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2 DR THAISE MELO (Orcid ID : 0000-0003-0983-4602)

3 DR MARINA R. S. FORTES (Orcid ID : 0000-0002-7254-1960)

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6 Article type : Original Article

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9 Short Running Title: Across-breed QTL validation for sexual precocity in tropical cattle 10 Title: ACROSS-BREED VALIDATION STUDY CONFIRMS AND IDENTIFIES 11 NEW LOCI ASSOCIATED WITH SEXUAL PRECOCITY IN BRAHMAN AND 12 NELLORE CATTLE1 13 Thaise Pinto de Melo*, Marina Rufino Salinas Fortes†‡, Ben Hayes‡, Lucia Galvão de 14 Albuquerque*§, Roberto Carvalheiro*§ 15 16 *Department of Animal Science, School of Agricultural and Veterinarian Sciences, 17 FCAV/ UNESP - Sao Paulo State University, Jaboticabal, Sao Paulo, 14884-900, 18 Brazil. 19 †The University of Queensland, School of Chemistry and Molecular Biosciences, St 20 Lucia, Queensland 4072, Australia. 21 ‡The University of Queensland, Queensland Alliance for Agriculture and Food 22 Innovation, St Lucia, Queensland 4072, Australia. 23 §National Council for Scientific and Technological Development (CNPq), Brasília, 24 Distrito Federal, Brazil. 25 Corresponding author: Roberto Carvalheiro, School of Agricultural and Veterinarian 26 Sciences, FCAV/ UNESP - Sao Paulo State University, Jaboticabal, Brazil. Email:

27 [email protected] Manuscript 28

This is the author manuscript accepted for publication and has undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/JBG.12429

This article is protected by copyright. All rights reserved 29 ABSTRACT: The aim of this study was to identify candidate regions associated with 30 sexual precocity in Bos indicus. Nellore and Brahman were set as validation and 31 discovery populations, respectively. SNP selected in Brahman to validate in Nellore 32 were from: gene regions affecting reproductive traits (G1), and significant SNP (P ≤ 10- 33 3) from a meta-analysis (G2). In the validation population early pregnancy (EP) and 34 scrotal circumference (SC) were evaluated. To perform GWAS in validation population 35 we used regression and Bayes C. SNP with P ≤ 10-3 in regression and Bayes Factor ≥ 3 36 in Bayes C were deemed significant. Significant SNP (for EP or SC) or SNP in their ± 37 250 Kb vicinity region, which were in at least one discovery set (G1 or G2) were 38 considered validated. SNP identified in both G1 and G2 were considered candidate. For 39 EP 145 SNP were validated in G1 and 41 in G2, for SC these numbers were 14 and 2. 40 For EP 21 candidate SNP were detected (G1 and G2). For SC no candidate SNP were 41 identified. Validated SNP and their vicinity region were located close to QTL or genes 42 related to reproductive traits and were enriched in gene ontology terms related with 43 reproductive success. These are therefore, strong candidate regions for sexual precocity 44 in Nellore and Brahman. 45 Keywords: Bos indicus, discovery population, reproductive traits, SNP validation, 46 tropical beef cattle 47 INTRODUCTION 48 49 Across-breed validation studies are commonly used to validate quantitative trait 50 loci (QTL) for several traits. In Genome-wide association studies (GWAS) those 51 significant markers under an empirical P-value for the same or correlated traits in 52 different breeds are likely tagging QTL that segregate across-breeds. These QTLs may 53 harbor some important genes affecting both populations. Karlsson et al. (2007) used this 54 approach to validate single nucleotide polymorphisms (SNP) markers in different dog 55 breeds. They notice that this strategy was highly efficient to fine-mapping across 56 breeds. 57 The probability of finding common QTL for correlated traits in breeds that share 58 common ancestry is expected to be higher than in breeds with very distinct genetic Author Manuscript 59 origin. This is because breeds that do not share a recent common ancestor are more 60 genetically distinct from each other. Genetic differences increase with distance to 61 common ancestors. Distinct genetic origin affects the linkage disequilibrium pattern 62 between SNPs at long-ranges, and by consequence it affects QTL mapping (Goddard &

This article is protected by copyright. All rights reserved 63 Hayes, 2009). As Nellore and Brahman are both Bos indicus breeds, and Brahman was 64 originally developed by three base breeds, Gir, Guzerat and Nellore (Briggs & Briggs, 65 1980), the likelihood of both breeds sharing QTL controlling correlated traits is higher 66 than in unrelated breeds. 67 Several strategies have been used to conduct across-breed validation studies. 68 Pryce et al. (2010) used two dairy breeds to validate QTL for milk production and 69 fertility traits. They distributed Holstein bulls in a discovery population and younger 70 Holstein bulls and Jersey bulls in a validation population. SNP that were detected as 71 significant at an empirical threshold P-value in discovery and validation populations 72 were considered validated. Also validating fertility traits in dairy cattle, Höglund et al. 73 (2014) used three breeds to validate genomic associations. They used one breed as 74 discovery population and the other two breeds as validation populations. They argued 75 that using two populations simultaneously to validate significant associations is a 76 powerful strategy to decrease the risk of false positive association. 77 Genic regions are strong candidate regions to present QTL segregating across 78 related breeds because it is expected that the metabolic pathways in which these genes 79 are involved are conserved across breeds. Also, regions with pleiotropic effect across 80 related traits could result in higher number of true positive validated associations across 81 breeds, because genes that are controlling multiple traits in a breed might preserve 82 similar pattern of pleiotropic effect in another related breed (Saatchi et al., 2014). 83 The aim of this study was to validate in a Nellore population genomic regions 84 associated with sexual precocity that were reported for Brahman. We used as discovery 85 data two SNP sets pre-selected in a Brahman population, 1) from gene regions 86 previously reported as significant for reproductive traits, and 2) from significant 87 associations detected in a meta-analysis study of sexual precocity traits. 88 89 MATERIAL AND METHODS 90 Ethics Statement 91 All managements and procedures involving production, maintenance and use of 92 Nellore animals were certified and approved by the National Council of Animal Author Manuscript 93 Experimentation Control (CONCEA, 2008) and Use Committee at University of Sao 94 Paulo, Jaboticabal Campus (18.340/16). Regarding Brahman animals, Animal care and 95 Use committee approval was not required because the data is from existing databases 96 described in the following section.

This article is protected by copyright. All rights reserved 97 98 Discovery population 99 The discovery population was composed by Brahman animals. Phenotypes were 100 provided by Cooperative Research Centre for Beef Genetic Technologies (Beef CRC). 101 Brahman phenotypes included the female traits age when the first corpus luteum (CL) 102 was observed (AGECL), first postpartum anoestrus interval (PPAI), ability to ovulate 103 prior to weaning the calf (PW), and the male traits scrotal circumference (SC) measured

104 at 12, 18 and 24 months of age (SC12, SC18, SC24). 105 The AGECL was defined as the number of days from the heifer birth to the first 106 CL detected. PPAI, measured in days, was calculated as the difference between the 107 calving date and the date of the first observed ovulation postpartum. PW, a binary trait 108 was defined as 0 for females that had success to ovulate before weaning her calf or 1 for 109 those females that failed. For all female traits ovarian ultrasounds were carried out to 110 verify the presence of CL that is an indicator of the ovulation, at every 4 to 6 weeks 111 after heifers achieved 200 Kg of weight. 112 Scrotal circumference was measured in cm, with a standard metal tape. For 113 females and males, contemporary groups (CG) were defined by the concatenation year 114 of birth and management group information (defined as cohorts). The age of young 115 bulls at recording was considered a covariate for SC. Details about animals, cohorts and 116 phenotypes are described in Johnston et al. (2009), Johnston et al. (2010), Burns et al. 117 (2013), Corbet et al. (2013) and Fortes et al. (2018). 118 Animals were genotyped with the Illumina BovineSNP50 V1 and V2. Genotypes 119 were imputed for high-density panel using Beagle software v.3.2 (Browning & 120 Browning, 2009) and a reference population of representative animals of the Beef CRC 121 population genotyped using the high-density Illumina Bovine HD Assay (Illumina, San 122 Diego, CA, USA), as described by Fortes et al. (2013a). Quality control excluded 123 samples with call rate < 98%, SNP in non-autosomal regions, with call rate < 85% and 124 minor allele frequency (MAF) < 0.02. The number of SNP after quality control was 125 625,041 for females and 612,992 for males. Details about genotypes and imputation are 126 described in Fortes et al. (2013a). Author Manuscript 127 128 Validation population 129 Data from Nellore animals were used as validation population. Phenotypic 130 information was obtained from Alliance Nellore dataset. The animals considered in this

This article is protected by copyright. All rights reserved 131 study were born in eight farms distributed over Midwest, Southeast and Northeast of 132 Brazil. In general, two breeding seasons are applied during the year, where the females 133 are either artificially inseminated or naturally mated. The heifers are exposed in the 134 early breeding season at around 16 months of age. After 60 days of the early breeding 135 season, pregnancy is confirmed and those females that failed in conceiving in the first 136 breeding season had a second opportunity at around 2 years old. 137 Nellore phenotypes used here are early pregnancy (EP) and scrotal circumference

138 (SCN). The EP, a binary trait, assumed the value of 2 for heifers that had success in 139 calving before 31 months of age; and 1 for heifers that failed in calving before that age. 140 And SC was measured, in cm, from the widest point of the scrotum, at around 16 141 months of age. Details about Nellore animals and phenotypes are described by Costa et 142 al. (2015) and Irano et al. (2016). Summary statistics of all traits for both populations 143 are presented in Table 1.

144 Fixed effects for EP and SCN were concatenated in CG and included information

145 of herd, year and season of birth, weaning and yearling management groups. For SCN, it 146 was excluded phenotypic information that was not in the interval of ± 3 SD from the 147 mean of each CG. Also, CG with less than 3 animals were excluded. For EP, were 148 excluded CG without variability, in which all females had the same categorical

149 response, and CG with less than four animals. For SCN, the age of the animal at the 150 recording was included as a covariate in the model. It was considered in the analysis 151 only animals with age ranging from 10 to 24 months. A total of 20 animals that 152 presented ages out of this interval were removed. 153 As Nellore dataset presented both genotyped and non-genotyped animals, for this 154 population phenotypes were pre-corrected for the fixed effect CG to avoid biased fixed 155 effect estimates. A regular mixed animal model (Henderson, 1984) was used to pre- 156 correct phenotypes. Pre-corrected EP was expressed in a continuous scale. 157 Markers were genotyped using the high-density Illumina Bovine HD Assay 158 (Illumina, San Diego, CA, USA) and GeneSeek Genomic Profiler Indicus HD - 159 GGP75Ki (Neogen Corporation, Lincoln, NE, USA), which contain 777,962 and 74,677 160 SNP, respectively. Imputation of the smaller panel (GGP75Ki) to the high-density panel Author Manuscript 161 was performed by using the software FImpute v.2.2 (Sargolzaei et al., 2014). It were 162 excluded animals with call rate < 0.90, SNP with MAF < 0.01, call rate < 0.95, Hardy- 163 Weinberg equilibrium test P-value < 10-5 and in non-autosomal regions. After quality

This article is protected by copyright. All rights reserved 164 control, remained 1,796 females genotyped for 412,876 SNP and 4,261 males 165 genotyped for 512,063 SNP. 166 167 Across-breed Validation 168 To select significant SNP from the discovery population two selection approaches 169 were adopted: 1) SNP in gene regions that were previously associated with sexual 170 precocity traits in a Brahman population (G1), or 2) significant SNP from two 171 independent meta-analyses, one for female and other for male traits, measured in the 172 same Brahman population of G1 (G2). Details about these meta-analyses are further 173 described. 174 To select SNP in genic regions (G1), it was firstly verified which genes were 175 associated with sexual precocity traits in Brahman cattle. These genes were pre-selected 176 from previous studies using the same Brahman population used here (Fortes et al., 177 2012a; Fortes et al., 2012b; Porto-Neto et al., 2015; Fortes et al., 2016; Nguyen et al., 178 2017). Those studies were either GWAS or transcriptional gene expression studies. SNP 179 inside genes or that were located in a region of 250 Kb upstream or downstream from 180 genes were selected for the discovery dataset. A total of 2,753 genes located in 181 autosome chromosomes were described in those papers. These genes were mapped by 182 using the Biomart R package (Durinck et al., 2005, 2009). 183 For selecting SNP for G2, it was verified which SNP presented significant 184 association (P-value ≤ 10-3) in both meta-analyses for female (AGECL, PPAI and PW)

185 and male (SC12, SC18, SC24). 186 A total of 30 SNP were in both SNP sets, i.e., in genic regions and in significant 187 regions of the meta-analysis study for female traits. For male traits, just one SNP was in 188 common between these two SNP sets. 189 A genome mixed model proposed by Kang et al. (2010) was used to estimate SNP 190 effects and their standard errors used in meta-analyses, as follows: 191 = + + + , (1) 192 where y is the vector of Brahman phenotypes, AGECL, PPAI, PW, SC , SC , or SC , � �� �� �� � 12 18 24 193 X is an incidence matrix relating CG fixed effects in β with the phenotypes in y, and the Author Manuscript 194 age of the young bull at the measurement as a covariate for SC, s is a vector with 195 genotypes coded as 0, 1 or 2 according to the number of B allele copies, is a vector 196 containing allelic substitution effects, Z is the incidence matrix of polygenic random � 197 effects of the animals in u and ε is the vector of residuals. Vectors u and ε followed

This article is protected by copyright. All rights reserved 2 2 198 normal distribution with u~N(0, Gσ a) and ε~N(0, Iσ e), respectively, and G is the 199 genomic relationship matrix, that relates all individuals, calculated as in the first method

2 200 described in VanRaden (2008), σ a is the additive genetic variance, I is an identity 2 201 matrix and σ e is the residual variance. SNP effects were calculated by using the SNP & 202 Variation Suite (SVS) software (Release 8.3.0, Golden Helix, Inc., 2014). 203 A multi-trait approach described by Bolormaa et al. (2014) was used to perform 204 the meta-analyses. This method is a statistic test that follows a χ2 distribution with n 205 degrees of freedom, and n is the number of traits considered in meta-analysis. The χ2 206 statistic is calculated as follows:

2 -1 207 Multi-trait χ = t’i V ti, (2) -1 208 where t’i is the transpose vector of ti, and V is a 3 x 3 inverse matrix of the correlation 209 between the t-values of the three traits for female and male across all SNP markers in 210 common among these traits. The vector containing the t-values of the ith SNP effects

211 estimated by each independent GWAS (ti) was computed as:

212 ti=ai /SE(ai), (3)

213 where SE (ai) is the standard error of the SNP effect vector ai. 214 SNP with an empirical P-value ≤ 10-3 were considered significant in the meta- 215 analysis of the discovery population. 216 217 Statistical Methods 218 To perform GWAS in Nellore validation population (700 K panel) two statistical 219 methods were used, regression (Zhang et al., 2010) and Bayes C (Habier et al., 2011), 220 which model was implemented as:

221 = + = 1 + , (4) � 222 Where y is the vector � containing1� ∑� pre-corrected������ � phenotypes (corrected as

223 previously described) for Nellore traits, EP and SCN, 1 is a vector of ones, μ is the

224 overall mean, gi is the vector with the genotypes of the animals (coded as 0, 1 or 2, th 225 according to the number of B allele copies) for the i SNP effect in bi, and δi is an 226 indicator variable, which takes value 0 or 1, and is sampled from a binomial distribution

227 with parametersAuthor Manuscript n and π, where n is the total number of SNP and π is the proportion of 228 SNP with null effect in the model. It was assumed that π followed a prior beta 229 distribution with parameters α = 108 and β = 1010, which in practice is equivalent to fix

This article is protected by copyright. All rights reserved 2 230 π = 0.99 (Legarra et al., 2014). For the variance of SNP effects (σ g) and the residual 2 231 variance (σ e) it was assumed a scaled inverse chi-squared prior distribution. 232 Bayes C analyses were performed by using GS3 software (Legarra et al., 2014). It 233 was ran a single Markov chain Monte Carlo with 500,000 iterations, a burn-in period of 234 50,000, and a thinning interval of 50 iterations. 235 Model used in regression analyses was similar to that presented in Equation 1, 236 except that the vector containing the fixed effects and its incidence matrix ( were 237 replaced by a vector of ones and the mean ( ), with the same assumption for the ��) 238 distribution of random effects described in Equation 1. This model was implemented in 1� 239 the GAPIT software (Zhang et al., 2010), and consists in a regular mixed linear model 240 with a genomic relationship matrix. 241 242 SNP validation criteria 243 The validation criteria for SNPs followed 5 steps: 244 1) Verify which SNPs were significant from regression analysis (P ≤ 10-3); 245 2) Verify which SNPs were significant from Bayes Cpi analysis (Bayes Factor ≥ 3); 246 3) Select corroborate SNPs in common between regression and Bayes Cpi methods; 247 4) Identify which SNPs selected in step 3 were located in genic regions (± 250 Kb) 248 associated with sexual precocity in the Brahman population studied here; 249 5) Identify which SNPs selected in step 3 were significant in the meta-analysis with 250 Brahman traits (or were in ± 250 Kb away). 251 Steps 1 and 2 were performed in the validation population, i.e., in Nellore, while 252 steps 4 and 5 were performed in Brahman, that was the discovery population. SNPs 253 selected in steps 4 and 5 were validated for G1 and G2, respectively. SNPs in common 254 between G1 and G2 were considered strong candidates. These steps are summarized in 255 Figure 1. 256 Bayes Factor was calculated as in Varona et al. (2001):

(1 ) 257 � = ― � (5) (1 ) � �� ― � 258 where p is a posteriori probability of an SNP present a non-zero effect and π is a priori Author Manuscript 259 probability of an SNP to be included in analysis. 260 261 Gene Ontology Analysis

This article is protected by copyright. All rights reserved 262 The region of ± 250 Kb surrounding the validated SNP was scanned to find 263 neighbour genes, which were used to perform the gene ontology analysis using David 264 software (v.6.7) (Huang et al., 2009a; 2009b). G1 and G2 genes were analysed together

265 for EP and SCN. There were a total of 579 genes for EP and 110 genes for SC (G1 and 266 G2), from which 467 and 104 genes were recognized by David software for EP and

267 SCN, respectively. 268 269 RESULTS 270 The total number of significant SNP detected in meta-analyses was 747 SNP for 271 female traits and 10 SNP for male traits (P-value ≤ 0.001). This large difference may be 272 explained because the most significant SNP for SC in Brahman were located on 273 chromosome X, which was removed in the current analysis. 274 Regression and Bayesian methods identified some of the same SNP as significant:

275 a total of 302 SNP for EP and 40 SNP for SCN were in common for both methods. For

276 EP a total of 145 SNP were validated in G1 and 41 SNP were validated in G2. For SCN 277 a total of 14 and 2 SNP were validated in G1 and G2 respectively, under a P-value ≤ 10- 278 3. 279 The low number of validated SNP for SC in G2 may be explained due to most of 280 the significant SNP for this trait in Brahman being located on X chromosome for all 281 evaluated ages, which was not observed for Nellore (data not shown). 282 283 Validated and candidate SNP for EP 284 A total of 145 SNP were validated for EP in G1. They were distributed over 285 chromosomes 2, 3, 4, 5, 6, 7, 8, 11, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24 and 27. 286 Most of them were located on BTA3 (14.5%). For G2, validated SNP were located on 287 chromosomes 6, 8, 14, 15, 17, 21 and 24, and most of them (46.3%) were on BTA21. 288 Table 2 presents the most significant validated SNP for each chromosome for EP in G1 289 and G2. The complete list of validated and candidate SNP for EP are presented in 290 Supplementary Table 1. 291 A total of 21 candidate SNP were detected for female sexual precocity, that is Author Manuscript 292 SNP validated for both, G1 and G2. These SNP were located on chromosomes 6, 8, 14, 293 15, 21 and 24, and most of them were on BTA6 (38%). Table 3 presents the most 294 significant candidate SNP by chromosome for EP.

This article is protected by copyright. All rights reserved 295 These results showed that even though the SNP that were validated for Nellore 296 were not exactly the same that were important for Brahman, they were located in the 297 vicinity (± 250 Kb) of the important SNP for Brahman, which could be explained by the 298 difference of linkage disequilibrium among breeds. 299 Comparing GWAS results individually, the majority of candidate SNP for EP (in 300 Nellore) was generally significant for AGECL in Brahman, but was not significant for 301 PW or PPAI, which suggests that EP and AGECL should be more correlated than EP 302 and PPAI or PW. This is reasonable, as both traits are associated with the age of sexual 303 maturity. 304 The 21 candidate SNP for EP identified here are plausible candidates to be 305 affecting the sexual precocity in Nellore and Brahman populations, and are likely in LD 306 with a QTL segregating in both breeds. 307

308 Validated and candidate SNP for SCN 309 The most significant SNP (P-value ≤ 10-3) for each chromosome validated in G1

310 and G2 for SCN were distributed over chromosomes 11, 12, 15, 16, 17, 19, 23 and 29,

311 (Table 4). The complete list of validated SNP for SCN are presented in Supplementary 312 Table 2. 313 No candidate SNP, i.e., SNP in common between G1 and G2, were found for

314 SCN, mainly due to the low number of validated SNP that were found in G2 for SCN. 315 316 Gene ontology analysis 317 A total of 2 significant gene ontology terms (P ≤ 10-3) were enriched for EP 318 genes: IPR:018363 ~ Conserved Site: CD59 Antigen (CD177, LYPD3, LYPD5, PLAUR, 319 TEX101) and IPR:003006 ~ Conserved Site: Immunoglobulin/major histocompatibility 320 complex, conserved site (ENSBTAG00000005146, AGER, BCAN¸ 321 ENSBTAG00000038619, HLA-DMA, BOLA-DMB, ENSBTAG00000002581.

-3 322 SCN genes were enriched in 5 gene ontology terms (P ≤ 10 ): GO:0042157 ~ 323 Biological Process: Lipoprotein metabolic process (NMT1, APOA1, APOA4, APOA5, 324 APOC3), GO:0008289 ~ Molecular Function: Lipid binding (ACBD4, APOA1, APOA4, Author Manuscript 325 APOA5, APOC3, HIP1R, VPS36), GO:0034369 ~ Biological Process: Plasma 326 lipoprotein particle remodelling (APOA4, APOA5, APOC3), GO:0034367 ~ Biological 327 process: Macromolecular complex remodelling (APOA4, APOA5, APOC3),

This article is protected by copyright. All rights reserved 328 GO:0034368 ~ Biological Process: Protein-lipid complex remodelling (APOA4, 329 APOA5, APOC3). 330 331 DISCUSSION 332 333 Genes and QTLs in the validated regions 334 According to the reference Brahman studies, in which the genes were collected for 335 selection in G1, some of the candidate genes close to the validated SNP for EP were 336 either differentially expressed in pituitary gland of Brahman heifers, comparing pre- 337 pubertal and pos-pubertal heifers (Nguyen et al., 2017), differentially expressed in 338 pituitary gland and grouped in pathways related to reproduction (Nguyen et al., 2017), 339 differentially expressed in the hypothalamus of pos versus pre pubertal Brahman heifers 340 (Fortes et al., 2016) or differentially expressed in ovary of Brahman females (Nguyen et

341 al., 2017). Candidate genes for SCN close to the validated SNP were either differentially 342 expressed in pituitary gland of Brahman heifers, comparing pre-pubertal and pos- 343 pubertal heifers (Nguyen et al., 2017), differentially expressed in pituitary gland and 344 grouped in pathways related to reproduction (Nguyen et al., 2017) or were differentially 345 expressed in the hypothalamus of pos versus pre pubertal Brahman heifers (Fortes et al., 346 2016). The axis hypothalamus-pituitary gland is responsible to control the production of 347 estrogens hormones in ovaries. These hormones have an important role in the 348 preparation of uterus for the reproduction. 349 Some of the validated SNP for EP were previously associated with other 350 reproductive traits for the same populations studied here. For example, Costa et al. 351 (2015) found SNP associated with age at first calving and heifer rebreeding on 352 chromosome 3 at 6 Mb in Nellore. In chromosome 5 (Table 2) the top SNP 353 “BovineHD0500031072” (107.89 Mb) was located close to a significant signal (108 354 Mb) for the trait inhibin in Brahman bulls (Fortes et al., 2013b). Dias et al. (2015) found 355 three genes related with lipid metabolism that were also associated with sexual 356 precocity in Nellore and were mapped close to significant regions found here: genes 357 UCP-1 (BTA17 at 17 Mb), GH-1 (BTA19 at 48 Mb) and TNF (BTA23 at 27 Mb). On Author Manuscript 358 chromosome 21 the top SNP “BovineHD2100000944” (Table 2) was located in a 359 distance of 395,444 bp away from a SNP that was significant for pregnancy outcome 360 after fixed-time AI of Brahman heifers (Porto-Neto et al., 2015). These authors verified 361 that this SNP was in an intronic region of the gene LRRK1.

This article is protected by copyright. All rights reserved 362 Other populations presented QTL related to sexual precocity in regions close to 363 those reported here (less than 0.5 Mb of distance). Some regions were close to the 364 validated SNP for EP, as Cochran et al. (2013), that found a SNP on BTA3 at 6 Mb 365 associated with daughter pregnancy rate, heifer conception rate and cow conception rate 366 in Holstein. This SNP was mapped into the gene HSD17B7, which was also detected in 367 the genes selected as important for Brahman (Table 2). Also, these authors found on 368 BTA23 at 27 Mb another SNP associated with those traits in the gene NFKBIL1, which 369 is 294.03 bp away from the top SNP found in this region. Buzanskas et al. (2017) found 370 a SNP on BTA5 at 107 Mb associated with scrotal circumference at 420 days of age in 371 Canchim cattle. Oliveira Júnior et al. (2017) studying early pregnancy in Nellore found 372 some genomic 1 Mb windows on BTA18 at 54 - 56 Mb explaining more than 1% of the 373 additive genetic variance for this trait. In Brangus cows Peters et al. (2013) found a SNP 374 associated with first service conception (FSC) on chromosome 19 at 49 Mb, which is 375 close to a significant SNP detected here at 48.7 Mb. Fontanesi et al. (2014) also found 376 on BTA19 at 48.7 Mb markers associated with fertility index in Holstein. 377 Other regions were close to the candidate SNP for EP, as on BTA14 at 16 Mb, 378 where Mota et al. (2017) found a SNP window associated with age at first calving in 379 Nellore. Parker Gaddis et al. (2016) found on chromosome 15 at 31-38 Mb an 380 association between some markers in this region and the traits daughter pregnancy rate, 381 cow conception rate and heifer conception rate in Holstein cattle. Also, some regions

382 validated for SCN were reported in other studies, as in McClure et al. (2010) that found 383 QTL associated with scrotal circumference in Angus cattle on chromosome 19 at 45.1 384 Mb, which was close to the SNP BovineHD1900012747 at 45.3 Mb (Table 4). Also, 385 Sahana et al. (2010) found SNP associated with fertility index and days from first to last 386 insemination in Holstein in this genomic region. 387 In Table 2 (EP validated SNP) some genes were previously related to reproductive 388 processes. On BTA2, STAT1 gene is involved in apoptotic process in female granulosa 389 cells (Benifla et al., 2002). Also this gene was reported to be activated during the 390 spermatozoa capacitation and after the fertilization, acting in the male pronucleus 391 (Bastián et al., 2007). The mRNA of MYO1B gene was transcript in man reproductive Author Manuscript 392 tissues which sample sperms failed to promote pregnancy (García-Herrero et al., 2010). 393 This gene expression was abundant in fish eggs after photo stimulation treatment to 394 induce ovulation (Bonnet et al., 2007). Ortega et al. (2016) in a GWAS identify a 395 significant SNP associated with heifer conception rate inside the gene HSD17B7 in

This article is protected by copyright. All rights reserved 396 Holstein cows. This gene, located on BTA3 in bovine, is associated with production of 397 stradiol, an important female hormone, in corpus luteum and with embryo development 398 in mice (Gibori et al., 2009) and was involved in both sex steroid hormones synthesis, 399 in human (Osuch et al., 2012). 400 On BTA4 the gene CREB3L2-201 was expressed in human placenta and in fetal 401 tissues (Storlazzi et al., 2004). On BTA5, the SLC6A13 gene was differentially 402 expressed in mouse blastocysts (Giritharan et al., 2010). This gene was down-regulated 403 in the presence of estrogen in the posterior part of adult female rats hypothalamus (Xu 404 et al., 2008). KDM5A gene is involved in the regulation of spermiogenesis in mice 405 (Lambrot et al., 2008). This gene was identified as a regulator of bovine milk fatty acid 406 content (Pegolo et al., 2017). Boschiero et al. (2013) proposed this gene as a candidate 407 gene associated with fat deposition in chickens. 408 On BTA6 the MARCH1 gene was associated with semen production traits in 409 Chinese Holstein bulls (Liu et al., 2017). Also this gene is associated with the Major 410 Histocompatibility Complex I (MHC I), acting in the process of recognition of antigen 411 presentation (Wilson et al., 2018) and was found in a candidate region affecting female 412 sexual precocity (Table 3). On BTA7, PBX4 gene is located in mouse testis and 413 participates of spermatogenesis (Wagner et al., 2001). NDUFA13 gene was associated 414 with asthenozoospermia, a male pathology that reduces spermatozoa motility in mouse, 415 causing infertility (Yang et al., 2017). This gene was overexpressed in blastocysts of 416 super ovulated heifers (Gad et al., 2011). 417 Transcription of gene NFIB, on BTA8, is essential for lung and brain development 418 in mice embryos (Steele-Perkins et al., 2005). This gene was located in a candidate 419 region for female sexual precocity (Table 3). On BTA13, SNAI1 is essential for the 420 normal cardiovascular system development (Lomelí et al., 2009), and TMEM189 was 421 upregulated in the porcine endometria in days 12 and 16 of gestation versus the other 422 days of estrous cycle (Kiewisz et al., 2014). On BTA14, the ST3GAL1 was expressed in 423 bovine cervical tissue (Pluta et al., 2012). TG gene was identified in several GWAS 424 associated with fat deposition in cattle (Gan et al., 2008; Anton et al., 2011). On 425 BTA15, TAGLN was associated with endometriosis (dos Santos Hidalgo et al., 2011). Author Manuscript 426 This gene was also detected in reproductive tract of pregnant mice and in hens 427 (Kaftanovskaya et al., 2015; Riou et al., 2015). On BTA16, the gene LMOD1 was 428 regulated by androgen and progesterone receptors in the human endometrium affecting 429 the decidualizing process (Cloke et al., 2008).

This article is protected by copyright. All rights reserved 430 On BTA17, CLGN is associated with the capacity of the sperm binding in the 431 mice zona pellucida during fertilization (Yamaguchi et al., 2006). CLGN was also 432 expressed in porcine spermatozoa (Kempisty et al., 2008). This gene was enriched in the 433 blastocysts of unstimulated heifers compared with those that were superovulated (Gad 434 et al., 2011). On BTA18, mutant NAPA gene caused embryo lethality and infertility in 435 mouse, due to a defect in acrosome reaction (Chae et al., 2004; Bátiz et al., 2009). 436 STRADA gene, on BTA19, participates of neuronal embryo formation (Orlova et al., 437 2010; Crino, 2015). The gene CHSY1 (BTA21) was overexpressed in bovine cumulus 438 cells 6 hour after the LH surge (Assidi et al., 2010) and was located in a candidate 439 region of this study (Table 3). PGAM2 (BTA22), was differentially expressed in 440 asthenozoospermic sperm from human sperm (Jodar et al., 2017). 441 ATF6B gene, on BTA23, was up-regulated in porcine fertilized blastocysts (Xu et 442 al., 2015). This gene was associated with growth traits in bovine (Mao et al., 2016) and 443 with reproductive traits in porcine (Liu et al., 2018). ENSBTAG00000006864 gene was 444 located in a region in association with serum IGF-1 concentration in dairy cows 445 (Gobikrushanth et al., 2018). C4A gene was downregulated in low infertility risk group 446 patients compared to intermittent infertility risk group of boys with cryptorchidism 447 (Hadziselimovic et al., 2009). This gene is associated with recurrent spontaneous 448 abortions in humans (Laitinen et al., 1991). Furthermore, C4A and C2 genes are 449 associated with the Major histocompatibility complex (MHC), which is involved in 450 inflammatory and immune responses (Perlmutter et al., 1986; Lokki & Laitinen, 2001). 451 On BTA27, the ASAH1 gene regulates the function of a steroidogenic fator in human 452 adrenochotical cells (Lucki et al., 2012). This gene was related with embryo lethality (Li 453 et al., 2002; Eliyahu et al., 2007). 454 Some of the genes presented in Table 4 (SNP validated for SC) were related to 455 reproductive events. On BTA11, the gene C11H2orf49, homologue of C2orf49, was 456 down-regulated in uterus of repeat breeder cows compared with non-repeat breeder 457 cows (Hayashi et al., 2017). On BTA12, the gene NEK3 is associated with prolactin 458 receptor in humans (Miller et al., 2005). Devi and Halperin (2014) discussed the role of 459 prolactin hormone in some reproduction process in rodents and human. This gene was Author Manuscript 460 down-regulated in F3 of mice males exposed to an organochlorine insecticide with 461 estrogenic properties, promoting a reduction in spermatogonia numbers (Gely-Pernot et 462 al., 2018). Gene FOXO1 showed an increasing of expression in the endometrium of 463 women with polycystic ovary syndrome (Kohan et al., 2010). Lappas et al. (2009)

This article is protected by copyright. All rights reserved 464 suggested that FOXO1 is related to gestation maintenance in humans. The expression of 465 this gene could be observed in spermatogonia and granulosa cells of several mammal 466 species, as mouse, rat, dog, cow, rhesus, chimpanzee and human (Tarnawa et al., 2013). 467 On BTA15, the ZPR1 gene is associated with embryo development; Gangwani et 468 al. (2005) observed that mice embryos with disruption in this gene died in early 469 embryonic development stage. APOA4 gene was associated with follicular development 470 in pigs oocyte (Ji et al., 2010). It was observed an increasing of this gene protein 471 expression in the later rat embryonic development stages (Dihazi et al., 2015), and those 472 authors suggest an association of this protein with steroid metabolic process and 473 cholesterol synthesis. Also APOC3 gene is related to cholesterol metabolism and 474 Tabatabaie et al. (2011) raised the hypothesis of this gene can be affect gonadal 475 maturity in rats. On BTA17, HCAR1 gene is commonly expressed in adipocytes and 476 was involved in the regulation of lipolysis in Holstein cows during the transition period 477 from late pregnancy to lactation (Weber et al., 2016). 478 On BTA19, GFAP gene is associated with the regulation of estrous cycle in cows 479 and mouse (Garcia-Segura et al., 1994; Stone et al., 1998). HEXIM1 and HEXIM2 genes 480 are associated with cell proliferation, and participate of mouse embryo development 481 (Yik et al., 2005). Gene TFEB was grouped in clusters functionally associated with 482 placentation on the branch ancestral to Hominidae, i.e., human, chimp, gorilla and 483 orangutan (Crosley et al., 2013). This gene was also reported as playing an important 484 role in normal placenta vascularization in mice (Steingrímsson et al., 1998). CCND3 485 gene was down-regulated in endometrium of patients with endometriosis (Ohlsson 486 Teague et al., 2009). This gene was listed by Choudhury and Kanapp (2001) as 487 associated with fertility, reproduction and development in human and rodents. This gene 488 presented significant expression in bovine granulosa cells (Shimizu et al., 2013). TAF8 489 gene was associated with embryo development in bovine (Al Naib et al., 2012). 490 MRPS10 was associated with luteolysis in ovine corpus luteum (Xu et al., 2017). On 491 BTA29 HIKESHI gene is associated with cellular stress response, as promoted by heat 492 shock (Kose et al., 2012). The gene EED is associated with female puberty in rats 493 (Lomniczi et al., 2013). Author Manuscript 494 495 Gene Ontology Analysis 496 Significant gene ontology terms enriched for EP were associated with immune 497 processes. Some Major Histocompatibility Complex (MHC) genes Classes I and II were

This article is protected by copyright. All rights reserved 498 enriched in these terms/pathways (ENSBTAG00000005146, ENSBTAG00000038619, 499 HLA-DMA, BOLA-DMB, ENSBTAG00000002581, BOLA-DOA). The relationship 500 between MHC and reproductive processes is well discussed in literature and briefly, has 501 association with maternal-fetal immune tolerance (Riley, 2008), conception success 502 (Fernandez et al., 1999) and sexual partner choice (Ziegler et al., 2010). 503 Melo et al. (2017) in a GWAS of number of calving at 53 months of age (NC53), 504 using the same Nellore population, found MHC Class II as the most significant term 505 enriched for this trait. However, the genomic region found here (for G1) was the BTA23 506 at 6.9-7.4 Mb, while in Melo et al. (2017) the MHC genes were detected in another 507 region, on BTA23 at 25-26 Mb. NC53 is a trait that reflects the ability of female to stay 508 in herd productively, while EP represents the female precocity. Besides these traits are 509 different and are measured in different female ages they both express the reproductive 510 potential of females to get pregnant, which could explain the similarity in the gene 511 pathways that they share. This found is an extra evidence of the importance of this gene 512 complex for female pregnancy success, apparently independent of the female age.

513 Most of the SCN genes were enriched in terms related to lipid metabolism. The 514 lipid metabolism is associated with a range of metabolic processes as: energy supply, 515 carbohydrate metabolism, endocrine system, hormones biosynthesis, as progesterone 516 and testosterone, which are dependent of the cholesterol molecule for their synthesis. 517 The importance of lipid metabolism for the reproductive performance in cows has 518 been well described in literature (Rodney et al., 2015; Wathes et al., 2013; Snijders et 519 al., 2000; Leroy et al., 2008). Females that present some nutritional lack affecting their 520 energy reserves will present problems to ovulate or to maintain a gestation. Likewise, 521 the lipid metabolism is also fundamental for male fertility (Kim et al., 2017). Some fatty 522 acids present crucial role in the maintenance of sperm integrity, sperm motility, viability 523 and fertility in several livestock species (Van Tran et al., 2016). Rezende et al. (2018) 524 found some genes associated with sire conception rate that were enriched in a functional 525 term named “Fatty acid degradation”, and reported previous studies that explained the 526 relationship between fatty acids and the ATP synthesis, promoting the sperm motility 527 (Amaral et al., 2013). Author Manuscript 528 In summary, we could validate genomic regions in a Brazilian Nellore cattle 529 population that were previous known as affecting sexual precocity traits in an 530 Australian Brahman cattle population. Also, we found new loci associated with sexual 531 precocity in common for both breeds. A total of 21 SNP were found as strong

This article is protected by copyright. All rights reserved 532 candidates to be affecting sexual precocity in Brahman and Nellore females. SNP that 533 were significant for Brahman generally were not the same for Nellore, however they 534 were close to significant SNP for Nellore. The reason for this could be the difference in 535 the linkage disequilibrium pattern between these breeds, i.e., different mutations 536 segregating across breeds that can be indicating the same gene or genomic region. The 537 different definition of female phenotypes used for both breeds may also be another 538 explanation for the found results. 539 For male, fewer regions could be validated than for female, especially for G2 and 540 no candidate SNP were found. This could be explained because for SC in Brahman the 541 X chromosome has an important effect, which could not be observed in the Nellore 542 population (results not shown), which led us to do not use this chromosome in our 543 analysis. 544 Some genes that were found close to validated SNP seem to be affecting sexual 545 precocity traits in females and males, suggesting the action of pleiotropic effects. 546 Results also showed that some of the candidate SNP from both validation sets (G1 and 547 G2), were located near genes playing roles in reproductive events in several mammal 548 species, including bovine. Therefore, those genes are strong candidates to be affecting 549 sexual precocity in tropical beef cattle. The genomic regions described here seem to be 550 related to the expression of the sexual precocity in Nellore and Brahman. 551 552 ACKNOWLEDGEMENTS 553 The authors acknowledge the researcher mobility International Cooperation 554 Program CAPES/COFECUB (Grant nº: 88881.133149/2016-01) that facilitated the 555 collaborations between UNESP and the University of Queensland. Financial support for 556 this research was granted by Fundação de Amparo à Pesquisa (FAPESP - Grant nº 557 2009/16118-5), Conselho Nacional de Desenvolvimento Científico e Tecnológico 558 (CNPq - Grant no 559631/2009-0) and Coordenação de Aperfeiçoamento de pessoal de 559 nível superior (CAPES). This work used the legacy dataset of the Cooperative Research 560 Centre for Beef Genetic Technologies (www.beefcrc.com) and the Alliance Nellore 561 dataset (www.gensys.com.br). Author Manuscript 562 CONFLICT OF INTEREST 563 The authors have no conflict of interest. 564 565 DATA AVAILABLE STATEMENT

This article is protected by copyright. All rights reserved 566 The Brahman data that support the findings of this study are available from the 567 Cooperative Research Centre for Beef Genetic Technologies. Restrictions apply to the 568 availability of these data, which were used under a research only license for this study. 569 Data are available from www.beefcrc.com with the permission of Meat and Livestock 570 Australia and the University of Queensland (if interested please contact Dr Marina 571 Fortes). 572 The Nellore data that support the findings of this study are available from the 573 Alliance Nellore dataset. Restrictions apply to the availability of these data, which were 574 used under license for this study. Data are available from https://gensys.com.br/ with the 575 permission of Alliance Nellore and Dr. Vanerlei Roso. 576 577 REFERENCES 578 Al Naib, A., Mamo, S., & Lonergan, P. (2012). Investigation of a Preferentially 579 Upregulated Gene Cluster in Day 7 Bovine Embryos Derived from RNA Sequencing 580 Data. Reproduction, Fertility and Development, 25, 256-256. 581 https://doi.org/10.1071/RDv25n1Ab215 582 583 Amaral, A., Castillo, J., Estanyol, J. M., Ballescà, J. L., Ramalho-Santos, J., & Oliva, R. 584 (2013). Human sperm tail proteome suggests new endogenous metabolic 585 pathways. Molecular & Cellular Proteomics, 12(2), 330-342. 586 https://doi.org/10.1074/mcp.M112.020552 587 588 Anton, I., Kovacs, K., Holló, G., Farkas, V., Lehel, L., Hajda, Z., & Zsolnai, A. (2011). 589 Effect of leptin, DGAT1 and TG gene polymorphisms on the intramuscular fat of 590 Angus cattle in Hungary. Livestock Science, 135, 300-303. 591 https://doi.org/10.1016/j.livsci.2010.07.012 592 593 Assidi, M., Dieleman. S. J., & Sirard, M. A. (2010). Cumulus cell gene expression 594 following the LH surge in bovine preovulatory follicles: potential early markers of 595 oocyte competence. Reproduction, 140, 835-852. https://doi.org/10.1530/REP-10-0248 Author Manuscript 596 597 Aquila, S., Bonofiglio, D., Gentile, M., Middea, E., Gabriele, S., Belmonte, M., ... & 598 Andò, S. (2006). Peroxisome proliferator activated receptor (PPAR) γ is expressed by

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1189 measured at 12, 18 and 24 months of age (SC12, SC18, SC24) in Brahman cattle. Number of Trait Mean ± SE observations EP (%) 1,849 28.3 ± 1.10 SC (cm) 4,248 26.57 ± 2.56 AGECL (days) 1,007 750.6 ± 142.14 PPAI (days) 629 180.11 ± 108.71 PW (%) 629 52.78 ± 2.00

SC12 (cm) 1,098 21.40 ± 2.41 Author Manuscript

SC18 (cm) 1,203 26.51 ± 2.76

SC24 (cm) 1,098 29.89 ± 2.86 1190 1191 Table 2. Validated top SNP for EP in G1 and G2 (P-value ≤ 10-3).

This article is protected by copyright. All rights reserved SNP BTA† Position† (Mb) P-value Gene‡ (symbol§)/ SNP¶ G1 BovineHD0200022985 2 79.97 8.7x10-4 ENSBTAG00000007867 (STAT1) ENSBTAG0000001125 (MYO1B) BovineHD0300002093 3 6.66 1.1x10-4 ENSBTAG00000005976 (HSD17B7) BovineHD0400028801 4 102.42 3.9x10-4 ENSBTAG00000015802 (CREB3L2-201) BovineHD0500031072 5 107.89 3.6x10-4 ENSBTAG00000038415 (SLC6A12) ENSBTAG00000014525 (SLC6A13) ENSBTAG00000020472 (KDM5A) BovineHD0600034574 6 1.74 5.1x10-5 ENSBTAG00000044082 (MARCH1)/ BovineHD0600000418 BovineHD0700001070 7 3.77 1.6x10-4 ENSBTAG00000009975 (PBX4) ENSBTAG00000007812 (NDUFA13) BovineHD0800009146 8 30.10 4.3x10-4 ENSBTAG00000027442 (NFIB) BovineHD1100024980 11 86.98 5.6x10-4 ENSBTAG00000004259 (HPCAL1) BovineHD1300022820 13 78.85 2.0x10-4 ENSBTAG00000014554 (SNAI1) ENSBTAG00000010135 Author Manuscript (TMEM189) BovineHD1400002554 14 9.18 9.6x10-5 ENSBTAG00000001156 (ST3GAL1)

This article is protected by copyright. All rights reserved ENSBTAG00000007823 (TG) BovineHD1500007541 15 28.10 1.8x10-4 ENSBTAG00000002650 (ZPR1) ENSBTAG00000019770 (APOA4) ENSBTAG00000012398 (APOC3) ENSBTAG00000007196 (TAGLN) ENSBTAG00000019764 (APOA5) BovineHD1600013840 16 49.84 6.5x10-5 ENSBTAG00000021576 (LMOD1) BovineHD1700005155 17 17.82 7.9x10-5 ENSBTAG00000001580 (CLGN) BovineHD1800016044 18 54.75 1.2x10-4 ENSBTAG00000013084 (NAPA) BovineHD1900013552 19 48.75 7.0x10-4 ENSBTAG00000000056 (STRADA) BovineHD2100000944 21 5.30 1.3x10-5 ENSBTAG00000007357 (CHSY1)/ BovineHD2100001004 BovineHD2200000079 22 0.37 7.8x10-5 ENSBTAG00000014547 (PGAM2) ENSBTAG00000012073 (VOPP1) BovineHD2300007469 23 27.26 4.9x10-5 ENSBTAG00000008794 (ATF6B) ENSBTAG00000006864 Author Manuscript ENSBTAG00000037533 (C4A) ENSBTAG00000007450

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BovineHD2400002342 24 8.37 3.8x10-4 ENSBTAG00000006726 (CCDC102B)/ BovineHD2400002368 BovineHD2700005243 27 18.18 8.8x10-4 ENSBTAG00000011257 (ASAH1) G2 BovineHD0800012292 8 4.12 4.0x10-4 BovineHD0800012229 BovineHD1400004742 14 16.71 2.6x10-4 BTA-122375-no-rs BovineHD1500008343 15 31.06 1.1x10-4 BovineHD1500008365 BovineHD1700009553 17 34.48 2.7x10-4 BovineHD1700009509 1192 †SNP were mapped to the UMD3.1 Bovine Assembly. 1193 ‡Gene = Important genes for Brahman reproductive traits (interval of ± 250 Kb). 1194 §Gene symbols were researched at Ensembl website (Cow UMD3.1). 1195 ¶SNP = Closest significant SNP of the Brahman meta-analysis (± 250 Kb). 1196 SNP in bold were in common between G1 and G2. 1197 1198 Table 3. Candidate top SNP per chromosome for EP (P-value ≤ 10-3). SNP BTA† Position (Mb) † P-value Gene‡ (symbol) §/ SNP¶ BovineHD0600034574 6 1.74 5.1x10-5 ENSBTAG00000044082 (MARCH1)/ BovineHD0600000418 BovineHD0800009146 8 30.10 4.3x10-4 ENSBTAG00000027442 (NFIB)/ BovineHD0800009169 BovineHD1400004742 14 16.71 2.6x10-4 ENSBTAG00000009394 (NSMCE2) BTA-122375-no-rs BovineHD1500008850 15 32.60 2.8x10-4 ENSBTAG00000019246(

Author Manuscript SC5D)/ BovineHD1500008844

This article is protected by copyright. All rights reserved BovineHD2100000944 21 5.30 1.3x10-5 ENSBTAG00000007357 (CHSY1)/ BovineHD2100001004 BovineHD2400002342 24 8.37 3.8x10-4 ENSBTAG00000006726 (CCDC102B)/ BovineHD2400002368 1199 †SNP were mapped to the UMD3.1 Bovine Assembly. 1200 ‡Gene = Closest gene, important for Brahman reproductive traits (± 250 Kb). 1201 §Gene symbols were researched at Ensembl website (Cow UMD3.1). 1202 ¶SNP = Closest significant SNP of the Brahman meta-analysis (± 250 Kb). 1203 1204 Table 4. Validated top SNP for SC in G1 and G2 (P-value ≤ 10-3). SNP BTA† Position† (Mb) P-value Gene‡ (symbol§)/ SNP¶ G1 BovineHD1100003302 11 9.35 2.4x10-4 ENSBTAG00000012332 (C2orf49) BovineHD1200006565 12 21.81 2.3x10-4 ENSBTAG00000020612 (NEK3) ENSBTAG00000011647 (SLC25A15) ENSBTAG00000044105 (FOXO1) BovineHD1500007531 15 28.06 1.2x10-4 ENSBTAG00000002650 (ZPR1) ENSBTAG00000019770 (APOA4) ENSBTAG00000012398 (APOC3) ENSBTAG00000019764 (APOA5) Author Manuscript BovineHD1700015592 17 54.94 4.3x10-5 ENSBTAG00000000908 (HCAR1) BovineHD1900012747 19 45.37 3.4x10-6 ENSBTAG00000013534

This article is protected by copyright. All rights reserved (GFAP) ENSBTAG00000006056 (HEXIM1) ENSBTAG00000024974 (HEXIM2) BovineHD2300015274 23 15.69 7.3x10-5 ENSBTAG00000012384 (TFEB) ENSBTAG00000008977 (TOMM6) ENSBTAG00000010100 (MED20) ENSBTAG00000010106 (CCND3) ENSBTAG00000011339 (TAF8) ENSBTAG00000015301 (MRPS10) BovineHD2900002704 29 9.16 8.8x10-5 ENSBTAG00000019995 (HIKESHI) ENSBTAG00000007847 (EED) G2 BovineHD1600000479 16 1.86 1.8x10-4 BovineHD1600000503 1205 †SNP were mapped to the UMD3.1 Bovine Assembly. 1206 ‡Gene = Important genes for Brahman reproductive traits (± 250 Kb). 1207 §Gene symbols were researched at Ensembl website (Cow UMD3.1). 1208 ¶SNP = Closest significant SNP of the Brahman meta-analysis (± 250 Kb). 1209 1210 FIGURE LEGENDS 1211 Figure 1. Scheme of across breed SNP validation for Brahman and Nellore populations. Author Manuscript 1212 EP = Early pregnancy and SC = Scrotal circumference, both measured in Nellore, G1 = 1213 Significant SNP in Nellore in genic regions important for Brahman, G2 = Significant 1214 SNP in Nellore close to significant SNP from Brahman meta-analyses.

This article is protected by copyright. All rights reserved jbg_12429_f1.tiff Author Manuscript

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