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Yanlan Liu

Publications and source records attributed to Yanlan Liu.

2 recordsLinked to original sources

Integrated Multi-Omics Analysis Reveals the Genetic Basis of Phenotypic Variation in Tibetan Sheep.

Body size is a key economic trait influencing the profitability of farmed animals. This study used genome-wide association studies (GWAS) to identify five single nucleotide polymorphisms (SNPs) significantly associated with body size in the Tibetan sheep population, advancing molecular breeding and providing a basis for genomic selection. These SNPs are located within five candidate genes. SNaPshot validated GWAS results, demonstrating significant correlations between candidate SNPs and body size traits in Tibetan sheep. Concurrently, hematoxylin and eosin staining, alongside muscle fiber analysis, confirmed pronounced morphological differences in muscle tissue between sheep of varying conformation. Therefore, transcriptome and proteomics were performed on the longest dorsi muscle from large and small Tibetan sheep of both sexes. The transcriptome, together with weighted gene co-expression network analysis (WGCNA), identified VEPH1 and PRKG1 as core genes regulating body characteristics in Tibetan sheep through their involvement in the PI3K-Akt signaling pathway and pathways related to fat deposition. The integrative analyses demonstrated significantly different expression of CARNS1 and CRYAB at both transcriptional and protein levels between the muscles of large- and small-sized Tibetan sheep of both sexes, suggesting their importance in body size traits by influencing muscle morphology. This study provides valuable genomic resources that advance sheep genetics research.

GWAS

Integrated bulk and single-cell RNA sequencing reveals a prognostic neuro-mimicry signature in papillary thyroid carcinoma.

BACKGROUND: Cancer cells can acquire neuron-like characteristics ("neural mimicry") to promote progression. However, the role of specific ion channel genes in Papillary Thyroid Carcinoma (PTC) and their clinical significance remains unclear. METHODS: We included transcriptomic data from 521 PTC patients in the TCGA cohort. A neuron-specific gene set was used to screen for potential targets. We constructed a prognostic model using LASSO logistic regression. To verify the cellular origin of the signature, we performed single-cell RNA sequencing (scRNA-seq) analysis on the GSE184362 dataset. RESULTS: We established an 8-gene signature involving KCNN4, KCNN1, KCNT2, SNAP25, KCNK16, GABRG1, GABRG2, and GABRB2. The model demonstrated good predictive performance for lymph node metastasis, with an AUC of 0.721 (95% CI 0.677-0.765). Single-cell analysis of seven integrated tumor samples (N = 65,744 cells) confirmed that GABRB2 was specifically enriched in malignant thyrocytes (EPCAM+/KRT18+) at 200-fold higher detection rates than immune cells (20.0% vs. 0.1%, P ≈ 0), supporting tumor-intrinsic neural mimicry. High-risk patients showed immunosuppressive features with altered immune cell infiltration patterns. CONCLUSION: This study identifies a malignant cell-intrinsic signature for predicting PTC prognosis. Validated by single-cell data, our findings suggest that targeting ion channels may represent a potential therapeutic strategy for modulating neuro-immune interactions in thyroid cancer, pending experimental validation.

GABRB2