Abstract:Chinese pigs have been undergoing both natural and artificial selection for thousands of years. Jinhua pigs are of great importance, as they can be a valuable model for exploring the genetic mechanisms linked to meat quality and other traits such as disease resistance, reproduction and production. The purpose of this study was to identify distinctive footprints of selection between Jinhua pigs and other breeds utilizing genome-wide SNP data. Genotyping by genome reducing and sequencing was implemented in order… Show more
“…A ROH island on SSC2 partially overlapped with a selection region for intramuscular fat and backfat thickness in two Duroc populations, which spanned three genes ( ABCC8, MYOD1 , and PIK3C2A ) (Kim et al, 2015). The MYOD1 gene in this region was also detected in the selection signatures between Jinhua pig group and European breeds group (Li et al, 2016).…”
Jinhua pig, a well-known Chinese indigenous breed, has evolved as a pig breed with excellent meat quality, greater disease resistance, and higher prolificacy. The reduction in the number of Jinhua pigs over the past years has raised concerns about inbreeding. Runs of homozygosity (ROH) along the genome have been applied to quantify individual autozygosity to improve the understanding of inbreeding depression and identify genes associated with traits of interest. Here, we investigated the occurrence and distribution of ROH using next-generation sequencing data to characterize autozygosity in 202 Jinhua pigs, as well as to identify the genomic regions with high ROH frequencies within individuals. The average inbreeding coefficient, based on ROH longer than 1 Mb, was 0.168 ± 0.052. In total, 18,690 ROH were identified in all individuals, among which shorter segments (1–5 Mb) predominated. Individual ROH autosome coverage ranged from 5.32 to 29.14% in the Jinhua population. On average, approximately 16.8% of the whole genome was covered by ROH segments, with the lowest coverage on SSC11 and the highest coverage on SSC17. A total of 824 SNPs (about 0.5%) and 11 ROH island regions were identified (occurring in over 45% of the samples). Genes associated with reproduction (
HOXA3, HOXA7, HOXA10
, and
HOXA11
), meat quality (
MYOD1, LPIN3
, and
CTNNBL1
), appetite (
NUCB2
) and disease resistance traits (
MUC4, MUC13, MUC20, LMLN, ITGB5, HEG1, SLC12A8
, and
MYLK
) were identified in ROH islands. Moreover, several quantitative trait loci for ham weight and ham fat thickness were detected. Genes in ROH islands suggested, at least partially, a selection for economic traits and environmental adaptation, and should be subject of future investigation. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the pig genome.
“…A ROH island on SSC2 partially overlapped with a selection region for intramuscular fat and backfat thickness in two Duroc populations, which spanned three genes ( ABCC8, MYOD1 , and PIK3C2A ) (Kim et al, 2015). The MYOD1 gene in this region was also detected in the selection signatures between Jinhua pig group and European breeds group (Li et al, 2016).…”
Jinhua pig, a well-known Chinese indigenous breed, has evolved as a pig breed with excellent meat quality, greater disease resistance, and higher prolificacy. The reduction in the number of Jinhua pigs over the past years has raised concerns about inbreeding. Runs of homozygosity (ROH) along the genome have been applied to quantify individual autozygosity to improve the understanding of inbreeding depression and identify genes associated with traits of interest. Here, we investigated the occurrence and distribution of ROH using next-generation sequencing data to characterize autozygosity in 202 Jinhua pigs, as well as to identify the genomic regions with high ROH frequencies within individuals. The average inbreeding coefficient, based on ROH longer than 1 Mb, was 0.168 ± 0.052. In total, 18,690 ROH were identified in all individuals, among which shorter segments (1–5 Mb) predominated. Individual ROH autosome coverage ranged from 5.32 to 29.14% in the Jinhua population. On average, approximately 16.8% of the whole genome was covered by ROH segments, with the lowest coverage on SSC11 and the highest coverage on SSC17. A total of 824 SNPs (about 0.5%) and 11 ROH island regions were identified (occurring in over 45% of the samples). Genes associated with reproduction (
HOXA3, HOXA7, HOXA10
, and
HOXA11
), meat quality (
MYOD1, LPIN3
, and
CTNNBL1
), appetite (
NUCB2
) and disease resistance traits (
MUC4, MUC13, MUC20, LMLN, ITGB5, HEG1, SLC12A8
, and
MYLK
) were identified in ROH islands. Moreover, several quantitative trait loci for ham weight and ham fat thickness were detected. Genes in ROH islands suggested, at least partially, a selection for economic traits and environmental adaptation, and should be subject of future investigation. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the pig genome.
“…Table 1 lists detailed information of the sampled pig breeds in this study, including breed name, abbreviations and sample size. Most of the reduced-representation genotyping data has been described in previous studies 23 – 26 , except for that from the Pietrain and Berkshire populations. Figure 1 Sample location of Chinese indigenous pig populations within the Yangtze River Delta used in this study.…”
The differences in artificial and natural selection have been some of the factors contributing to phenotypic diversity between Chinese and western pigs. Here, 830 individuals from western and Chinese pig breeds were genotyped using the reduced-representation genotyping method. First, we identified the selection signatures for different pig breeds. By comparing Chinese pigs and western pigs along the first principal component, the growth gene IGF1R; the immune genes IL1R1, IL1RL1, DUSP10, RAC3 and SWAP70; the meat quality-related gene SNORA50 and the olfactory gene OR1F1 were identified as candidate differentiated targets. Further, along a principal component separating Pudong White pigs from others, a potential causal gene for coat colour (EDNRB) was discovered. In addition, the divergent signatures evaluated by Fst within Chinese pig breeds found genes associated with the phenotypic features of coat colour, meat quality and feed efficiency among these indigenous pigs. Second, admixture and genomic introgression analysis were performed. Shan pigs have introgressed genes from Berkshire, Yorkshire and Hongdenglong pigs. The results of introgression mapping showed that this introgression conferred adaption to the local environment and coat colour of Chinese pigs and the superior productivity of western pigs.
“…Some examples of LD-based methods used to explore the domestication process includes an analysis using LRH to detect signatures of selection associated to dairy and beef cattle breeds ( Bomba et al, 2015 ), a study using the XP-EHH statistic to find signals of selective sweeps in Jinhua pigs ( Li et al, 2016 ), and a paper focused on the diversification of goat landraces that calculated the iHS and the XP-EHH statistics alongside other tests to detect selective sweeps between goat breeds ( Bertolini et al, 2018 ).…”
Section: Identifying Genes Under Selection During Domesticationmentioning
In the last decade, genomics and the related fields of transcriptomics and epigenomics have revolutionized the study of the domestication process in plants and animals, leading to new discoveries and new unresolved questions. Given that some domesticated taxa have been more studied than others, the extent of genomic data can range from vast to nonexistent, depending on the domesticated taxon of interest. This review is meant as a rough guide for students and academics that want to start a domestication research project using modern genomic tools, as well as for researchers already conducting domestication studies that are interested in following a genomic approach and looking for alternate strategies (cheaper or more efficient) and future directions. We summarize the theoretical and technical background needed to carry out domestication genomics, starting from the acquisition of a reference genome and genome assembly, to the sampling design for population genomics, paleogenomics, transcriptomics, epigenomics and experimental validation of domestication-related genes. We also describe some examples of the aforementioned approaches and the relevant discoveries they made to understand the domestication of the studied taxa.
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