetic and environmental background. However, until now, the genetic architecture of ICP has remained largely unclear. METHODS: Twenty-six clinical data points were recorded for 151 Chinese ICP patients. The data generated from whole-exome sequencing (WES) using the BGISEQ-500 platform were further analyzed by Burrows-Wheeler Aligner (BWA) software, Genome Analysis Toolkit (GATK), ANNOVAR tool, etc. R packages were used to conduct t-test, Fisher's test and receiver operating characteristic (ROC) curve analyses. RESULTS: We identified eighteen possible pathogenic loci associated with ICP disease in known genes, covering ABCB4, ABCB11, ATP8B1 and TJP2. The loci Lys386Gln, Gly527Gln and Trp708Ter in ABCB4, Leu589Met, Gln605Pro and Gln1194Ter in ABCB11, and Arg189Ser in TJP2 were novel discoveries. In addition, WES analysis indicated that the gene ANO8 involved in the transport of bile salts is newly identified as associated with ICP. The functional network of the ANO8 gene confirmed this finding. ANO8 contained 8 rare missense mutations that were found in eight patients among the 151 cases and were absent from 1029 controls. Out of the eight SNPs, 3 were known, and the remaining five are newly identified. These variants have a low frequency, ranging from 0.000008 to 0.00001 in the ExAC, gnomAD - Genomes and TOPMED databases. Bioinformatics analysis showed that the sites and their corresponding amino acids were both highly conserved among vertebrates. Moreover, the influences of all the mutations on protein function were predicted to be damaging by the SIFT tool. Combining clinical data, it was found that the mutation group (93.36 µmol/L) had significantly (P = 0.038) higher total bile acid (TBA) levels than the wild-type group (40.81 µmol/L). CONCLUSIONS: To the best of our knowledge, this is the first study to employ WES technology to detect genetic loci for ICP. Our results provide new insights into the genetic basis of ICP and will benefit the final identification of the underlying mutations.

Protective effects of alpinetin on lipopolysaccharide/d-Galactosamine-induced liver injury through inhibiting inflammatory and oxidative responses.

Alpinetin, a type of novel plant flavonoid derived from Alpinia katsumadai Hayata, has been reported to have anti-inflammatory effects. The aim of this investigation was designed to reveal the protective effects of alpinetin on Lipopolysaccharide (LPS)/d-galactosamine (D-Gal)-induced liver injury in mice. Alpinetin (12.5, 25, 50 mg/kg) were given 1 h before LPS and D-Gal treatment. 12 h after LPS and D-Gal treatment, the liver tissues and serum were collected. Our results showed that alpinetin treatment improved liver histology, indicating a marked decrease of inflammatory cell infiltration and restore hepatic lobular architecture. Alpinetin also inhibited liver myeloperoxidase (MPO) activity and malondialdehyde (MDA) level. Furthermore, LPS/D-Gal-induced tumor necrosis factor-α (TNF-α) and Interleukin-1ß (IL-1ß) production were dose-dependently inhibited by alpinetin. Alpinetin also attenuated LPS/D-Gal-induced expression of phospho-NF-κB p65 and phospho-IκBα. In addition, alpinetin was found to increase the expression of nuclear factor E2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1). In conclusion, these findings suggested that alpinetin inhibited liver injury through inhibiting NF-κB and activating the Nrf2 signaling pathway.

Muscle glycogen level and occurrence of acid meat in commercial hybrid pigs are regulated by two low-frequency causal variants with large effects and multiple common variants with small effects.

BACKGROUND: Meat production from the commercial crossbred Duroc × (Landrace × Yorkshire) (DLY) pig is predominant in the pork industry, but its meat quality is often impaired by low ultimate pH (pHu). Muscle glycogen level at slaughter is closely associated with pHu and meat technological quality, but its genetic basis remains elusive. The aim of this study was to identify genes and/or causative mutations associated with muscle glycogen level and other meat quality traits by performing a genome-wide association study (GWAS) and additional analyses in a population of 610 DLY pigs. RESULTS: Our initial GWAS identified a genome-wide significant (P = 2.54e-11) quantitative trait locus (QTL) on SSC15 (SSC for Sus scrofa chromosome) for the level of residual glycogen and glucose (RG) in the longissimus muscle at 45 min post-mortem. Then, we demonstrated that a low-frequency (minor allele frequency = 0.014) R200Q missense mutation in the PRKAG3 (RN) gene caused this major QTL effect on RG. Moreover, we showed that the 200Q (RN-) allele was introgressed from the Hampshire breed into more than one of the parental breeds of the DLY pigs. After conditioning on R200Q, re-association analysis revealed three additional QTL for RG on SSC3 and 4, and on an unmapped scaffold (AEMK02000452.1). The SSC3 QTL was most likely caused by a splice mutation (g.8283C>A) in the PHKG1 gene that we had previously identified. Based on functional annotation, the genes TMCO1 on SSC4 and CKB on the scaffold represent promising candidate genes for the other two QTL. There were significant interaction effects of the GWAS tag SNPs at those two loci with PRKAG3 R200Q on RG. In addition, a number of common variants with potentially smaller effects on RG (P < 10-4) were uncovered by a second conditional GWAS after adjusting for the two causal SNPs, R200Q and g.8283C>A. CONCLUSIONS: We found that the RN- allele segregates in the parental lines of our DLY population and strongly influences its meat quality. Our findings also indicate that the genetic basis of RG in DLY can be mainly attributed to two major genes (PRKAG3 and PHKG1), along with many minor genes.

Enhanced self-assembly for the solubilization of cholesterol in molecular solvent/ionic liquid mixtures.

The development of new solvents combining greatly enhanced solubility for sparingly soluble compounds and good kinetic properties is challenging. In this study, we constructed a family of new molecular solvent/ionic liquid (IL) mixtures with amphiphilic, anionic functional long-chain carboxylate ionic liquids (LCC-ILs) as a key component for the solubilization of sparingly soluble compounds, using cholesterol as a model solute. Polarized optical microscopy (POM), wide angle X-ray diffraction (WAXD), Fourier-transform infrared (FTIR) spectra and 1H NMR showed that ordered mesoscopic structures, such as liquid crystals (LCs), were formed when cholesterol was dissolved in the mixtures, presenting a self-assembly induced dissolution mechanism driven by H-bond interaction and van der Waals forces in the mixtures. A synergistic effect between the molecular solvents and LCC-ILs was revealed, which contributed to enhanced solute-solvent self-assembly in dissolution over pure LCC-ILs and thus elevated solubility. Additionally, the effect of IL concentration, solvent type and anionic alkyl-chain length on self-assembly and solubility was investigated. These mixtures showed unparalleled solubilities for cholesterol, while maintaining a low viscosity. The quantitative solubilities (g g-1) of cholesterol were as high as 0.70, 0.84 and 0.82, respectively, at 25 °C in ethyl acetate/[P4444][C15H31COO] (50 wt%), n-heptane/[P4444][C15H31COO] (40 wt%) and ethyl acetate/[P4444][C17H35COO] (50 wt%) mixtures, which were the highest solubilities of cholesterol ever reported, six- to 980-fold higher than traditional molecular solvents and even one- to seven-fold higher compared to pure LCC-ILs. These results demonstrated the considerable potential of molecular solvent/LCC-ILs mixtures as promising solvents for solubilization and advanced separation processes.

A splice mutation in the PHKG1 gene causes high glycogen content and low meat quality in pig skeletal muscle.

Glycolytic potential (GP) in skeletal muscle is economically important in the pig industry because of its effect on pork processing yield. We have previously mapped a major quantitative trait loci (QTL) for GP on chromosome 3 in a White Duroc × Erhualian F2 intercross. We herein performed a systems genetic analysis to identify the causal variant underlying the phenotype QTL (pQTL). We first conducted genome-wide association analyses in the F2 intercross and an F19 Sutai pig population. The QTL was then refined to an 180-kb interval based on the 2-LOD drop method. We then performed expression QTL (eQTL) mapping using muscle transcriptome data from 497 F2 animals. Within the QTL interval, only one gene (PHKG1) has a cis-eQTL that was colocolizated with pQTL peaked at the same SNP. The PHKG1 gene encodes a catalytic subunit of the phosphorylase kinase (PhK), which functions in the cascade activation of glycogen breakdown. Deep sequencing of PHKG1 revealed a point mutation (C>A) in a splice acceptor site of intron 9, resulting in a 32-bp deletion in the open reading frame and generating a premature stop codon. The aberrant transcript induces nonsense-mediated decay, leading to lower protein level and weaker enzymatic activity in affected animals. The mutation causes an increase of 43% in GP and a decrease of>20% in water-holding capacity of pork. These effects were consistent across the F2 and Sutai populations, as well as Duroc × (Landrace × Yorkshire) hybrid pigs. The unfavorable allele exists predominantly in Duroc-derived pigs. The findings provide new insights into understanding risk factors affecting glucose metabolism, and would greatly contribute to the genetic improvement of meat quality in Duroc related pigs.

Genome-wide association analysis reveals genetic loci and candidate genes for meat quality traits in Chinese Laiwu pigs.

Meat quality traits have economically significant impacts on the pig industry, and can be improved using molecular approaches in pig breeding. Since 1994 when the first genome-wide scan for quantitative trait loci (QTLs) in pig was reported, over the past two decades, numerous QTLs have been identified for meat quality traits by family based linkage analyses. However, little is known about the genetic variants for meat quality traits in Chinese purebred or outbred populations. To unveil it, we performed a genome-wide association study for 10 meat quality traits in Chinese purebred Laiwu pigs. In total, 75 significant SNPs (P < 1.01 × 10(-6)) and 33 suggestive SNPs (P < 2.03 × 10(-5)) were identified. On SSC12, a region between 56.22 and 61.49 Mb harbored a cluster of SNPs that were associated with meat color parameters (L*, lightness; a*, redness; b*, yellowness) and moisture content of longissimus muscle (LM) and semimembranosus muscle at the genome-wide significance level. A region on SSC4 also has pleiotropic effects on moisture content and drip loss of LM. In addition, this study revealed at least five novel QTLs and several candidate genes including 4-linked MYH genes (MYH1, MYH2, MYH3, and MYH13), MAL2, LPAR1, and PRKAG3 at four significant loci. Except for the SSC12 QTL, other QTLs are likely tissue-specific. These results provide new insights into the genetic basis of meat quality traits in Chinese Laiwu pigs and some significant SNPs reported here could be incorporated into the selection programs involving this breed.

Nonaqueous lyotropic ionic liquid crystals: preparation, characterization, and application in extraction.

A class of new ionic liquid (IL)-based nonaqueous lyotropic liquid crystals (LLCs) and the development of an efficient IL extraction process based on LC chemistry are reported. The nonaqueous LLCs feature extraordinarily high extraction capacity, excellent separation selectivity, easy recovery, and biocompatibility. This work also demonstrates that the introduction of self-assembled anisotropic nanostructures into an IL system is an efficient way to overcome the intrinsically strong polarity of ILs and enhances the molecular recognition ability of ILs. The distribution coefficients of IL-based LLCs for organic compounds with H-bond donors reached unprecedented values of 50-60 at very high feed concentrations (>100 mg mL(-1) ), which are 800-1000 times greater than those of common ILs as well as traditional organic and polymer extractants. The IL-based nonaqueous LLCs combining the unique properties of ILs and LCs open a new avenue for the development of high-performance extraction methods.

Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) commercial population.

BACKGROUND: Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F2 crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population. METHODS: Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F2 and Sutai pig populations. RESULTS: We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes. CONCLUSIONS: These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.

Single-cell RNA sequencing reveals heterogeneity and differential expression of the maternal-fetal interface during ICP and normal pregnancy.

OBJECTIVE: Intrahepatic cholestasis of pregnancy (ICP) can cause adverse perinatal outcomes. Previous studies have demonstrated that the placenta of an ICP pregnancy differs in morphology and gene expression from the placenta of a normal pregnancy. To date, however, the genetic mechanism by which ICP affects the placenta is poorly understood. Therefore, the aim of this study was to investigate the differences in main cell types, gene signatures, cell ratio, and functional changes in the placenta between ICP and normal pregnancy. METHODS: Single-cell RNA sequencing (scRNA-seq) technology was used to detect the gene expression of all cells at the placental maternal-fetal interface. Two individuals were analyzed - one with ICP and one without ICP. The classification of cell types was determined by a graph-based clustering algorithm. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the R software phyper () function and DAVID website. The differentially expressed genes (DEGs) encoding transcription factors (TFs) were identified using getorf and DIAMOND software. RESULTS: We identified 14 cell types and 22 distinct cell subtypes that showed unique functional properties. Additionally, we found differences in the proportions of fibroblasts 1, helper T (Th) cells, extravillous trophoblasts, and villous cytotrophoblasts, and we observed heterogeneity of gene expression between ICP and control placentas. Furthermore, we identified 263 DEGs that belonged to TF families, including zf-C2H2, HMGI/HMGY, and Homeobox. In addition, 28 imprinted genes were preferentially expressed in specific cell types, such as PEG3 and PEG10 in trophoblasts as well as DLK1 and DIO3 in fibroblasts. CONCLUSIONS: Our results revealed the differences in cell-type ratios, gene expression, and functional changes between ICP and normal placentas, and heterogeneity was found among cell subgroups. Hence, the imbalance of various cell types affects placental activity to varying degrees, indicating the complexity of the cell networks that form the placental tissue system, and this alteration of placental function is associated with adverse events in the perinatal period.

Associations between ALDOB polymorphisms and intrahepatic cholestasis of pregnancy susceptibility in the Chinese Han population.

OBJECTIVES: To research the associations between fructose-bisphosphate aldolase B (ALDOB) gene polymorphisms and intrahepatic cholestasis of pregnancy (ICP) risk. MATERIAL AND METHODS: Whole-genome sequencing (WGS) was performed to detect ALDOB polymorphisms. Five web-available tools were employed to predict the effect of the site variant on the protein. Protein structure comparisons between the reference and ALDOB-modified samples were performed by SWISS-MODEL and Chimera 1.14rc, respectively. RESULTS: We identified 28 genetic variants in the ALDOB gene. When the cut-off value of minor allele frequency (MAF) of loci was 0.001 in four databases, five missense variants, including rs747604233, rs759204107, rs758242037, rs371526091 and rs77718928, were reserved for subsequent analysis. These variants were absent from the 1029 control individuals. The influence of all five variants on protein function was predicted to be damaging by the abovementioned five prediction software programs. Bioinformatics analysis demonstrated that these five missense variants were highly conserved among vertebrates. Compared to the wild-type protein structure, all five mutated protein structures showed a slight change in the chemical bond lengths of the enzyme activity domains. The combined clinical data indicate that the variant group had a significantly older age (p = 0.038), a higher level of indirect bilirubin (IDBIL, p = 0.033), and lower counts of white blood cells (WBCs, p = 7.38E-05) and platelets (PLTs, p = 0.018) than the wild-type group. CONCLUSIONS: This is the first study to examine the associations between ALDOB polymorphisms and ICP disease in 249 Chinese patients with ICP. Our present study expands the understanding of the pathogenesis of ICP.