Genome-wide detection of selective signatures in Simmental cattle

Artificial selection has greatly improved the beef production performance and changed its genetic basis. High-density SNP markers provide a way to track these changes and use selective signatures to search for the genes associated with artificial selection. In this study, we performed extended haplotype homozygosity (EHH) tests based on Illumina BovineSNP50 (54 K) Chip data from 942 Simmental cattle to identify significant core regions containing selective signatures, then verified the biological significance of these identified regions based on some commonly used bioinformatics analyses. A total of 224 regions over the whole genome in Simmental cattle showing the highest significance and containing some important functional genes, such as GHSR, TG and CANCNA2D1 were chosen. We also observed some significant terms in the enrichment analyses of second GO terms and KEGG pathways, indicating that these genes are associated with economically relevant cattle traits. This is the first detection of selection signature in Simmental cattle. Our findings significantly expand the selection signature map of the cattle genome, and identify functional candidate genes under positive selection for future genetic research.     

Whole-genome resequencing reveals selection signatures associated with milk production traits in African Kenana dairy zebu cattle

Milk production and composition are the most economically important traits affecting profitability in dairy cattle. In this study, we aimed at detecting signatures of positive selection in Kenana, known as one of the high milk production African indigenous zebu cattle, using next-generation sequencing data. To detect genomic signatures of positive selection, we applied three methods based on population comparison, fixation index (F_ST), cross population composite likelihood ratio (XP-CLR) and nucleotide diversity (Pi). Further analysis showed that several candidate genes such as CSN3, IGFBP-2, RORA, ABCG2, B4GALT1 and GHR are positively selected for milk production traits in Kenana cattle. The candidate genes and enriched pathways identified in this study may provide a basis for future genome-wide association studies and investigations into genomic targets of selection in dairy cattle.     

Genome-wide association study of economically important traits in Charolais and Limousin beef cows

Genomic selection has proven effective for advancing genetic gain for key profit traits in dairy cattle production systems. However, its impact to-date on genetic improvement programs for beef cattle has been less effective. Despite this, the technology is thought to be particularly useful for low heritability traits such as those associated with reproductive efficiency. The objective of this study was to identify genetic variants associated with key determinants of reproductive and overall productive efficiency in beef cows. The analysis employed a large dataset derived from the national genetic evaluation program in Ireland for two of the most predominant beef breeds, viz. Charolais (n = 5 244 cows) and Limousin (n = 7 304 cows). Single nucleotide polymorphisms (SNPs) were identified as being statistically significantly associated (adj. P < 0.05) with both reproductive and productive traits for both breed types. However, there was little across breed commonality, with only two SNPs (rs110240246 and rs110344317; adj. P < 0.05) located within the genomic regions of the LCORL and MSTN genes respectively, identified in both Charolais and Limousin populations, associated with traits including carcass weight, cull-cow weight and live-weight. Significant SNPs within the MSTN gene were also associated with both reproduction and production related traits within each breed. Finally, traits including calving difficulty, calf mortality and calving interval were associated with SNPs within genomic regions comprising genes involved in cellular growth and lipid metabolism. Genetic variants identified as associated with both important reproductive efficiency and production related traits from this study warrant further analyses for their potential incorporation into breeding programmes to support the sustainability of beef cattle production.     

Expression analysis, single nucleotide polymorphisms and combined genotypes in candidate genes and their associations with growth and carcass traits in Qinchuan cattle

The apolipoprotein E (ApoE) gene is an important component of plasma lipoprotein, and Fas apoptosis inhibitory molecule (FAIM) is a novel anti-apoptotic gene. In this study, we researched and discussed seven genes in eight different tissues in Qinchuan cattle by quantitative Real-time PCR. The result of analysis showed that ApoE and FAIM ₂ genes had a correlation with muscle and fat. PCR–RFLP was applied to analyze the genetic variations of the ApoE and FAIM ₂ genes and verify the effect on growth and carcass traits in a total of 365 Qinchuan cattles. The result of haplotype analysis showed that nine different haplotypes were identified among the four SNPs in ApoE and FAIM ₂ genes. The statistical analyses indicated that the four SNPs were significant association with growth and carcass traits (P < 0.05, N = 365); and the four SNPs were significant association between nine combined genotypes of candidate genes and growth and carcass traits. Taken together, our results provide the evidence that polymorphisms in candidate genes are associated with growth and carcass traits in Qinchuan cattle, and may be used as a possible candidate for marker-assisted selection and management in beef cattle breeding program.     

Signatures of selection in Nelore cattle revealed by whole-genome sequencing data

Nelore cattle breed was farmed worldwide due to its economic importance in the beef market and adaptation to the tropics. In Brazil, purebred Nelore animals (PO) receive a certificate from the breeders' association based on the animal's genealogy and morphological characterization. The top 20 to 30% of the superior animals are eligible to receive the Special Certificate of Identification and Production (CEIP), meaning animals from this category were selected and evaluated in a breeding program to improve economically important traits. We used whole-genome sequencing and approaches based on haplotype differentiation and allelic differentiation to detect regions of selection signatures in Nelore cattle by comparing animals from PO and CEIP categories. From a total of 150 animals, a hierarchical clustering analysis was performed to choose the more unrelated animals from each category (16 PO and 40 CEIP). The hapFLK statistic was performed, and extensions of hapFLK values were investigated considering continuous regions with significant q-values. The Weir and Cockerham's Fst estimator (wcFst) was computed using the GPAT++ software library. The total of 82,326 SNPs with hapFLK values passed the FDR control (q-value<0.05), and 718 segments were target as signatures of selection. A total of 1713 highly differentiated genomic regions were identified based on the segmentFst approach. The signatures of selection were spread across the genome. Annotation of overlapping selection signature regions between the two methods revealed 118 genes in common. A variant located within the 3′ region of the BOLA-DRB3 gene was found as a promising candidate polymorphism. Within genomic regions that deserves attention, we found genes previously associated with adaptation to tropical environments (HELB), growth and navel size (HMGA2), fat deposition and domestication (IRAK3), and feed efficiency and postmortem carcass traits (GABRG3). The genes BOLA-DQA2, BOLA-DQB, BOLA-DQA5, BOLA-DQA1, BOLA-DRB3, ENSBTAG00000038397 on chromosome 23 are part of the Bovine Major Histocompatibility Complex (MHC) Class II gene family, representing good candidates for immune response and adaptation to tropical conditions. The BoLA family genes and the interaction of ROBO1 with SLIT genes appeared in the enrichment results. Genomic regions located in intronic regions were also identified and might play a regulatory role in traits under selection in PO and CEIP subpopulations. The regions here identified contribute to our knowledge regarding genes and variants that have an important role in complex traits selected in this breed     

Detection of selection signatures in the genome of a farmed population of anadromous rainbow trout (Oncorhynchus mykiss)

Domestication processes and artificial selection are likely to leave signatures that can be detected at a molecular level in farmed rainbow trout (Oncorhynchus mykiss). These signatures of selection are genomic regions that contain functional genetic variants conferring a higher fitness to their bearers. We genotyped 749 rainbow trout from a commercial population using a rainbow trout Axiom 57 K SNP array panel and identified putative genomic regions under selection using the pcadapt, Composite Likelihood Ratio (CLR) and Integrated Haplotype Score (iHS) methods. After applying quality-control pipelines and statistical analyses, we detected 12, 96 and 16 SNPs putatively under selection, associated with 96, 781 and 115 candidate genes, respectively. Several of these candidate genes were associated with growth, early development, reproduction, behavior and immune system traits. In addition, some of the SNPs were found in interesting regions located in autosomal inversions on Omy05 and Omy20. These findings could represent a genome-wide map of selection signatures in farmed rainbow trout and could be important in explaining domestication and selection for genetic traits of commercial interest.     

Identification of contemporary selection signatures using composite log likelihood and their associations with marbling score in Korean cattle

Positive selection not only increases beneficial allele frequency but also causes augmentation of allele frequencies of sequence variants in close proximity. Signals for positive selection were detected by the statistical differences in subsequent allele frequencies. To identify selection signatures in Korean cattle, we applied a composite log‐likelihood (CLL)‐based method, which calculates a composite likelihood of the allelic frequencies observed across sliding windows of five adjacent loci and compares the value with the critical statistic estimated by 50 000 permutations. Data for a total of 11 799 nucleotide polymorphisms were used with 71 Korean cattle and 209 foreign beef cattle. As a result, 147 signals were identified for Korean cattle based on CLL estimates (P < 0.01). The signals might be candidate genetic factors for meat quality by which the Korean cattle have been selected. Further genetic association analysis with 41 intragenic variants in the selection signatures with the greatest CLL for each chromosome revealed that marbling score was associated with five variants. Intensive association studies with all the selection signatures identified in this study are required to exclude signals associated with other phenotypes or signals falsely detected and thus to identify genetic markers for meat quality.     

Selection for complex traits leaves little or no classic signatures of selection

Background

Selection signatures aim to identify genomic regions underlying recent adaptations in populations. However, the effects of selection in the genome are difficult to distinguish from random processes, such as genetic drift. Often associations between selection signatures and selected variants for complex traits is assumed even though this is rarely (if ever) tested. In this paper, we use 8 breeds of domestic cattle under strong artificial selection to investigate if selection signatures are co-located in genomic regions which are likely to be under selection.

Results

Our approaches to identify selection signatures (haplotype heterozygosity, integrated haplotype score and F_ST) identified strong and recent selection near many loci with mutations affecting simple traits under strong selection, such as coat colour. However, there was little evidence for a genome-wide association between strong selection signatures and regions affecting complex traits under selection, such as milk yield in dairy cattle. Even identifying selection signatures near some major loci was hindered by factors including allelic heterogeneity, selection for ancestral alleles and interactions with nearby selected loci.

Conclusions

Selection signatures detect loci with large effects under strong selection. However, the methodology is often assumed to also detect loci affecting complex traits where the selection pressure at an individual locus is weak. We present empirical evidence to suggests little discernible ‘selection signature’ for complex traits in the genome of dairy cattle despite very strong and recent artificial selection.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-246) contains supplementary material, which is available to authorized users.     

Genome-Wide Detection of Selective Signature in Chinese Holstein

Selective signatures in whole genome can help us understand the mechanisms of selection and target causal variants for breeding program. In present study, we performed Extended Haplotype Homozygosity (EHH) tests to identify significant core regions harboring such signals in Chinese Holstein, and then verified the biological significance of these identified regions based on commonly-used bioinformatics analyses. Results showed a total of 125 significant regions in entire genome containing some of important functional genes such as LEP, ABCG2, CSN1S1, CSN3 and TNF based on the Gene Ontology database. Some of these annotated genes involved in the core regions overlapped with those identified in our previous GWAS as well as those involved in a recently constructed candidate gene database for cattle, further indicating these genes under positive selection maybe underlie milk production traits and other important traits in Chinese Holstein. Furthermore, in the enrichment analyses for the second level GO terms and pathways, we observed some significant terms over represented in these identified regions as compared to the entire bovine genome. This indicates that some functional genes associated with milk production traits, as reflected by GO terms, could be clustered in core regions, which provided promising evidence for the exploitability of the core regions identified by EHH tests. Findings in our study could help detect functional candidate genes under positive selection for further genetic and breeding research in Chinese Holstein.     

A genome‐wide association study suggests several novel candidate genes for carcass traits in Chinese Simmental beef cattle

A genome‐wide association study (GWAS) was conducted for two carcass traits in Chinese Simmental beef cattle. The experimental population consisted of 1301 individuals genotyped with the Illumina BovineHD SNP BeadChip (770K). After quality control, 671 990 SNPs and 1217 individuals were retained for the GWAS. The phenotypic traits included carcass weight and bone weight, which were measured after the cattle were slaughtered at 16 to 18 months of age. Three statistical models—a fixed polygene model, a random polygene model and a composite interval mapping polygene model—were used for the GWAS. The genome‐wide significance threshold after Bonferroni correction was 7.44E‐08 (= 0.05/671 990). In this study, we detected eight and seven SNPs significantly associated with carcass weight and bone weight respectively. In total, 11 candidate genes were identified within or close to these significant SNPs. Of these, we found several novel candidate genes, including PBX1, GCNT4, ALDH1A2, LCORL and WDFY3, to be associated with carcass weight and bone weight in Chinese Simmental beef cattle, and their functional roles need to be verified in further studies.     

Genome-wide association study identifies loci and candidate genes for meat quality traits in Simmental beef cattle

Improving meat quality is the best way to enhance profitability and strengthen competitiveness in beef industry. Identification of genetic variants that control beef quality traits can help breeders design optimal breeding programs to achieve this goal. We carried out a genome-wide association study for meat quality traits in 1141 Simmental cattle using the Illumina Bovine HD 770K SNP array to identify the candidate genes and genomic regions associated with meat quality traits for beef cattle, including fat color, meat color, marbling score, longissimus muscle area, and shear force. In our study, we identified twenty significant single-nucleotide polymorphisms (SNPs) (p < 1.47 × 10^?6) associated with these five meat quality traits. Notably, we observed several SNPs were in or near eleven genes which have been reported previously, including TMEM236, SORL1, TRDN, S100A10, AP2S1, KCTD16, LOC506594, DHX15, LAMA4, PREX1, and BRINP3. We identified a haplotype block on BTA13 containing five significant SNPs associated with fat color trait. We also found one of 19 SNPs was associated with multiple traits (shear force and longissimus muscle area) on BTA7. Our results offer valuable insights to further explore the potential mechanism of meat quality traits in Simmental beef cattle.     

Signatures of selection in five Italian cattle breeds detected by a 54K SNP panel

In this study we used a medium density panel of SNP markers to perform population genetic analysis in five Italian cattle breeds. The BovineSNP50 BeadChip was used to genotype a total of 2,935 bulls of Piedmontese, Marchigiana, Italian Holstein, Italian Brown and Italian Pezzata Rossa breeds. To determine a genome-wide pattern of positive selection we mapped the F _st values against genome location. The highest F _st peaks were obtained on BTA6 and BTA13 where some candidate genes are located. We identified selection signatures peculiar of each breed which suggest selection for genes involved in milk or meat traits. The genetic structure was investigated by using a multidimensional scaling of the genetic distance matrix and a Bayesian approach implemented in the STRUCTURE software. The genotyping data showed a clear partitioning of the cattle genetic diversity into distinct breeds if a number of clusters equal to the number of populations were given. Assuming a lower number of clusters beef breeds group together. Both methods showed all five breeds separated in well defined clusters and the Bayesian approach assigned individuals to the breed of origin. The work is of interest not only because it enriches the knowledge on the process of evolution but also because the results generated could have implications for selective breeding programs.     

Use of locally weighted scatterplot smoothing (LOWESS) regression to study selection signatures in Piedmontese and Italian Brown cattle breeds

Selection is the major force affecting local levels of genetic variation in species. The availability of dense marker maps offers new opportunities for a detailed understanding of genetic diversity distribution across the animal genome. Over the last 50 years, cattle breeds have been subjected to intense artificial selection. Consequently, regions controlling traits of economic importance are expected to exhibit selection signatures. The fixation index (F_st) is an estimate of population differentiation, based on genetic polymorphism data, and it is calculated using the relationship between inbreeding and heterozygosity. In the present study, locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach were used to investigate selection signatures in two cattle breeds with different production aptitudes (dairy and beef). F_st was calculated for 42 514 SNP marker loci distributed across the genome in 749 Italian Brown and 364 Piedmontese bulls. The statistical significance of F_st values was assessed using a control chart. The LOWESS technique was efficient in removing noise from the raw data and was able to highlight selection signatures in chromosomes known to harbour genes affecting dairy and beef traits. Examples include the peaks detected for BTA2 in the region where the myostatin gene is located and for BTA6 in the region harbouring the ABCG2 locus. Moreover, several loci not previously reported in cattle studies were detected.     

Detection of selection signatures in dairy and beef cattle using high-density genomic information

Background

Artificial selection for economically important traits in cattle is expected to have left distinctive selection signatures on the genome. Access to high-density genotypes facilitates the accurate identification of genomic regions that have undergone positive selection. These findings help to better elucidate the mechanisms of selection and to identify candidate genes of interest to breeding programs.

Results

Information on 705 243 autosomal single nucleotide polymorphisms (SNPs) in 3122 dairy and beef male animals from seven cattle breeds (Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental) were used to detect selection signatures by applying two complementary methods, integrated haplotype score (iHS) and global fixation index (F_ST). To control for false positive results, we used false discovery rate (FDR) adjustment to calculate adjusted iHS within each breed and the genome-wide significance level was about 0.003. Using the iHS method, 83, 92, 91, 101, 85, 101 and 86 significant genomic regions were detected for Angus, Belgian Blue, Charolais, Hereford, Holstein-Friesian, Limousin and Simmental cattle, respectively. None of these regions was common to all seven breeds. Using the F_ST approach, 704 individual SNPs were detected across breeds. Annotation of the regions of the genome that showed selection signatures revealed several interesting candidate genes i.e. DGAT1, ABCG2, MSTN, CAPN3, FABP3, CHCHD7, PLAG1, JAZF1, PRKG2, ACTC1, TBC1D1, GHR, BMP2, TSG1, LYN, KIT and MC1R that play a role in milk production, reproduction, body size, muscle formation or coat color. Fifty-seven common candidate genes were found by both the iHS and global F_ST methods across the seven breeds. Moreover, many novel genomic regions and genes were detected within the regions that showed selection signatures; for some candidate genes, signatures of positive selection exist in the human genome. Multilevel bioinformatic analyses of the detected candidate genes suggested that the PPAR pathway may have been subjected to positive selection.

Conclusions

This study provides a high-resolution bovine genomic map of positive selection signatures that are either specific to one breed or common to a subset of the seven breeds analyzed. Our results will contribute to the detection of functional candidate genes that have undergone positive selection in future studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0127-3) contains supplementary material, which is available to authorized users.     

SNV and haplotype analysis reveals new CSRP1 variants associated with growth and carcass traits

The cysteine and glycine-rich protein 1 and 2 genes (CSRP1 and CSRP2) are an effective growth factor in promoting skeletal muscle growth in vitro and vivo. However, in cattle, the information on the CSRP1 and CSRP2 genes is very limited. The aim of this study was to examine the association of the CSRP1 and CSRP2 variants with growth and carcass traits in cattle breeds. Three single nucleotide variants (SNVs) were identified within the bovine CSRP1 gene, whereas CSRP2 gene has not detected any SNVs, using DNA pooled sequencing, PCR-RFLP, and forced PCR-RFLP methods. These SNVs include g. 801T>C (Intron 2), g. 46T>C (Exon 3) and g. 99C>G (Intron 3). Besides, we also investigated haplotype frequencies and linkage disequilibrium (LD) coefficients for three SNVs in all study populations. LD and haplotype structure of CSRP1 were different between breeds. The result of haplotype analysis demonstrated eight haplotype present in QC (Qinchuan) and one haplotype in CH (Chinese Holstein). Only haplotype 1 (TTC), shared by all two populations, comprised 10.74% and 100.00%, of all haplotypes observed in QC and CH, respectively. Haplotype 5 (CTC) had the highest haplotype frequencies in QC (30.98%) and haplotype 1 had the highest haplotype frequencies in CH (100.00%). The statistical analyses indicated that one single SNV and 19 combined haplotypes were significantly or highly significantly associated with growth and carcass traits in the QC cattle population (P < 0.05 or P < 0.01). Quantitative real-time PCR (qRT-PCR) analyses showed that the bovine CSRP1 and CSRP2 genes were widely expressed in many tissues. The results of this study suggest that the CSRP1 gene possibly is a strong candidate gene that affects growth and carcass traits in the Chinese beef cattle breeding.     

Sequence variants of the <Emphasis Type="Italic">LCORL</Emphasis> gene and its association with growth and carcass traits in Qinchuan cattle in China

Molecular marker-assisted selection is a better way to satisfy the growing customer requirement with the development of beef cattle growth and breeding research. For now, quantitative trait locus (QTL) for cattle growth and carcass traits, just like body height, body length and carcass weight have been detected on bovine chromosome 6. In this study, ligand-dependent nuclear receptor corepressor-like (LCORL) was selected as the potential positional candidate gene located in chromosome 6 which is closely connected with the bovine growth and carcass traits. A total of 450 Qinchuan beef cattle were used to detect mutations in exon and its neighbouring region, and the promoter region of the bovine LCORL gene. The methods for SNPs detection were polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and created restriction site PCR (CRS-PCR), and the results of this study show that there were two variations in intron regions, the other four variations were located in the promoter region. Linkage disequilibrium analysis and haplotype analysis indicated that L78-Q4 had strong linkage disequilibrium, A T G C G C (16.2%) and G C G C A T (16.7%) had higher haplotype frequencies, G C A C A C (0.8%) and G T A C A T (0.7%) had lower haplotype frequencies. Correlation analysis indicated that SNP g. INT + 52098A >G was significantly associated with slaughter weight and carcass weight. Based on the research, we selected LCORL as the candidate gene that can contribute to improved marker-assisted selection for the meat performance of Qinchuan beef cattle.     

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and F_ST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and F_ST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.     

Association of HSL gene E1-c.276C>T and E8-c.51C>T mutation with economical traits of Chinese Simmental cattle

Hormone-sensitive lipase (HSL) is responsible for the decomposition of triglycerides in adipose tissue to release free fatty acids, and it is a key rate-limiting enzyme in the regulation of adipose tissue deposition and decomposition. The objective of this study was to evaluate the association between novel SNPs in the coding region of bovine HSL gene and carcass and meat quality traits of Chinese Simmental-cross steers. Two novel SNPs were genotyped and the 47 traits of carcass and meat quality traits were measured in the population studied. Statistical analysis revealed that the SNPs of HSL gene were associated with the carcass and meat quality traits. The individuals with TT genotypes of E1-276C>T showed significant higher dressing percentage, net meat rate, hind legs circumference, fat coverage rate, mesenteric fat and kidney fat (p < 0.05). E8-51C>T (P17S) also showed a significant association with the pH of beef and fatty acids content in Chinese Simmental cattle (p < 0.01). Our findings indicated that polymorphisms in HSL might be one of important genetic factors that influence carcass yield and meat quality in beef cattle, and it may be a useful marker for meat quality traits in future marker-assisted selection programs in beef cattle breeding and production.     

Genome-wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Genetic associations of nucleotide sequence variants with carcass traits in beef cattle were investigated using a genome-wide single nucleotide polymorphism (SNP) assay. Three hundred and thirteen Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,129 SNPs from 311 animals were analysed for each carcass phenotype after filtering by quality assurance. Five sequence markers were associated with one of the meat quantity or quality traits; rs109593638 on chromosome 3 with marbling score, rs109821175 on chromosome 11 and rs110862496 on chromosome 13 with backfat thickness (BFT), and rs110228023 on chromosome 6 and rs110201414 on chromosome 16 with eye muscle area (EMA) (P < 1.27 × 10(-6) , Bonferonni P < 0.05). The ss96319521 SNP, located within a gene with functions of muscle development, dishevelled homolog 1 (DVL1), would be a desirable candidate marker. Individuals with genotype CC at this gene appeared to have increased both EMA and carcass weight. Fine-mapping would be required to refine each of the five association signals shown in the current study for future application in marker-assisted selection for genetic improvement of beef quality and quantity.     

QTL and gene expression analyses identify genes affecting carcass weight and marbling on BTA14 in Hanwoo (Korean Cattle)

Causal mutations affecting quantitative trait variation can be good targets for marker-assisted selection for carcass traits in beef cattle. In this study, linkage and linkage disequilibrium analysis (LDLA) for four carcass traits was undertaken using 19 markers on bovine chromosome 14. The LDLA analysis detected quantitative trait loci (QTL) for carcass weight (CWT) and eye muscle area (EMA) at the same position at around 50?cM and surrounded by the markers FABP4SNP2774C>G and FABP4_??sat3237. The QTL for marbling (MAR) was identified at the midpoint of markers BMS4513 and RM137 in a 3.5-cM marker interval. The most likely position for a second QTL for CWT was found at the midpoint of tenth marker bracket (FABP4SNP2774C>G and FABP4_??sat3237). For this marker bracket, the total number of haplotypes was 34 with a most common frequency of 0.118. Effects of haplotypes on CWT varied from a ?5-kg deviation for haplotype 6 to +8?kg for haplotype 23. To determine which genes contribute to the QTL effect, gene expression analysis was performed in muscle for a wide range of phenotypes. The results demonstrate that two genes, LOC781182 (p?=?0.002) and TRPS1 (p?=?0.006) were upregulated with increasing CWT and EMA, whereas only LOC614744 (p?=?0.04) has a significant effect on intramuscular fat (IMF) content. Two genetic markers detected in FABP4 were the most likely QTL position in this QTL study, but FABP4 did not show a significant effect on both traits (CWT and EMA) in gene expression analysis. We conclude that three genes could be potential causal genes affecting carcass traits CWT, EMA, and IMF in Hanwoo.