Downregulation of miR-192 Alleviates Oxidative Stress-Induced Porcine Granulosa Cell Injury by Directly Targeting Acvr2a

Identification of 8 candidate microsatellite instability loci in colorectal cancer and validation of the ACVR2A mechanism in the tumor progression

This study probes the utility of biomarkers for microsatellite instability (MSI) detection and elucidates the molecular dynamics propelling colorectal cancer (CRC) progression. We synthesized a primer panel targeting 725 MSI loci, informed by The Cancer Genome Atlas (TCGA) and ancillary databases, to construct an amplicon library for next-generation sequencing (NGS). K-means clustering facilitated the distillation of 8 prime MSI loci, including activin A receptor type 2A (ACVR2A). Subsequently, we explored ACVR2A's influence on CRC advancement through in vivo tumor experiments and hematoxylin-eosin (HE) staining. Transwell assays gauged ACVR2A's role in CRC cell migration and invasion, while colony formation assays appraised cell proliferation. Western blotting illuminated the impact of ACVR2A suppression on CRC's PI3K/AKT/mTOR pathway protein expressions under hypoxia. Additionally, ACVR2A's influence on CRC-induced angiogenesis was quantified via angiogenesis assays. K-means clustering of NGS data pinpointed 32 MSI loci specific to tumor and DNA mismatch repair deficiency (dMMR) tissues. ACVR2A emerged as a pivotal biomarker, discerning MSI-H tissues with 90.97% sensitivity. A curated 8-loci set demonstrated 100% sensitivity and specificity for MSI-H detection in CRC. In vitro analyses corroborated ACVR2A's critical role, revealing its suppression of CRC proliferation, migration, and invasion. Moreover, ACVR2A inhibition under CRC-induced hypoxia markedly escalated MMP3, CyclinA, CyclinD1, and HIF1α protein expressions, alongside angiogenesis, by triggering the PI3K/AKT/mTOR cascade. The 8-loci ensemble stands as the optimal marker for MSI-H identification in CRC. ACVR2A, a central element within this group, deters CRC progression, while its suppression amplifies PI3K/AKT/mTOR signaling and angiogenesis under hypoxic stress.

Characterizing structural variants based on graph-genotyping provides insights into pig domestication and local adaption

Structural variants (SVs), such as deletions (DELs) and insertions (INSs), contribute substantially to pig genetic diversity and phenotypic variation. Using a library of SVs discovered from long-read primary assemblies and short-read sequenced genomes, we map pig genomic SVs with a graph-based method for re-genotyping SVs in 402 genomes. Our results demonstrate that those SVs harboring specific trait-associated genes may greatly shape pig domestication and local adaptation. Further characterization of SVs reveals that some population-stratified SVs may alter the transcription of genes by affecting regulatory elements. We identify that the genotypes of two DELs (296-bp DEL, chr7: 52,172,101-52,172,397; 278-bp DEL, chr18: 23,840,143-23,840,421) located in muscle-specific enhancers are associated with the expression of target genes related to meat quality (FSD2) and muscle fiber hypertrophy (LMOD2 and WASL) in pigs. Our results highlight the role of SVs in domestic porcine evolution, and the identified candidate functional genes and SVs are valuable resources for future genomic research and breeding programs in pigs.

GWAS of Reproductive Traits in Large White Pigs on Chip and Imputed Whole-Genome Sequencing Data

Total number born (TNB), number of stillborn (NSB), and gestation length (GL) are economically important traits in pig production, and disentangling the molecular mechanisms associated with traits can provide valuable insights into their genetic structure. Genotype imputation can be used as a practical tool to improve the marker density of single-nucleotide polymorphism (SNP) chips based on sequence data, thereby dramatically improving the power of genome-wide association studies (GWAS). In this study, we applied Beagle software to impute the 50 K chip data to the whole-genome sequencing (WGS) data with average imputation accuracy (R2) of 0.876. The target pigs, 2655 Large White pigs introduced from Canadian and French lines, were genotyped by a GeneSeek Porcine 50K chip. The 30 Large White reference pigs were the key ancestral individuals sequenced by whole-genome resequencing. To avoid population stratification, we identified genetic variants associated with reproductive traits by performing within-population GWAS and cross-population meta-analyses with data before and after imputation. Finally, several genes were detected and regarded as potential candidate genes for each of the traits: for the TNB trait: NOTCH2, KLF3, PLXDC2, NDUFV1, TLR10, CDC14A, EPC2, ORC4, ACVR2A, and GSC; for the NSB trait: NUB1, TGFBR3, ZDHHC14, FGF14, BAIAP2L1, EVI5, TAF1B, and BCAR3; for the GL trait: PPP2R2B, AMBP, MALRD1, HOXA11, and BICC1. In conclusion, expanding the size of the reference population and finding an optimal imputation strategy to ensure that more loci are obtained for GWAS under high imputation accuracy will contribute to the identification of causal mutations in pig breeding.