- Email: [email protected]
Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population
Author’s Accepted Manuscript Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population J.H. Kang, E.A. Lee, S.H. Lee, S.H. Kim, D.H. Lee, K.C. Hong, H.B. Park www.elsevier.com/locate/livsci
PII: DOI: Reference:
S1871-1413(17)30155-5 http://dx.doi.org/10.1016/j.livsci.2017.05.013 LIVSCI3221
To appear in: Livestock Science Received date: 8 December 2016 Revised date: 17 May 2017 Accepted date: 18 May 2017 Cite this article as: J.H. Kang, E.A. Lee, S.H. Lee, S.H. Kim, D.H. Lee, K.C. Hong and H.B. Park, Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population, Livestock Science, http://dx.doi.org/10.1016/j.livsci.2017.05.013 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Short communication Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population
J.H. Kanga, E.A. Leea, S.H. Leea, S.H. Kimb, D.H. Leec, K.C. Honga1, H.B. Parkd1 a
Division of Biotechnology, College of Life Sciences and Biotechnology, Korea University,
Anamro 145, 02841 Seoul, Republic of Korea. b
PigGene Korea, Inc. 2794 Yonggu-daero, 16866 Youngin, Republic of Korea
c
Department of Animal Life and Environment Science, Hankyong National University, 327,
Chungang-ro 327, 17579 Anseong, Republic of Korea d
Subtropical Livestock Research Institute, National Institute of Animal Science, Rural
Development Administration, 59350 Jeju, Republic of Korea
[email protected] [email protected]
Address for corresponding authors: Ki-Chang Hong, Division of biotechnology, College of Life Sciences and Biotechnology, Korea University, Anamro 145, Sungbuk-gu, 02841 Seoul, Republic of Korea
1
These corresponding authors contributed equally to this work 1
Hee-Bok Park, Subtropical Livestock Research Institute, National Institute of Animal Science, Rural Development Administration, 59350 Jeju, Republic of Korea
Abstract Improvement of sow lifetime productivity (SLP) is expected to increase farm performance and profitability. Many genes and environmental factors influence these complex traits. To identify quantitative trait loci and positional candidate genes for SLP-related traits, we performed a genome-wide association study (GWAS) using 656 Landrace purebred pigs from a commercial breeding stock farm. All sows in the study population were genotyped with the Illumina Porcine SNP60 BeadChip, and GWAS analyzed by linear mixed-effects model based association analysis using the GCTA program. Five genome-wide suggestive single nucleotide polymorphism markers were identified for the lifetime total number of born piglets and final parity. All five of these markers were highly associated with other SLPrelated traits, and all these markers were located within or near one particular gene, MEGF11 (multiple epidermal growth factor-like domains protein 11), on chromosome 1. This new positional candidate gene could contribute to increased sow lifetime productivity after the validation in other populations. Keywords: Sow lifetime productivity, genome-wide association study, Landrace pigs, quantitative trait loci.
2
1. Introduction The improvement of sow lifetime productivity (SLP)-related traits has become a great concern to the swine industry because enhancing such traits could substantially influence the profitability of commercial pig farms. SLP-related traits can be calculated via several methods based on data obtained from lifetime reproduction records (Serenius and Stalder, 2004). The SLP-related traits can be simply calculated by summation of piglets during entire lifetime of sows (e.g. lifetime total number of born piglets, lifetime total number of born alive piglets). On the other hand, these traits can be measured as lifetime pig production per pig day, which is called lifetime efficiency (e.g. lifetime total number of born piglets per day, lifetime total number of born alive piglets per day), to deal with both fertility and prolificacy of sows (Sasaki and Koketsu, 2008; Sobczyńska et al., 2013). Although higher parity sows are generally more profitable, they are often culled due to an increased risk of reproductive problems and low litter sizes. In fact, more than 30% of farmed sows are culled before their third parity, and almost 50% of farmed sows are replaced annually. This fast turnover rate is expected to increase genetic progress. However, this also can lead to reductions in economic efficiency for commercial swine farms (Rodriguez-Zas et al., 2003; Engblom et al., 2007). Therefore, sustained sow reproductive success should also be considered as one of the most critical profitability factors for pig farms (Sasaki and Koketsu, 2008; Sobczyńska et al., 2013; Iida et al., 2015). Because SLP-related traits can also be regarded as complex quantitative traits influenced by multiple genetic factors that are sensitive to environmental conditions, and because these traits can only be recorded when sows are culled, traditional selective breeding strategies are limited in their ability to improve SLP-related traits. Advancements in DNA technologies and statistical methodologies have facilitated the 3
detection of individual genetic factors at the quantitative trait locus (QTL) or quantitative trait nucleotide (QTN) level, which affect economically important traits in livestock (Andersson and Georges, 2004; Georges, 2007; Andersson, 2013). Genome-wide association studies (GWASs) using high-density single nucleotide polymorphism (SNP) chips, which encompass an entire genome and use historical recombination events accumulated within a population over many generations, have recently been used to identify QTL or QTN (Balding, 2006; Fan et al., 2006). Therefore, the identified QTL or QTN can be used for optimizing breeding programs focused on improving SLP-related traits. Onteru et al. (2011) reported their GWAS results on SLP-related traits. However, reports on GWAS for SLP-related traits are still quite rare. Thus, the aim of our study was to conduct GWAS to identify genetic markers and their positional candidate genes associated with several SLP-related traits in a Landrace purebred population.
2. Materials and methods 2.1 Experimental animals and phenotype recoding A total of 656 purebred Landrace female pigs (born between 2006 and 2014) from a single commercial breeding stock farm were used for this study. All animals were reared under the same controlled conditions. Average (SD) lactation days were 23.5 (5.5) and phenotypes were recorded on-site at the farm. Recorded SLP-related traits included lifetime total number of born (LTNB) piglets, lifetime total number of born alive (LNBA) piglets, and lifetime total number of piglets weaned (LPW). The lifetime TNB efficiency (LTNB365) was calculated as the LTNB divided by the length of lifetime in years. Likewise, the lifetime NBA efficiency (LNBA365) was calculated as the LNBA divided by the length of lifetime in years. In addition, the length of productive lifetime (LPL; first farrowing to culling), and lifetime non4
productive days per parity (LNDPP; non-productive days was defined as the number of days of farrowing and culling intervals) and final parity (FP) were used as phenotypes of this study as previously described (Serenius and Stalder, 2004, Onteru et al., 2011, Sasaki and Koketsu, 2008). Descriptive phenotypic statistics are listed in Supplementary table S1. This study followed animal care guidelines as prescribed by the institutional Animal Care and Use Committee at the National Institute of Animal Science, Republic of Korea.
2.2 Genome-wide association analysis Genomic DNA from blood samples was prepared using an iNtRONBio G-spin™ Total DNA Extraction Kit (iNtRON Biotechnology, Korea), and all pigs were genotyped with the Illumina PorcineSNP60 BeadChip (Illumina, USA). SNP markers were filtered according to the following criteria: (1) minor allele frequency < 0.05, (2) call rates < 90%, (3) HardyWeinberg equilibrium test (P ≤ 0.001, as calculated from the 2d.f.=1-test). After filtering, 36,926 autosomal SNP markers remained for GWAS. This quality control processes were conducted using the PLINK program (Purcell et al., 2007). Linear mixed-model association analysis was performed on this SNP chip data using the GCTA program (Yang et al., 2011). To account for the kinship relatedness within the study population, a single-marker association was performed using the mlma command in GCTA. The following linear mixed-effects model was used to evaluate the association between SNP markers and SLP-related traits:
y = Xb + Z1a + Z2u + e
where, y is the vector of each SLP-related trait; b is the vector of fixed effects, including 5
batch, age of first farrowing, and the number of live piglets at first parity; a represents SNP marker effects; u is the vector of random additive effects having a distribution u ~N(0, Ga2), where G is the genomic relationship matrix constructed using the 36,926 SNP markers and a2 is the additive genetic variance; e is a vector of random residual following a distribution e ~N(0, Ie2), in which I is the identity matrix and e2 is the residual variance. Z1 is the incidence matrix for a. X and Z2 are the incidence matrices for b and u. Bonferroni-adjusted “significant” (i.e., 0.05/36,926 SNPs; significant P = 1.35 × 106) and “suggestive” (i.e., 1/36,926 SNPs; suggestive P = 2.71 × 105) thresholds were established to address multiple testing issues. Unless otherwise stated, P-values are nominal.
3. Results and discussion Although no genome-wide significant SNP marker was identified, five genome-wide suggestive SNPs associated with the LTNB and FP traits were detected. H3GA0003177, located on chromosome 1, was the SNP marker most strongly associated with both LTNB (P = 8.33 × 106) and FP (P = 1.29 × 105). Moreover, these five SNP markers were also associated with other SLP traits at a genome-wide suggestive significance level, as indicated in Table 1. Specifically, H3GA0003177 was also associated with LNBA (P = 2.23 × 105) and LPL (P = 2.21 × 105), respectively. ASGA0005093 and ASGA0005108, both located on chromosome 1, were associated with LTNB, LNBA, LPL and FP (Table 1). ALGA0006736, located on chromosome 1, was associated with LTNB (P = 1.12 × 105), LPL (P = 2.26 × 105) and FP (P = 1.43 × 105), respectively. ASGA0005085, located on chromosome 1, was associated with LTNB (P = 2.36 × 105) and FP (P = 2.25 × 105) at the genome-wide suggestive level. The Manhattan plots for LTNB, LNBA and LPL traits are shown in Figure 1. 6
Interestingly, all five SNPs were located within (H3GA0003177) or near (ALGA0006736, ASGA0005085, ASGA0005093 and ASGA0005108) one particular gene, known as MEGF11 (multiple epidermal growth factor-like domains protein 11), as shown in Table 1. MEGF11 is located between base pairs 181,546,697 and 181,569,956 on chromosome 1. This region overlaps with QTLs affecting reproductive traits, such as teat number and non-functional nipples (Guo et al., 2008; Jonas et al., 2008), and exterior traits, especially feet conformation (Lee et al., 2003; Laenoi et al., 2011), as indicated in previous QTL mapping studies (PigQTLdb, http://www.animalgenome.org/cgi-bin/QTLdb/SS/index). Fewer non-functional nipples or strong leg performance may be associated with sow robustness and longevity. In humans, high expressions of MEGF11 in both adult and fetal brain tissue (especially in the cerebellum) was detected, whereas moderate expression was detected in the adult ovary (Nagase et al., 2001). These expression patterns may be similar to those seen in pigs and may serve important roles in both sow and fetus. MEGF11 is homologous with MEGF10 and performs a similar function (Suzuki and Nakayama, 2007; Kay et al., 2012). In fruit flies, drpr (Draper, CG2086), the sole Drosophila homolog of human genes MEGF11 and MEGF10 (Ziegenfuss et al., 2008), leads to significantly reduced median lifespans (six to eight weeks) and age-dependent declines in climbing performance (Draper et al., 2014). Although no functional research currently supports an association between MEGF11 and SLP traits, further study of this new candidate gene for SLP is necessary to verify its involvement in reproductive physiology affecting SLP. In summary, we performed a GWAS and detected a QTL and a novel positional candidate gene associated with SLP-related traits. This result could be useful to optimize breeding program to improve the SLP-related traits after further functional studies and validation of the association in other independent populations. 7
Conflict of interest statement None.
Acknowledgements This research was conducted with the support of the Bio-industry Technology Development Program (grant number 114065), Ministry of Agriculture, Food and Rural Affairs, Republic of Korea.
References Andersson, L., 2013. Molecular consequences of animal breeding. Curr. Opin. Genet. Dev. 23, 295-301. Andersson, L., Georges, M., 2004. Domestic-animal genomics: deciphering the genetics of complex traits. Nat. Rev. Genet. 5, 202-212. Balding, D.J., 2006. A tutorial on statistical methods for population association studies. Nat. Rev. Genet. 7, 781-791. Draper, I., Mahoney, L.J., Mitsuhashi, S., Pacak, C.A., Salomon, R.N., Kang, P.B., 2014. Silencing of drpr Leads to Muscle and Brain Degeneration in Adult Drosophila. Am. J. Pathol. 184, 2653-2661. Engblom, L., Lundeheim, N., Dalin, A.-M., Andersson, K., 2007. Sow removal in Swedish commercial herds. Livest. Sci. 106, 76-86. Fan, J.-B., Chee, M.S., Gunderson, K.L., 2006. Highly parallel genomic assays. Nat. Rev. Genet. 7, 632-644. 8
Georges, M., 2007. Mapping, Fine Mapping, and Molecular Dissection of Quantitative Trait Loci in Domestic Animals. Annu. Rev. Genomics Hum. Genet. 8, 131-162. Guo, Y.M., Lee, G.J., Archibald, A.L., Haley, C.S., 2008. Quantitative trait loci for production traits in pigs: a combined analysis of two Meishan × Large White populations. Anim. Genet. 39, 486-495. Iida, R., Piñeiro, C., Koketsu, Y., 2015. High lifetime and reproductive performance of sows on southern European Union commercial farms can be predicted by high numbers of pigs born alive in parity one1. J. Anim. Sci. 93, 2501-2508. Jonas, E., Schreinemachers, H.-J., Kleinwächter, T., Ün, C., Oltmanns, I., Tetzlaff, S., Jennen, D., Tesfaye, D., Ponsuksili, S., Murani, E., Juengst, H., Tholen, E., Schellander, K., Wimmers, K., 2008. QTL for the heritable inverted teat defect in pigs. Mamm. Genome 19, 127-138. Kay, J.N., Chu, M.W., Sanes, J.R., 2012. MEGF10 and MEGF11 mediate homotypic interactions required for mosaic spacing of retinal neurons. Nature 483, 465-469. Laenoi, W., Uddin, M.J., Cinar, M.U., Große-Brinkhaus, C., Tesfaye, D., Jonas, E., Scholz, A.M., Tholen, E., Looft, C., Wimmers, K., Phatsara, C., Juengst, H., Sauerwein, H., Mielenz, M., Schellander, K., 2011. Quantitative trait loci analysis for leg weaknessrelated traits in a Duroc × Pietrain crossbred population. Genet. Sel. Evol. 43, 13. Lee, G., Archibald, A., Garth, G., Law, A., Nicholson, D., Barr, A., Haley, C., 2003. Detection of quantitative trait loci for locomotion and osteochondrosis-related traits in Large White x Meishan pigs. Anim. Sci. 76, 155-166. Nagase, T., Nakayama, M., Nakajima, D., Kikuno, R., Ohara, O., 2001. Prediction of the Coding Sequences of Unidentified Human Genes. XX. The Complete Sequences of 100 New cDNA Clones from Brain Which Code for Large Proteins in vitro. DNA Res. 8, 859
95. Onteru, S.K., Fan, B., Nikkilä, M.T., Garrick, D.J., Stalder, K.J., Rothschild, M.F., 2011. Whole-genome association analyses for lifetime reproductive traits in the pig. J. Anim. Sci. 89, 988-995. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.R., Bender, D., Maller, J., Sklar, P., de Bakker, P.I.W., Daly, M.J., Sham, P.C., 2007. PLINK: A Tool Set for WholeGenome Association and Population-Based Linkage Analyses. Am. J. Hum. Genet. 81, 559-575. Rodriguez-Zas, S.L., Southey, B.R., Knox, R.V., Connor, J.F., Lowe, J.F., Roskamp, B.J., 2003. Bioeconomic evaluation of sow longevity and profitability. J. Anim. Sci. 81, 29152922. Sasaki, Y., Koketsu, Y., 2008. Sows having high lifetime efficiency and high longevity associated with herd productivity in commercial herds. Livest. Sci. 118, 140-146. Serenius, T., Stalder, K.J., 2004. Genetics of length of productive life and lifetime prolificacy in the Finnish Landrace and Large White pig populations1. J. Anim. Sci. 82, 3111-3117. Sobczyńska, M., Blicharski, T., Tyra, M., 2013. Relationships between longevity, lifetime productivity, carcass traits and conformation in Polish maternal pig breeds. J. Anim. Breed. Genet. 130, 361-371. Suzuki, E., Nakayama, M., 2007. The mammalian Ced-1 ortholog MEGF10/KIAA1780 displays a novel adhesion pattern. Exp. Cell Res. 313, 2451-2464. Yang, J., Lee, S.H., Goddard, M.E., Visscher, P.M., 2011. GCTA: A Tool for Genome-wide Complex Trait Analysis. Am. J. Hum. Genet. 88, 76-82. Ziegenfuss, J.S., Biswas, R., Avery, M.A., Hong, K., Sheehan, A.E., Yeung, Y.-G., Stanley, E.R., Freeman, M.R., 2008. Draper-dependent glial phagocytic activity is mediated by 10
Src and Syk family kinase signalling. Nature 453, 935-939.
11
SNP ID (Accession number) ALGA0006736 (rs81349337) H3GA0003177 (rs81349342) ASGA0005085 (rs81349346) ASGA0005093 (rs81349365) ASGA0005108 (rs81349396)
181,685,718
181,534,272
G/A
T/C
T/C
0.50
0.50
0.42
0.42
MEGF11
MEGF11
MEGF11
MEGF11
MEGF11
RAB11A
54,286
41,786
8,211
within
96,517
41,119
1.35 × 10-5*
1.47 × 10-5*
2.36 × 10-5*
8.33 × 10-6*
1.12 × 10-5*
P-value
LTNB
1.63 × 10-4
1.44 × 10-4
2.13 × 10-4
3.18 × 10-5
4.87 × 10-5
P-value
LTNB365
1.64 × 10-5*
2.12 × 10-5*
3.39 × 10-5
2.23 × 10-5*
2.61 × 10-5
P-value
LNBA
3.34 × 10-4
3.75 × 10-4
5.37 × 10-4
2.55 × 10-4
3.23 × 10-4
P-value
LNBA365
7.65 × 10-4
9.16 × 10-4
1.17 × 10-3
3.54 × 10-3
2.99 × 10-3
P-value
LPW
1.48 × 10-5*
1.65 × 10-5*
2.69 × 10-5
2.21 × 10-5*
2.26 × 10-5*
P-value
LPL
1.29 × 10-5*
1.38 × 10-5*
2.25 × 10-5*
1.29 × 10-5*
1.43 × 10-5*
P-value
FP
MAF4 Closest genes5 Distance (bp)7
181,708,122
A/G
0.50
Alleles3
181,741,697
A/G
Location (bp)2
181,754,197
Table 1. Single nucleotide polymorphism markers identified by the genome-wide association study.
SSC1
1
1
1
1
1
Sus scrofa chromosome
1
SNP position reported according to the SSCROFA 10.2 genome annotation.
2
Major and minor alleles
3
Minor allele frequency
4
Nearest gene to indicated SNP defined in a region of ±500 kb
5
Coordinates of the indicated genes according to SSCROFA 10.2
6
SNP designated as within a gene or as distance (bp) from a gene region
7
Genome-wide suggestive significant
*
12
Fig. 1. GWAS results for SLP-related traits in a purebred Landrace population. Panels on the left represent the association between SLP-related traits and 36,926 mapped SNP markers on 18 porcine autosomes. In these panels, the y-axis represents the log10 (P-values) and x- axis indicates the physical map position of the SNP markers on the pig chromosome. Red horizontal lines represent genome-wide “significant” thresholds (5.87); blue horizontal lines represent genome-wide “suggestive” thresholds (4.57). Panels on the right represent the corresponding quantile-quantile (QQ) plots for the association of 36,926 SNP markers with SLP-related traits: (a) LTNB, (b) LNBA, and (c) LPL. 13
Highlight Sow lifetime productivity (SLP)-related traits are important because enhancing such traits could substantially affect the profitability of commercial pig farms. A genome-wide association study was performed to identify quantitative trait loci and their positional candidate genes, which could be used for breeding programs for SLP-related traits. A total of five genome-wide suggestive significant single nucleotide polymorphisms were identified. All five SNPs were located within or near MEGF11 (multiple epidermal growth factor-like domains protein 11) on chromosome 1.
14
PII: DOI: Reference:
S1871-1413(17)30155-5 http://dx.doi.org/10.1016/j.livsci.2017.05.013 LIVSCI3221
To appear in: Livestock Science Received date: 8 December 2016 Revised date: 17 May 2017 Accepted date: 18 May 2017 Cite this article as: J.H. Kang, E.A. Lee, S.H. Lee, S.H. Kim, D.H. Lee, K.C. Hong and H.B. Park, Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population, Livestock Science, http://dx.doi.org/10.1016/j.livsci.2017.05.013 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Short communication Genome-wide association study for sow lifetime productivity related traits in a Landrace purebred population
J.H. Kanga, E.A. Leea, S.H. Leea, S.H. Kimb, D.H. Leec, K.C. Honga1, H.B. Parkd1 a
Division of Biotechnology, College of Life Sciences and Biotechnology, Korea University,
Anamro 145, 02841 Seoul, Republic of Korea. b
PigGene Korea, Inc. 2794 Yonggu-daero, 16866 Youngin, Republic of Korea
c
Department of Animal Life and Environment Science, Hankyong National University, 327,
Chungang-ro 327, 17579 Anseong, Republic of Korea d
Subtropical Livestock Research Institute, National Institute of Animal Science, Rural
Development Administration, 59350 Jeju, Republic of Korea
[email protected] [email protected]
Address for corresponding authors: Ki-Chang Hong, Division of biotechnology, College of Life Sciences and Biotechnology, Korea University, Anamro 145, Sungbuk-gu, 02841 Seoul, Republic of Korea
1
These corresponding authors contributed equally to this work 1
Hee-Bok Park, Subtropical Livestock Research Institute, National Institute of Animal Science, Rural Development Administration, 59350 Jeju, Republic of Korea
Abstract Improvement of sow lifetime productivity (SLP) is expected to increase farm performance and profitability. Many genes and environmental factors influence these complex traits. To identify quantitative trait loci and positional candidate genes for SLP-related traits, we performed a genome-wide association study (GWAS) using 656 Landrace purebred pigs from a commercial breeding stock farm. All sows in the study population were genotyped with the Illumina Porcine SNP60 BeadChip, and GWAS analyzed by linear mixed-effects model based association analysis using the GCTA program. Five genome-wide suggestive single nucleotide polymorphism markers were identified for the lifetime total number of born piglets and final parity. All five of these markers were highly associated with other SLPrelated traits, and all these markers were located within or near one particular gene, MEGF11 (multiple epidermal growth factor-like domains protein 11), on chromosome 1. This new positional candidate gene could contribute to increased sow lifetime productivity after the validation in other populations. Keywords: Sow lifetime productivity, genome-wide association study, Landrace pigs, quantitative trait loci.
2
1. Introduction The improvement of sow lifetime productivity (SLP)-related traits has become a great concern to the swine industry because enhancing such traits could substantially influence the profitability of commercial pig farms. SLP-related traits can be calculated via several methods based on data obtained from lifetime reproduction records (Serenius and Stalder, 2004). The SLP-related traits can be simply calculated by summation of piglets during entire lifetime of sows (e.g. lifetime total number of born piglets, lifetime total number of born alive piglets). On the other hand, these traits can be measured as lifetime pig production per pig day, which is called lifetime efficiency (e.g. lifetime total number of born piglets per day, lifetime total number of born alive piglets per day), to deal with both fertility and prolificacy of sows (Sasaki and Koketsu, 2008; Sobczyńska et al., 2013). Although higher parity sows are generally more profitable, they are often culled due to an increased risk of reproductive problems and low litter sizes. In fact, more than 30% of farmed sows are culled before their third parity, and almost 50% of farmed sows are replaced annually. This fast turnover rate is expected to increase genetic progress. However, this also can lead to reductions in economic efficiency for commercial swine farms (Rodriguez-Zas et al., 2003; Engblom et al., 2007). Therefore, sustained sow reproductive success should also be considered as one of the most critical profitability factors for pig farms (Sasaki and Koketsu, 2008; Sobczyńska et al., 2013; Iida et al., 2015). Because SLP-related traits can also be regarded as complex quantitative traits influenced by multiple genetic factors that are sensitive to environmental conditions, and because these traits can only be recorded when sows are culled, traditional selective breeding strategies are limited in their ability to improve SLP-related traits. Advancements in DNA technologies and statistical methodologies have facilitated the 3
detection of individual genetic factors at the quantitative trait locus (QTL) or quantitative trait nucleotide (QTN) level, which affect economically important traits in livestock (Andersson and Georges, 2004; Georges, 2007; Andersson, 2013). Genome-wide association studies (GWASs) using high-density single nucleotide polymorphism (SNP) chips, which encompass an entire genome and use historical recombination events accumulated within a population over many generations, have recently been used to identify QTL or QTN (Balding, 2006; Fan et al., 2006). Therefore, the identified QTL or QTN can be used for optimizing breeding programs focused on improving SLP-related traits. Onteru et al. (2011) reported their GWAS results on SLP-related traits. However, reports on GWAS for SLP-related traits are still quite rare. Thus, the aim of our study was to conduct GWAS to identify genetic markers and their positional candidate genes associated with several SLP-related traits in a Landrace purebred population.
2. Materials and methods 2.1 Experimental animals and phenotype recoding A total of 656 purebred Landrace female pigs (born between 2006 and 2014) from a single commercial breeding stock farm were used for this study. All animals were reared under the same controlled conditions. Average (SD) lactation days were 23.5 (5.5) and phenotypes were recorded on-site at the farm. Recorded SLP-related traits included lifetime total number of born (LTNB) piglets, lifetime total number of born alive (LNBA) piglets, and lifetime total number of piglets weaned (LPW). The lifetime TNB efficiency (LTNB365) was calculated as the LTNB divided by the length of lifetime in years. Likewise, the lifetime NBA efficiency (LNBA365) was calculated as the LNBA divided by the length of lifetime in years. In addition, the length of productive lifetime (LPL; first farrowing to culling), and lifetime non4
productive days per parity (LNDPP; non-productive days was defined as the number of days of farrowing and culling intervals) and final parity (FP) were used as phenotypes of this study as previously described (Serenius and Stalder, 2004, Onteru et al., 2011, Sasaki and Koketsu, 2008). Descriptive phenotypic statistics are listed in Supplementary table S1. This study followed animal care guidelines as prescribed by the institutional Animal Care and Use Committee at the National Institute of Animal Science, Republic of Korea.
2.2 Genome-wide association analysis Genomic DNA from blood samples was prepared using an iNtRONBio G-spin™ Total DNA Extraction Kit (iNtRON Biotechnology, Korea), and all pigs were genotyped with the Illumina PorcineSNP60 BeadChip (Illumina, USA). SNP markers were filtered according to the following criteria: (1) minor allele frequency < 0.05, (2) call rates < 90%, (3) HardyWeinberg equilibrium test (P ≤ 0.001, as calculated from the 2d.f.=1-test). After filtering, 36,926 autosomal SNP markers remained for GWAS. This quality control processes were conducted using the PLINK program (Purcell et al., 2007). Linear mixed-model association analysis was performed on this SNP chip data using the GCTA program (Yang et al., 2011). To account for the kinship relatedness within the study population, a single-marker association was performed using the mlma command in GCTA. The following linear mixed-effects model was used to evaluate the association between SNP markers and SLP-related traits:
y = Xb + Z1a + Z2u + e
where, y is the vector of each SLP-related trait; b is the vector of fixed effects, including 5
batch, age of first farrowing, and the number of live piglets at first parity; a represents SNP marker effects; u is the vector of random additive effects having a distribution u ~N(0, Ga2), where G is the genomic relationship matrix constructed using the 36,926 SNP markers and a2 is the additive genetic variance; e is a vector of random residual following a distribution e ~N(0, Ie2), in which I is the identity matrix and e2 is the residual variance. Z1 is the incidence matrix for a. X and Z2 are the incidence matrices for b and u. Bonferroni-adjusted “significant” (i.e., 0.05/36,926 SNPs; significant P = 1.35 × 106) and “suggestive” (i.e., 1/36,926 SNPs; suggestive P = 2.71 × 105) thresholds were established to address multiple testing issues. Unless otherwise stated, P-values are nominal.
3. Results and discussion Although no genome-wide significant SNP marker was identified, five genome-wide suggestive SNPs associated with the LTNB and FP traits were detected. H3GA0003177, located on chromosome 1, was the SNP marker most strongly associated with both LTNB (P = 8.33 × 106) and FP (P = 1.29 × 105). Moreover, these five SNP markers were also associated with other SLP traits at a genome-wide suggestive significance level, as indicated in Table 1. Specifically, H3GA0003177 was also associated with LNBA (P = 2.23 × 105) and LPL (P = 2.21 × 105), respectively. ASGA0005093 and ASGA0005108, both located on chromosome 1, were associated with LTNB, LNBA, LPL and FP (Table 1). ALGA0006736, located on chromosome 1, was associated with LTNB (P = 1.12 × 105), LPL (P = 2.26 × 105) and FP (P = 1.43 × 105), respectively. ASGA0005085, located on chromosome 1, was associated with LTNB (P = 2.36 × 105) and FP (P = 2.25 × 105) at the genome-wide suggestive level. The Manhattan plots for LTNB, LNBA and LPL traits are shown in Figure 1. 6
Interestingly, all five SNPs were located within (H3GA0003177) or near (ALGA0006736, ASGA0005085, ASGA0005093 and ASGA0005108) one particular gene, known as MEGF11 (multiple epidermal growth factor-like domains protein 11), as shown in Table 1. MEGF11 is located between base pairs 181,546,697 and 181,569,956 on chromosome 1. This region overlaps with QTLs affecting reproductive traits, such as teat number and non-functional nipples (Guo et al., 2008; Jonas et al., 2008), and exterior traits, especially feet conformation (Lee et al., 2003; Laenoi et al., 2011), as indicated in previous QTL mapping studies (PigQTLdb, http://www.animalgenome.org/cgi-bin/QTLdb/SS/index). Fewer non-functional nipples or strong leg performance may be associated with sow robustness and longevity. In humans, high expressions of MEGF11 in both adult and fetal brain tissue (especially in the cerebellum) was detected, whereas moderate expression was detected in the adult ovary (Nagase et al., 2001). These expression patterns may be similar to those seen in pigs and may serve important roles in both sow and fetus. MEGF11 is homologous with MEGF10 and performs a similar function (Suzuki and Nakayama, 2007; Kay et al., 2012). In fruit flies, drpr (Draper, CG2086), the sole Drosophila homolog of human genes MEGF11 and MEGF10 (Ziegenfuss et al., 2008), leads to significantly reduced median lifespans (six to eight weeks) and age-dependent declines in climbing performance (Draper et al., 2014). Although no functional research currently supports an association between MEGF11 and SLP traits, further study of this new candidate gene for SLP is necessary to verify its involvement in reproductive physiology affecting SLP. In summary, we performed a GWAS and detected a QTL and a novel positional candidate gene associated with SLP-related traits. This result could be useful to optimize breeding program to improve the SLP-related traits after further functional studies and validation of the association in other independent populations. 7
Conflict of interest statement None.
Acknowledgements This research was conducted with the support of the Bio-industry Technology Development Program (grant number 114065), Ministry of Agriculture, Food and Rural Affairs, Republic of Korea.
References Andersson, L., 2013. Molecular consequences of animal breeding. Curr. Opin. Genet. Dev. 23, 295-301. Andersson, L., Georges, M., 2004. Domestic-animal genomics: deciphering the genetics of complex traits. Nat. Rev. Genet. 5, 202-212. Balding, D.J., 2006. A tutorial on statistical methods for population association studies. Nat. Rev. Genet. 7, 781-791. Draper, I., Mahoney, L.J., Mitsuhashi, S., Pacak, C.A., Salomon, R.N., Kang, P.B., 2014. Silencing of drpr Leads to Muscle and Brain Degeneration in Adult Drosophila. Am. J. Pathol. 184, 2653-2661. Engblom, L., Lundeheim, N., Dalin, A.-M., Andersson, K., 2007. Sow removal in Swedish commercial herds. Livest. Sci. 106, 76-86. Fan, J.-B., Chee, M.S., Gunderson, K.L., 2006. Highly parallel genomic assays. Nat. Rev. Genet. 7, 632-644. 8
Georges, M., 2007. Mapping, Fine Mapping, and Molecular Dissection of Quantitative Trait Loci in Domestic Animals. Annu. Rev. Genomics Hum. Genet. 8, 131-162. Guo, Y.M., Lee, G.J., Archibald, A.L., Haley, C.S., 2008. Quantitative trait loci for production traits in pigs: a combined analysis of two Meishan × Large White populations. Anim. Genet. 39, 486-495. Iida, R., Piñeiro, C., Koketsu, Y., 2015. High lifetime and reproductive performance of sows on southern European Union commercial farms can be predicted by high numbers of pigs born alive in parity one1. J. Anim. Sci. 93, 2501-2508. Jonas, E., Schreinemachers, H.-J., Kleinwächter, T., Ün, C., Oltmanns, I., Tetzlaff, S., Jennen, D., Tesfaye, D., Ponsuksili, S., Murani, E., Juengst, H., Tholen, E., Schellander, K., Wimmers, K., 2008. QTL for the heritable inverted teat defect in pigs. Mamm. Genome 19, 127-138. Kay, J.N., Chu, M.W., Sanes, J.R., 2012. MEGF10 and MEGF11 mediate homotypic interactions required for mosaic spacing of retinal neurons. Nature 483, 465-469. Laenoi, W., Uddin, M.J., Cinar, M.U., Große-Brinkhaus, C., Tesfaye, D., Jonas, E., Scholz, A.M., Tholen, E., Looft, C., Wimmers, K., Phatsara, C., Juengst, H., Sauerwein, H., Mielenz, M., Schellander, K., 2011. Quantitative trait loci analysis for leg weaknessrelated traits in a Duroc × Pietrain crossbred population. Genet. Sel. Evol. 43, 13. Lee, G., Archibald, A., Garth, G., Law, A., Nicholson, D., Barr, A., Haley, C., 2003. Detection of quantitative trait loci for locomotion and osteochondrosis-related traits in Large White x Meishan pigs. Anim. Sci. 76, 155-166. Nagase, T., Nakayama, M., Nakajima, D., Kikuno, R., Ohara, O., 2001. Prediction of the Coding Sequences of Unidentified Human Genes. XX. The Complete Sequences of 100 New cDNA Clones from Brain Which Code for Large Proteins in vitro. DNA Res. 8, 859
95. Onteru, S.K., Fan, B., Nikkilä, M.T., Garrick, D.J., Stalder, K.J., Rothschild, M.F., 2011. Whole-genome association analyses for lifetime reproductive traits in the pig. J. Anim. Sci. 89, 988-995. Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M.A.R., Bender, D., Maller, J., Sklar, P., de Bakker, P.I.W., Daly, M.J., Sham, P.C., 2007. PLINK: A Tool Set for WholeGenome Association and Population-Based Linkage Analyses. Am. J. Hum. Genet. 81, 559-575. Rodriguez-Zas, S.L., Southey, B.R., Knox, R.V., Connor, J.F., Lowe, J.F., Roskamp, B.J., 2003. Bioeconomic evaluation of sow longevity and profitability. J. Anim. Sci. 81, 29152922. Sasaki, Y., Koketsu, Y., 2008. Sows having high lifetime efficiency and high longevity associated with herd productivity in commercial herds. Livest. Sci. 118, 140-146. Serenius, T., Stalder, K.J., 2004. Genetics of length of productive life and lifetime prolificacy in the Finnish Landrace and Large White pig populations1. J. Anim. Sci. 82, 3111-3117. Sobczyńska, M., Blicharski, T., Tyra, M., 2013. Relationships between longevity, lifetime productivity, carcass traits and conformation in Polish maternal pig breeds. J. Anim. Breed. Genet. 130, 361-371. Suzuki, E., Nakayama, M., 2007. The mammalian Ced-1 ortholog MEGF10/KIAA1780 displays a novel adhesion pattern. Exp. Cell Res. 313, 2451-2464. Yang, J., Lee, S.H., Goddard, M.E., Visscher, P.M., 2011. GCTA: A Tool for Genome-wide Complex Trait Analysis. Am. J. Hum. Genet. 88, 76-82. Ziegenfuss, J.S., Biswas, R., Avery, M.A., Hong, K., Sheehan, A.E., Yeung, Y.-G., Stanley, E.R., Freeman, M.R., 2008. Draper-dependent glial phagocytic activity is mediated by 10
Src and Syk family kinase signalling. Nature 453, 935-939.
11
SNP ID (Accession number) ALGA0006736 (rs81349337) H3GA0003177 (rs81349342) ASGA0005085 (rs81349346) ASGA0005093 (rs81349365) ASGA0005108 (rs81349396)
181,685,718
181,534,272
G/A
T/C
T/C
0.50
0.50
0.42
0.42
MEGF11
MEGF11
MEGF11
MEGF11
MEGF11
RAB11A
54,286
41,786
8,211
within
96,517
41,119
1.35 × 10-5*
1.47 × 10-5*
2.36 × 10-5*
8.33 × 10-6*
1.12 × 10-5*
P-value
LTNB
1.63 × 10-4
1.44 × 10-4
2.13 × 10-4
3.18 × 10-5
4.87 × 10-5
P-value
LTNB365
1.64 × 10-5*
2.12 × 10-5*
3.39 × 10-5
2.23 × 10-5*
2.61 × 10-5
P-value
LNBA
3.34 × 10-4
3.75 × 10-4
5.37 × 10-4
2.55 × 10-4
3.23 × 10-4
P-value
LNBA365
7.65 × 10-4
9.16 × 10-4
1.17 × 10-3
3.54 × 10-3
2.99 × 10-3
P-value
LPW
1.48 × 10-5*
1.65 × 10-5*
2.69 × 10-5
2.21 × 10-5*
2.26 × 10-5*
P-value
LPL
1.29 × 10-5*
1.38 × 10-5*
2.25 × 10-5*
1.29 × 10-5*
1.43 × 10-5*
P-value
FP
MAF4 Closest genes5 Distance (bp)7
181,708,122
A/G
0.50
Alleles3
181,741,697
A/G
Location (bp)2
181,754,197
Table 1. Single nucleotide polymorphism markers identified by the genome-wide association study.
SSC1
1
1
1
1
1
Sus scrofa chromosome
1
SNP position reported according to the SSCROFA 10.2 genome annotation.
2
Major and minor alleles
3
Minor allele frequency
4
Nearest gene to indicated SNP defined in a region of ±500 kb
5
Coordinates of the indicated genes according to SSCROFA 10.2
6
SNP designated as within a gene or as distance (bp) from a gene region
7
Genome-wide suggestive significant
*
12
Fig. 1. GWAS results for SLP-related traits in a purebred Landrace population. Panels on the left represent the association between SLP-related traits and 36,926 mapped SNP markers on 18 porcine autosomes. In these panels, the y-axis represents the log10 (P-values) and x- axis indicates the physical map position of the SNP markers on the pig chromosome. Red horizontal lines represent genome-wide “significant” thresholds (5.87); blue horizontal lines represent genome-wide “suggestive” thresholds (4.57). Panels on the right represent the corresponding quantile-quantile (QQ) plots for the association of 36,926 SNP markers with SLP-related traits: (a) LTNB, (b) LNBA, and (c) LPL. 13
Highlight Sow lifetime productivity (SLP)-related traits are important because enhancing such traits could substantially affect the profitability of commercial pig farms. A genome-wide association study was performed to identify quantitative trait loci and their positional candidate genes, which could be used for breeding programs for SLP-related traits. A total of five genome-wide suggestive significant single nucleotide polymorphisms were identified. All five SNPs were located within or near MEGF11 (multiple epidermal growth factor-like domains protein 11) on chromosome 1.
14