Prevalence and genetic analysis of triplicated α-globin gene in Ganzhou region using high-throughput sequencing.

α-globin gene triplication carriers were not anemic in general, while some studies found that α-globin gene triplication coinherited with heterozygous ß-thalassemia may cause adverse clinical symptoms, which yet lacks sufficient evidence in large populations. In this study, we investigated the prevalence and distribution of α-globin gene triplication as well as the phenotypic characteristics of α-globin gene triplication coinherited with heterozygous ß-thalassemia in Ganzhou city, southern China. During 2021-2022, a total of 73,967 random individuals who received routine health examinations before marriage were genotyped for globin gene mutations by high-throughput sequencing. Among them, 1,443 were α-globin gene triplication carriers, with a carrier rate of 1.95%. The most prevalent mutation was αααanti3.7/αα (43.10%), followed by αααanti4.2/αα (38.12%). 42 individuals had coinherited α-globin gene triplication and heterozygous ß-thalassemia. However, they did not differ from the individuals with heterozygous ß-thalassemia and normal α-globin (αα/αα) in terms of mean corpuscular volume (MCV) and mean corpuscular hemoglobin (MCH) levels. In addition, heterogenous clinical phenotypes were found in two individuals with the same genotype. Our study established a database of Ganzhou α-globin gene triplication and provided practical advice for the clinical diagnosis of α-globin gene triplication.

Cluster analysis and potential influencing factors of boars with different fertility.

The fertility of boars is intimately tied to the pig farm's economic benefits. This study aimed to rapidly categorize boars of different fertility and investigate the factors influencing the categorization using the production data in a large pig farm in northern China, including 11,163 semen collection records of Yorkshire boars (215), 11,163 breeding records and 8770 records of farrowing performance of Yorkshire sows (4505), as well as 4720 records of selection indices (sire line index and dam line index) for boars and sows (215 and 4505) between 2017 and 2020. The boar population was classified by two-step cluster analysis, followed by factor analysis to minimize the dimensionality of data variables and eliminate multicollinearity, and then using ordinal logistic regression model to investigate the risk variables impacting boar fertility categorization. Results showed that the two-step clustering divided the 215 boars into three subgroups: high-fertility (n = 61, 28.4%), medium-fertility (n = 127, 59.1%) and low-fertility (n = 27, 12.6%). The high-fertility boars were shown to be substantially greater than the medium-fertility or low-fertility boars (p < 0.05) in average total litter size, number of born alive, and number of healthy piglets of mated sows. Compared with low-fertility boars, the high-fertility boars were also significantly higher (p < 0.05) in the pregnancy rate and farrowing rate of mated sows. However, the three boar subgroups showed no difference (p > 0.05) in semen quality information (average sperm motility, average sperm density, and average sperm volume). Collinearity diagnosis indicated severe multicollinearity among the 20 data variables, which were reduced to 8 factor variables (factors 1-8) by factor analysis, and further collinearity diagnosis exhibited no multicollinearity among the 8 factor variables. Ordered logistic regression analysis revealed a significant and positive correlation (p < 0.05) of boar fertility with factor 2 (average total litter size, number of born alive, number of healthy piglets), factor 4 (average number of weak piglets and average weak piglet rate), factor 6 (sire line index of boars and dam line index of boars), factor 8 (pregnancy rate and farrowing rate), highlighting factor 2 as the most important factor influencing the classification of boar fertility. Our results indicate that the two-step cluster analysis can be used as a simple and effective method to screen boars with different fertility and that farm producers should pay attention to the recording of the reproductive performance of the mated sows due to its role as the risk factor for classification of boar fertility.

Identifying Candidate Genes for Short Gestation Length Trait in Chinese Qingping Pigs by Whole-Genome Resequencing and RNA Sequencing.

Gestation length is a complex polygenic trait that affects pig fetal development. The Qingping (QP) pig, a Chinese native black pig breed, is characterized by short gestation length. However, the genetic architecture of short gestation length is still not clear. The present study aimed to explore the genetic architecture of short gestation length in QP pigs. In this study, selective sweep analyses were performed to detect selective sweep signatures for short gestation length traits between 100 QP pigs and 219 pigs from 15 other breeds. In addition, differentially expressed genes for the short gestation length between QP pigs and Large White pigs were detected by RNA sequencing. Comparing candidate genes from these methods with known genes for preterm birth in the database, we obtained 111 candidate genes that were known preterm birth genes. Prioritizing other candidate genes, 839 novel prioritized candidate genes were found to have significant functional similarity to preterm birth genes. In particular, we highlighted EGFR, which was the most prioritized novel candidate relative to preterm birth genes. Experimental validations in placental and porcine trophectoderm cells suggest that EGFR is highly expressed in the QP pigs with short gestation length and could regulate the NF-κΒ pathway and downstream expression of PTGS2. These findings comprehensively identified candidate genes for short gestation length trait at the genomic and transcriptomic levels. These candidate genes provide an important new resource for further investigation and genetic improvement of gestation length.

A Whole Genome Sequencing-Based Genome-Wide Association Study Reveals the Potential Associations of Teat Number in Qingping Pigs.

Teat number plays an important role in the reproductive performance of sows and the growth of piglets. However, the quantitative trait loci (QTLs) and candidate genes for the teat number-related traits in Qingping pigs remain unknown. In this study, we performed GWAS based on whole-genome single-nucleotide polymorphisms (SNPs) and insertions/deletions (Indels) for the total number of teats and five other related traits in 100 Qingping pigs. SNPs and Indels of all 100 pigs were genotyped using 10× whole genome resequencing. GWAS using General Linear Models (GLM) detected a total of 28 SNPs and 45 Indels as peak markers for these six traits. We also performed GWAS for the absolute difference between left and right teat number (ADIFF) using Fixed and random model Circulating Probability Unification (FarmCPU). The most strongly associated SNP and Indel with a distance of 562,788 bp were significantly associated with ADIFF in both GLM and FarmCPU models. In the 1-Mb regions of the most strongly associated SNP and Indel, there were five annotated genes, including TRIML1, TRIML2, ZFP42, FAT1 and MTNR1A. We also highlighted TBX3 as an interesting candidate gene for SSC14. Enrichment analysis of candidate genes suggested the Wnt signaling pathway may contribute to teat number-related traits. This study expanded significant marker-trait associations for teat number and provided useful molecular markers and candidate genes for teat number improvement in the breeding of sows.

miR-132-3p Modulates DUSP9-Dependent p38/JNK Signaling Pathways to Enhance Inflammation in the Amnion Leading to Labor.

Labor is a process of inflammation and hormonal changes involving both fetal and maternal compartments. MicroRNA-132-3p (miR-132-3p) has been reported to be involved in the development of inflammation-related diseases. However, little is known about its potential role in labor onset. This study aimed to explore the mechanism of miR-132-3p in amnion for labor initiation. In the mouse amnion membranes, the expression of miR-132-3p was found to increase gradually during late gestation. In human amniotic epithelial cell line (WISH), upregulation of miR-132-3p was found to increase proinflammatory cytokines and cyclooxygenase 2 (COX2) as well as prostaglandin E2 (PGE2), which was suppressed by miR-132-3p inhibitor. Dual-specificity phosphatase 9 (DUSP9) was identified as a novel target gene of miR-132-3p, which could be negatively regulated by miR-132-3p. DUSP9 was present in the mouse amnion epithelial cells, with a decrease in its abundance at 18.5 days post coitum (dpc) relative to 15.5 dpc. Silencing DUSP9 was found to facilitate the expression of proinflammatory cytokines and COX2 as well as PGE2 secretion in WISH cells, which could be attenuated by p38 inhibitor SB203580 or JNK inhibitor SP600125. Additionally, intraperitoneal injection of pregnant mice with miR-132-3p agomir not only caused preterm birth, but also promoted the abundance of COX2 as well as phosphorylated JNK and p38 levels, and decreased DUSP9 level in mouse amnion membranes. Collectively, miR-132-3p might participate in inflammation and PGE2 release via targeting DUSP9-dependent p38 and JNK signaling pathways to cause preterm birth.

Elucidating a molecular mechanism that the deterioration of porcine meat quality responds to increased cortisol based on transcriptome sequencing.

Stress response is tightly linked to meat quality. The current understanding of the intrinsic mechanism of meat deterioration under stress is limited. Here, male piglets were randomly assigned to cortisol and control groups. Our results showed that when serum cortisol level was significantly increased, the meat color at 1 h postmortem, muscle bundle ratio, apoptosis rate, and gene expression levels of calcium channel and cell apoptosis including SERCA1, IP3R1, BAX, Bcl-2, and Caspase-3, were notably increased. However, the value of drip loss at 24 h postmortem and serum CK were significantly decreased. Additionally, a large number of differentially expressed genes (DEGs) in GC regulation mechanism were screened out using transcriptome sequencing technology. A total of 223 DEGs were found, including 80 up-regulated genes and 143 down-regulated genes. A total of 204 genes were enriched in GO terms, and 140 genes annotated into in KEGG database. Numerous genes were primarily involved in defense, inflammatory and wound responses. This study not only identifies important genes and signalling pathways that may affect the meat quality but also offers a reference for breeding and feeding management to provide consumers with better quality pork products.