Understanding the underlying genetic mechanisms for age at first calving, inter-calving period and scrotal circumference in Bonsmara cattle

Background Reproduction is a key feature of the sustainability of a species and thus represents an important component in livestock genetic improvement programs. Most reproductive traits are lowly heritable. In order to gain a better understanding of the underlying genetic basis of these traits, a genome-wide association was conducted for age at first calving (AFC), first inter-calving period (ICP) and scrotal circumference (SC) within the South African Bonsmara breed. Phenotypes and genotypes (120,692 single nucleotide polymorphisms (SNPs) post editing) were available on 7,128 South African Bonsmara cattle; the association analyses were undertaken using linear mixed models. Results Genomic restricted maximum likelihood analysis of the 7,128 SA Bonsmara cattle yielded genomic heritability’s of 0.183 (SE = 0.021) for AFC, 0.207 (SE = 0.022) for ICP and 0.209 (SE = 0.019) for SC. A total of 16, 23 and 51 suggestive (P ≤ 4 × 10-6) SNPs were associated with AFC, ICP and SC, while 11, 11 and 44 significant (P ≤ 4 × 10-7) SNPs were associated with AFC, ICP and SC respectively. A total of 11 quantitative trait loci (QTL) and 11 candidate genes were co-located with these associated SNPs for AFC, with 10 QTL harbouring 11 candidate genes for ICP and 41 QTL containing 40 candidate genes for SC. The QTL identified were close to genes previously associated with carcass, fertility, growth and milk-related traits. The biological pathways influenced by these genes include carbohydrate catabolic processes, cellular development, iron homeostasis, lipid metabolism and storage, immune response, ovarian follicle development and the regulation of DNA transcription and RNA translation. Conclusions This was the first attempt to study the underlying polymorphisms associated with reproduction in South African beef cattle. Genes previously reported in cattle breeds for numerous traits bar AFC, ICP or SC were detected in this study. Over 20 different genes have not been previously reported in beef cattle populations and may have been associated due to the unique genetic composite background of the SA Bonsmara breed.

Understanding the underlying genetic mechanisms for age at first calving, intercalving period and scrotal circumference in Bonsmara cattle

Background
The improvement of reproductive efficiency is of major economic importance in beef production systems and improvements in total lifetime productivity is a key metric for efficiency, which is a function of both reproduction and total output per cow [1,2].In South Africa (SA), the majority of beef is produced under extensive production systems with average calving percentages (i.e., the proportion of cows that give birth in comparison to the number of cows that could possibly give birth) of 62% [3].Bonsmara cattle are a beef breed, developed during the nineteen-sixties, resulting in a composite comprised of approximately 5/8 Afrikaner and 3/8 exotic breeds [4].It is the largest breed represented in the seed stock and commercial beef industry in SA.As the beef industry primarily relies on reproductive efficiency, a reduction in the unproductive period of a female's life would positively impact production costs and profit as well as having a favourable impact on the carbon footprint.
Genetic improvement in reproductive performance remains challenging, hindered by the generally low associated heritability (h 2 ), coupled with the complexity of recording these traits and/or the late expression of reproductive traits [5][6][7].The age at onset of puberty can impact overall productivity through the heifer becoming productive at an earlier age [8].Puberty is experienced earlier in composite and crossbred animals compared to their purebred counterparts with the same trend observed for early maturing versus late maturing beef breeds [9].Age of puberty is however difficult to record, and therefore age at first calving (AFC) is often used as an indicator of heifer fertility.The heritability estimates reported for AFC differ depending on the breed, with [10] estimating a h 2 = 0.10 in Brahman cattle, [8,11,12] reporting on Nellore cattle (0.01 to 0.31) and [13] estimating a h 2 = 0.08 for AFC in Angus and Hereford cattle.Recent studies on South African populations are limited with [14] reporting a h 2 = 0.08 in Bonsmara cross cattle, while [5] reported higher heritability for AFC in Afrikaner (0.27) and Drakensberger (0.30) Sanga cattle breeds.Inter-calving period (ICP) is a relatively easy trait to record and is included in most beef and dairy breed societies recording schemes in South Africa [15].Estimates of ICP yield low to moderate heritability (0.01-0.10) in Brahman and composite beef cattle breeds [6,10,16].As scrotal circumference (SC) in bulls is relatively easy to measure, with a moderate to high heritability [6,12,[17][18][19], it has been suggested as an indicator trait for age at puberty, the latter being resource-intensive to measure.
Several studies have reported positive genetic correlations between SC and growth traits like mature body weight (r g = 0.37-0.40) in composite beef cattle [20], weaning and mature weight (r g = 0.60-0.72) in Bos indicus cattle [21] as well as weaning (r g = 0.312) and yearling (r g = 0.519) weight in Nellore cattle [22].Although weaker genetic correlations between SC and weaning weight (r g = 0.15) have been reported in SA Bonsmara bulls [23], genomic analyses of SC and SCrelated traits have identified genes which are also known to associate with growth traits [24].
The SA Bonsmara, classified as a Sanga type, is a unique composite breed of 3/8 exotic (Milk Shorthorn, Hereford) and 5/8 Afrikaner [4].The breed was established through a well-documented crossbreeding program, with the aim of founding a local composite breed that was well adapted to the challenges of a diverse SA climate.This study was the first attempt to apply GWAS for fertility traits in SA Bonsmara cattle to provide insight on gene regions in the SA Bonsmara.The objective of this study was to perform a genome-wide association study for three reproductive traits (AFC, ICP and SC) in a South African Bonsmara population in order to identify quantitative trait loci (QTL) for these traits.

Variance components estimation
A genetic correlation of 0.37 was estimated between AFC and ICP in the SA Bonsmara using the breeding values derived from the bivariate model.Pedigree heritability estimates were 0.22 for AFC, 0.13 for ICP and 0.38 for SC.The genomic REML analysis yielded genomic heritability and standard errors (SE) of 0.183 (SE = 0.021) for AFC, 0.207 (SE = 0.022) for ICP and 0.209 (SE = 0.019) for SC.

Genomic population quality control
Individual based quality control resulted in the omission of ninety-five SA Bonsmara genotypes across the five genotyping arrays available.Assessment of identical by state (IBS) genetic distances yielded a multidimensional scaled plot (MDS; Fig. 1).Identification of outliers as well as their genotyped progeny led to the further removal of 103 genotypes (Fig. 2) resulting in a final sample population of 7,128 SA Bonsmara animals (4,403 males, 2,725 females).The effect of filtering out animals with reliabilities smaller than 0.01 and an effective record count (ERC) of less than 0.50 culminated in genome-wide population sizes of 4,460 animals for AFC (median ERC = 1.758), 4,276 animals (median ERC = 1.717) for ICP1, and 5,452 animals for SC (median ERC = 1.004).

Age at first calving
Eleven single nucleotide polymorphisms (SNPs) at the genome wide threshold p-value of less than 4 × 10 − 7 and a further 16 suggestive SNPs at a p-value of less than 4 × 10 − 6 were associated with AFC (Fig. 3).Pair-wise linkage disequilibrium (LD) analysis of significant SNPs resulted in the identification of 11 QTL across eight autosomes (Table 1).A total of 11 different genes were co-located with the associated QTL, with the frequency of the major alleles being between 0.527 and 0.982, respectively.Bos taurus autosome (BTA) 7 harboured two QTL containing nine genes (ARAP3, CLINT1, FCHSD1, LSM11, PCDHGA, PCDHGB, PCDHGC, RELL2 and THG1L) with each of these QTL having seven SNPs in pair-wise LD.The most significant QTL, located on BTA 17, was a single intergenic SNP with a minor allele frequency (MAF) of 0.13.The gene, PLCB1, resides in a QTL that spans four SNPs in pair-wise LD (r 2 > 0.50), 212.17 kilobase pairs (kbp) across BTA 13, with the

Inter-calving period
Eleven SNPs were significantly associated with ICP, with a further 23 SNPs being suggestively associated (Fig. 4).The most significant SNP (BTA-16,045-no-rs; P = 2.83 × 10 − 16 , MAF = 0.13) was on BTA 17 and was an intergenic SNP.A total of ten QTL across eight autosomes were significantly associated with ICP (Table 2).A QTL 337.43 kbp in length containing six genes (ARAP3, FCHSD1, PCDHGA, PCDHGB, PCDHGC and RELL2) and a second QTL of 158.19 kbp in length harbouring three genes (CLINT1, LSM11 and THG1L) were both positioned on BTA 7. A QTL containing the LDAH gene, is a 131.85 kbp long and contains two SNPs in high LD (r 2 = 0.74).

Discussion
This study was the first attempt to gain insight into the underlying genetic mechanisms for reproductive traits in a South African beef cattle breed.The pedigree and genomic based heritability estimates for AFC, ICP and SC were similar to those identified in studies in beef cattle breeds [6,8,[10][11][12][13][14][17][18][19].The low to moderate heritability estimates for most reproductive traits and limited genomic studies on indigenous breeds in Southern Africa [34][35][36] justifies the further investigation of this study.Genomic tools hold the potential to unlock invaluable information [37], that may help explain physiological conditions that currently remain unanswered [38].

Age at first calving
In this study, a total of eleven significant SNPs associated with AFC were observed; none of these have been previously reported in Bos indicus and crossbred beef cattle to be associated with AFC.Of the eleven genes and two CNVs located in QTL associated with AFC, ten of these genes have not been previously associated with AFC or sexual precocity in beef cattle populations but have been reported in human [39] and sheep [40] populations.Four of the genes observed in this study (ENS-BTAG00000032764, FCHSD1, PLCB1 and RELL2) have been previously associated in beef cattle populations [41][42][43] with two of these genes involved in more than one trait.Physical growth and body composition have a developmental effect on the reproductive organs which would determine the onset of puberty and subsequent AFC [44,45].ENSBTAG00000032764 (pseudogene) was previously reported as a candidate gene associated with carcass traits [41].The resultant translated protein facilitates the storage of iron in a soluble, non-toxic form, which is an essential component for iron homeostasis.

Inter-calving period
The inter calving period which is the period between two calvingss has the lowest genetic and genomic heritability of all three traits in this study and, in practice, is a function of the ability to ovulate post-calving [45], express oestrus, establish and maintain pregnancy and gestation length [29,46].A total of eleven genes and three CNVs were based in QTL associated with ICP which included ten genes not previously associated with ICP or reproduction in beef cattle.The 337.43 kbp QTL on BTA 7 contains three genes (PCDHGA, PCDHGB, PCDHGC) from the protocadherin (PCDH) family group.Studies have shown the PCDH genes play an integral role in ovarian follicular [47] and embryonic [48] development.LDAH is a lipid droplet-associated hydrolase that is essential in lipid storage and was previously associated with feet and leg disorders in Danish Holstein cattle [49].

Scrotal circumference
Pair-wise LD analysis identified a total of 41 QTL across 14 autosomes (Table 3).Genes not previously reported in beef cattle populations include AAK1, ACAD19, CHST13, CNRIP1, CRISP1, DERA, KIF2A, PARVB, PNPO, PXK, RPP14, SKAP1, SLC41A3, SNRNP27, SSBP2, TCOM5B, TJP2, TTLL6, UBE2Z, UROC1 and ZXDC.Most of these genes have not been previously reported to be associated with SC or sperm-related traits, but upon further investigation into the biological pathways that the genes are involved in, it becomes clear that the genes may play some role in the expression of fertility related traits.Biological pathways discussed below include carbohydrate catabolic processes (CHST13, DERA and UROC1), cellular development (HOXB5, HOXB7, HOXB9, HOXB13 and TTL13), lipid metabolism (ABCA12, ABHD6, ACAD9 and PARVB), immune response (SKAP1) and regulation of DNA transcription and RNA translation (CDKAL1, E2F3, MXD1, RPP14, SNRNP27, SSBP2 and ZXDC).ABCA12 mediates lipid transporter activity, signals receptor binding, and has active trans-membrane transporter activity [50,51] identified that ABCA12 is the major gene that influences Harlequin Ichthyosis in humans and later was identified in livestock species.ABCA12 was associated with birth weight in Holstein cattle [52].Monoacylglycerol lipase (ABHD6) is a lipase and the major enzyme for bone morphogenic protein catabolism, which plays a key role in the formation of intraluminal vesicles and in lipid sorting [53].Although not previously associated with SC or fertility traits in cattle breeds, ABHD6 was associated with average daily gain in crossbred beef cattle [54] as well as identified as a positional candidate gene for milk cholesterol in dairy cattle [55].ACAD9, which catalyses the rate limiting step during the beta-oxidation of fatty acyl-CoA, was identified as a CNV in Italian sheep [56] and was found to be significantly associated with intramuscular fat content in Large White pigs [57].Parvin beta (PARVB) is essential in establishing and/or maintaining cell polarity as well as actine cytoskeleton reorganization.Although not previously reported in beef cattle, a study on ketosis in German Holstein cattle [58] associated PARVB with non-alcoholic fatty liver disease, indicating that PARVB could be a part of lipid metabolism.An investigation into selection signatures in Indian swamp buffaloes identified PARVB [59].Two genes previously reported to be linked to fertility traits in cattle include FXN and GMCL1.Frataxin (FXN) promotes the biosynthesis of heme and plays a role in the protection against iron-catalysed oxidative stress.FXN was the second ranking SNP in a logistic regression analysis of pregnancy status in Santa Gertrudis cows [60].GMCL1 appears to be located in an extended selection signature that shows high haplotypic homozygosity [61] and was previously associated with fertility traits in beef cattle breeds [62].Single Stranded Binding Protein (SSBP2), located on BTA 7, is a candidate QTL for conferring resistance to Johne's disease in cattle [63,64].SSBP2 is involved in the positive regulation of transcription by RNA polymerase II and transcription by RNA polymerase II.A study in Holstein cattle associated SSBP2 with body conformation traits [65].PPP3R1 is a regulatory subunit of calcineurin, which plays a role in neuronal calcium signalling.A study on transcriptome profiling of muscle in Nelore cattle [66] identified PPP3R1 participates in mitogen-activated protein kinase (MAPK) signalling pathway which is responsible for cell proliferation, differentiation, and apoptosis.
A range of genes identified to be associated with SC have not been previously identified in cattle, but have been in water buffaloes and crossbred buffaloes.ALDH1L1 [67], TJP2 [67] and TCOM5B [68] were all linked to milk composition traits, more specifically fat and protein yield.The QTL containing ALDH1L1, CHST13, SLC41A3, TXNRD3, UROC1 and ZXDC on BTA 22 was previously reported to be associated with somatic cell score in Holstein cattle [69].The TXNRD3 genes is known to affect adipocyte differentiation through the Wnt signalling pathway [70].
On BTA 19, an SC-associated QTL harbours four homeobox genes and TTLL6.TTLL6 is a gene in a strong candidate region, which included HOXB7 and HOXB9, for controlling skeletal tail length in sheep [71].The four HOXB genes in this QTL have not been previously reported in beef cattle, but other HOX gene clusters are known to affect sperm quality in humans [72].It is known that poor sperm DNA methylation is associated with decreased male fertility and low embryo quality.The hypomethylation of microRNA and HOX gene clusters play a significant role in embryonic development and is evidence of the sperm's epigenetic contribution.KIF2A is known modulate mitotic events during spermatogenesis [73].
A limited number of studies have considered SC as a direct trait of interest for genomic investigations.Reviews of literature on bull fertility highlight the biological processes associated with sperm quality, motility, and scrotal volume [24,74,75].More recent association studies revolve around sexual precocity, especially in tropical cattle [32,74,[76][77][78][79] located in Central and Southern America.

Overlapping genes across traits
Of the genes observed to be significantly associated with both AFC and ICP in the present study, PLCB1 was identified to be linked to stay-ability in Nelore cattle [80].PLCB1 is known to be a target of a micro interfering RNA (miR-301b), which has been associated with ovarian follicle development in cattle breeds [81].Puberty in a heifer occurs upon ovulation of a potentially fertile oocyte [44], while [82,83] stress the importance of proper nutrition postpartum in order to re-establish ovarian activity for a shortened ICP.PLCB1 is an enzyme that hydrolyses phospholipids into fatty acids as well as other lipophilic molecules and is involved in oxidative stress responses [84].The regulation of adipose tissue affects the metabolic hormone leptin, known to regulate reproductive function in female animals [85,86].Twelve haplotype blocks for PLCB1 were identified through an association analysis of carcass traits in Hanwoo cattle [42] and through ontology of this gene linked it to lipid metabolism.ARAP3, a GTPase-activating protein, and the multiple genes that are members of the PCDH family group have been reported as a selection signature in cattle related to immune response [87].Although immunological studies in livestock species are limited, [88] reviewed the effect immune cells have on ovarian follicle development and the establishment of pregnancy.
FCHSD1 and RELL2 are located in a long run of homozygosity (ROH) detected in multiple Alpine-based dual-purpose breeds.These two genes are involved in the MAPK14/p38 cascade as well as apoptosis.Clathrin interactor 1 (CLINT1) plays a major role in the formation of coated vesicles.This gene was associated with milk yield, fat yield and percentage as well as protein yield and percentage in dairy cattle [84], while was linked to milk fat content in Simmental cows [43].LSM11 and THG1L have not been previously reported in cattle breeds but have been associated with milk protein yield and milk protein percentages in Valle del Belice dairy sheep [40].LSM11 being a small nuclear RNA that has processes the mRNA 3'-end prior to translation while THG1L is involved in the regulation of tRNA processing during translation.
The number of overlapping genes co-located in QTL shared by AFC and ICP, alongside the moderate genetic correlation (0.37) in this study, indicates fertility is initiated, regulated and maintained by pleiotropic genetic mechanisms.Multiple genes in this study have no obvious direct link with fertility traits and this further demonstrates the complexity of genetic mechanisms for traits such as AFC and ICP.

Conclusion
In this study numerous genes, ARAP3, CLINT1, FCHSD1, LSM11, PLCB1, RELL2, SM11 and THG1L were co-located in QTL that had a significant or suggestive association with both AFC and ICP.Numerous QTL were identified across 14 autosomes for SC, the majority of which had never been previously reported to be linked to reproductive traits.The identification of different genes with similar molecular and biological characteristics for these sex-limited traits reaffirms our understanding that these lowly heritable traits are influenced by many genes each contributing a small amount to the variation in these traits' expression.Some genes related to carbohydrate catabolic processes, cellular development, iron homeostasis, lipid metabolism and storage, immune response, ovarian follicle development and the regulation of DNA transcription and RNA translation were identified as candidate genes for reproductive traits in SA Bonsmara cattle.

Genotypic data
Genotypes from 7,326 SA Bonsmara animals originating from one of five possible genotype arrays were available.A total of 1,950 animals were genotyped on the GeneSeek Genomic Profiler (GGP) 150K (140,113 SNPs), while 597 animals were genotyped on the GGP 80K (76,883 SNPs), 2,625 animals were genotyped on the Versa 50K (49,855 SNPs), 1,326 animals were genotyped on the SASB 50K (54,394 SNPs) with the remaining 828 on the ICBF IDB v.2 platform (52,445 SNPs).Only autosomal SNPs with a known base pair position, a call rate ≥ 0.90, a MAF ≥ 0.10 and did not significantly deviate from Hardy-Weinberg equilibrium (p > 0.001) were retained.All SNP locations were based on the UMD 3.1 genome build (GCF_000003055.6;[89]).Animals had a call rate of > 90%, while individuals with ≥ 0.95 identical genotypes were discarded as were families with more than 10% Mendelian errors.Quality control of SNP data was carried out using PLINK v.1.9[90].

Population stratification
Identical by state genetic distances between animals were computed through a MDS analysis with PLINK v.1.9[90].The analysis involved a total of 7,231 SA Bonsmara genotypes at a density of 24,216 SNPs that are truly genotyped across all five arrays.Visualisation of the data, reduced into two dimensions, allowed for the detection of possible population stratification as well as outliers.The remaining SA Bonsmara genotypes (4,403 males, 2,725 females) were imputed to 120,692 SNPs using FImpute v.3 [91].

Phenotypic data
The SA Bonsmara minimum breed standards [92] [93].This was accompanied by pedigree information on 2,135,235 animals dating back to 01 June 1949, as well as data on the contributing systematic environmental effects associated with these traits.

Deregression of breeding values
In order to predict estimated breeding values, a bivariate animal linear model for AFC and ICP and a univariate animal linear model for SC were defined as follows; where, y is the vector of phenotypes for AFC, ICP and SC; b is a vector of fixed effects which include sex, herd, birth month and year, age in days at measurement of the phenotype covariate (linear regression); u is a vector representing the direct additive-genetic effects, with u ~ N(0,A σ 2 u ), where A is the pedigree-based matrix and σ 2 u is the direct genetic variance; e represents the residual, where e ~ N(0,Iσ 2 e ), with σ 2 e representing the residual variance and I the identity matrix; X and Z are incidence matrices for b and u respectively.Estimation of variance components for the animal model stated above was calculated using restricted estimated maximised likelihood (REML) optimised with quasi-Newton procedure using analytical gradients in Variance Component Estimation (VCE) [94] software.MiX99 [95] was used to predict breeding values for AFC, ICP and SC using the same model in the estimation of variance components.Effective record contributions (ERCs) for each animal and trait were generated as described in [96] using the reversed reliability approximation method in APaX99 [97].The EBVs of the genotyped animals for each trait were then deregressed using the Secant method [98] in MiX99 [95] alongside the generated ERC.Deregressed EBVs (DEBVs) were weighted using the formula set out by [99]; where, w is the weighting factor of the ith animal with a DEBV; h 2 is the heritability estimate for the respective traits, r 2 is the reliability of the DEBV for the ith animal for a specific trait and, c is the proportion of genetic variance not accounted by the SNPs with a value of 0.90 being used for all weighting factors between all the traits under analysis.
Only animals with an ERC ≥ 0.50 and a reliability ≥ 0.01 were retained for each trait analysis.

Association analyses
A genomic relationship matrix (GRM) was constructed for each trait using the VanRaden method 1 [100].Additive and residual genetic variances for each trait were computed via genomic REML (GREML) using GCTA v1.94 [101].Weighted DEBVs were regressed on each SNP individually using a linear mixed model in WOM-BAT [102].y = µ + SN P + a + e where, y is the vector of phenotypes, the weighted DEBV; µ is the fixed effect of the population mean; SNP is the fixed effect of allele dosage for each SNP (coded as 0, 1 or 2); a is the random effect of the animal, where a ~ (0,Gσ 2 a ), with σ 2 a representing the additive genetic variance of the animal; G is the genomic relationship matrix among animals, e represents the residual, where e ~ N(0,Iσ 2 e ), with σ 2 e representing the residual variance and I the identity matrix.
The t-test statistics for all SNPs were obtained and subsequently transformed into lower tail p-values.To minimise false positives, the Benjamini-Hochberg False Discovery Rate (B-H FDR) method was applied to each SNP.SNPs with a P ≤ 4 × 10 − 7 were considered to be genome-wide significant as per Bonferroni correction, with SNPs with a P ≤ 4 × 10 − 6 being deemed suggestive.Manhattan plots, Figs. 3, 4 and 5, were generated in R using the qqman [103] package.

Defining QTLs and candidate genes
The extent of LD among significant SNPs (P ≤ 4 × 10 − 7 ) was estimated, as was the pairwise LD among all SNPs within 5 Mb up and downstream of the significant SNP [104].The start and end of each QTL was defined by SNPs furthest up and downstream of the significant SNP and had an r 2 > 0.50 with other significant SNPs.If any QTL were deemed to be overlapping, these were consolidated into one large QTL.If no SNPs were in LD with the significant SNP, that SNP was deemed a quantitative trait nucleotide.Identified QTL were then explored using ENSEMBL (https://www.ensembl.org/)according to the UMD 3.1 genome build in order to detect candidate genes residing within and Panther [105] was used to list the biological and metabolic functions and/or processes of possible genes.Funding was provided by the South African Beef Genomics Project for the creation of a reference population.

Data Availability
The datasets generated and/or analysed during the current study are available at https://doi.org/10.6084/m9.figshare.21800117.

Table 1
List of identified QTLs and genes associated with Age at First Calving

Table 3
List of identified QTL and genes significantly associated with Scrotal Circumference

BTA 1 SNPs in QTL 2 Start -End Significant SNP P-value MAF 3 Genes in quantitative trait loci
1BTA Bos taurus autosome.2SNPsin QTL Number of single nucleotide polymorphisms in this quantitative trait loci.
indicate that a heifer must calve before 39 months of age and the first ICP cannot exceed 790 days.SA Bonsmara animals occur throughout all nine of South Africa's provinces and are mainly raised in extensive natural pasture systems.The recording of weaning weight (205-day weight) is compulsory and facilitates the selection of bulls for post-weaning growth tests.Scrotal circumference is measured on bulls participating in central and farm-based growth tests at around 12 to 18 months of age.Standardised phenotypes for AFC (days), first ICP (days), and SC (millimetres) were available on 347,749 records for AFC, 206,505 for records ICP and 238,454 records for SC in individual SA Bonsmara animals from the LOGIX Genetic Evaluation System