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University of Copenhagen, Grønnegårdsvej 7, 1870 Frederiksberg, Denmark Cesses Covered Were Related to Each Other Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with feed conversion ratio in beef cattle Satana, Miguel Henrique de Almedia ; Junior, Gerson Antônio Oliveira ; Cesar, Aline Silva Mello; Freua, Mateus Castelani; Gomes, Rodrigo da Costra ; Silva, Saulo da Luz e ; Leme, Paulo Roberto; Fukumasu, Heidge; Carvalho, Minos Esperandio; Ventura, Ricardo Vierira; Coutinho, Luiz Lehmann; Kadarmideen, Haja; Ferraz, José Bento Sterman Published in: Journal of Applied Genetics DOI: 10.1007/s13353-016-0344-7 Publication date: 2016 Document license: Other Citation for published version (APA): Satana, M. H. D. A., Junior, G. A. O., Cesar, A. S. M., Freua, M. C., Gomes, R. D. C., Silva, S. D. L. E., Leme, P. R., Fukumasu, H., Carvalho, M. E., Ventura, R. V., Coutinho, L. L., Kadarmideen, H., & Ferraz, J. B. S. (2016). Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with feed conversion ratio in beef cattle. Journal of Applied Genetics, 57(4), 495-504. https://doi.org/10.1007/s13353-016-0344-7 Download date: 25. Sep. 2021 J Appl Genetics DOI 10.1007/s13353-016-0344-7 ANIMAL GENETICS • ORIGINAL PAPER Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle Miguel Henrique de Almeida Santana1,2 & Gerson Antônio Oliveira Junior3 & Aline Silva Mello Cesar3 & Mateus Castelani Freua2 & Rodrigo da Costa Gomes4 & Saulo da Luz e Silva2 & Paulo Roberto Leme2 & Heidge Fukumasu2 & Minos Esperândio Carvalho2 & Ricardo Vieira Ventura2,5 & Luiz Lehmann Coutinho6 & Haja N. Kadarmideen1 & José Bento Sterman Ferraz2 Received: 29 September 2015 /Revised: 20 January 2016 /Accepted: 2 March 2016 # Institute of Plant Genetics, Polish Academy of Sciences, Poznan 2016 Abstract The use of genome-wide association results com- explained by each window. The CNVs were detected with bined with other genomic approaches may uncover genes and PennCNV software using the log R ratio and B allele fre- metabolic pathways related to complex traits. In this study, the quency data. CNV regions (CNVRs) were identified with phenotypic and genotypic data of 1475 Nellore (Bos indicus) CNVRuler and a linear regression was used to associate cattle and 941,033 single nucleotide polymorphisms (SNPs) CNVRs and the FCR. Functional annotation of associated were used for genome-wide association study (GWAS) and genomic regions was performed with the Database for copy number variations (CNVs) analysis in order to identify Annotation, Visualization and Integrated Discovery candidate genes and putative pathways involved with the feed (DAVID) and the metabolic pathways were obtained from conversion ratio (FCR). The GWASwas based on the Bayes B the Kyoto Encyclopedia of Genes and Genomes (KEGG). approach analyzing genomic windows with multiple regres- We showed five genomic windows distributed over chro- sion models to estimate the proportion of genetic variance mosomes4,6,7,8,and24thatexplain12%ofthetotal genetic variance for FCR, and detected 12 CNVRs (chro- mosomes 1, 5, 7, 10, and 12) significantly associated [false discovery rate (FDR) < 0.05] with the FCR. Significant ge- nomic regions (GWAS and CNV) harbor candidate genes Communicated by: Maciej Szydlowski involved in pathways related to energetic, lipid, and pro- tein metabolism. The metabolic pathways found in this * Miguel Henrique de Almeida Santana study are related to processes directly connected to feed efficiency in beef cattle. It was observed that, even though different genomic regions and genes were found between the two approaches (GWAS and CNV), the metabolic pro- 1 Faculty of Health and Medical Sciences, University of Copenhagen, Grønnegårdsvej 7, 1870 Frederiksberg, Denmark cesses covered were related to each other. Therefore, a combination of the approaches complement each other 2 Faculdade de Zootecnia e Engenharia de Alimentos, University of São Paulo, Duque de Caxias Norte, 225, and lead to a better understanding of the FCR. 13635-900 Pirassununga, Brazil . 3 Department of Animal Science, Iowa State University, Keywords CNV Feed efficiency Genomics GWAS Ames, IA 50011, USA Nellore cattle . SNPs 4 Empresa Brasileira de Pesquisa Agropecuária, CNPGC/EMBRAPA, BR 262 km 4, 79002-970 Campo Grande, Brazil 5 University of Guelph, 50 Stone Road East, Guelph, Ontario N1G Introduction 2W1, Canada 6 Escola Superior de Agricultura Luiz de Queiroz, University of São Feeding cattle is a major cost in beef production and it directly Paulo, 13418-900 Piracicaba, Brazil affects the overall profitability of the meat industry. Several J Appl Genetics strategies have been proposed to reduce this cost, focusing samples taken from each of the tests had been approved by mainly on the improvement of feed efficiency. The feed con- the respective ethics committees of each study (Gomes et al. version ratio (FCR) is a feed efficiency trait that measures the 2013; Santana et al. 2013; Alexandre et al. 2015). animal’s capacity to convert feed consumed into the desired output (e.g., meat deposition or gained mass). The FCR is not Animals and phenotype a direct measurement, and it is computed as a function of the feed consumed, body weight gain, and duration of the trial The phenotypic data of 1475 Nellore (B. indicus) young bulls (Arthur et al. 2001). and steers were used from 16 different studies focusing on The discovery of DNA variants, such as single nucleotide feed efficiency conducted in Brazil from 2007 to 2013. The polymorphisms (SNPs) and copy number variations (CNVs), number of animals evaluated per test ranged from 45 to 120, which may be associated with the genetic variation of desired and the animals had an average age of 574 ± 95 days and live economic traits, has played an important role in livestock ge- weight of 381 ± 45 kg at the beginning of the experiments. netics (Kijas et al. 2011). In recent years, high-throughput These animals were from different breeding programs. technologies have led to the discovery of markers associated The tests were conducted in feedlots equipped with three with economic traits by genome-wide association studies different types of installation: two automated systems (GWAS), which allowed the identification of subsets of (GrowSafe and Calan Gates) and an individual pen system. markers that explain an important portion of the variation of Before testing, a period of adaptation to diets and facilities was these traits (Barendse et al. 2007; Moore et al. 2009;Rolfetal. conducted for no less than 21 days. Individual feed 2012). The use of genomic information can be a strategy for intake was measured daily for 70 to 90 days, with an the improvement of interesting phenotypes such as the FCR average of 84 days. In addition, the feed was periodically by increasing the prediction accuracy of young animal candi- analyzed for its chemical composition in order to adjust the dates for genetic selection (Hayes et al. 2007), and, thus, ac- dry matter intake (DMI). The diet was offered twice daily as celerating genetic gain by reducing the generation interval. total mixed ration. More details about the tests, diets, and The association between markers and important phenotypes managements appear in Gomes et al. (2013), Santana et al. can be improved by using other genomic approaches, such as (2013), and Alexandre et al. (2015). genomic prediction, to select animals (Bishop and Woolliams During the experimental period, the animals were weighed 2014;Kadarmideen2014). regularly every 21 days to obtain the individual body weight Additionally, several studies have reported the viability of (BW). These data were used to calculate the average daily gain using the information from SNPs to identify quantitative trait (ADG), which was estimated as the slope of the linear regres- loci (QTL) and candidate genes associated with phenotypes of sion of BW by individual experimental days. Feed efficiency interest. Moreover, pathway analyses from GWAS results have was evaluated by the FCR, which was estimated by dividing been applied to aggregate information about genes and the the DMI by the ADG. Phenotypes (ADG, DMI, and FCR) were physiology involved with important diseases and economical tested for normality (Shapiro–Wilk, P < 0.05) and the data that traits (Carbonetto and Stephens 2013),andtounderstandthe exceeded three standard deviations above or below the mean molecular and physiological mechanisms involved in feed ef- were considered outliers and excluded from further analyses. ficiency in beef cattle (Bolormaa et al. 2011; Snelling et al. 2011;Luetal.2013). Thus, the combination of GWAS with Genotypes, imputation, and informativeness other approaches can be interesting to better explain these genes and pathways related to complex traits. There are alter- The genotypic data from 3776 Nellore cattle were used in this native frameworks, such as CNVs, that can be useful to explain study and these animals were genotyped with four different the variability and unveil the molecular architecture of com- commercial products according to manufacturer: Illumina plex traits (Hou et al. 2012b; Tamari et al. 2013;Bickhartand BovineSNP50® version 2 BeadChip (54,609 SNPs), Liu 2014). The objective of this study was to identify candidate Illumina BovineHD® Genotyping BeadChip (777,962 genes and putative pathways involved with the FCR in Nellore SNPs), GGP Indicus Neogen HD® (84,379 SNPs), and cattle (Bos indicus) from GWAS and CNV results. Affymetrix Axiom® Genome-Wide BOS 1 Array (648,874 SNPs). The genotypes were tested to ensure that they were determined correctly and clustering provided by the manufac- Materials and methods turer was correct. First, only samples with genotype calls greater than 0.70 and call rate over 90 % were retained. Ethical statement Additionally, errors of duplicate samples were tested by cal- culating the proportion of alleles identical by state (IBS) of 10, No statement by the local ethics committee was required be- 000 SNPs randomly sampled, and all possible pairs of sam- cause the data used were from other experiments.
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