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Livestock Genomics, Genetics and Breeding
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Livestock Genomics, Genetics and Breeding

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 6545

Special Issue Editors

Prof. Dr. Yongju Zhao

E-Mail Website
Guest Editor
College of Animal Science and Technology, Southwest University, Chongqing 400715, China
Interests: livestock science; genetic improvement; genetic resources protection; animal breeding
Dr. Naiyi Xu

E-Mail Website
Guest Editor Assistant
College of Animal Science and Technology, Southwest University, Chongqing 400715, China
Interests: bioinformatics analysis; multi-omics research

Special Issue Information

Dear Colleagues,

Livestock is important for biodiversity and the development of global animal husbandry. Therefore, this Special Issue, “Livestock Genomics, Genetics and Breeding”, aims to collect high-quality research articles, review articles and communications on the recent advances in molecular genetics, genomics and breeding of livestock. The publication of the accurate livestock reference genome (goat, sheep, cattle, etc.)  and the rapid development of the newest wide-range high-throughput techniques have enabled us to reveal the complicated molecular mechanisms of important phenotypic traits and estimate the quantitative traits important for the breeding of livestock. Based on this, we hope to present the state of the art in the field of livestock genetics, genomics and breeding using multi-omics approaches (for GWAS, GS, epigenomics, transcriptomics, proteomics, and metabolomics). With the help of your contribution, We look forward to witnessing more cutting-edge research for the genomics, genetics and the breeding of livestock.

Topics of interest for this Special Issue include but are not limited to the following:

  • Molecular mechanisms research;
  • Multi-omics data analysis;
  • Genome selection;
  • Genome-wide association analysis;
  • Gene regulation and expression;
  • Screening of important loci and genes.

Prof. Dr. Yongju Zhao
Guest Editor
Dr. Naiyi Xu
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • goat
  • sheep
  • cattle
  • horse
  • rabbit
  • traits
  • molecular mechanism
  • molecular breeding
  • multi-omics
  • genomics

Published Papers (5 papers)

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Research

13 pages, 2044 KiB  
Article
Marker Density and Models to Improve the Accuracy of Genomic Selection for Growth and Slaughter Traits in Meat Rabbits
by Wenjie Li, Wenqiang Li, Zichen Song, Zihao Gao, Kerui Xie, Yubing Wang, Bo Wang, Jiaqing Hu, Qin Zhang, Chao Ning, Dan Wang and Xinzhong Fan
Genes 2024, 15(4), 454; https://doi.org/10.3390/genes15040454 - 03 Apr 2024
Viewed by 518
Abstract
The selection and breeding of good meat rabbit breeds are fundamental to their industrial development, and genomic selection (GS) can employ genomic information to make up for the shortcomings of traditional phenotype-based breeding methods. For the practical implementation of GS in meat rabbit [...] Read more.
The selection and breeding of good meat rabbit breeds are fundamental to their industrial development, and genomic selection (GS) can employ genomic information to make up for the shortcomings of traditional phenotype-based breeding methods. For the practical implementation of GS in meat rabbit breeding, it is necessary to assess different marker densities and GS models. Here, we obtained low-coverage whole-genome sequencing (lcWGS) data from 1515 meat rabbits (including parent herd and half-sibling offspring). The specific objectives were (1) to derive a baseline for heritability estimates and genomic predictions based on randomly selected marker densities and (2) to assess the accuracy of genomic predictions for single- and multiple-trait linear mixed models. We found that a marker density of 50 K can be used as a baseline for heritability estimation and genomic prediction. For GS, the multi-trait genomic best linear unbiased prediction (GBLUP) model results in more accurate predictions for virtually all traits compared to the single-trait model, with improvements greater than 15% for all of them, which may be attributed to the use of information on genetically related traits. In addition, we discovered a positive correlation between the performance of the multi-trait GBLUP and the genetic correlation between the traits. We anticipate that this approach will provide solutions for GS, as well as optimize breeding programs, in meat rabbits. Full article
(This article belongs to the Special Issue Livestock Genomics, Genetics and Breeding)
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13 pages, 1933 KiB  
Article
Integrated Metabolomics and Transcriptomics Analyses Reveal the Candidate Genes Regulating the Meat Quality Change by Castration in Yudong Black Goats (Capra hircus)
by Songjian Yang, Xinyue Zhang, Xingchun Li, Jikang Zheng, Le Zhao, Chengli Fan and Yongju Zhao
Genes 2024, 15(1), 43; https://doi.org/10.3390/genes15010043 - 27 Dec 2023
Viewed by 849
Abstract
Yudong black goats (YDGs) are a local breed in southwest China that possess unique meat qualities and produce a high meat yield, making them ideal models for studying goat meat quality. Castration may decrease off-odors, significantly change metabolites and improve meat quality. Using [...] Read more.
Yudong black goats (YDGs) are a local breed in southwest China that possess unique meat qualities and produce a high meat yield, making them ideal models for studying goat meat quality. Castration may decrease off-odors, significantly change metabolites and improve meat quality. Using multi-omics techniques, this study focused on Yudong black goat wethers (YDW, n = 4) and Yudong black bucks (YDB, n = 4). The findings revealed that 33 differentially expressed genes (DEGs) and 279 significantly changed metabolites (SCMs) influenced goat meat quality by affecting fat accumulation and lipolysis regulatory processes. Herein, several candidate genes (IGF1, TNNT2, PPP2R2C, MAPK10 and VNN1, etc.) were identified that play a role in regulating meat quality, non-castrated and castrated, alongside a series of metabolites that may serve as potential meat quality biomarkers. Lipids (triglycerides, oxidized lipids_5-iso PGF2VI, ceramide (t18:1/36:2(2OH)) and Carnitine C20:5, etc.) were significantly higher in the castrated goats. These results revealed that lipids and hydrophilic metabolites were affected by castration, which might be beneficial in terms of goat meat quality. This study aimed to investigate the differences in meat quality between uncastrated and castrated male goats and the possible molecular regulatory mechanisms. Full article
(This article belongs to the Special Issue Livestock Genomics, Genetics and Breeding)
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12 pages, 2900 KiB  
Article
Genome-Wide Association Study of the Reproductive Traits of the Dazu Black Goat (Capra hircus) Using Whole-Genome Resequencing
by Xingqiang Fang, Bowen Gu, Meixi Chen, Ruifan Sun, Jipan Zhang, Le Zhao and Yongju Zhao
Genes 2023, 14(10), 1960; https://doi.org/10.3390/genes14101960 - 19 Oct 2023
Viewed by 1413
Abstract
Reproductive traits are the basic economic traits of goats and important indicators in goat breeding. In this study, Dazu black goats (DBGs; n = 150), an important Chinese local goat breed with excellent reproductive performance, were used to screen for important variation loci [...] Read more.
Reproductive traits are the basic economic traits of goats and important indicators in goat breeding. In this study, Dazu black goats (DBGs; n = 150), an important Chinese local goat breed with excellent reproductive performance, were used to screen for important variation loci and genes of reproductive traits. Through genome-wide association studies (GWAS), 18 SNPs were found to be associated with kidding traits (average litter size, average litter size in the first three parity, and average litter size in the first six parity), and 10 SNPs were associated with udder traits (udder depth, teat diameter, teat length, and supernumerary teat). After gene annotation of the associated SNPs and in combination with relevant references, the candidate genes, namely ATP1A1, LRRC4C, SPCS2, XRRA1, CELF4, NTM, TMEM45B, ATE1, and FGFR2, were associated with udder traits, while the ENSCHIG00000017110, SLC9A8, GLRB, GRIA2, GASK1B, and ENSCHIG00000026285 genes were associated with litter size. These SNPs and candidate genes can provide useful biological information for improvement of the reproductive traits of goats. Full article
(This article belongs to the Special Issue Livestock Genomics, Genetics and Breeding)
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17 pages, 7571 KiB  
Article
Integrated Multi-Tissue Transcriptome Profiling Characterizes the Genetic Basis and Biomarkers Affecting Reproduction in Sheep (Ovis aries)
by Zaixia Liu, Shaoyin Fu, Xiaolong He, Lingli Dai, Xuewen Liu, Narisu, Caixia Shi, Mingjuan Gu, Yu Wang, Manda, Lili Guo, Yanchun Bao, Baiyinbatu, Chencheng Chang, Yongbin Liu and Wenguang Zhang
Genes 2023, 14(10), 1881; https://doi.org/10.3390/genes14101881 - 27 Sep 2023
Cited by 1 | Viewed by 1089
Abstract
The heritability of litter size in sheep is low and controlled by multiple genes, but the research on its related genes is not sufficient. Here, to explore the expression pattern of multi-tissue genes in Chinese native sheep, we selected 10 tissues of the [...] Read more.
The heritability of litter size in sheep is low and controlled by multiple genes, but the research on its related genes is not sufficient. Here, to explore the expression pattern of multi-tissue genes in Chinese native sheep, we selected 10 tissues of the three adult ewes with the highest estimated breeding value in the early study of the prolific Xinggao sheep population. The global gene expression analysis showed that the ovary, uterus, and hypothalamus expressed the most genes. Using the Uniform Manifold Approximation and Projection (UMAP) cluster analysis, these samples were clustered into eight clusters. The functional enrichment analysis showed that the genes expressed in the spleen, uterus, and ovary were significantly enriched in the Ataxia Telangiectasia Mutated Protein (ATM) signaling pathway, and most genes in the liver, spleen, and ovary were enriched in the immune response pathway. Moreover, we focus on the expression genes of the hypothalamic–pituitary–ovarian axis (HPO) and found that 11,016 genes were co-expressed in the three tissues, and different tissues have different functions, but the oxytocin signaling pathway was widely enriched. To further explore the differences in the expression genes (DEGs) of HPO in different sheep breeds, we downloaded the transcriptome data in the public data, and the analysis of DEGs (Xinggao sheep vs. Sunite sheep in Hypothalamus, Xinggao sheep vs. Sunite sheep in Pituitary, and Xinggao sheep vs. Suffolk sheep in Ovary) revealed the neuroactive ligand–receptor interactions. In addition, the gene subsets of the transcription factors (TFs) of DEGs were identified. The results suggest that 51 TF genes and the homeobox TF may play an important role in transcriptional variation across the HPO. Altogether, our study provided the first fundamental resource to investigate the physiological functions and regulation mechanisms in sheep. This important data contributes to improving our understanding of the reproductive biology of sheep and isolating effecting molecular markers that can be used for genetic selection in sheep. Full article
(This article belongs to the Special Issue Livestock Genomics, Genetics and Breeding)
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14 pages, 2527 KiB  
Article
Identifying Candidate Genes for Litter Size and Three Morphological Traits in Youzhou Dark Goats Based on Genome-Wide SNP Markers
by Xiaoyan Sun, Qunhao Niu, Jing Jiang, Gaofu Wang, Peng Zhou, Jie Li, Cancan Chen, Liangjia Liu, Lingyang Xu and Hangxing Ren
Genes 2023, 14(6), 1183; https://doi.org/10.3390/genes14061183 - 29 May 2023
Cited by 3 | Viewed by 1902
Abstract
This study aimed to reveal the potential genetic basis for litter size, coat colour, black middorsal stripe and skin colour by combining genome-wide association analysis (GWAS) and selection signature analysis and ROH detection within the Youzhou dark (YZD) goat population (n = 206) [...] Read more.
This study aimed to reveal the potential genetic basis for litter size, coat colour, black middorsal stripe and skin colour by combining genome-wide association analysis (GWAS) and selection signature analysis and ROH detection within the Youzhou dark (YZD) goat population (n = 206) using the Illumina GoatSNP54 BeadChip. In the GWAS, we identified one SNP (snp54094-scaffold824-899720) on chromosome 11 for litter size, two SNPs on chromosome 26 (snp11508-scaffold142-1990450, SORCS3) and chromosome 12 (snp55048-scaffold842-324525, LOC102187779) for coat colour and one SNP on chromosome 18 (snp56013-scaffold873-22716, TCF25) for the black middorsal stripe. In contrast, no SNPs were identified for skin colour. In selection signature analysis, 295 significant iHS genomic regions with a mean |iHS| score > 2.66, containing selection signatures encompassing 232 candidate genes were detected. In particular, 43 GO terms and one KEGG pathway were significantly enriched in the selected genes, which may contribute to the excellent environmental adaptability and characteristic trait formation during the domestication of YZD goats. In ROH detection, we identified 4446 ROH segments and 282 consensus ROH regions, among which nine common genes overlapped with those detected using the iHS method. Some known candidate genes for economic traits such as reproduction (TSHR, ANGPT4, CENPF, PIBF1, DACH1, DIS3, CHST1, COL4A1, PRKD1 and DNMT3B) and development and growth (TNPO2, IFT80, UCP2, UCP3, GHRHR, SIM1, CCM2L, CTNNA3 and CTNNA1) were revealed by iHS and ROH detection. Overall, this study is limited by the small population size, which affects the results of GWAS to a certain extent. Nevertheless, our findings could provide the first overview of the genetic mechanism underlying these important traits and provide novel insights into the future conservation and utilisation of Chinese goat germplasm resources. Full article
(This article belongs to the Special Issue Livestock Genomics, Genetics and Breeding)
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