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Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations.

ABSTRACT: Piglet splay leg syndrome (PSL) is one of the most frequent genetic defects, and can cause considerable economic loss in pig production. The present understanding of etiology and pathogenesis of PSL is poor. The current study focused on identifying loci associated with PSL through a genome-wide association study (GWAS) performed with the Illumina Porcine60 SNP Beadchip v2.0. The study was a case/control design with four pig populations (Duroc, Landrace, Yorkshire and one crossbred of Landrace × Yorkshire).After quality control of the genotyping data, 185 animals (73 cases, 112 controls) and 43,495 SNPs were retained for further analysis. Principal components (PCs) identified from the genomic kinship matrix were included in the statistical model for correcting the effect of population structure. Seven chromosome-wide significant SNPs were identified on Sus scrofa chromosome 1 (SSC1), SSC2 (2 SNPs), SSC7, SSC15 (2 SNPs) and SSC16 after strict Bonferroni correction. Four genes (HOMER1 and JMY on SSC2, ITGA1 on SSC16, and RAB32 on SSC1) related to muscle development, glycogen metabolism and mitochondrial dynamics were identified as potential candidate genes for PSL.We identified seven chromosome-wide significant SNPs associated with PSL and four potential candidate genes for PSL. To our knowledge, this is the first pilot study aiming to identify the loci associated with PSL using GWAS. Further investigations and validations for those findings are encouraged.

SUBMITTER: Hao X

PROVIDER: S-EPMC5499021 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations.

Hao Xingjie X Plastow Graham G Zhang Chunyan C Xu Sutong S Hu Zhiqiu Z Yang Tianfu T Wang Kai K Yang Huawei H Yin Xiaoxue X Liu Shili S Wang Zhenghua Z Wang Zhiquan Z Zhang Shujun S

BMC genetics 20170705 1

<h4>Background</h4>Piglet splay leg syndrome (PSL) is one of the most frequent genetic defects, and can cause considerable economic loss in pig production. The present understanding of etiology and pathogenesis of PSL is poor. The current study focused on identifying loci associated with PSL through a genome-wide association study (GWAS) performed with the Illumina Porcine60 SNP Beadchip v2.0. The study was a case/control design with four pig populations (Duroc, Landrace, Yorkshire and one cross ...[more]

PMID: 28679362

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Project description:Birth weight is an economically important trait in pig production because it directly impacts piglet growth and survival rate. In the present study, we performed a genome wide survey of candidate genes and pathways associated with individual birth weight (IBW) using the Illumina PorcineSNP60 BeadChip on 24 high (HEBV) and 24 low estimated breeding value (LEBV) animals. These animals were selected from a reference population of 522 individuals produced by three sires and six dam lines, which were crossbreds with multiple breeds. After quality-control, 43,257 SNPs (single nucleotide polymorphisms), including 42,243 autosomal SNPs and 1,014 SNPs on chromosome X, were used in the data analysis. A total of 27 differentially selected regions (DSRs), including 1 on Sus scrofa chromosome 1 (SSC1), 1 on SSC4, 2 on SSC5, 4 on SSC6, 2 on SSC7, 5 on SSC8, 3 on SSC9, 1 on SSC14, 3 on SSC18, and 5 on SSCX, were identified to show the genome wide separations between the HEBV and LEBV groups for IBW in piglets. A DSR with the most number of significant SNPs (including 7 top 0.1% and 31 top 5% SNPs) was located on SSC6, while another DSR with the largest genetic differences in F ST was found on SSC18. These regions harbor known functionally important genes involved in growth and development, such as TNFRSF9 (tumor necrosis factor receptor superfamily member 9), CA6 (carbonic anhydrase VI) and MDFIC (MyoD family inhibitor domain containing). A DSR rich in imprinting genes appeared on SSC9, which included PEG10 (paternally expressed 10), SGCE (sarcoglycan, epsilon), PPP1R9A (protein phosphatase 1, regulatory subunit 9A) and ASB4 (ankyrin repeat and SOCS box containing 4). More importantly, our present study provided evidence to support six quantitative trait loci (QTL) regions for pig birth weight, six QTL regions for average birth weight (ABW) and three QTL regions for litter birth weight (LBW) reported previously by other groups. Furthermore, gene ontology analysis with 183 genes harbored in these 27 DSRs suggested that protein, metal, ion and ATP binding, viral process and innate immune response present important pathways for deciphering their roles in fetal growth or development. Overall, our study provides useful information on candidate genes and pathways for regulating birth weight in piglets, thus improving our understanding of the genetic mechanisms involved in porcine embryonic or fetal development.

Project description:BACKGROUND: In pigs, the perinatal period is the most critical time for survival. Piglet maturation, which occurs at the end of gestation, leads to a state of full development after birth. Therefore, maturity is an important determinant of early survival. Skeletal muscle plays a key role in adaptation to extra-uterine life, e.g. glycogen storage and thermoregulation. In this study, we performed microarray analysis to identify the genes and biological processes involved in piglet muscle maturity. Progeny from two breeds with extreme muscle maturity phenotypes were analyzed at two time points during gestation (gestational days 90 and 110). The Large White (LW) breed is a selected breed with an increased rate of mortality at birth, whereas the Meishan (MS) breed produces piglets with extremely low mortality at birth. The impact of the parental genome was analyzed with reciprocal crossed fetuses. RESULTS: Microarray analysis identified 12,326 differentially expressed probes for gestational age and genotype. Such a high number reflects an important transcriptomic change that occurs between 90 and 110 days of gestation. 2,000 probes, corresponding to 1,120 unique annotated genes, involved more particularly in the maturation process were further studied. Functional enrichment and graph inference studies underlined genes involved in muscular development around 90 days of gestation, and genes involved in metabolic functions, such as gluconeogenesis, around 110 days of gestation. Moreover, a difference in the expression of key genes, e.g. PCK2, LDHA or PGK1, was detected between MS and LW just before birth. Reciprocal crossing analysis resulted in the identification of 472 genes with an expression preferentially regulated by one parental genome. Most of these genes (366) were regulated by the paternal genome. Among these paternally regulated genes, some known imprinted genes, such as MAGEL2 or IGF2, were identified and could have a key role in the maturation process. CONCLUSION: These results reveal the biological mechanisms that regulate muscle maturity in piglets. Maturity is also under the conflicting regulation of the parental genomes. Crucial genes, which could explain the biological differences in maturity observed between LW and MS breeds, were identified. These genes could be excellent candidates for a key role in the maturity.

Project description:AimsGenome-wide association studies (GWASs) have discovered hundreds of common genetic variants for atherosclerotic disease and cardiovascular risk factors. The translation of susceptibility loci into biological mechanisms and targets for drug discovery remains challenging. Intersecting genetic and gene expression data has led to the identification of candidate genes. However, previously studied tissues are often non-diseased and heterogeneous in cell composition, hindering accurate candidate prioritization. Therefore, we analysed single-cell transcriptomics from atherosclerotic plaques for cell-type-specific expression to identify atherosclerosis-associated candidate gene-cell pairs.Methods and resultsWe applied gene-based analyses using GWAS summary statistics from 46 atherosclerotic and cardiovascular disease, risk factors, and other traits. We then intersected these candidates with single-cell RNA sequencing (scRNA-seq) data to identify genes specific for individual cell (sub)populations in atherosclerotic plaques. The coronary artery disease (CAD) loci demonstrated a prominent signal in plaque smooth muscle cells (SMCs) (SKI, KANK2, and SORT1) P-adj. = 0.0012, and endothelial cells (ECs) (SLC44A1, ATP2B1) P-adj. = 0.0011. Finally, we used liver-derived scRNA-seq data and showed hepatocyte-specific enrichment of genes involved in serum lipid levels.ConclusionWe discovered novel and known gene-cell pairs pointing to new biological mechanisms of atherosclerotic disease. We highlight that loci associated with CAD reveal prominent association levels in mainly plaque SMC and EC populations. We present an intuitive single-cell transcriptomics-driven workflow rooted in human large-scale genetic studies to identify putative candidate genes and affected cells associated with cardiovascular traits. Collectively, our workflow allows for the identification of cell-specific targets relevant for atherosclerosis and can be universally applied to other complex genetic diseases and traits.

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Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations.

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Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations.

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