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. 2024 Feb 5;21(1):e20230110. doi: 10.1590/1984-3143-AR2023-0110

Genome-wide association study of Nelore and Angus heifers with low and high ovarian follicle counts

Bárbara Loureiro 1, Ronaldo Luiz Ereno 2, Antônio Guilherme Roncada Pupulim 2, Maria Clara Viana Barroso Tramontana 1, Henrique Passos Tabosa 1, Ciro Moraes Barros 2, Maurício Gomes Favoreto 1,2,*
PMCID: PMC10878542  PMID: 38384724

Abstract

The number of antral follicles is considered an important fertility trait because animals with a high follicle count (HFC) produce more oocytes and embryos per cycle. Identification of these animals by genetic markers such as single nucleotide polymorphisms (SNPs) can accelerate selection of future generations. The aim of this study was to perform a genome wide association study (GWAS) on Nelore and Angus heifers with HFC and low (LFC) antral follicle counts. The groups HFC and LFC for genotyping were formed based on the average of total follicles (≥ 3 mm) counted in each breed consistently ± standard deviation. A total of 72 Nelore heifers (32 HFC and 40 LFC) and 48 Angus heifers (21 HFC and 27 LFC) were selected and the DNA was extracted from blood and hair bulb. Genotyping was done using the Illumina Bovine HD 770K BeadChip. The GWAS analysis showed 181 and 201 SNPs with genotype/phenotype association (P ≤ 0.01) in Nelore and Angus heifers, respectively. Functional enrichment analysis was performed on candidate genes that were associated with SNPs. A total of 97 genes were associated to the 181 SNPs in the Nelore heifers and the functional analysis identified genes (ROBO1 and SLIT3) in the ROBO-SLIT pathway that can be involved in the control of germ cell migration in the ovary as it is involved in lutheal cell migration and fetal ovary development. In the Angus heifers, 57 genes were associated with the 201 SNPs, highlighting Fribilin 1 (FBN1) gene, involved in regulation of growth factors directly involved in follicle activation and development. In summary, GWAS for Nelore and Angus heifers showed SNPs associated with higher follicle count phenotype. Furthermore, these findings offer valuable insights for the further investigation of potential mechanism involved in follicle formation and development, important for breeding programs for both breeds.

Keywords: Bovine HD 770 K SNP, candidate genes, follicle, reproduction, SNPs

Introduction

Reproductive performance is an important trait in livestock production. The number of antral follicles (AFC) greater than 3 mm has been associated with fertility in dairy cows. Dairy cows with low follicle counts have lower pregnancy rates at first service, a longer interval from calving to conception, and a higher number of services during the breeding season compared to cows with high follicle counts (HFC; Mossa et al., 2012). In addition, cows with a HFC have a higher number of total oocyte recovery by ultrasound-guided follicular aspiration (OPU) and consequently a greater number of viable embryos produced in vitro (Ireland et al., 2007).

Indicine animals (Brahman and Nelore) have been shown to have a greater number of antral follicles, whereas taurine animals (Angus) have a greater number of preantral follicles (Cushman et al., 2019; Favoreto et al., 2019). In addition, a microarray study showed that the gene expression profile differs between these breeds. Several genes associate with osteoblast differentiation (BMP4, IGF1, IGFBP3 and IGFBP5), cell proliferation (BMP4, SATB1, EMX2, IGF1, MAP7, EMPEP and FABP7) and bone development (BMP4, COL13A1, IGF1, IGFBP3 and IGFBP5) showed higher expression in follicles of Nelore heifers. The genes are related to follicle activation and development (Favoreto et al., 2019). Moreover, genomic studies have shown that Indian and Taurine cattle differ in the expression of genes associated with important traits (Liu et al., 2021), SNPs (Dar et al., 2021; Verardo et al., 2021), gene ontologies (Cortez et al., 2022), and chromatin and methylation profiles (Powell et al., 2023; Capra et al., 2023). Even though there are studies showing that zebu and taurine cattle trace back to a common ancestor, Bos primigenius (Perez-Pardal et al., 2010; Pitt et al., 2018).

In the past years, the use of genomic information has been widely employed as a strategy to improve selection for phenotypes such as increased milk production (Chamberlain et al., 2012), fertility (Huang et al., 2010; Peñagaricano et al., 2012), and other traits of economic interest in cattle. Genome-wide association studies (GWAS) are a method in genetics that aims to identify specific genetic variations, known as single nucleotide polymorphisms (SNPs). The studies are made based on a population that has a specific trait, these animals will have their genotype searched for a common SNPs that can be associated with the phenotype (Dehghan, 2018). Single nucleotide polymorphisms (SNP) enabled the identification of a subset of markers that can explain important portions of the variation in these traits. An alternative approach to identifying SNPs associated with a phenotype of interest is a candidate gene approach, in which individual genes are selected as candidates based on their known function (Naukkarinen et al., 2010).

Identification of SNPs and possible genes responsible for genetic variation in Nelore and Angus with HFC and LFC may improve understanding of the biological pathways involved in the AFC phenotype.

In summary, animals that are considered HFC are associated with better fertility as they allow more oocytes per cycle and thus more embryos in in vivo and in vitro embryo production (Ireland et al., 2007). The identification of these animals by genetic markers could improve the fertility of future generations. Therefore, the aim of the present work was to perform a GWAS study in Nelore and Angus heifers with HFC and LFC using the high-density SNP array to identify genetic variants and possible genes associated with these phenotypes. The main hypothesis was that HFC animals have genetic markers associated with follicular development that could be used as biomarkers for genomic selection.

Material and methods

Animals selection and phenotypic data

Animals were maintained according to the Bioethics Committee of the Faculty of Veterinary Medicine (N° 439) and Animal Sciences of the São Paulo State University (Botucatu, São Paulo, Brazil) and in accordance with the specific guidelines and standards of the SSR.

To pre-select animals, a group of 155 Nelore and 132 Angus heifers of similar body weight (Nelore = 442.93 ± 6.97 kg and Angus = 466.23 ± 10,13) and age (25.57 ± 2,05) were examined by ultrasound (US; Mindray Vet DPS 2200, São Paulo, Brazil) with a 7.5-MHz probe on a random day of the estrous cycle. Only heifers that were cyclic and did not have a follicle greater than 5 mm were selected. In this initial evaluation, the total number of follicles ≥ 3 mm in both ovaries was counted and the mean follicle number for each breed was determined. These heifers were injected with two doses of PGF2 alpha 11 days apart to initiate luteolysis and synchronize the occurrence of ovulation. The ovaries of each animal were examined one day after ovulation in three consecutive estrous cycles to determine the high (HFC) and low (LFC) follicle count groups. Groups were formed based on the average of total follicles counted (≥ 3 mm) for each breed consistently ± standard deviation (Table 1). A total of 72 Nelore heifers were selected and classified into the groups: 32 animals were classified as HFC (40 ≥ follicles) and 40 animals were classified as LHC (20 ≤ follicles). For Angus heifers, 48 animals were selected and assigned to the groups: 21 animals were classified as HFC (20 ≥ follicles) and 27 as LFC (≤ 10 follicles).

Table 1. Numbers of animals, follicle average count and standard deviation for Nelore and Angus heifers with HFC and LFC.

Nelore Angus
Number of animals 43 35 22 27
Fol average count 49 15 25 6
Standard deviation 9.3 3.9 5.1 2.3
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Sample and DNA extraction

During ultrasound examination a sample of blood from the tail vein or capillary bulbs from the tail hair were collected from all selected animals for DNA extraction. For the blood samples, DNA was extracted using the MiniPrep kit (Axygen bioscience, Union City, New Jersey, USA), while the capillary bulb was extracted using the NucleoSpin Tissue Kit (Macherey-Nagel, Duren, Germany) according to the manufacturer’s instructions. After extraction, the quality of the DNA samples was assessed by determining the A260/280 ratio in a biophotometer. Samples were accepted if the values were between 1.8 and 2.0. DNA was quantified and diluted to a concentration between 50 ng/µL and 150 ng/µL for subsequent genotyping.

Genotyping and SNPs quality control

Genotyping was performed by DEOXI BIOTECNOLGIA LTDA, Araçatuba, São Paulo, Brazil, using the Illumina Bovine HD 770 K BeadChip (Infinium BeadChip, Illumina, San Diego, CA) according to the protocol of the manufacturer’s instructions. Genotypes were determined in Illumina A/B allele format and used to represent a covariate value at each locus coded as 0, 1, or 2 indicating the number of B alleles. Initial data analysis and visualization was performed using GenomeStudio Data Analysis Software (Illumina, 2023). For GWAS, SNPs were quality controlled using only autosomal SNPs with known genomic coordinates according to UMD 3.1 Bovine Genome. Samples with a call rate (IDCR) of less than 90% were removed from the study. SNPs were removed if they had a minor allele frequency ≤ 0.02, a call rate ≤ 0.98, and a P value for the Fisher exact test for Hardy-Weindberg equilibrium ≤ 1 x 0.00001. After filtering, 538.575 SNPs were used for the GWAS study.

GWAS test and gene enrichment analysis

The Cochran-Armitage test has been used for genomic association between HFC and LFC in Nelore and Angus heifers. This test is commonly used as a genotype-based test for candidate gene association. It uses a range of scores that can be obtained as an efficient score test for logistic regression (Clarke et al., 2011). In this analysis, it was used for comparisons as a case-control study (GenABEL package; Aulchenko et al., 2007) with LFC as the control group in both subspecies. Significant SNPs (P ≤ 0.001) were mapped to corresponding or nearby genes by linkage disequilibrium (LD) using the software PLINK (Bush et al., 2009; Bohmanova et al., 2010). We considered only the genes with r2 > 0.8 significant for functional analysis. The genes associated with SNPs directly or indirectly by linkage disequilibrium were subjected to the functional enrichment analyzes on DAVID (Database for Annotation, Visualization and Integrated Discovery; (Dennis et al., 2003) to determine gene ontologies (GO), functions, and pathways in which the genes were overrepresented at P < 0.05.

Results

After quality control, a total of 538.575 SNPs distributed on 29 chromosomes were used to study the association between phenotype and genotype. The profiles of p-values (in terms of -log[p]) of all tested SNPs for Nelore and Angus heifers are shown in Figures 1 and 2. A total of 181 SNPs for Nelore and 201 SNPs for Angus heifers showed an association (p ≤ 0.001) between the HFC and LFC groups.

Figure 1. Genome-wide association analysis for HFC comparing with LFC in Nelore heifers. The Manhattan plot demonstrates the results of association after correction for population structure. The horizontal red line indicates the whole-genome with significance threshold [-log (p ≤ 10E-3)].

Figure 1

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Figure 2. Genome-wide association analysis for HFC comparing with LFC in Angus heifers. The Manhattan plot demonstrates the results of association after correction for population structure. The horizontal red line indicates the whole-genome with significance threshold [-log (p ≤ 10E-3)].

Figure 2

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The 181 SNPs of Nelore heifers were mapped on 23 different chromosomes, and the most significant SNPs (p ≤ 0.00098) were located on chromosomes 1, 3, 7, 14, 16, and 22 (Table 2). In Angus heifers, all 201 were mapped on 29 chromosomes, and the most significant SNP (p = 0.000124) is located on chromosome 3 (Table 2).

Table 2. Description of the most significant SNPs for Nelore e Angus heifers.

Chromosome SNPs
1 rs136289764 (8.11E-04)
1 rs109443367 (8.47E-04)
3 rs43704025 (5.39E-04) rs43338364 (1.24E-04)
7 rs110807077 (4.53E-04)
9 rs136692332 (5.39E-04)
14 rs132707253 (8.01E-04)
14 rs41730052 (8.01E-04)
14 rs110253276 (8.01E-04)
16 rs109100442 (2.47E-04)
22 rs133905094 (9.38E-04)
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SNPs Identification: see Ensembl (2023).

GWAS revealed a total of 97 different genes associated directly or indirectly via LD (r2> 0.8) with all 181 SNPs of Nelore heifers (Table 3). Functional enrichment analysis was applied to all 97 genes associated in the integrated network using the DAVID Functional Annotation Tool. In Nelore heifers, a total of 5 gene ontologies (GO) were significantly overrepresented in 2 categories: biological process and cellular component (Table 5). In Angus heifers, 52 genes were associated with all 201 SNPs (Table 4), and functional enrichment analysis showed that 18 genes were significantly GO (p < 0.05) overrepresented in the 3 categories (biological process, cellular component, and molecular function; Table 5).

Table 3. Associated SNPs with respective candidate genes for Nelore heifers.

Gene Chromosome SNP Gene Chromosome SNP Gene Chromosome SNP
RSRC1 1 BTB-01568926 DC1I1 4 BovineHD0400003849 SGK3 14 Hapmap49131-BTA-34531
PLCH1 1 BovineHD0100031992 AGMO 4 BovineHD0400007019 PREX2 14 BovineHD1400009858
ANKUB1 1 BovineHD0100033727 A0JNG1 4 BovineHD0400001266 KCNB2 14 BTA-107899-no-rs
WWTR1 1 BovineHD0100033813 RERG 5 BovineHD0500027036 JPH1 14 BovineHD1400011391
AT1B3 1 BovineHD0100036157 BST1 6 BovineHD0600032820 SNTB1 14 BovineHD1400023903
EPHB1 1 BovineHD0100038454 NPNT 6 BovineHD0600005674 ZC3H12C 15 BovineHD1500005193
CEP63 1 BTB-00063883 A0JN38 6 BovineHD0600019557 F1N2Z9 15 BovineHD1500005842
APC13 1 BovineHD0100038705 EPHA5 6 BovineHD0600022781 E1BA24 15 BovineHD1500009535
ENTK 1 BovineHD0100005454 ART3 6 BovineHD0600025443 STIM1 15 BTA-114838-no-rs
C21orf63 1 BovineHD0100000686 11-Sep 6 BovineHD0600025874 LOC790886 16 BovineHD1600001673
ROBO1 1 BovineHD0100007707 FRAS1 6 BovineHD0600026271 RALGPS2 16 BovineHD1600017259
E1BJS9 1 BovineHD0100010534 SGCD 7 BovineHD0700020503 ANGL1 16 BovineHD1600017298
A5PKG1 1 BovineHD0100022104 HEM2 8 BovineHD0800031076 FBXW8 17 BovineHD1700017212
SMARCAL1 2 BovineHD0200030269 CLCN3 8 BovineHD0800000483 ADAMTS18 18 BovineHD1800001383
F1MTX0 2 BovineHD0200040258 TMEM2 8 BovineHD0800014467 F1MX91 18 ARS-BFGL-NGS-59215
KIAA1486 2 BovineHD0200033024 RIMS1 9 BovineHD0900002983 DOCK2 20 BovineHD2000000529
NMI 2 BovineHD0200013025 ZNF292 9 Hapmap54718-rs29022960 RNF180 20 BovineHD2000021261
MYO7B 2 BovineHD0200001364 EML5 10 BovineHD1000029437 FAM196B 20 BovineHD2000000555
IWS1 2 BovineHD0200001420 A6QLI2 10 BTA-114684-no-rs SLIT3 20 BovineHD2000000133
DNAH7 2 BovineHD0200024162 A7YWN4 11 ARS-BFGL-NGS-10436 F1MJV4 20 BovineHD2000018883
ORC2 2 BovineHD0200025582 LBH 11 BovineHD1100019791 CCDC33 21 BovineHD2100021281
NRP2 2 BovineHD0200027119 FAM179A 11 BovineHD1100020297 LYZL4 22 BovineHD2200004477
PIK3R3 3 BTA-20822-no-rs IFT172 11 BovineHD1100020629 F2Z4H7 22 BovineHD2200005456
NHRF3 3 BovineHD0300006834 Q3SZR7 11 BovineHD1100022452 AZI2 22 BovineHD2200000741
SYWM 3 BovineHD0300007564 HS1BP3 11 BovineHD4100009043 ZCWPW2 22 BovineHD4100015404
TBX15 3 BovineHD0300007604 XRN2 13 BovineHD1300011855 RBMS3 22 BTB-00830411
SPAG17 3 BovineHD0300007956 C20orf123 13 BovineHD1300021958 ATP2B2 22 ARS-BFGL-NGS-14331
MAN1A2 3 BovineHD0300035509 KIAA0146 14 BovineHD1400005988 EGFR 22 BovineHD2200000246
ATP1A1 3 BovineHD0300036028 PRKDC 14 BovineHD1400006081 DCDC2 23 BovineHD2300009744
Q2KI63 3 BovineHD0300002619 A6QLA9 14 BovineHD4100011332 TTC39C 24 BTB-01623856
ECHD2 3 BovineHD0300027093 A4IFV2 14 BovineHD4100011399 RB27B 24 BovineHD2400015606
AT1A2 3 BovineHD0300003116 TRIM55 14 BovineHD1400009278 CTNNA3 28 BTB-00980953
F1MY54 4 BovineHD0400033064
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Table 5. Gene Ontology terms related to biological process, cellular component and molecular function of the genes associated directly or indirectly with SNPs in the HFC from Nelore and Angus heifers.

Category GO ~ Term Count % P Value Genes
Nelore GOTERM_BP_FAT GO:0006928 ~ cell motion 5 11.4 0.02 ROBO1, PRKDC, DCDC2, DNAH7, SLIT3
GOTERM_BP_FAT GO:0048870 ~ cell motility 4 9.1 0.03 ROBO1, PRKDC, DCDC2, DNAH7
GOTERM_BP_FAT GO:0051674 ~ localization of cell 4 9.1 0.03 ROBO1, PRKDC, DCDC2, DNAH7
GOTERM_CC_FAT GO:0044459 ~ plasma membrane part 11 25.0 0.01 EPHA5, ART3, CLCN3, ROBO1, KCNB2, SNTB1, SGCD, STIM1, ATP1A1, RIMS1, CTNNA3
GOTERM_CC_FAT GO:0016010 ~ dystrophin-associated glycoprotein complex 2 4.5 0.03 SNTB1, SGCD
Angus GOTERM_BP_FAT GO:0001822 ~ kidney development 3 8.3 0.01 PKHD1, FBN1, NID1
GOTERM_BP_FAT GO:0001655 ~ urogenital system development 3 8.3 0.02 PKHD1, FBN1, NID1
GOTERM_CC_FAT GO:0043228 ~ non-membrane-bounded organelle 12 33.3 0.00 FNTB, TNS3, PARN, PKHD1, MYO16, RBM19, WDR1, MYH14, DNAH2, SHANK1, XRN2, CBS
GOTERM_CC_FAT GO:0043232 ~ intracellular non-membrane-bounded organelle 12 33.3 0.00 FNTB, TNS3, PARN, PKHD1, MYO16, RBM19, WDR1, MYH14, DNAH2, SHANK1, XRN2, CBS
GOTERM_CC_FAT GO:0005604 ~ basement membrane 3 8.3 0.01 FRAS1, FBN1, NID1
GOTERM_CC_FAT GO:0044420 ~ extracellular matrix part 3 8.3 0.02 FRAS1, FBN1, NID1
GOTERM_CC_FAT GO:0044430 ~ cytoskeletal part 6 16.7 0.03 FNTB, PKHD1, MYO16, MYH14, DNAH2, SHANK1
GOTERM_CC_FAT GO:0005730 ~ nucleolus 5 13.9 0.04 TNS3, PARN, RBM19, XRN2, CBS
GOTERM_CC_FAT GO:0005856 ~ cytoskeleton 7 19.4 0.04 FNTB, PKHD1, MYO16, WDR1, MYH14, DNAH2, SHANK1
GOTERM_MF_FAT GO:0004532 ~ exoribonuclease activity 2 5.6 0.02 PARN, XRN2
GOTERM_MF_FAT GO:0016896 ~ exoribonuclease activity, producing
5'-phosphomonoesters		 2 5.6 0.02 PARN, XRN2
GOTERM_MF_FAT GO:0003779 ~ actin binding 4 11.1 0.02 MYO16, WDR1, MYH14, MYLK
GOTERM_MF_FAT GO:0005516 ~ calmodulin binding 3 8.3 0.03 ADCY1, MYH14, MYLK
GOTERM_MF_FAT GO:0003774 ~ motor activity 3 8.3 0.03 MYO16, MYH14, DNAH2
GOTERM_MF_FAT GO:0016796 ~ exonuclease activity, active with either ribo- or deoxyribonucleic acids and producing 5'-phosphomonoesters 2 5.6 0.03 PARN, XRN2
GOTERM_MF_FAT GO:0046872 ~ metal ion binding 14 38.9 0.04 FRAS1, ADCY1, RBM20, FBN1, SYT9, PRKCH, NID1, FNTB, TNS3, PARN, EBF1, XRN2, MYLK, CBS
GOTERM_MF_FAT GO:0043169 ~ cation binding 14 38.9 0.04 FRAS1, ADCY1, RBM20, FBN1, SYT9, PRKCH, NID1, FNTB, TNS3, PARN, EBF1, XRN2, MYLK, CBS
GOTERM_MF_FAT GO:0043167 ~ ion binding 14 38.9 0.04 FRAS1, ADCY1, RBM20, FBN1, SYT9, PRKCH, NID1, FNTB, TNS3, PARN, EBF1, XRN2, MYLK, CBS
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Table 4. Associated SNPs with respective candidate genes for Angus heifers.

Gene Chromosome SNP Gene Chromosome SNP Gene Chromosome SNP
Q32KQ4 1 BovineHD0100028647 FBN1 10 BovineHD1000017884 SHANK1 18 ARS-BFGL-NGS-25117
CBS 1 BovineHD0100041801 PRKCH 10 BovineHD1000021003 DNAH2 19 BovineHD1900008265
MYLK 1 BovineHD0100019384 FNTB 10 BovineHD1000022127 LEPREL4 19 BovineHD1900012163
A8E661 2 BovineHD0200026032 A8E641 11 BovineHD1100020762 PSA4 21 ARS-BFGL-NGS-24797
PALMD 3 BovineHD0300013319 MYO16 12 BovineHD1200025736 PTPRG 22 BovineHD2200011275
IFI44 3 BovineHD0300019648 RALGAPA2 13 BovineHD1300011643 ATG7 22 BovineHD2200016071
KAD5 3 BovineHD0300019991 KIZ 13 BovineHD1300011819 CRISP1 23 BovineHD2300005886
ACM2 4 BovineHD0400028468 XRN2 13 BovineHD1300011851 PKHD1 23 BovineHD2300006404
TNS3 4 BovineHD0400020885 A6QQD3 15 BTB-01820462 FAM59A 24 BovineHD2400006778
ADCY1 4 BovineHD0400021263 SYT9 15 BovineHD1500013002 TNFRSF11A 24 BovineHD2400017755
F19A5 5 BovineHD0500034919 A6QNL3 16 BovineHD1600012798 PARN 25 BovineHD2500003745
PPP2R2C 6 BovineHD0600029214 F262 16 BovineHD1600001371 LIPA 26 BTA-62081-no-rs
SLC2A9 6 BovineHD0600030984 CD045 17 BovineHD1700011280 SORCS1 26 BovineHD2600007572
WDR1 6 BovineHD0600031016 CUX2 17 BovineHD1700016280 RBM20 26 BovineHD2600008410
A7YWG6 6 BovineHD0600008622 RBM19 17 BovineHD1700017987 F1MX91 18 ARS-BFGL-NGS-59215
FRAS1 6 BovineHD0600026329 LRBA 17 BovineHD1700002101 DOCK2 20 BovineHD2000000529
EBF1 7 BovineHD0700021323 MYH14 18 ARS-BFGL-NGS-3584 RNF180 20 BovineHD2000021261
A1A4J5 8 ARS-BFGL-NGS-1787 FAM196B 20 BovineHD2000000555
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Discussion

Genome-wide association studies (GWAS) were conducted to identify quantitative trait loci (QTL) and candidate genes associated with fertility in cattle. The most common traits that affect reproduction and are candidates for genetic selection are age at first calving (Hutchison et al., 2017; Mota et al., 2020), conception rate (Galvão et al., 2013), and daughter pregnancy rate (Parker Gaddis et al., 2014).

In Nelore and Angus heifers, the GWAS study showed no genomic region associated with variation in antral follicle number across all 29 autosomal chromosomes, which is shown in the Manhattan plots (Figures 1 and 2). The mean/low peaks observed in the figures can be attributed to two factors: Many SNPs have a small effect on phenotype and variable antral follicle number in cattle is regulated by many genes. GWAS identified several SNPs with association and candidate genes in animals with HFC in Nelore and Angus heifers when analyzed separately.

In Nelore heifers, the epidermal growth factor receptor (EGFR) gene was associated with the SNP BovineHD2200000246 on chromosome 22 (Table 3). EGFR is a transmembrane glycoprotein consisting of an extracellular ligand-binding domain and a cytoplasmic segment with tyrosine kynase activity, which is central to the cell proliferative effects of EGF. EGF has been shown to play a role in spermatogenesis, oocyte development and maturation (Wald, 2005; Richani and Gilchrist, 2018). In spermatogenesis, EGF enhances the effect of gonadotropin on testicular testosterone production by modulating the activity of enzymes involved in the biosynthetic pathway of testosterone and by increasing the availability of cholesterol for mitochondrial steroidogenesis (Wald, 2005). In follicular development, the EGF network is an essential component of the ovulatory cascade by relaying the signal LH from the periphery of the follicle to the cumulus-oocyte complex (COC). Although the EGF network act in the late stages of follicle development, a new concept to emerge is that cumulus cell acquisition of EGF receptor responsiveness in early stages of development represents a developmental hallmark in folliculogenesis. (Richani and Gilchrist, 2018; Ritter et al., 2015).

Nominal associated gene analyzes using DAVID bioinformatics resources identified several functional categories that differed in the HFC group compared with the LFC group in Nelore and Angus heifers. Notably, cell motion (ROBO1, PRKDC, DCDC2, DNAH7, and SLIT3), cell motility (ROBO1, PRKDC, DCDC2, and DNAH7), and localization (ROBO1, PRKDC, DCDC2, and DNAH7) were the GO associated with biological process in Nelore heifers. The Roundabout (ROBO) transmembrane proteins constitute a conserved family of receptors that includes ROBO1, ROBO2, ROBO3, and ROBO4, which together with their repellent ligand SLIT (SLIT1, SLIT2, and SLIT3) play an important role in regulating axon guidance decisions (Devine and Key, 2008). However, there is evidence that the SLIT/ROBO pathway also plays a role in cellular processes outside the nervous system (Wong et al., 2002). In a study of adult human ovaries, the expression of SLIT2, SLIT3, and ROBO2 was increased during the luteal phase and was negatively regulated by hCG and cortisol (Dickinson et al., 2008). In addition, blocking the activity of SLIT-ROBO decreased apoptosis and increased migration in luteal cells (Dickinson et al., 2008). In ovarian development, the SLIT-ROBO signaling pathway may be involved in controlling germ cell migration. Gene expression of SLIT2, SLIT3, ROBO1, ROBO2, and ROBO4 was detected in the ovine fetal ovary at days 50, 60, 70, and 80 of gestation, the time when follicles are formed. In addition, at the time of increased SLIT-ROBO expression, there was a significant reduction in the proliferation of oocytes in the developing ovary (Dickinson et al., 2010). Although GWAS showed that the ROBO1 (BovineHD0100007707) and SLIT3 (BovineHD2000000133) genes are associated with HFC in Nelore, the influence of the SLIT-ROBO pathway on follicle formation in this breed remains to be confirmed by other functional experiments. Nevertheless, this opens a new field for studies on how and whether the SLIT-ROBO pathway affects AFC in Nelore heifers.

A hapFLK study of the Nelore bull genome identified 83,326 SNPs. Most of these are in Chr1, Chr2, Chr5, Chr11, Chr13, and Chr17. The is region in Chr11 is located near genes just between the FSHR and NRXN1 genes. FSHR is required for ovarian follicle development. The authors also highlighted the ‘Roundabout signaling pathway’ involving the ROBO1 and SLIT protein genes (Maiorano et al., 2022). This signaling pathway is important for physiological adaptation of grazing cattle (Muroya et al., 2015).

Two GO terms related to biological processes, kidney development (PKHD1, FBN1, and NID1) and urogenital system development (PKHD1, FBN1, and NID1), were significantly associated with Angus heifers. Fibrillins (FBN1, 2, and 3) are glycoproteins found in connective tissues (Zhang et al., 1995) and form the backbone structure of small diameter microfibrils (Sakai et al., 1991). In addition, fibrillins have regulatory functions by binding and sequestering growth factors. Fibrillin contributes to the extracellular regulation of endogenous TGFB activity by providing a structural platform that controls the diffusion, storage, presentation, and release (Ramirez and Sakai, 2010). In addition, they also interact with the prodomains of bone morphogenic proteins (BMPs) and growth and differentiation factors (GDFs; Sengle et al., 2008), which are members of the TGFB superfamily and have been described as important for ovarian follicular development and function (Dong et al., 1996; McNatty et al., 2000; Yan et al., 2001; Knight and Glister, 2006).

Taurine animals have been shown to have more preantral follicles than indicine animals. On the other hand, indicine animals have more antral follicles counted by ultrasound and histology (Cushman et al., 2019; Favoreto et al., 2019). In addition, follicles from Nelore heifers show higher expression of IGF, BMP, and TGFbeta family genes (Favoreto et al., 2019). These genes are known to be associated with follicle activation and development. The fact that Angus heifers have a polymorphism associated with fibrillin, which regulates these important growth factors, may be one of the reasons for the difference in preantral and antral follicle density in these animals.

Understanding how candidate genes act in modeling the phenotype is a major challenge that is further complicated by the fact that the environment can influence the phenotype. However, the functional information obtained in the present GWAS has focused the study of biological processes and may contribute to future research aimed at validating these genes and elucidating the mechanisms involved in the phenotype. The trait age at first calving in heifers from Nellore exposed to different environmental conditions, especially rainfall and feeding, is associated with regions showing environmental dependence. In animals reared under different environmental conditions, the genomic region on BTA14 acts on metabolic substrates, and these variations are directly involved in the control of reproductive pathways that are essential for early maturity (Mota et al., 2020). BTA 14 also has significant SNPs associated with reproductive function here and in other studies (Kneeland et al., 2004; Buzanskas et al., 2017).

In summary, the GWAS in Nelore and Angus heifers showed SNPs associated with the higher follicle count phenotype. In addition, the HFC heifers had SNPs associated with follicle formation and development.

Acknowledgements

The authors thank São Paulo Research Foundation (FAPESP) for funding (Grant #2011/50964-0) and scholarships for Favoreto, Loureiro, Ereno, Pupulim and Queiroz.

Funding Statement

Financial support: Received funding for this research from Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP). Grant: #2011/50964-0.

Footnotes

Financial support: Received funding for this research from Fundação de Amparo a Pesquisa do Estado de São Paulo (FAPESP). Grant: #2011/50964-0.

How to cite: Loureiro B, Ereno RL, Pupulim AGR, Tramontana MCVB, Tabosa HP, Barros CM, Favoreto MG. Genome-wide association study of Nelore and Angus heifers with low and high ovarian follicle counts. Anim Reprod. 2024;21(1):e20230110. https://doi.org/10.1590/1984-3143-AR2023-0110

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