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Genes
Special Issues
Pig Genomics, Quantitative Traits and Breeding
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Pig Genomics, Quantitative Traits 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: closed (10 June 2023) | Viewed by 3973

Special Issue Editors

Dr. Xiang Zhou

E-Mail Website
Guest Editor
Key Laboratory of Swine Genetics and Breeding of Ministry of Agriculture, Huazhong Agricultural University, Wuhan 430070, China
Interests: pig; genome; RNA-seq; disease-resistant breeding; PRRSV
Special Issues, Collections and Topics in MDPI journals
Dr. Xiuling Li

E-Mail Website
Guest Editor
College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, China
Interests: pig; genome; meat quality; genome selection; selective sweep

Special Issue Information

Dear Colleagues,

The last decade has witnessed great progress in the community of pig genetics and breeding. With the publication of the pig genome and the application of advanced genomics technologies, such as high-throughput sequencing, genome-wide association analysis, comparative genomics, and metagenomics, the research focus has shifted from individual genes to networks of genes with a common function. Thousands of gene mutations and gene candidates have been characterized, enabling the estimation of quantitative traits important for the breeding industry and the underlying genetic basis of quantitative traits. Moreover, rapidly evolving breeding technologies, such as genome selection and gene editing, offer exciting opportunities for molecular breeding by design. Genetically improving pig breeds is becoming feasible for more and more traits. In the Special Issue, we welcome all types of submissions, including articles, reviews, methodologies, opinion articles, and prospects in the pig breeding field, including but not limited to QTL mining, genetic dissection, genome selection, and gene editing of economically important quantitative traits (i.e., growth rate, meat quality, feed utilization efficiency, reproduction, and disease resistance).

Dr. Xiang Zhou
Dr. Xiuling Li
Guest Editors

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

  • pig
  • swine
  • quantitative traits
  • genomics
  • genetics
  • mapping
  • quantitative trait loci
  • breeding

Published Papers (2 papers)

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Research

10 pages, 2607 KiB  
Article
Screening Discriminating SNPs for Chinese Indigenous Pig Breeds Identification Using a Random Forests Algorithm
by Jun Gao, Lingwei Sun, Shushan Zhang, Jiehuan Xu, Mengqian He, Defu Zhang, Caifeng Wu and Jianjun Dai
Genes 2022, 13(12), 2207; https://doi.org/10.3390/genes13122207 - 25 Nov 2022
Cited by 3 | Viewed by 1323
Abstract
Chinese indigenous pig breeds have unique genetic characteristics and a rich diversity; however, effective breed identification methods have not yet been well established. In this study, a genotype file of 62,822 single-nucleotide polymorphisms (SNPs), which were obtained from 1059 individuals of 18 Chinese [...] Read more.
Chinese indigenous pig breeds have unique genetic characteristics and a rich diversity; however, effective breed identification methods have not yet been well established. In this study, a genotype file of 62,822 single-nucleotide polymorphisms (SNPs), which were obtained from 1059 individuals of 18 Chinese indigenous pig breeds and 5 cosmopolitan breeds, were used to screen the discriminating SNPs for pig breed identification. After linkage disequilibrium (LD) pruning filtering, this study excluded 396 SNPs on non-constant chromosomes and retained 20.92~−27.84% of SNPs for each of the 18 autosomes, leaving a total of 14,823 SNPs. The principal component analysis (PCA) showed the largest differences between cosmopolitan and Chinese pig breeds (PC1 = 10.452%), while relatively small differences were found among the 18 indigenous pig breeds from the Yangtze River Delta region of China. Next, a random forest (RF) algorithm was used to filter these SNPs and obtain the optimal number of decision trees (ntree = 1000) using corresponding out-of-bag (OOB) error rates. By comparing two different SNP ranking methods in the RF analysis, the mean decreasing accuracy (MDA) and mean decreasing Gini index (MDG), the effects of panels with different numbers of SNPs on the assignment accuracy, and the statistics of SNP distribution on each chromosome in the panels, a panel of 1000 of the most breed-discriminative tagged SNPs were finally selected based on the MDA screening method. A high accuracy (>99.3%) was obtained by the breed prediction of 318 samples in the RF test set; thus, a machine learning classification method was established for the multi-breed identification of Chinese indigenous pigs based on a low-density panel of SNPs. Full article
(This article belongs to the Special Issue Pig Genomics, Quantitative Traits and Breeding)
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22 pages, 3406 KiB  
Article
Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population
by Huiyu Wang, Xiaoyi Wang, Mingli Li, Hao Sun, Qiang Chen, Dawei Yan, Xinxing Dong, Yuchun Pan and Shaoxiong Lu
Genes 2022, 13(11), 1990; https://doi.org/10.3390/genes13111990 - 31 Oct 2022
Cited by 6 | Viewed by 1957
Abstract
Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the [...] Read more.
Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30–60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding. Full article
(This article belongs to the Special Issue Pig Genomics, Quantitative Traits and Breeding)
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