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Brief Introduction for the Special Issue of JIA

• I. Title of the Special Issue

  Precision Identification of Superior Genetic Resources and Application of Breeding Biotechnology for Domesticated Ruminants 

   

  II. Scope of the Special Issue

  This special issue focuses on three major themes related to the precision identification for the excellent genetic resources of domesticated ruminants, including: 1) the development and application of liquid-phase genotyping chips (Genotyping by target sequencing), 2) the construction of high-throughput phenotyping platforms, and 3) the profiling of molecular phenotypes and the analysis systems. The details of the three major themes are as follows:

   

  2.1 Development and Application of Liquid-Phase Genotyping Chips in Precision Identification of Excellent Genetic Resources in Domesticated Ruminants (approx. 5 papers) 

  This section welcomes studies on:

  1) The development and application of novel liquid-phase genotyping chips tailored for agricultural ruminant species; the construction of reference panels optimized for low-coverage whole-genome sequencing data; and the establishment of efficient and accurate high-throughput genotyping technologies;

  2) Systematic analyses of population genetic structure, phylogenetic relationships, genetic diversity, and inbreeding levels in cattle, yak, sheep, goat and other domesticated ruminants in China and worldwide;

  3) Integrating chip-based genomic data with breeding programs to accelerate genetic gain and promote the sustainable development of ruminant agriculture;

  4) Employing genomic information to formulate scientifically grounded breeding strategies, thereby enabling the effective conservation and utilization of excellent genetic resources.

   

  2.2. Construction and Application of High-Throughput Phenotyping Platforms (approx. 5 papers)

  This section welcomes studies on:

  The integration of computer vision, artificial intelligence, and big data analytics to establish standardized protocols and operating procedures for high-throughput phenotypic data acquisition across multiple traits in domesticated ruminants, providing essential technical support for the systematic mining of germplasm resources and the innovation of superior germplasm in major ruminant species.

   

  2.3. Technologies and Platforms for Precise Molecular Phenotype Profiling and Analysis (approx. 10 papers)

  This section welcomes studies on:

  Utilizing multi-omics approaches—such as genome-wide association studies (GWAS), transcriptomics, epigenomics, metabolomics, and microbiomics—to dissect the genetic basis of key economic and functional traits, including production performance (meat, milk, and fiber quality), reproductive performance, disease resistance, and environmental adaptability; identifying molecular phenotypes associated with these traits, thereby providing theoretical foundations and genetic resources for molecular design breeding.

  We sincerely invite submissions of original research articles aligned with the above themes to jointly advance scientific innovation and technological progress in the evaluation, conservation, and breeding application of genetic resources in domesticated ruminants.

   

  III. Guest Editors

  · Menghua Li, Professor, China Agricultural University;  Research focus: Sheep Biological Breeding

  · Ying Yu, Professor, China Agricultural University;  Research focus: Cattle Genetics and Breeding

  · Wenrong Li, Professor, Xinjiang Academy of Animal Science;  Research focus: Sheep Biological Breeding

  · Feng Wang, Professor, Nanjing Agricultural University;  Research focus: Goat Biological Breeding

  · Ruijun Long, Professor, Lanzhou University;  Research focus: Cattle Biological Breeding

  · Jun Zhang, Associate Professor, Beijing Academy of Agriculture and Forestry Sciences;  Research focus: Biological Information Technology

   

  IV. Invited Contributors (to be need updated)

  · Songsong Xu, Associate Professor, China Agricultural University;  Research focus: Sheep Breeding

  · Wenrong Li, Professor, Xinjiang Academy of Animal Science;  Research focus: Sheep Breeding

  · Jie Kang, Charles Perkins Centre, The University of Sydney; Sydney Precision Data Science Centre, The University of Sydney; School of Mathematics and Statistics, The University of Sydney.

  · Jiang Di, Professor, Xinjiang Academy of Animal Science;  Research focus: Sheep Breeding

  · Zhihong Liu, Professor, Inner Mongolia Agricultural University;  Research focus: Sheep Breeding

  · Kexin Li, Professor, Lanzhou University;  Research focus: Sheep Breeding

  · Zhibin Ji, Associate Professor, Shandong Agricultural University;  Research focus: Sheep Breeding

  · Feng Su, Associate Professor, Shandong Agricultural University;  Research focus: Goat Breeding

  · Guomin Zhang, Associate Professor, Nanjing Agricultural University;  Research focus: Sheep Breeding

  · Husseinflsamahy, Animal Production Research Institute (APRI) Dokki, Giza Governorate, Cairo, Egypt

  · Russell G. Snell, Applied Translational Genetics Group, School of Biological Sciences, The University of Auckland, Auckland, New Zealand.

  · T. Naicy, Department of Animal Breeding, Genetics and Biostatistics, College of Veterinary and Animal Sciences, Thrissur, Kerala, India

  · Ying Yu, Professor, China Agricultural University;  Research focus: Cattle Breeding

  · Yachun Wang, Professor, China Agricultural University;  Research focus: Cattle Breeding

  · Bo Han, Associate Professor, China Agricultural University;  Research focus: Cattle Breeding

  · Yali Zhang, Associate Professor, China Agricultural University;  Research focus: Dairy Science and Nutrition

  · Xixia Huang, Professor, Xinjiang Agricultural University;  Research focus: Cattle Breeding

  · Qiuming Chen, Professor, Xinjiang Agricultural University;  Research focus: Cattle Breeding

  · Qin Zhang, Professor, Shandong Agricultural University;  Research focus: Cattle Breeding

  · Kerong Shi, Professor, Shandong Agricultural University;  Research focus: Cattle Breeding

  · Shanyuan Chen, Professor, Yunnan University;  Research focus: Cattle Breeding

  · Xiaodan Huang, Associate Professor, Lanzhou University;  Research focus: Cattle Breeding

  · Yan Li, Professor, Yunnan University;  Research focus: Cattle Breeding

  · Yi Zhang, Professor, China Agricultural University;  Research focus: Cattle Breeding

  · Jun Zhang, Associate Professor, Beijing Academy of Agriculture and Forestry Sciences;  Research focus: Biological Information Technology

  · Wenguang Zhang, Professor, Inner Mongolia Agricultural University;  Research focus: Sheep Breeding

  · Changrong Ye, Associate Research Fellow, Higentec Co.,Ltd.;  Research focus: Genotyping Chip Development

   

  Special emphasis: Submissions involving international collaborative institutions are encouraged to enhance the proportion of internationally co-authored papers.

   

  VI. Submission Timeline

  · Submission Deadline: April 20, 2026  Please add “[SI-chip]” before the manuscript title to indicate submission to this special issue.

  · Submission Portal: https://www.chinaagrisci.com/Jwk_zgnykxen/EN/2095-3119/home.shtml

  · Acceptance Deadline: Mid-September 2026

  To ensure timely publication, manuscripts not accepted by this date cannot be included in the special issue, but may be considered for regular issues afterward.

  · Special Issue Publication Time: November 2026

  · Peer Review: All submissions will undergo rigorous academic evaluation by the Section Editor-in-Chief, Guest Editors, and external reviewers to ensure the scientific quality of the special issue.

   

  JIA Section Editorial Contact:

  Juan Zhang

  November 27, 2025

Pubdate： 2025-12-16    Viewed： 67