Publications by authors named "JunYa Li"

The genetic improvement of beef cattle breeds is crucial for the advancement of the beef cattle industry. Whole-genome resequencing technology has been widely applied in genetic breeding as well as research on selection signatures in beef cattle. In this study, 20× whole-genome resequencing was performed on 282 Angus cattle from the Ningxia region, and a high-quality dataset encompassing extensive genomic variations across the entire genome was constructed.

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Background: Integrating multi-layered information can enhance the accuracy of genomic prediction for complex traits. However, the improvement and application of effective strategies for genomic prediction (GP) using multi-omics data remains challenging.

Methods: We generated 11 feature sets for sequencing variants from genomics, transcriptomics, metabolomics, and epigenetics data in beef cattle, then we assessed the contribution of functional variants using genomic restricted maximum likelihood (GREML).

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Dysregulation of histone supply is implicated in various cancers, including lung adenocarcinoma (LUAD), although the underlying mechanisms remain poorly understood. Here, we demonstrate that knockout of Fbxo45 in mouse alveolar epithelial type 2 (AT2) cells leads to spontaneous LUAD. Our findings reveal that FBXO45 is a novel cell-cycle-regulated protein that is degraded upon phosphorylation by CDK1 during the S/G2 phase.

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Background/objectives: There is a considerable global population of beef cattle, with numerous small-scale groups. Establishing separate reference groups for each breed in breeding practices is challenging, severely limiting the genome selection (GS) application. Combining data from multiple populations becomes particularly attractive and practical for small-scale populations, offering increased reference population size, operational ease, and data sharing.

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Background: Genomic mating (GM) can effectively control the growth rate of inbreeding in population and achieve long-term sustainable genetic progress. However, the design of GM method and assessment of its effects during long-term selection have not been fully explored in beef cattle breeding.

Results: In this study, we constructed a simulated population based on the real genotypes of Huaxi cattle, where five generations of simulated breeding were carried out using the genomic optimal contribution selection (GOCS), genetic algorithms strategy and three traditional mating strategies.

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The KRAS/ERK pathway is crucial in cancer progression and chemotherapy resistance, yet its upstream regulatory mechanism remains elusive. We identified MSI2 as a new promoter of chemotherapy resistance in cancers. MSI2 directly binds to a specific class of mature miRNAs by recognizing the 'UAG' motif and interacts with the essential effector AGO2, highlighting MSI2 as a novel regulatory factor within the miRNA pathway.

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Article Synopsis
  • Copy number variation (CNV) contributes to genetic diversity in mammals and affects complex traits, particularly in Pingliang red cattle, known for tender meat and superior marbling quality.
  • Researchers created a genome-wide CNV map for these cattle, identifying 755 CNV regions that represent about 3.24% of the cattle's genome, including 270 breed-specific CNVRs linked to critical traits.
  • The study's findings suggest potential candidate genes related to meat quality traits, providing insights that could enhance breeding programs aimed at improving the meat quality of Pingliang red cattle.
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Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G × E). The inclusion of G × E in genome-wide association analyses is essential to understand animal environmental adaptations and improve the efficiency of breeding decisions. Here, we systematically investigated the G × E of growth traits (including weaning weight, yearling weight, 18-month body weight, and 24-month body weight) with environmental factors (farm and temperature) using genome-wide genotype-by-environment interaction association studies (GWEIS) with a dataset of 1350 cattle.

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Extensive application of rare earth element oxide nanoparticles (REE NPs) has raised a concern over the possible toxic health effects after human exposure. Once entering the body, REE NPs are primarily processed by phagocytes in particular macrophages and undergo biotic phosphate complexation in lysosomal compartment. Such biotransformation affects the target organs and in vivo fate of REE NPs after escaping the lysosomes.

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Compensatory growth (CG) is a physiological response that accelerates growth following a period of nutrient limitation, with the potential to improve growth efficiency and meat quality in cattle. However, the underlying molecular mechanisms remain poorly understood. In this study, 60 Huaxi cattle were divided into one ad libitum feeding (ALF) group and two restricted feeding groups (75% restricted, RF75; 50% restricted, RF50) undergoing a short-term restriction period followed by evaluation of CG.

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Article Synopsis
  • The study focused on using advanced models like BayesR and GBLUP with genetic relationship matrices to find the most effective method for multi-breed genomic selection in three beef cattle breeds.
  • Results showed that BayesR generally provided higher prediction accuracy compared to GBLUP, particularly when using whole-genome sequencing data, with notable improvements in predicting breeding values in the evaluated cattle breeds.
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Article Synopsis
  • * A comprehensive whole-genome analysis was performed using SNP chip data from 17 bovine breeds, revealing unique genetic features and a hybrid lineage for Pingliang red cattle, distinguishing it from other breeds.
  • * The study uncovers that Pingliang red cattle share genetic ties with Qinchuan cattle and have undergone gene exchanges with South Devon and Red Angus breeds, with significant contributions of East Asian taurine and Chinese indicine in their ancestry.
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Coat color and birth weight, as easily selected traits in cattle, play important roles in cattle breeding. Therefore, we carried out a genome-wide association study on birth weight and coat color to identify loci or potential linkage regions in 233 Simmental × Holstein crossbred beef cattle. The results revealed that nine SNPs were significantly associated with coat color (, , , , , , , , and ), and these were in , , , , and on BTA5.

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Article Synopsis
  • * The researchers identified over 112,000 CNVs and conducted a genome-wide association study (GWAS) on six meat quality traits, finding 12 significant CNV segments linked to eight candidate genes.
  • * One notable discovery was a 34 kb duplication associated with meat color, located within the keratin gene family, which can enhance breeding strategies for improving meat quality traits.
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Article Synopsis
  • The study investigates fetal cartilage development in bovine by isolating chondrocytes from 90-day-old fetuses and analyzing gene expression using ATAC-seq and RNA-seq.
  • Researchers identified 9,686 open chromatin regions, with 45% located in promoter areas, and conducted GO and KEGG analyses highlighting processes related to growth and development.
  • Key transcription factors associated with cartilage development, including FOS, FOSL2, and NFY, were identified, contributing to a better understanding of the regulatory mechanisms in bovine cartilage formation.
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Caffeic acid phenethyl ester (CAPE) is one of the main active ingredients of propolis with good antitumor activities. However, the potential effects of CAPE on the glycolysis and lipid metabolism of tumor cells are unclear. Here, the anti-tumor effects of CAPE on MDA-MB-231 cells in an inflammatory microenvironment stimulated with lipopolysaccharide (LPS) were studied by estimating the inflammatory mediators and the key factors of glycolysis and lipid metabolism.

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Skeletal muscles consist of heterogeneous fibers with various contractile and metabolic properties that affect meat quality. The size of muscle fibers contributes to muscle mass and myopathy. Thus, improved understanding of the expression patterns underlying fiber size might open possibilities to change them using genetic methods.

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The optimized selection method can maximize the genetic gain in offspring under the premise of controlling the inbreeding level of the population. At present, genetic gain has been largely improved by using genomic selection in multiple farm animals. However, the design of the optimal selection method and assessment of its effects during long-term selection in beef cattle breeding are yet to be fully explored.

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Enveloped viruses have been the leading causative agents of viral epidemics in the past decade, including the ongoing coronavirus disease 2019 outbreak. In epidemics caused by enveloped viruses, direct contact is a common route of infection, while indirect transmissions through the environment also contribute to the spread of the disease, although their significance remains controversial. Bridging the knowledge gap regarding the influence of interfacial interactions on the persistence of enveloped viruses in the environment reveals the transmission mechanisms when the virus undergoes mutations and prevents excessive disinfection during viral epidemics.

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Background: A detailed understanding of genetic variants that affect beef merit helps maximize the efficiency of breeding for improved production merit in beef cattle. To prioritize the putative variants and genes, we ran a comprehensive genome-wide association studies (GWAS) analysis for 21 agronomic traits using imputed whole-genome variants in Simmental beef cattle. Then, we applied expression quantitative trait loci (eQTL) mapping between the genotype variants and transcriptome of three tissues (longissimus dorsi muscle, backfat, and liver) in 120 cattle.

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We have been effectively protected by disposable propylene face masks during the COVID-19 pandemic; however, they may pose health risks due to the release of fine particles and chemicals. We measured micro/nanoparticles and organic chemicals in disposable medical masks, surgical masks, and (K)N95 respirators. In the breathing-simulation experiment, no notable differences were found in the total number of particles among mask types or between breathing intensities.

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Incorporating the genotypic and phenotypic of the correlated traits into the multi-trait model can significantly improve the prediction accuracy of the target trait in animal and plant breeding, as well as human genetics. However, in most cases, the phenotypic information of the correlated and target trait of the individual to be evaluated was null simultaneously, particularly for the newborn. Therefore, we propose a machine learning framework, MAK, to improve the prediction accuracy of the target trait by constructing the multi-target ensemble regression chains and selecting the assistant trait automatically, which predicted the genomic estimated breeding values of the target trait using genotypic information only.

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Locating the genetic variation of important livestock and poultry economic traits is essential for genetic improvement in breeding programs. Identifying the candidate genes for the productive ability of Huaxi cattle was one crucial element for practical breeding. Based on the genotype and phenotype data of 1,478 individuals and the RNA-seq data of 120 individuals contained in 1,478 individuals, we implemented genome-wide association studies (GWAS), transcriptome-wide association studies (TWAS), and Fisher's combined test (FCT) to identify the candidate genes for the carcass trait, the weight of longissimus dorsi muscle (LDM).

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Fat deposition traits are influenced by genetics and environment, which affect meat quality, growth rate, and energy metabolism of domestic animals. However, at present, the molecular mechanism of fat deposition is not entirely understood in beef cattle. Therefore, the current study conducted transcriptomics and lipid metabolomics analysis of subcutaneous, visceral, and abdominal adipose tissue (SAT, VAT, and AAT) of Huaxi cattle to investigate the differences among these adipose tissues and systematically explore how candidate genes interact with metabolites to affect fat deposition.

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Genomic prediction (GP) based on haplotype alleles can capture quantitative trait loci (QTL) effects and increase predictive ability because the haplotypes are expected to be in linkage disequilibrium (LD) with QTL. In this study, we constructed haploblocks using LD-based and the fixed number of single nucleotide polymorphisms (fixed-SNP) methods with Illumina BovineHD chip in beef cattle. To evaluate the performance of different haplotype block partitioning methods, we constructed haploblocks based on LD thresholds (from  > 0.

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