A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Fu, Lu; Jiang, Yao; Wang, Chonglong; Mei, Mengran; Zhou, Ziwen; Jiang, Yifan; Song, Huihui; Ding, Xiangdong

doi:10.3389/fgene.2020.00692

Cited by 23 publications

(18 citation statements)

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“…The proposed biomarkers can be also confronted to genomic regions identified by genome-wide association study (GWAS) as affecting FE traits. For instance, TEX2 (Testis Expressed 2 protein) identified here as a predictive biomarker for RFI classification, was identified as a positional candidate in SNP detected for average daily feed intake (a FE related trait) in Landrace pigs [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

et al. 2021

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Background Improving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts. Results Gene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred’s (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R2 = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression. Conclusion From small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.

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Section: Discussionmentioning

confidence: 99%

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

et al. 2021

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“…Almost all GWAS for body length, body height, and total teat number were performed by single-locus GWAS. Weighted single-step GWAS (WssGWAS) is widely used in association analysis to increase the number of genotyped animals in livestock ( Suwannasing et al, 2018 ; Lee et al, 2019 ; Fu et al, 2020 ). WssGWAS is a promising method allowing utilization of phenotypes from ungenotyped animals based on pedigree information, so we compared the result from two methods on body length, body height, and total teat number in pigs.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Hong

Dong

et al. 2021

Front. Genet.

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Body length, body height, and total teat number are economically important traits in pig breeding, as these traits are usually associated with the growth, reproductivity, and longevity potential of piglets. Here, we report a genetic analysis of these traits using a population comprising 2,068 Large White pigs. A genotyping-by-sequencing (GBS) approach was used to provide high-density genome-wide SNP discovery and genotyping. Univariate and bivariate animal models were used to estimate heritability and genetic correlations. The results showed that heritability estimates for body length, body height, and total teat number were 0.25 ± 0.04, 0.11 ± 0.03, and 0.22 ± 0.04, respectively. The genetic correlation between body length and body height exhibited a strongly positive correlation (0.63 ± 0.15), while a positive but low genetic correlation was observed between total teat number and body length. Furthermore, we used two different genome-wide association study (GWAS) approaches: single-locus GWAS and weighted single-step GWAS (WssGWAS), to identify candidate genes for these traits. Single-locus GWAS detected 76, 13, and 29 significant single-nucleotide polymorphisms (SNPs) associated with body length, body height, and total teat number. Notably, the most significant SNP (S17_15781294), which is located 20 kb downstream of the BMP2 gene, explained 9.09% of the genetic variance for body length traits, and it also explained 9.57% of the genetic variance for body height traits. In addition, another significant SNP (S7_97595973), which is located in the ABCD4 gene, explained 8.92% of the genetic variance for total teat number traits. GWAS results for these traits identified some candidate genomic regions, such as SSC6: 14.96–15.02 Mb, SSC7: 97.18–98.18 Mb, SSC14: 128.29–131.15 Mb, SSC17: 15.39–17.27 Mb, and SSC17: 22.04–24.15 Mb, providing a starting point for further inheritance research. Most quantitative trait loci were detected by single-locus GWAS and WssGWAS. These findings reveal the complexity of the genetic mechanism of the three traits and provide guidance for subsequent genetic improvement through genome selection.

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“…The understanding of the interrelationship process among FE traits at the molecular level could provide new insights into the biological pathways involved and their genetic regulation. To date, a wide range of pathways have been associated with these traits, including forebrain development and neuron differentiation, hormone and growth factors, gluconeogenesis, lipogenesis, epithelial cell differentiation and hematopoietic cell lineage ( McKenna et al, 2018 ; Li et al, 2019 ; Fu et al, 2020 ; Lindholm-Perry et al, 2020 ; Marchesi et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…In agreement with a study in another farmed species, spam1 and hyal4 , both genes found within the significant QTL for FI, have been previously reported as associated with FI in Landrace pigs. The authors suggest a role of these genes in fat synthesis and in lipid associated pathways, such as transport and metabolism ( Fu et al, 2020 ). This could be explained by the fact that the amount of lipids plays a key role in the control of feed intake, as has been reported in livestock species ( Harvatine and Allen, 2006 ; Kuhla et al, 2016 ), mainly by acting on the hypothalamic signals regulating feed consumption and energy expenditure ( Allen et al, 2005 ; Relling et al, 2010 ).…”

Section: Discussionmentioning

confidence: 99%

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

et al. 2021

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Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; −0.60 and −0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

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A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Cited by 23 publications

References 84 publications

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

Genome-Wide Association Study for Body Length, Body Height, and Total Teat Number in Large White Pigs

Genomic Selection and Genome-wide Association Study for Feed-Efficiency Traits in a Farmed Nile Tilapia (Oreochromis niloticus) Population

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