Genome-Wide Association Studies of Growth Trait Heterosis in Crossbred Meat Rabbits

The application of heterosis can not only effectively improve the disease resistance and meat quality of livestock, but also significantly enhance the reproduction and growth of livestock and poultry. We conducted genome-wide association studies using data from F2 crossbred meat rabbits to screen out candidate genes with significant dominant effects associated with economic trait variation. High-throughput sequencing technology was used to obtain SNPs covering the whole genome to evaluate the homozygosity of the population genome, and analyze the number, length, frequency, and distribution of ROHs in the population. Candidate genes related to economic traits of meat rabbits were searched based on high-frequency ROH regions. After quality control filtering of genotype data, 380 F2 crossbred rabbits were identified with 78,579 SNPs and 42,018 ROHs on the autosomes. The fitting of the Logistic growth curve model showed that 49-day-old rabbits were a growth inflection point. Then, through genome-wide association studies, 10 SNP loci and seven growth trait candidate genes were found to be significantly related to body weight in meat rabbits at 84 days of age. In addition, we revealed the functional roles and locations of 20 candidate genes in the high-frequency ROH region associated with economic traits in meat rabbits. This study identified potential genes associated with growth and development in the high-frequency ROH region of meat rabbits. In this study, the identified candidate genes can be used as molecular markers for assisted selection in meat rabbits. At the same time, the inbreeding situation based on ROH assessment can provide reference for breeding and breeding preservation of meat rabbits.

Genome-wide association and functional annotation analysis for the calving interval in Nellore cattle

Calving interval (CI) measures the number of days between two consecutive calves of the same cow, and previous studies based on phenotype and pedigree data reported low heritability for this trait. However, the genetic architecture of CI in the Nellore breed was not evaluated based on genomic data. Thus, this study aimed to estimate the heritability based on genomic data and carry out a genome-wide association study (GWAS) for CI in the Nellore breed, using 12,599 pedigree records, 5078 CI records, and 3818 animals genotyped with 50k SNPchip panel. Both quality control and GWAS were performed in BLUPF90 family packages, which use the single-step genomic best linear unbiased predictor (ssGBLUP) method. The average CI was 427.6 days, with a standard deviation of 106.9 and a total range of 270-730 days. The heritability estimate was 0.04 ± 0.04. The p-values of GWAS analysis resulted in a genomic inflation factor (lambda) of 1.08. The only significant SNP (rs136725686) at the genome-wide level (p-value = 1.53E-06) was located on BTA13. Other 19 SNPs were significant at the chromosome-wide level, distributed on BTA1, 2, 3, 6, 10, 13, 14, 17, 18, 22, and 26. Functional annotation analysis found thirty-six protein-coding genes, including genes related to cell cycle (RAD21, BCAR3), oocyte function (LHX8, CLPX, UTP23), immune system (TXK, TEC, NFATC2), endocrine function (LRRFIP2, GPR158), estrous cycle (SLC38A7), and female fertility (CCK, LYZL4, TRAK1, FOXP1, STAC). Therefore, CI is a complex trait with small heritability in Nellore cattle, and various biological processes may be involved with the genetic architecture of CI in Nellore cattle.

Evidence of differentiation and population structure in Charolais cattle of Mexico

Charolais is one of the most important beef cattle breeds in the world. In Mexico, it was introduced almost a century ago, and it has been suggested that particular breeding management and genetic material origin have caused a process of divergence among the current population. By a high-density SNP array genome-wide analysis, this study aimed to assess the proposed differentiation and population structure of local populations by genetic distances and structure approaches, and a European Charolais sample was included as a reference population. The differentiation statistics indicated that local populations exhibit moderate divergence, confirming a significant differentiation process between northeastern and northwestern Charolais populations (Fst≥ 0.043, D≥ 0.031). These results were strongly supported by PCA and structure analysis. Genetic isolation and low genetic flow between populations and divergent origins of introduced genetic material (i.e., semen) are likely the main drivers of the outcomes. Some implications are discussed.

Genetic improvement of economic traits in Murrah buffalo using significant SNPs from genome-wide association study

GWAS helps to identify QTL and candidate genes of specific traits. Buffalo breeding has primarily focused on milk production, but its negative correlation with reproduction traits resulted in unfavorable decline of reproductive performance among buffaloes. A genome wide scan was performed on a total of 120 Murrah buffaloes genotyped by ddRAD sequencing for 13 traits related to female fertility, production, and growth. The identified 25 significant single nucleotide polymorphisms (SNPs) (P <1×10⁶) are associated with age at first calving (AFC), age at first service (AFS), period from calving to 1^st Artifical Insemination (AI), service period (SP) and 6 month body weight (6M). Fifteen genetic variants overlapped with different QTL regions of reported studies. Among the associated loci, outstanding candidate genes for fertility, including AQP1, TRNAE-CUC, NRIP1, CPNE4, and VOPP1, have effect in different fertility traits. AQP1 gene is expressed in ovulatory phase and various stages of pregnancy. TRNAE-CUC gene is associated with AFC and number . of calvings after 4 years of age. Glycogen content-associated gene CPNE4 regulates muscle glycogen and is upregulated during early pregnancy. NRIP1 generegulates ovulation, corpus luteum at pregnancy, and mammary gland development. The objective is to identify potential genomic regions and genetic variants associated with economic traits and to select the most significant SNP which have positive effect on all the traits.

Genomic Uniqueness of Local Sheep Breeds From Morocco

Sheep farming is a major source of meat in Morocco and plays a key role in the country's agriculture. This study aims at characterizing the whole-genome diversity and demographic history of the main Moroccan sheep breeds, as well as to identify selection signatures within and between breeds. Whole genome data from 87 individuals representing the five predominant local breeds were used to estimate their level of neutral genetic diversity and to infer the variation of their effective population size over time. In addition, we used two methods to detect selection signatures: either for detecting selective sweeps within each breed separately or by detecting differentially selected regions by contrasting different breeds. We identified hundreds of genomic regions putatively under selection, which related to several biological terms involved in local adaptation or the expression of zootechnical performances such as Growth, UV protection, Cell maturation or Feeding behavior. The results of this study revealed selection signatures in genes that have an important role in traits of interest and increased our understanding of how genetic diversity is distributed in these local breeds. Thus, Moroccan local sheep breeds exhibit both a high genetic diversity and a large set of adaptive variations, and therefore, represent a valuable genetic resource for the conservation of sheep in the context of climate change.

Discovering of Genomic Variations Associated to Growth Traits by GWAS in Braunvieh Cattle

A genome-wide association study (GWAS) was performed to elucidate genetic architecture of growth traits in Braunvieh cattle. Methods: The study included 300 genotyped animals by the GeneSeek^® Genomic Profiler Bovine LDv.4 panel; after quality control, 22,734 SNP and 276 animals were maintained in the analysis. The examined phenotypic data considered birth (BW), weaning (WW), and yearling weights. The association analysis was performed using the principal components method via the egscore function of the GenABEL version 1.8-0 package in the R environment. The marker rs133262280 located in BTA 22 was associated with BW, and two SNPs were associated with WW, rs43668789 (BTA 11) and rs136155567 (BTA 27). New QTL associated with these liveweight traits and four positional and functional candidate genes potentially involved in variations of the analyzed traits were identified. The most important genes in these genomic regions were MCM2 (minichromosome maintenance complex component 2), TPRA1 (transmembrane protein adipocyte associated 1), GALM (galactose mutarotase), and NRG1 (neuregulin 1), related to embryonic cleavage, bone and tissue growth, cell adhesion, and organic development. This study is the first to present a GWAS conducted in Braunvieh cattle in Mexico providing evidence for genetic architecture of assessed growth traits. Further specific analysis of found associated genes and regions will clarify its contribution to the genetic basis of growth-related traits.

Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle

Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.

Assessing the genetic background and genomic relatedness of red cattle populations originating from Northern Europe

Background

Local cattle breeds need special attention, as they are valuable reservoirs of genetic diversity. Appropriate breeding decisions and adequate genomic management of numerically smaller populations are required for their conservation. At this point, the analysis of dense genome-wide marker arrays provides encompassing insights into the genomic constitution of livestock populations. We have analyzed the genetic characterization of ten cattle breeds originating from Germany, The Netherlands and Denmark belonging to the group of red dairy breeds in Northern Europe. The results are intended to provide initial evidence on whether joint genomic breeding strategies of these populations will be successful.

Results

Traditional Danish Red and Groningen White-Headed were the most genetically differentiated breeds and their populations showed the highest levels of inbreeding. In contrast, close genetic relationships and shared ancestry were observed for the populations of German Red and White Dual-Purpose, Dutch Meuse-Rhine-Yssel, and Dutch Deep Red breeds, reflecting their common histories. A considerable amount of gene flow from Red Holstein to German Angler and to German Red and White Dual-Purpose was revealed, which is consistent with frequent crossbreeding to improve productivity of these local breeds. In Red Holstein, marked genomic signatures of selection were reported on chromosome 18, suggesting directed selection for important breeding goal traits. Furthermore, tests for signatures of selection between Red Holstein, Red and White Dual-Purpose, and Meuse-Rhine-Yssel uncovered signals for all investigated pairs of populations. The corresponding genomic regions, which were putatively under different selection pressures, harboured various genes which are associated with traits such as milk and beef production, mastitis and female fertility.

Conclusions

This study provides comprehensive knowledge on the genetic constitution and genomic connectedness of divergent red cattle populations in Northern Europe. The results will help to design and optimize breeding strategies. A joint genomic evaluation including some of the breeds studied here seems feasible.

Genome-wide association study identified genomic regions and putative candidate genes affecting meat color traits in Nellore cattle

Single and multiple-trait GWAS were conducted to detect genomic regions and candidate genes associated with meat color traits (L*, lightness; a*, redness; b*, yellowness) in Nellore cattle. Phenotypic records of 5000 animals, and 3794 genotypes for 614,274 SNPs were used. The BLUPF90 family programs were used through single step GWAS approach. The top 10 genomic regions from single-trait GWAS explained 13.64%, 15.12% and 13% of genetic variance of L*, a* and b*, which harbored 129, 70, and 84 candidate genes, respectively. Regarding multiple-trait GWAS, the top 10 SNP windows explained 17.46%, 18.98% and 13.74% of genetic variance of L*, a* and b*, and harbored 124, 86, and 82 candidate genes, respectively. Pleiotropic effects were evidenced by the overlapping regions detected on BTA 15 and 26 associated with L* and a* (genetic correlation of -0.53), and on BTA 18 associated with a* and b* (genetic correlation of 0.60). Similar genomic regions located on BTA 2, 5, 6, and 18 were detected through single and multi-trait GWAS. Overlapped regions harbored a total of 30 functional candidate genes involved in mitochondrial activity, structural integrity of muscles, lipid oxidation, anaerobic metabolism, and muscular pH.

Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle

Background

Body size traits as one of the main breeding selection criteria was widely used to monitor cattle growth and to evaluate the selection response. In this study, body size was defined as body height (BH), body length (BL), hip height (HH), heart size (HS), abdominal size (AS), and cannon bone size (CS). We performed genome-wide association studies (GWAS) of these traits over the course of three growth stages (6, 12 and 18 months after birth) using three statistical models, single-trait GWAS, multi-trait GWAS and LONG-GWAS. The Illumina Bovine HD 770 K BeadChip was used to identify genomic single nucleotide polymorphisms (SNPs) in 1217 individuals.

Results

In total, 19, 29, and 10 significant SNPs were identified by the three models, respectively. Among these, 21 genes were promising candidate genes, including SOX2, SNRPD1, RASGEF1B, EFNA5, PTBP1, SNX9, SV2C, PKDCC, SYNDIG1, AKR1E2, and PRIM2 identified by single-trait analysis; SLC37A1, LAP3, PCDH7, MANEA, and LHCGR identified by multi-trait analysis; and P2RY1, MPZL1, LINGO2, CMIP, and WSCD1 identified by LONG-GWAS.

Conclusions

Multiple association analysis was performed for six growth traits at each growth stage. These findings offer valuable insights for the further investigation of potential genetic mechanism of growth traits in Simmental beef cattle.

Weighted Single-Step Genome-Wide Association Study for Growth Traits in Chinese Simmental Beef Cattle

Improving the genetic process of growth traits is one of the major goals in the beef cattle industry, as it can increase meat production and reduce the cost of raising animals. Although several quantitative trait loci affecting growth traits in beef cattle have been identified, the genetic architecture of these economically important traits remains elusive. This study aims to map single nucleotide polymorphisms (SNPs) and genes associated with birth weight (BW), yearling weight (YW), average daily gain from birth to yearling (BYADG), and body weight at the age of 18 months (18MW) in a Chinese Simmental beef cattle population using a weighted, single-step, genome-wide association study (wssGWAS). Phenotypic and pedigree data from 6022 animals and genotypes from 744 animals (596,297 SNPs) were used for an association analysis. The results showed that 66 genomic windows explained 1.01-20.15% of the genetic variance for the four examined traits, together with the genes near the top SNP within each window. Furthermore, the identified genomic windows (>1%) explained 50.56%, 57.71%, 61.78%, and 37.82% of the genetic variances for BW, YW, BYADG, and 18MW, respectively. Genes with potential functions in muscle development and regulation of cell growth were highlighted as candidates for growth traits in Simmental cattle (SQOR and TBCB for BW, MYH10 for YW, RLF for BYADG, and ARHGAP31 for 18MW). Moreover, we found 40 SNPs that had not previously been identified as being associated with growth traits in cattle. These findings will further advance our understanding of the genetic basis for growth traits and will be useful for the molecular breeding of BW, YW, BYADG, and 18MW in the context of genomic selection in beef cattle.

Adaptive introgression from indicine cattle into white cattle breeds from Central Italy

Cattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies.

Accuracies of direct genomic breeding values for birth and weaning weights of registered Charolais cattle in Mexico

Context Genomic prediction is now routinely used in many livestock species to rank individuals based on genomic breeding values (GEBV). Aims This study reports the first assessment aimed to evaluate the accuracy of direct GEBV for birth (BW) and weaning (WW) weights of registered Charolais cattle in Mexico. Methods The population assessed included 823 animals genotyped with an array of 77000 single nucleotide polymorphisms. Genomic prediction used genomic best linear unbiased prediction (GBLUP), Bayes C (BC), and single-step Bayesian regression (SSBR) methods in comparison with a pedigree-based BLUP method. Key results Our results show that the genomic prediction methods provided low and similar accuracies to BLUP. The prediction accuracy of GBLUP and BC were identical at 0.31 for BW and 0.29 for WW, similar to BLUP. Prediction accuracies of SSBR for BW and WW were up to 4% higher than those by BLUP. Conclusions Genomic prediction is feasible under current conditions, and provides a slight improvement using SSBR. Implications Some limitations on reference population size and structure were identified and need to be addressed to obtain more accurate predictions in liveweight traits under the prevalent cattle breeding conditions of Mexico.

Genomic Prediction and Association Analysis with Models Including Dominance Effects for Important Traits in Chinese Simmental Beef Cattle

Simple Summary

Dominance effects play important roles in determining genetic changes with regard to complex traits. We conducted genomic predictions and genome-wide association studies in order to investigate the effects of dominance on carcass weight, dressing percentage, meat percentage, average daily gain, and chuck roll in 1233 Simmental beef cattle. Using dominance models, we improved the predictive abilities and found several candidate single-nucleotide polymorphisms (SNPs) and genes associated with these traits. Our studies helped us to understand causal mutation mapping and genomic selection models with dominance effects in Chinese Simmental beef cattle.

Abstract

Non-additive effects play important roles in determining genetic changes with regard to complex traits; however, such effects are usually ignored in genetic evaluation and quantitative trait locus (QTL) mapping analysis. In this study, a two-component genome-based restricted maximum likelihood (GREML) was applied to obtain the additive genetic variance and dominance variance for carcass weight (CW), dressing percentage (DP), meat percentage (MP), average daily gain (ADG), and chuck roll (CR) in 1233 Simmental beef cattle. We estimated predictive abilities using additive models (genomic best linear unbiased prediction (GBLUP) and BayesA) and dominance models (GBLUP-D and BayesAD). Moreover, genome-wide association studies (GWAS) considering both additive and dominance effects were performed using a multi-locus mixed-model (MLMM) approach. We found that the estimated dominance variances accounted for 15.8%, 16.1%, 5.1%, 4.2%, and 9.7% of the total phenotypic variance for CW, DP, MP, ADG, and CR, respectively. Compared with BayesA and GBLUP, we observed 0.5–1.1% increases in predictive abilities of BayesAD and 0.5–0.9% increases in predictive abilities of GBLUP-D, respectively. Notably, we identified a dominance association signal for carcass weight within RIMS2, a candidate gene that has been associated with carcass weight in beef cattle. Our results suggest that dominance effects yield variable degrees of contribution to the total genetic variance of the studied traits in Simmental beef cattle. BayesAD and GBLUP-D are convenient models for the improvement of genomic prediction, and the detection of QTLs using a dominance model shows promise for use in GWAS in cattle.

Genetic variances and covariances of live weight traits in Charolais cattle by multi-trait analysis

Live weight traits are economically important for beef cattle production systems. Genetic analysis of live weight traits frequently presents a problem due to animal records, in that matter, not all the animals have complete records as many young animals leave the herd because of sale, transfer to another herd, or culling reasons. Therefore, the use of multi-trait genetic analysis might be of assistance to help overcome any possible loss of information for those animals with incomplete records. In this study, genetic variances and covariances were obtained to estimate genetic parameters for birth (BW), weaning (WW), and yearling (YW) live weights in a registered Charolais beef cattle population using a multivariate model, where a considerable reduction of data from birth weight to year weight was observed. Direct and maternal heritabilities for BW, WW, and YW were 0.50, 0.30, and 0.28, and 0.31, 0.25, and 0.14, respectively. Direct and maternal genetic correlations were negative in all live weight traits. Genetic correlations among direct BW with direct WW and YW were low, while genetic correlations among maternal traits were medium or high (r>0.39). Comparison between univariate and multi-trait models with substantial reduction of information revealed important differences, implying that multi-trait analysis is better for the structure of data allowing a better fitting of genetic effects by covariance among evaluated traits. Results support multi-trait analysis implementation for genetic evaluations for live weight traits of Charolais cattle.

The PLAG1 mRNA expression analysis among genetic variants and relevance to growth traits in Chinese cattle

Pleomorphic adenoma gene 1 (PLAG1) encodes a developmentally regulated zinc finger protein, locating in growth-related QTNs. The mRNA expression of this gene was investigated in different tissues and from two different developmental periods, whilst to explore the functions of PLAG1 in growth traits of cattle. The results showed that PLAG1 was expressed in all examined tissues. However, PLAG1 expression levels in all examined tissues were significantly different between the 5-month fetus and 36-month adult cattle. Our juvenile results indicated PLAG1 is primarily expressed in embryonic tissues of Chinese cattle. Furthermore, two variations were identified. Association analysis revealed that the two variations were associated with growth traits (p < 0.05 or p < 0.01). These new findings provide a comprehensive overview of the critical roles of PLAG1 in growth traits modulation and can be highlighted as candidate molecular markers in cattle breeding.

Signatures of selection in Charolais beef cattle identified by genome-wide analysis

Charolais cattle are one of the most important breeds for meat production worldwide; in México, its selection is mainly made by live weight traits. One strategy for mapping important genomic regions that might influence productive traits is the identification of signatures of selection. This type of genomic features contains loci with extended linkage disequilibrium (LD) and homozygosity patterns that are commonly associated with sites of quantitative trait locus (QTL). Therefore, the objective of this study was to identify the signatures of selection in Charolais cattle genotyped with the GeneSeek Genomic Profiler Bovine HD panel consisting of 77 K single nucleotide polymorphisms (SNPs). A total 61,311 SNPs and 819 samples were used for the analysis. Identification of signatures of selection was carried out using the integrated haplotype score (iHS) methodology implemented in the rehh R package. The top ten SNPs with the highest piHS values were located on BTA 4, 5, 6 and 14. By identifying markers in LD with top ten SNPs, the candidate regions defined were mapped to 52.8-59.3 Mb on BTA 4; 67.5-69.3 on BTA 5; 39.5-41.0 Mb on BTA 6; and 26.4-29.6 Mb on BTA 14. The comparison of these candidate regions with the bovine QTLdb effectively confirmed the association (p < 0.05) with QTL related to growth traits and other important productive traits. The genomic regions identified in this study indicated selection for growth traits on the Charolais population via the conservation of haplotypes on various chromosomes. These genomic regions and their associated genes could serve as the basis for haplotype association studies and for the identification of causal genes related to growth traits.

Genome-wide association scan for heterotic quantitative trait loci in multi-breed and crossbred beef cattle

BACKGROUND

Heterosis has been suggested to be caused by dominance effects. We performed a joint genome-wide association analysis (GWAS) using data from multi-breed and crossbred beef cattle to identify single nucleotide polymorphisms (SNPs) with significant dominance effects associated with variation in growth and carcass traits and to understand the mode of action of these associations.

METHODS

Illumina BovineSNP50 genotypes and phenotypes for 11 growth and carcass traits were available for 6796 multi-breed and crossbred beef cattle. After performing quality control, 42,610 SNPs and 6794 animals were used for further analyses. A single-SNP GWAS for the joint association of additive and dominance effects was conducted in purebred, crossbred, and combined datasets using the ASReml software. Genomic breed composition predicted from admixture analyses was included in the mixed effect model to account for possible population stratification and breed effects. A threshold of 10% genome-wide false discovery rate was applied to declare associations as significant. The significant SNPs with dominance association were mapped to their corresponding genes at 100 kb.

RESULTS

Seven SNPs with significant dominance associations were detected for birth weight, weaning weight, pre-weaning daily gain, yearling weight and marbling score across the three datasets at a false discovery rate of 10%. These SNPs were located on bovine chromosomes 1, 3, 4, 6 and 21 and mapped to six putative candidate genes: U6atac, AGBL4, bta-mir-2888-1, REPIN1, ICA1 and NXPH1. These genes have interesting biological functions related to the regulation of gene expression, glucose and lipid metabolism and body fat mass. For most of the identified loci, we observed over-dominance association with the studied traits, such that the heterozygous individuals at any of these loci had greater genotypic values for the trait than either of the homozygous individuals.

CONCLUSIONS

Our results revealed very few regions with significant dominance genetic effects across all the traits studied in the three datasets used. Regarding the SNPs that were detected with dominance associations, further investigation is needed to determine their relevance in crossbreeding programs assuming that dominance effects are the main cause of (or contribute usefully to) heterosis.

Genome-wide association studies identified multiple genetic loci for body size at four growth stages in Chinese Holstein cattle

The growth and maturity of cattle body size affect not only feed efficiency, but also productivity and longevity. Dissecting the genetic architecture of body size is critical for cattle breeding to improve both efficiency and productivity. The volume and weight of body size are indicated by several measurements. Among them, Heart Girth (HG) and Hip Height (HH) are the most important traits. They are widely used as predictors of body weight (BW). Few association studies have been conducted for HG and HH in cattle focusing on single growth stage. In this study, we extended the Genome-wide association studies to a full spectrum of four growth stages (6-, 12-, 18-, and 24-months after birth) in Chinese Holstein heifers. The whole genomic single nucleotide polymorphisms (SNPs) were obtained from the Illumina BovineSNP50 v2 BeadChip genotyped on 3,325 individuals. Estimated breeding values (EBVs) were derived for both HG and HH at the four different ages and analyzed separately for GWAS by using the Fixed and random model Circuitous Probability Unification (FarmCPU) method. In total, 27 SNPs were identified to be significantly associated with HG and HH at different growth stages. We found 66 candidate genes located nearby the associated SNPs, including nine genes that were known as highly related to development and skeletal and muscular growth. In addition, biological function analysis was performed by Ingenuity Pathway Analysis and an interaction network related to development was obtained, which contained 16 genes out of the 66 candidates. The set of putative genes provided valuable resources and can help elucidate the genomic architecture and mechanisms underlying growth traits in dairy cattle.