Genetic improvement of local rabbit breeds using modern approaches such as marker-assisted selection requires accurate and precise information about marker‒trait associations in animals with different genetic backgrounds. Therefore, this study was designed to estimate the association between two mutations located in the Neuropeptide Y (NPY, g.1778G > C) and Phosphoglycerate Mutase 2 (PGAM2, c.195 C > T) genes in New Zealand White (NZW), Baladi (BR), and V-line rabbits. The first mutation was genotyped using high-resolution melting, and the second mutation was genotyped using the PCR-RFLP method. The results revealed significant associations between the NPY mutation and body weight at 10 (V-line) and 12 weeks of age (NZW, BR, and V-line), body weight gain (BWG) from 10 to 12 weeks of age (BR), BWG from 6 to 12 weeks of age (NZW, BR, and V-line), average daily gain (NZW, BR, and V-line, and BR), growth rate (GR) from 8 to10 weeks (V-line), 10 to 12 weeks (BR), and GR from 6 to 12 weeks of age (BR, and V-line). The PGAM2 mutation was associated with body weight at 10 (V-line) and 12 (NZW, and V-line) weeks of age, with significant positive additive effects at 12 weeks of age in all breeds, and was associated with BWG from 8 to 10 and 10 to 12 in BR, and BWG from 6 to 12 weeks of age (NZW, and BR), and average daily gain (NZW, and BR), and was associated with GR form 8 to 10 weeks (BR), from10 to 12 weeks (BR, and V-line) and from 6 to 12 weeks (BR). The results highlighted the importance of the two mutations in growth development, and the possibility of considering them as candidate genes for late growth in rabbits.

The uncertainty resulting from missing genotypes in low-coverage whole-genome sequencing (LCWGS) data complicates genotype imputation. The aim of this study is to find out an optimal strategy for accurately imputing LCWGS data and assess its effectiveness for genomic prediction (GP) and genome-wide association study (GWAS) on economically important traits of Large White pigs. The LCWGS data of 1 423 Large White pigs were imputed using three different strategies: (1) using the high-coverage whole-genome sequencing (HCWGS) of 30 key progenitors as the reference panel (Ref_LG); (2) mixing HCWGS of key progenitors with LCWGS (Mix_HLG) and (3) self-imputation in LCWGS (Within_LG). Additionally, to compare the imputation effects of LCWGS, we also imputed SNP chip data of 1 423 Large White pigs to the whole-genome sequencing level using the reference panel consisting of key progenitors (Ref_SNP). To evaluate effects of the imputed sequencing data, we compared the accuracies of GP and statistical power of GWAS for four reproductive traits based on the chip data, sequencing data imputed from chip data and LCWGS data using an optimal strategy. The average imputation accuracies of the Within_LG, Ref_LG and Mix_HLG were 0.9893, 0.9899 and 0.9875, respectively, which were higher than that of the Ref_SNP (0.8522). Using the imputed sequencing data from LCWGS with the Ref_LG imputation strategy, the accuracies of GP for four traits improved by approximately 0.31-1.04% compared to the chip data, and by 0.7-1.05% compared to the imputed sequencing data from chip data. Furthermore, by using the sequence data imputed from LCWGS with the Ref_LG, 18 candidate genes were identified to be associated with the four reproductive traits of interest in Large White pigs: total number of piglets born - EPC2, MBD5, ORC4 and ACVR2A; number of piglets born healthy - IKBKE; total litter weight of piglets born alive - HSPA13 and CPA1; gestation length - GTF2H5, ITGAV, NFE2L2, CALCRL, ITGA4, STAT1, HOXD10, MSTN, COL5A2 and STAT4. With the exception of EPC2, ORC4, ACVR2A and MSTN, others represent novel candidates. Our findings can provide a reference for the application of LCWGS data in livestock and poultry.

The breeding of high-quality beef cattle breeds is crucial for the development of animal husbandry, and whole-genome resequencing is widely applicated in the field of molecular breeding. Advantages in growth and reproductive traits exist in Pinan cattle compared with other cattle breeds, but there is limited research on its genomic mechanism. Using whole-genome resequencing, the genetic structure and genomic selection signatures in Pinan cattle were investigated in this study. Phylogenetic, cluster, and admixture analysis results indicated that Pinan cattle have a closer genetic relationship with Kholmogory cattle and China north cattle breeds. Through a selective sweep strategy, 207 and 54 candidate genes related to growth and reproduction and immunity, respectively, were identified in the Pinan cattle population. Given the crucial role of the glutamate-cysteine ligase catalytic (GCLC) gene in muscle antioxidative defense, the high frequency of allele T of the GCLC c.429 C>T locus in the Pinan cattle population might partially contribute to the advantages of Pinan cattle in growth performance. This study laid the foundation for the genetic improvement in Chinese local beef cattle and provide background for the studies on the growth and development of Pinan cattle.

UNASSIGNED: Thyroid cancer is the most common malignancy of the endocrine system. PANoptosis is a specific form of inflammatory cell death. It mainly includes pyroptosis, apoptosis and necrotic apoptosis. There is increasing evidence that PANoptosis plays a crucial role in tumour development. However, no pathogenic mechanism associated with PANoptosis in thyroid cancer has been identified.
UNASSIGNED: Based on the currently identified PANoptosis genes, a dataset of thyroid cancer patients from the GEO database was analysed. To screen the common differentially expressed genes of thyroid cancer and PANoptosis. To analyse the functional characteristics of PANoptosis-related genes (PRGs) and screen key expression pathways. The prognostic model was established by LASSO regression and key genes were identified. The association between hub genes and immune cells was evaluated based on the CIBERSORT algorithm. Predictive models were validated by validation datasets, immunohistochemistry as well as drug-gene interactions were explored.
UNASSIGNED: The results showed that eight key genes (NUAK2, TNFRSF10B, TNFRSF10C, TNFRSF12A, UNC5B, and PMAIP1) exhibited good diagnostic performance in differentiating between thyroid cancer patients and controls. These key genes were associated with macrophages, CD4+ T cells and neutrophils. In addition, PRGs were mainly enriched in the immunomodulatory pathway and TNF signalling pathway. The predictive performance of the model was confirmed in the validation dataset. The DGIdb database reveals 36 potential therapeutic target drugs for thyroid cancer.
UNASSIGNED: Our study suggests that PANoptosis may be involved in immune dysregulation in thyroid cancer by regulating macrophages, CD4+ T cells and activated T and B cells and TNF signalling pathways. This study suggests potential targets and mechanisms for thyroid cancer development.

Tunchang pigs, mainly distributed throughout Hainan Province of China, are well-known for their superior meat quality, crude feed tolerance, and adaptability to high temperatures and humidity. Runs of homozygosity (ROH) can provide valuable information about the inbreeding coefficient in individuals and selection signals that may reveal candidate genes associated with key functional traits. Runs of heterozygosity (ROHet) are commonly associated with balance selection, which can help us understand the adaptive evolutionary history of domestic animals. In this study, we investigated ROHs and ROHets in 88 Tunchang pigs. We also compared the estimates of inbreeding coefficients in individuals calculated based on four methods. In summary, we detected a total of 16 ROH islands in our study, and 100 genes were found within ROH regions. These genes were correlated with economically important traits such as reproduction (e.g., SERPIND1, HIRA), meat quality (e.g., PI4KA, TBX1), immunity (e.g., ESS2, RANBP1), adaption to heat stress (TXNRD2 and DGCR8), and crude food tolerance (TRPM6). Moreover, we discovered 18 ROHet islands harbouring genes associated with reproduction (e.g., ARHGEF12, BMPR2), immune system (e.g., BRD4, DNMT3B). These findings may help us design effective breeding and conservation strategies for this unique breed.

BACKGROUND: Asthma is a heterogeneous disorder. This study aimed to identify changes in gene expression and molecular mechanisms associated with moderate to severe asthma.
METHODS: Differentially expressed genes (DEGs) were analyzed in GSE69683 dataset among moderate asthma and its controls as well as between severe asthma and moderate asthma. Key module genes were identified via co-expression analysis, and the molecular mechanism of the module genes was explored through enrichment analysis and gene set enrichment analysis (GSEA). GSE89809 was used to verify the characteristic genes related to moderate and severe asthma.
RESULTS: Accordingly, 2540 DEGs were present between moderate asthma and the control group, while 6781 DEGs existed between severe asthma and moderate asthma. These genes were identified into 14 co-expression modules. Module 7 had the highest positive correlation with severe asthma and was recognized to be a key module by STEM. Enrichment analysis demonstrated that the module genes were mainly involved in oxidative stress-related signaling pathways. The expression of HSPA1A, PIK3CG and PIK3R6 was associated with moderate asthma, while MAPK13 and MMP9 were associated with severe asthma. The AUC values were verified by GSE89809. Additionally, 322 drugs were predicted to target five genes.
CONCLUSIONS: These results identified characteristic genes related to moderate and severe asthma and their corresponding molecular mechanisms, providing a basis for future research.

UNASSIGNED: The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments.
UNASSIGNED: Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1).
UNASSIGNED: We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Recently, elevated seawater temperatures have resulted numerous adverse effects, including significant mortality among bivalves. The dwarf surf clam, Mulinia lateralis, is considered a valuable model species for bivalve research due to its rapid growth and short generation time. The successful cultivation in laboratory setting throughout its entire life cycle makes it an ideal candidate for exploring the potential mechanisms underlying bivalve responses to thermal stress. In this study, a total of 600 clams were subjected to a 17-day thermal stress experiment at a temperature of 30 °C which is the semi-lethal temperature for this species. Ninety individuals who perished initially were classified as heat-sensitive populations (HSP), while 89 individuals who survived the experiment were classified as heat-tolerant populations (HTP). Subsequently, 179 individuals were then sequenced, and 21,292 single nucleotide polymorphisms (SNPs) were genotyped for downstream analysis. The heritability estimate for survival status was found to be 0.375 ± 0.127 suggesting a genetic basis for thermal tolerance trait. Furthermore, a genome-wide association study (GWAS) identified three SNPs and 10 candidate genes associated with thermal tolerance trait in M. lateralis. These candidate genes were involved in the ETHR/EHF signaling pathway and played pivotal role in signal sensory, cell adhesion, oxidative stress, DNA damage repair, etc. Additionally, qPCR results indicated that, excluding MGAT4A, ZAN, and RFC1 genes, all others exhibited significantly higher expression in the HTP (p < 0.05), underscoring the critical involvement of the ETHR/EHF signaling pathway in M. lateralis\' thermal tolerance. These results unveil the presence of standing genetic variations associated with thermal tolerance in M. lateralis, highlighting the regulatory role of the ETHR/EHF signaling pathway in the bivalve\'s response to thermal stress, which contribute to comprehension of the genetic basis of thermal tolerance in bivalves.

Maize (Zea mays L.), a staple food and significant economic crop, is enriched with riboflavin, micronutrients and other compounds that are beneficial for human health. As emphasis on the nutritional quality of crops increases maize research has expanded to focus on both yield and quality. This study exploreed the genetic factors influencing micronutrient levels in maize kernels through a comprehensive genome-wide association study (GWAS). We utilized a diverse panel of 244 inbred maize lines and approximately 3 million single nucleotide polymorphisms (SNPs) to investigate the accumulation of essential and trace elements including cadmium (Cd), cobalt (Co), copper (Cu), nickel (Ni), selenium (Se) and zinc (Zn). Our analysis identified 842 quantitative trait loci (QTLs), with 12 QTLs shared across multiple elements and pinpointed 524 potential genes within a 100 kb radius of these QTLs. Notably ZmHMA3 has emerged as a key candidate gene previously reported to influence the Cd accumulation. We highlighted ten pivotal genes associated with trace element transport including those encoding heavy metal ATPases, MYB transcription factors, ABC transporters and other crucial proteins involved in metal handling. Additionally, haplotype analysis revealed that eight inbred linesaccumulated relatively high levels of beneficial elements while harmful elements were minimized. These findings elucidate the genetic mechanisms underlying trace element accumulation in maize kernels and provide a foundation for the breeding of nutritionally enhanced maize varieties.

Genome-wide association studies (GWAS) are employed to identify genomic regions and candidate genes associated with several traits. The aim of this study was to perform a GWAS to identify causative variants and genes associated with milk yield, frame, and udder conformation traits in Gir dairy cattle. Body conformation traits were classified as \"frame,\" and \"udder\" traits for this study. After genotyping imputation and quality control 42,105 polymorphisms were available for analyses and 24,489 cows with pedigree information had phenotypes. First, P-value was calculated based on the variance of the prediction error of the SNP-effects on the first iteration. After that, 2 more iterations were performed to carry out the weighted single-step genome-wide association methodology, performed using genomic moving windows defined based on linkage disequilibrium. The significant SNPs and top 10 windows explaining the highest percentage of additive genetic variance were selected and used for QTL and gene annotation. The variants identified in our work overlapped with QTLs from the animal QTL database on chromosomes 1 to 23, except for chromosome 4. The Gir breed is less studied than the Holstein breed and as such the animal QTL database is biased to Holstein results. Hence it is noteworthy that our GWAS had similarities with previously described QTLs. These previously known QTLs were related to milk yield, body height, rump angle, udder width, and udder depth. In total, 5 genes were annotated. Of these genes, FAM13A and CMSS1 had been previously related to bone and carcass weight in cattle.