Zhuangbiao Zhang

A telomere-to-telomere genome of Holstein cattle resolves chromosome-end architecture and the genetic basis of telomere length

This paper presents a telomere-to-telomere genome of Holstein cattle, identifies genetic loci associated with telomere length, and highlights key biological processes involved.

Cost-effective genomic prediction for fertility traits: A comparison of machine learning and conventional models using low-coverage sequencing in Holstein heifers

This study compares machine learning and conventional models for genomic prediction of fertility traits in Holstein heifers using low-coverage sequencing data, finding that KRR_GRM improves accuracy over traditional methods when using only genomic data.

Genomic Regions and Variant Analysis Reveal Candidate Genes Associated with Age at First Service in Chinese Holstein Heifers

This study identifies three genomic regions and 12 candidate genes associated with age at first service in Chinese Holstein heifers using GWAS and colocalization analysis, highlighting ANAPC4 as a putative causal gene.

GP-ML-DC: An Ensemble Machine Learning-Based Genomic Prediction Approach with Automated Two-Phase Dimensionality Reduction via Divide-and-Conquer Techniques

GP-ML-DC improves genome prediction by combining machine learning and deep learning with a two-phase dimensionality reduction approach, outperforming existing methods on cattle milk traits.

The first sheep graph-based pan-genome reveals the spectrum of structural variations and their effects on tail phenotypes

The paper constructs a graph-based sheep pan-genome to identify structural variations and their association with tail phenotypes in domestic and wild sheep.