Gene expression profile based classification models of psoriasis

AbstractPsoriasis is an autoimmune disease, which symptoms can significantly impair the patient's life quality. It is mainly diagnosed through the visual inspection of the lesion skin by experienced dermatologists. Currently no cure for psoriasis is available due to limited knowledge about its pathogenesis and development mechanisms. Previous studies have profiled hundreds of differentially expressed genes related to psoriasis, however with no robust psoriasis prediction model available. This study integrated the knowledge of three feature selection algorithms that revealed 21 features belonging to 18 genes as candidate markers. The final psoriasis classification model was established using the novel Incremental Feature Selection algorithm that utilizes only 3 features from 2 unique genes, IGFL1 and C10orf99. This model has demonstrated highly stable prediction accuracy (averaged at 99.81%) over three independent validation strategies. The two marker genes, IGFL1 and C10orf99, were revealed as the upstream components of growth signal transduction pathway of psoriatic pathogenesis

Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives

Abstract Background: Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown. Findings: We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression–based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation. Conclusions: These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments

Cas14a1-Mediated Nucleic Acid Diagnostics for Spinal Muscular Atrophy

Spinal muscular atrophy (SMA) is the main genetic cause of infant death. In >95% of the patients with SMA, the disease is caused by a single hotspot pathogenic mutation: homozygous deletion of exon 7 of the survival motor neuron 1 gene (SMN1). Recently, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated protein (Cas)-based assays have been developed as a promising new option for nucleic acid detection. Here, we developed a Cas14a1-based assay combined with asymmetric PCR to establish a method for detection of the homozygous deletion of SMN1 exon 7 in SMA patients. The minimum detectable concentration of genomic DNA reached 5.26 aM with our method, and the assessment of its detection performance in 33 clinical samples revealed that the results were completely consistent with those of multiple ligation-dependent probe amplification and quantitative PCR. Thus, our novel nucleic acid diagnostics combining CRISPR/Cas14a1 and asymmetric PCR not only provides specific and sensitive testing of the deletion of SMN1 exon 7, but also holds promise for an accurate detection platform of genetic diseases and pathogens in multiple sample types

Association of diet and lifestyle factors with semen quality in male partners of Chinese couples preparing for pregnancy

Abstract Background Semen quality significantly influences conception, and its preservation is crucial for couples seeking pregnancy. We investigated dietary and lifestyle risk factors impacting semen quality. Methods A total of 466 males from the Guangzhou Women and Children’s Medical Center’s pre-pregnancy consultation clinic were recruited between January 2021 and March 2023 for inclusion. Semen analysis was performed, and diet and lifestyle data were gathered via questionnaire. Logistic regression was utilized to examine the link between diet, lifestyle variables, and semen quality. Results Smoking worsened progressive sperm motility (38.0% vs. 36.0%, t = 2.262; P = 0.049). Alcohol consumption impaired progressive motility (40.5 ± 17.8% vs. 34.7 ± 16.1%, t = 3.396; P < 0.001) and total motility (56.0% vs. 64.0%; P = 0.001). Using plastic beverage bottles for oil or seasonings lowered sperm concentrations (40.4% vs. 59.0% vs. 65.5%; P = 0.032). A sweet diet correlated with higher total sperm motility (55.0% vs. 60.0%, 62.0% vs. 63.2%; P = 0.017). Higher milk product intake improved sperm concentration (41.610 6 vs. 63.7106 vs. 66.1*106; P = 0.021) and motility (54.5% vs. 56.0% vs. 63.0%; P = 0.033). More frequent egg consumption increased semen volume (3.1 mL vs. 3.8 mL vs. 4.0 mL; P = 0.038). Roughage intake enhanced sperm concentration (160.810 6 vs. 224.6106; P = 0.027), and adequate sleep improved progressive sperm motility rate (35.4% ± 18.2% vs. 40.2 ± 16.3%, F = 3.747; P = 0.024) and total motility (52.7% vs. 61.5%; P = 0.013). The regression model showed that using plastic containers for condiments was a protective factor for semen volume (OR: 0.12; CI 0.03–0.55; P = 0.006), sperm concentration (OR: 0.001, CI 0.00–0.30; P = 0.012), and count (OR: 0.12, CI 0.03–0.48; P = 0.003). Milk and egg consumption were also protective for semen volume (OR: 0.18, CI 0.06–0.51; P = 0.001 and OR: 0.11, CI 0.03–0.55; P = 0.006, respectively), while sufficient sleep benefitted total sperm motility (OR: 0.47, CI 0.24–0.95; P = 0.034). Conclusions Smoking and drinking, type of condiment container, diet preference, sleep duration, and milk, roughage, and egg consumption may reduce semen quality

Deciphering the microRNA transcriptome of skeletal muscle during porcine development

MicroRNAs (miRNAs) play critical roles in many important biological processes, such as growth and development in mammals. Various studies of porcine muscle development have mainly focused on identifying miRNAs that are important for fetal and adult muscle development; however, little is known about the role of miRNAs in middle-aged muscle development. Here, we present a comprehensive investigation of miRNA transcriptomes across five porcine muscle development stages, including one prenatal and four postnatal stages. We identified 404 known porcine miRNAs, 118 novel miRNAs, and 101 miRNAs that are conserved in other mammals. A set of universally abundant miRNAs was found across the distinct muscle development stages. This set of miRNAs may play important housekeeping roles that are involved in myogenesis. A short time-series expression miner analysis indicated significant variations in miRNA expression across distinct muscle development stages. We also found enhanced differentiation- and morphogenesis-related miRNA levels in the embryonic stage; conversely, apoptosis-related miRNA levels increased relatively later in muscle development. These results provide integral insight into miRNA function throughout pig muscle development stages. Our findings will promote further development of the pig as a model organism for human age-related muscle disease research

Association of living environmental and occupational factors with semen quality in chinese men: a cross-sectional study

Abstract Sperm quality can be easily influenced by living environmental and occupational factors. This study aimed to discover potential semen quality related living environmental and occupational factors, expand knowledge of risk factors for semen quality, strengthen men's awareness of protecting their own fertility and assist the clinicians to judge the patient’s fertility. 465 men without obese or underweight (18.5 < BMI < 28.5 kg/m2), long-term medical history and history of drug use, were recruited between June 2020 to July 2021, they are in reproductive age (25 < age < 45 years). We have collected their semen analysis results and clinical information. Logistic regression was applied to evaluate the association of semen quality with different factors. We found that living environment close to high voltage line (283.4 × 106/ml vs 219.8 × 106/ml, Cohen d = 0.116, P = 0.030) and substation (309.1 × 106/ml vs 222.4 × 106/ml, Cohen d = 0.085, P = 0.015) will influence sperm count. Experienced decoration in the past 6 months was a significant factor to sperm count (194.2 × 106/ml vs 261.0 × 106/ml, Cohen d = 0.120, P = 0.025). Living close to chemical plant will affect semen PH (7.5 vs 7.2, Cohen d = 0.181, P = 0.001). Domicile close to a power distribution room will affect progressive sperm motility (37.0% vs 34.0%, F = 4.773, Cohen d = 0.033, P = 0.030). Using computers will affect both progressive motility sperm (36.0% vs 28.1%, t = 2.762, Cohen d = 0.033, P = 0.006) and sperm total motility (57.0% vs 41.0%, Cohen d = 0.178, P = 0.009). After adjust for potential confounding factors (age and BMI), our regression model reveals that living close to high voltage line is a risk factor for sperm concentration (Adjusted OR 4.03, 95% CI 1.15–14.18, R2 = 0.048, P = 0.030), living close to Chemical plants is a protective factor for sperm concentration (Adjusted OR 0.15, 95% CI 0.05–0.46, R2 = 0.048, P = 0.001) and total sperm count (Adjusted OR 0.36, 95% CI 0.13–0.99, R2 = 0.026, P = 0.049). Time spends on computer will affect sperm total motility (Adjusted OR 2.29, 95% CI 1.11–4.73, R2 = 0.041, P = 0.025). Sum up, our results suggested that computer using, living and working surroundings (voltage line, substation and chemical plants, transformer room), and housing decoration may association with low semen quality. Suggesting that some easily ignored factors may affect male reproductive ability. Couples trying to become pregnant should try to avoid exposure to associated risk factors. The specific mechanism of risk factors affecting male reproductive ability remains to be elucidated