Introduction

The ear is primarily responsible for converting sound waves into nerve impulses that are translated in the brain into auditory perception in animals (Van 2003). The central nervous system in the brain then translates these impulses into a spoken language, birds chirping, or the cow’s moo. The ear serves other vital functions, like heat radiation (Law et al. 1979), sense of balance (Ekdale 2016; Horwitz et al. 2011; Torres and Giráldez 1998), and external signals in the mood besides auditory perception (Reefmann et al. 2009). The ear consists of three sections, i.e., external, middle, and inner ears (Webster 1966). The external ear includes an external auditory canal (Alvord and Farmer 1997), an eardrum, and a visible pinna that reside outside of the head and can collect sound and direct it down the ear canal. Over time, mammals adapt to their respective environmental conditions and evolve with an extraordinary variety of ear shapes and sizes. For example, animals adapt to high-temperature and hot environments and evolve with large ears to combat heat waves, such as African elephants. African elephants adjust their body temperature through their large ears, providing shade to reduce the loss of water in the body (Phillips and Heath 1992). Furthermore, a general observation includes large ear sizes in indicine cattle, such as Brahman and Burmese cattle, which harbor in harsh hot environments. By contrast, most animals inhabiting temperate or cold regions, such as the Arctic fox, tend to have small ears. The small size of the ear can help mammals to reduce heat dissipation and maintain their body temperature. Likewise, cattle adapting to cold environments, such as Yanbian, Yakut, and Tibetan cattle, share small ears.

Size and orthotropism are important conformational characteristics of ears with huge diversity in different species. With the development of the whole-genome resequencing technology, the genome-wide association study (GWAS) has been applied to reveal SNPs associated with complex ear traits in livestock. Previous studies showed that significant quantitative trait loci (QTLs) for pig ear size are located on Sus scrofa chromosomes (SSCs) 5 and 7 (Ma et al. 2009; Wei et al. 2007). A missense mutation (G32E) in the PPARD gene on SSC7 is considered to be responsible for the differences in porcine ear size (Ren et al. 2011; Wilkinson et al. 2013). The QTL fine mapping on SSC5 revealed that LEMD3 is one of the most important candidates for porcine ear size (Zhang et al. 2014). Moreover, GWAS revealed that DCC, SOX5, and PTPRD are potential candidate genes for ear size in sheep (Gao et al. 2018). Furthermore, genome fragments containing WIF1 and HMGA2 appear to control ear size in pigs and dogs (Vaysse et al. 2011). However, no current report exists on the ear size of cattle, but the available resources of cattle are rich worldwide.

Cattle are not only important for their meat and milk production but also represent an important large-animal model for the study of some important economic traits (Herath et al. 2006). Ear sizes among cattle breeds are diverse. Bos indicus breeds, such as Brahman cattle, have large and lop ears, whereas Bos taurus breeds have small and erect ears. Overall, ear size is an important distinguishing characteristic among subspecies. China has a wide geographical latitude span, with taurine and indicine cattle breeds distributed from north to south, and is a natural cattle breed resource bank for studying ear size. Yunling cattle is a typical hybrid cow with variable ear size, and therefore, it is an ideal model for studying the genetic basis of ear size traits. In the current study, GWAS is performed to screen potential candidate genes, which are further systematically analyzed to identify the associated loci and the candidate mutation in a particular gene or region. Our findings provide new insights into the genetic basis of the ear size of cattle and provide important molecular markers for the identification of cattle germplasm resources.

Materials and methods

Ethics statement

In accordance with the recommendation of the Regulations for the Administration of Affairs Concerning Experimental Animals of China, the Institutional Animal Care and Use Committee of Northwest A&F University approved all animal experiments.

Sample collection and genome sequencing

Individuals used for ear size trait comprised 158 adult female cattle aged around 2 years old (39 Brahman and 119 Yunling cattle). The Yunling cattle, a typical hybrid cattle breed, was bred by the Yunnan Academy of Grassland and Animal Science. Ear tissue samples were collected from adult females. The standard phenol–chloroform protocol was used to extract the genomic DNA from the ear tissue (Green et al. 2012). A total of 158 paired-end libraries with an insert size of 350 bp were constructed and sequenced using the Illumina NovaSeq. The length of the reads was 150 bp. The sequence data used in this paper were obtained from published papers where detailed information about sampling and sequencing was available (Chen et al. 2020).

Measurement and calculation of ear size

In this study, we used the “living pixel method” to collect the ear shape photo with a standard scale of 475 cattle (39 Brahman, 119 Yunling, 65 Simmental, 52 Burmese, 100 Wenshan, and 100 Dabieshan cattle). All individuals were female, aged 2 years, and had similar body sizes in one breed. The head of the cattle was restrained, and the scale-labeled left ear was flattened for the picture. Digital images were taken using a high-pixel camera in a horizontal position. The ear size of each animal was measured using Photoshop CS6 (Adobe, USA). First, the graphs of the ear range and 1 cm2 in the scale were obtained through the “magnetic lasso” tool, and pixel numbers corresponding to the above parameters were obtained through the “histogram” tool. The ear size could be obtained through the “measuring record” tool and the pixel ratio column.

Read mapping and SNP calling

Default parameters were used to map clean reads to the cattle reference assembly ARS-UCD1.2 (Rosen et al. 2020) by using BWA-MEM (Li and Durbin 2009). Duplicate reads were filtered using the “REMOVE_DUPLICATES = true” option of Picard tools. The “HaplotypeCaller”, “GenotypeGVCFs”, and “SelectVariants” arguments of the Genome analysis toolkit 3.8 (Nekrutenko and Taylor 2012) were used for calling raw SNPs. The average alignment rate and coverage were 99.54% and 5.61×, respectively. The argument “VariantFiltration” of the same software was applied to all raw SNPs with the following options: DP < 303 (1/3-fold total sequence depth for all individuals), DP > 2727 (threefold of total sequence depth for all individuals), QD < 2, FS > 60, MQ < 40.0, MQRankSum < −12.5, ReadPosRankSum < −8.0, and 1/3× < mean sequence depth (for all individuals) < 3×. In addition, the haplotype-phase inference and missing allele imputation were produced using Beagle v.4.1 (Browning and Browning 2007) to carry out the GWAS further. Based on about 41M autosomal SNPs, we estimated the eigenvectors by using the smartPCA of the EIGENSOFT v5.0 package (Patterson et al. 2006) to adjust the population structure in GWAS. The principal component 1 based on the genotype matrix separated the Brahman cattle from Yunling cattle, and this finding was in accordance with those in a previous study (Chen et al. 2020).

GWAS analysis

Based on 158 sequenced genomes, 13,057,965 SNPs (MAF > 0.10, missing rate > 0.1) were used in GWAS for the ear size trait. The primary association analysis was carried out using the genome-wide efficient mixed-model association (GEMMA) software package (Zhou and Stephens 2012). The mixed linear model assumed the following model:

$$y = {\mathrm{X}}\alpha + {\mathrm{S}}\beta + {\mathrm{K}}\mu + \varepsilon$$

where y is a vector of phenotypes, α is a vector of fixed effects representing marker effects, β is a vector of fixed effects representing nonmarker effects, and μ is a vector of unknown random effect. X, S, and K represent the incidence matrices relating α, β, and μ, respectively, and ε represents a vector of random residual effects. The top three PCs and feeding regimes were defined as the S matrix. The kinship matrix calculated from nucleotide polymorphism was defined as the K matrix.

The secondary association analysis used a multiple linear regression model using PLINK v. 1.90b6.21 (Purcell et al. 2007), combining body height, cross high, head length, head width, and top three PCs as covariates to perform GWAS on the ear size phenotype. The number of linkage disequilibrium (LD)-pruned SNPs (750,367) was defined as the effective number of independent SNPs and calculated using PLINK (–indep-pairwise 50 5 0.2) to estimate the correction required for multiple testing. Therefore, the significance and suggestive threshold were defined as approximately 5 × 10−8 (0.05/750,367) and 1 × 10−6 (1/750,367), respectively. Thresholds were widely used by numerous studies.

Identification of candidate genes in the GWAS-associated loci

We used the following strategy to narrow down our findings. First, PLINK (Purcell et al. 2007) was used to estimate candidate regions by using the pairwise LD correlation (r2 > 0.6) between SNPs related to ear size characteristics, and the count of suggestive SNPs < 3 was used as false positives and removed. Second, SNPs (leading SNPs) with Pwald values < 1 × 10−6 were characterized as candidate SNPs, and the functional annotation of suggestive associated SNPs was carried out in accordance with the Bos taurus reference genome in the package ANNOVAR version (Wang et al. 2010).

Selective sweep analysis

The genomes of groups with big and small ears were compared on the basis of the phenotype relationship of ear size to identify the signatures of positive selection. First, the genome-wide distribution of FST values was estimated using the VCFtools (Danecek et al. 2011) with 100 kb window size and 50 kb increment to investigate pairwise genetic differentiation among groups with big and small ears. To further identify the selection signals within each cattle breed, we used SweeD, an open-source tool for the rapid detection of selective sweeps in whole genomes (Pavlidis et al. 2013). We also calculated the SweeD for 14 cattle breeds (i.e., Angus, Brahman, Burmese, Hanwoo, Hereford, Holstein, Kazakh, Ji’an, Longlin, Mishima, Mongolian, Muturu, Simmental, and Yanbian cattle) by using the SweepFinder2 (DeGiorgio et al. 2016) with a sliding window approach (100 kb windows with 50 kb increments). Only the strong regions overlapping both methods (SweeD: top 1%, FST: top 1%) were defined as candidate regions under positive selection. A custom perl script was used to annotate the regions under selection on the basis of the Bos taurus reference genome (ARS-UCD1.2).

RNA extraction and quantitative PCR

Ear tissue samples from ten Simmental cattle with small ear sizes and ten Brahman cattle with large ear sizes were used for qRT-PCR analysis. Total RNA was extracted using the PrimeScriptTM RT reagent Kit with gDNA Eraser (Takara, Beijing, China). The first-strand cDNA was synthesized from 1 μg of total RNA using the Omniscript reverse transcriptase kit (Qiagen, Germany). qPCR was performed in a 20 μL reaction volume containing 2 μL of 3-fold diluted cDNA, 10 μL of 2× Power SYBR Green Master mix (Applied Biosystems, USA), and 150 nM of each primer, with the following thermocycling conditions: 10 min at 95 °C followed by 40 cycles at 95 °C for 15 s, 60 °C for 1 min and 72 °C for 30 s. Then, a dissociation curve analysis was performed.β-actin was used as an internal control (Livak and Schmittgen 2002). Gene-specific primers and probes were designed using the primer premier 5.0 software (forward primer CAGCAGCAACAGCACAGAGG and reverse primer CATTGGTGCCTGTTTGTTCAT). qPCR was performed using the 7500 Fast real-time PCR System (Applied Biosystems, USA). The experiment was repeated three times for each group.

Results

Ear size variation trait analyses

Ear sizes among different cattle individuals and breeds are evidently different. As a general observation, the ear size of Bos indicus in the Indo-Pak region was larger than that of Bos taurus in the world, whereas hybrid cattle breeds depicted diversified ear size (Fig. 1A). According to this observational phenomenon, ear size data were collected and calculated from 475 adult female cattle (Supplementary Table S1), including six representative breeds (i.e., Burmese, Brahman, Simmental, Yunling, Wenshan, and Dabieshan cattle) by using the pixel method (Yang et al. 2013). The overall ear size data ranged from 87.81 to 330.85 cm2. Bos indicus breeds (i.e., Brahman and Burmese cattle) had the largest mean values, which were 226.75 and 254.06 cm2, respectively. By contrast, Bos taurus (i.e., Simmental cattle) had the smallest mean value, which was 134.62 cm2. The sizes of hybrid breed (i.e., Yunling cattle) and Chinese indicine (i.e., Wenshan and Dabieshan cattle) cattle were relatively scattered. The Yunling, Wenshan, and Dabieshan cattle had average values of 164.21, 186.31, and 184.37 cm2, respectively (Table 1). The ear size distribution of all individuals showed a unimodal distribution according to the histogram and density plot (Fig. 1B) and could be well distinguished in three distinct intervals, i.e., big (>230 cm2), middle (<230 and >148 cm2), and small (<148 cm2) ears with 25 and 75% quantiles of all individuals’ boxplot analysis. The boxplot and F statistic were used to analyze the variance in the ear size among six cattle breeds. Results showed that the ear size of breeds followed the order: Bos indicus > hybrid (Yunling) and Chinese indicine (Wenshan and Dabieshan cattle) cattle > Bos taurus (Fig. 1C). Moreover, the F statistic results suggested that ear sizes among cattle breeds were significantly different, supporting the above statement.

Fig. 1: Statistical analysis of ear size.
figure 1

A Ear diversity of different cattle breeds, the first column was smaller ear size cattle (Simmental and Dabieshan cattle), and the second column represents hybrid cattle, while the third column shows the large ear size Bos indicus cattle (Brahman and Burmese cattle). B Histogram plot for 475 ear size data, the vertical axis on the left represents number of individuals in different sections. C Boxplot analysis for ear size among all individuals and six cattle breeds.

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Table 1 Descriptive statistics of ear size in cattle breeds.
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Genome-wide association studies for ear size trait

Based on 13,057,965 autosomal SNPs derived from 158 published resequencing cattle data (Supplementary Table S2) (Chen et al. 2020), a GEMMA (Zhou and Stephens 2012) was used in the primary GWAS to identify the significant loci. Figure 2A shows the Manhattan plot for the GWAS. Red and blue horizontal lines represent the Bonferroni-adjusted genome-wide significant and suggestive threshold. A total of 4 significant SNPs and 50 suggestive SNPs showed genome-wide associations with ear size (Supplementary Table S3). However, most of the significant potential SNPs were located on BTA6 (36.79–38.80 Mb) (Fig. 2B). The significant locus (P = 1.30 × 10−8) was located in the integrin-binding sialoprotein (IBSP) (Fig. 2C). The Quantile–Quantile plot (QQ-plot) in Fig. 2D showed the observed and expected P values of GWAS for ear size. The red line represents the distribution of SNPs under the null hypothesis of no association of SNPs with the trait of interest. The strong deviation of the observed from the expected P values for QQ-plots indicated more SNPs significantly associated with all ear size traits than would be expected by chance.

Fig. 2: Genome-wide association study of ear size.
figure 2

A Manhattan plot for ear size GWAS, B, C plot for regional association result for IBSP, the functional genes in this region were plotted in the box, and D Quantile–Quantile plot observed and expected p value (expressed as –log10(p)) of the GWAS for ear size.

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Considering that body size traits and ear size data could share an underlying genetic basis, the correlation was measured and analyzed for each trait in Supplementary Fig. S1. The Pearson correlation coefficient was used to assess the linear relationships between ear size and body size traits. Results showed that the body height, cross high, head length, and head width had weakly-to-moderately positive correlations with the ear size trait. The multiple linear regression model was analyzed using these related traits as covariates for the secondary GWAS by using PLINK (Purcell et al. 2007). The autosomal SNP scan for ear size revealed associated markers (Supplementary Fig. S2). A total of 293 SNPs were observed on the potential region, most of which were found on BTA6. The most significant SNP (P = 5.74 × 10−11) was located on IBSP. Two GWAS results strongly suggested that IBSP had a strong correlation with ear size and might be a key candidate gene influencing cattle ear size.

Genetic differentiation of the mutation in IBSP among groups with different ear sizes

In order to further screen candidate genes for ear size differentiation, genetic differentiation between Yunling cattle populations with ear sizes larger than 230 cm2 and smaller than 148 cm2 was measured using a pairwise fixation index (Fst) (Weir and Cockerham 1984). The two populations of Yunling cattle had the same genetic background and were similar, but the difference in ear size was significant. By annotating significant regions, the most significant loci (Fst = 0.68) (Fig. 3A) were located on the seventh exon of IBSP (Fig. 3C). At the same time, we also conducted similar genetic differentiation index analysis for different cattle breeds with significant differences in ear size, namely, two Zebu populations living in India and southern China, both belonging to Zebu with similar genetic background and significant differences in ear size. By annotating significant regions (Fst > 0.29, empirical P < 0.005), IBSP was also found in the most significant region on BTA6 (position: 36,840,001–36,890,000, Fst = 0.43) (Supplementary Fig. S3). Nine cattle breeds were used for Sweep Detector (SweeD) (Pavlidis et al. 2013) analyses to further investigate the differentiation of these mutation loci across diverse cattle breeds (Supplementary Fig. S4). Results showed that the SweeD value on these loci was observed to be near zero in Bos taurus (i.e., Angus, Kazakh, Hanwoo, Hereford, Holstein, Mishima, Simental, and Yanbian cattle) and over 200 in South Asian indicine cattle (i.e., Brahman and Burmese cattle), indicating that IBSP might be selected in indicine breeds (Fig. 3B). In accordance with the functional annotation, a missense mutation was found on the seventh exon of IBSP (Threonine-250→Isoleucine, T250I) (Fig. 3C). To further evaluate the functional impact of the variants, we aligned the mutant IBSP protein with its ortholog proteins in Bovidae (Fig. 3D) and other diverse vertebrates (Supplementary Fig. S5). The comparison revealed that T250 was a conserved amino acid mutation and varied among all the other animals we examined except Bos taurus (T250I), lesser mouse-deer (T250S), and white-lipped deer (T250A). We also have counted PhastCons and PhyloP of this mutation from UCSC. The score of 100 vertebrates conservation by PhastCons was 1, and the score of 100 vertebrates Basewise Conservation by PhyloP was 5.44393. These three mutant species had small ears, and this finding was consistent with our present hypothesis. We calculated the LD values of the SNPs, which were shared in the region of IBSP. We observed a strong linkage in this region (Supplementary Fig. S5). Furthermore, the prediction-based 3D structure of the protein predicted by the website https://seq2fun.dcmb.med.umich.edu/I-TASSER/ showed that the mutation site of IBSP could change its protein structure (Fig. 3E). Next, we compared the total mRNA levels of IBSP between small and big ear groups by using quantitative real-time PCR. Results showed that the mRNA expression of IBSP was significantly different (Fig. 3F). Taken together, our results suggest that T250I was a plausible candidate mutation for the IBSP sweep in cattle ear size.

Fig. 3: Selection and conservative analysis for IBSP.
figure 3

A Manhattan plot for Fst analysis of big and small ear among Yunling cattle group. The red box indicated the location of IBSP. B Line charts of SweeD in 9 cattle breeds on the gene regions of IBSP. C Gene structure of IBSP. D Conservative prediction of the mutant IBSP protein with its ortholog proteins in Bovidae. E 3D protein structure prediction of IBSP. F The mRNA expression of IBSP between big- and small-ear groups.

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Allele frequency of IBSP mutation among different cattle breeds indicating the origin

In this study, a region with strong linkage (BTA6: 36,851,626–36,929,220) was selected from the surrounding region of IBSP mutation site for haplotype network analysis, and the results showed that all samples formed two obvious branches. Cattle breeds with small ear sizes (Yanbian, Hanwoo, Mishima, Tibetan cattle, etc.) and cattle breeds (Brahman, Burma, Sahiwal, Nelore, Tharparkar, and Gir cattle) with larger ear sizes were clearly divided into one branch, respectively, while the breeds (Wannan, Wenshan, Wenling, Dehong, Dianzhong, and Minnan cattle) with middle ear size were mixed in these two branches (Fig. 4A). At the same time, we genotyped the DNA sequences of IBSP with 394 cattle representing Bos indicus, Bos taurus, and hybrid cattle to investigate the genotype frequency of the mutation loci across diverse cattle breeds. Two genotypes (A and G) of the IBSP mutation loci were found (Supplementary Table S4). The A allele of IBSP mutation occurred at low frequency in Burmese (0.06), Brahman (0.30), and Lingnan (0.40) cattle. In Wenshan, Shigatse, Weining, Hainan, Dianzhong, Jinjiang, Ji’an, Wannan, and Luxi cattle, the A allele of the two mutations showed a moderate frequency close to 0.5. By contrast, the A allele was almost equal to 1 in Yanbian, Kazakh, and Simmental cattle and other Bos taurus. At the same time, we searched the mutation frequency of IBSP among different cattle breeds in the world from the Bovine Genome Variation Database and Selective Signatures (http://animal.nwsuaf.edu.cn/code/index.php/BosVar) (Chen et al. 2019). The database contained 24 South Asian indicine, 19 Chinese indicine, 37 East Asian taurine, 38 European taurine, 19 Eurasian taurine, and 10 Africa taurine cattle. Results showed that the A allele frequency of IBSP was lowest in South Asian indicine cattle (0.10), and the frequency was 0.47 in Chinese indicine cattle. However, the A frequency of IBSP was near or equal to 1 in East Asian, European, and Eurasian taurine cattle (Fig. 4B). The allele distribution indicated that the A allele of IBSP might have originated in Bos taurus. Given the infiltration of South Asian indicine cattle, the Chinese indicine cattle caused a reduction in the A allele frequency. We also found the G allele in African taurine cattle at low frequency, which might be due to the large introduction of South Asian indicine cattle after the African rinderpest in 1890 (Phoofolo 1993).

Fig. 4: Haplotype network analysis and geographical distribution of the mutation among different cattle breeds.
figure 4

A Haplotype network analysis for the surrounding region of IBSP mutation site among different cattle breeds. B The mutation allele frequency distribution of six ancestral cattle groups. The size of the circle represents the count of the samples. The orange and brown colors represent G and A alleles, respectively.

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Discussion

The external ear of cattle is composed of cartilage and thin layers of skin. The function of cartilage in the external ear is a stent, which determines the size and shape of the ear (Bos et al. 2018). This is different from the candidate genes that have been reported to affect ear size in pigs, dogs, sheep, and other species, such as PPARD, LEMD3, DCC, SOX5, PTPRD, WIF1, HMGA2, etc. In this study, we identified IBSP as the main candidate gene affecting bovine ear size, and it is acceptable that the same trait is regulated by different candidate genes in different species. There are great genetic differences among different species, and ear size, as a quantitative trait, is regulated by multiple genes. In this study, two GWAS methods were used to identify the gene, and the hypothesis that the gene underlies the ear phenotype was supported by structural analysis. The IBSP has been mentioned many times in numerous studies of cartilage and chondrocytes (Fukui et al. 2008; Komori 2010, 2017, 2018; Lui et al. 2019). The main IBSP-knockout mice show a short body, reduced chondrocyte proliferation, and impaired cartilage absorption. At the same time, the lack of IBSP can alter bone growth and the formation and mineralization of primary bone (Bouleftour et al. 2014). The protein encoded by IBSP is the main structural protein in the bone matrix, and nearly 12% non-collagenous proteins are from IBSP in human osteoblasts, hypertrophic chondrocytes, and osteoclasts (Duncan et al. 2011; Kim et al. 1994; Wuttke et al. 2001). IBSP is related to tissue development and cell growth, which may relate to its mechanism in promoting or inhibiting the growth and proliferation of bovine ear chondrocytes.

We have discovered and validated one missense mutation at IBSP in Bos taurus, of which T250I occurs in a well-defined domain and quite conserved site (Supplementary Fig. S5). In nearly 70 vertebrate species except Bos taurus (T250I), lesser mouse-deer (T250S), and white-lipped deer (T250A), this mutation is conserved. We have found this missense mutation in IBSP that alters the 3D structure of the expressed protein, which may change the function of the protein. The analysis of the mRNA expression suggests that IBSP is highly expressed in small-ear cattle breeds and minimally expressed in big-ear cattle breeds, which may also be caused by this mutation. At the same time, the statistical analysis of the IBSP missense genotype among different cattle breeds shows that the GG genotype is presented in Bos indicus with a large ear size and that the AA genotype is presented in Bos taurus, which has a small ear size. Three genotypes are presented in hybrid cattle, which lives in the south of China and has complex ear sizes. Through the mutation frequency of the IBSP missense variant among different cattle breeds, we have found that the lowest frequency of the A allele is in South Asian indicine cattle and that the frequency is near or equal to 1 in East Asian, European, and Eurasian taurine cattle. Moreover, the mutations of the A allele are found in cattle with small ear sizes living in a cold environment, whereas the relatively large ear size of cattle living in tropical or subtropical regions has almost no mutation frequency. We speculate that the missense mutation of IBSP may be the main factor that affects the cattle ear size and that the mutations of the A allele in IBSP may originate from Bos taurus. The difference in ear size may be due to the variable environmental conditions in which they are located. The large ear area can help Bos indicus to dissipate heat temperature, and a small ear size may be helpful for Bos taurus to keep their temperature in a cold environment. The temperature in southern China is not high or low. Thus, hybrid cattle have diverse ear-size phenotypes. Meanwhile, the mutation site had a higher genetic differentiation index in the populations with significant ear size, which means that ear size may also be influenced by species differentiation. In conclusion, the IBSP loci related to cattle ear size is identified by GWAS, and the missense mutation in IBSP (T250I) is speculated to be the candidate mutation that affects ear size among cattle breeds. These findings have important theoretical significance for the exploration of major genes of ear size traits and provide important molecular markers for the identification of cattle germplasm resources.