Abstract Previous research regarding Holstein cows has mainly focused on increasing milk yield. However, in order to maximize the economical profits of Holstein cattle farming, it is necessary to fully take advantage of Holstein bulls to produce high-grade beef. The present study aims to investigate different transcriptomic profiling of Holstein bulls and steers, via high-throughput RNA-sequencing (RNA-seq). The growth and beef quality traits of Holstein steers and bulls were characterized via assessment of weight, rib eye area, marbling score, shear force and intramuscular fat percentage of the longissimus lumborum (LL) muscle. The results indicated that castration improved the meat quality, yet reduced the meat yield. Subsequently, RNA-seq of the LL muscle from Holstein steers and bulls revealed a total of 56 differentially expressed genes (DEGs). We performed the functional enrichment analysis in Gene Ontology (GO) annotations of the DEGs using GOseq R package software and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using KOBAS tool. Through the integrated analysis of DEGs with reported QTLs and SNPs, seven promising candidate genes potentially affecting the beef quality of LL muscle following castration were discovered, including muscle structural protein coding genes (MYH1, MYH4, MYH10) and functional protein coding genes (GADL1, CYP2R1, EEPD1, SHISA3). Among them, MYH10, GADL1, CYP2R1, EEPD1 and SHISA3 were novel candidate genes associated with beef quality traits. Notably, EEPD1 was associated with both meat quality and reproduction traits, thus indicating its overlapping role in responding to hormone change, and subsequently inducing beef quality improvement. Our findings provide a complete dataset of gene expression profile of LL in Holstein bulls and steers, and will aid in understanding how castration influence meat yield and quality. Introduction Holstein cattle, a common cattle breed, has been mainly raised for dairy purpose. However, to meet the growing demand for beef, more and more Holstein cattle are also used to produce meat. For many decades, research studies have focused on increasing milk yield and milk quality of Holstein cows, but have ignored the utilization value of Holstein bulls in beef production [[36]1–[37]3]. Therefore, in order to maximize economical profits of Holstein cattle farming, it is necessary to take fully advantage of Holstein bulls to produce high-grade beef. The beef yield and quality can be influenced by many factors, such as breed, feeding, age and castration [[38]4–[39]6]. Castration is an effective way to manage Holstein bulls, by which remarkably resulting in higher quality beef in steers [[40]7]. Beef quality may be assessed by intramuscular fat (IMF) deposition, as well as by marbling and fatty acid composition, which further determines meat palatability, including flavor, tenderness and juiciness [[41]8–[42]10]. Numerous trials regarding beef cattle breeds such as Bos indicus bulls, Qinchuan cattle, Chinese Simmental cattle and Korean cattle, have suggested that castration reduced meat yield, yet improved meat quality, including fatty acid composition and IMF content [[43]11–[44]14]. Two recent studies physicochemically characterized the beef quality of Holstein bulls, and the results suggested that the steer beef contained higher redness, intramuscular fat and soluble collagen, thus indicating a better eating quality than bull beef [[45]15,[46]16]. The gene expression profiling changes of the longissimus dorsi in beef cattle resulting from castration were described by two research groups. Zhou et al. identified several differentially expressed genes, such as ACTIN, TPM2, IGF1 and LIPE, between Chinese Simental steers and bulls, by means of the suppressive subtractive hybridization method, and the results indicated that these genes may contribute to the regulation of steer beef quality [[47]12]. Jeong et al. profiled the transcriptomic changes of LL muscle of Korean cattle following castration using microarray. They discovered several lipid metabolism genes differentially expressed in steers and bulls, such as PLIN2, ATP6V1C1 and COX11, thus indicating that the improvement of beef quality by castration attributed to better IMF deposition in longissimus dorsi muscle [[48]17]. With the advantages of high-throughput sequencing technologies, the genetic mapping of quantitative trait loci (QTL) and genome wide association studies have generated well-defined genetic maps for carcass and meat quality traits [[49]18–[50]22]. In addition, RNA-seq of beef cattle groups with divergent meat quality has revealed several meat quality related metabolic pathways and genes, such as PPAR signaling genes, cell morphology genes, lipid metabolism genes, and adipocytokine signaling pathway [[51]23–[52]25]. However, RNA-seq technology has yet to be used to profile the transcriptomic changes of bull muscle followed by castration. Therefore, the characterizations of castration effects on the gene expression profiles of Holstein bulls using high-throughput RNA-seq can provide valuable molecular and genetic information regarding how castration improves beef quality. The aim of the present study is to identify the important genes that respond to castration, and subsequently aid in improving beef quality in Holstein bulls via RNA-seq. Materials & methods Animals and management The animal experiment performed in this study was approved by the Animal Ethical and Welfare Committee (AEWC) at the College of Animal Science and Technology of Hebei Agricultural University (Approval number: 17–06). The animals were treated in accordance with the China National Institute of Health guidelines. Twenty healthy 11-month-old Holstein bulls with similar live weight, from different families, were selected at the cattle farm of Fucheng Wufeng Food Co., Ltd. (Langfang, China). The average live weight was 271.25±13.73 kg in this population and they were randomly assigned to one of two groups. Bulls of one group were castrated by surgically removing the testicles, while the other group had their testicles remain intact. All the animals were housed in the open barn at the cattle farm of Fucheng Wufeng Food Co., Ltd. Feeding management of the two groups was kept consistent before selection and throughout the experimental period. Referring to Nutrition Requirement of Beef Cattle (2000) and Japanese Feeding Standard for Beef Cattle (2008), the basic diet formulation was adjusted along with the growth of body weight ([53]S1 Table). The dietary nutrition levels of the two groups were identical. Following a 7 d adaption period, the experiment lasted for a total of 448 d. Slaughtering, tissue and blood sampling After 448 d of feeding, all of the cattle were driven to the abattoir (Fucheng Wufeng Food Co., Ltd., Langfang, China), located next to the feedlot. The cattle were feed fasted for 24 h and water fasted for 3 h before slaughter. Following electric shock, all cattle were slaughtered by exsanguination. The slaughtering process was performed according to the operating procedure of cattle slaughtering outlined in the China National Standard. Meanwhile, the hot carcass weight was recorded. Next, the carcasses were divided into two parts, weighed and chilled at 0~4°C for 48 h. After chilling, 1 kg of LL muscle on the right carcass side between the 12th and 13th ribs was removed. Half of the muscle samples were stored at -20°C for beef quality characterization, while the other half was cut into several pieces and placed quickly in liquid nitrogen, followed by storage at -80 °C until analysis. Measurements of beef quality parameters All of the measurements below were performed on the -20°C stored muscle samples. The perimeter of the rib eye area was traced on a sheet of sulfuric paper, followed by calculation with a planimeter (Jilin University, China). The marbling grade was determined according to the Japanese Marbling scores (5-Excellent; 4-Good; 3-Average; 2-Below average; 1-Poor). Immediately after this, the meat sample was boiled and cooled, and the shear force was measured using a Warner-Bratzler shear force machine (Bodine Electric Co., Chicago, IL, USA) according to the manufacturer’s instructions. According to the AOAC official methods, the meat samples were dried in a freeze dryer (LaboGene, Allerod, Denmark) to determine the contents of H[2]O, crude protein and IMF. The Kjeldahl method was then applied to analyze the crude protein content using a Kjeltec 8400 Analyzer Unit (Foss Analytical, Höganäs, Sweden). Finally, the total IMF percentage was determined by the Soxhlet extraction method. RNA extraction and quality analysis Three cattle were randomly selected from both the bull and steer groups for RNA-sequencing analysis. The total RNA was extracted from the tissues using TRIzol Reagent (Life Technologies, CA, USA) according to the manufacturer’s instructions. A Qubit^® RNA Assay Kit (Invitrogen, CA, USA) was used to determine the RNA concentration with a Qubit^® 2.0 Flurometer (Life Technologies, CA, USA). The RNA degradation and contamination were monitored by 1% agarose gel. The RNA purity was measured by a NanoPhotometer^® spectrophotometer (IMPLEN, CA, USA). Finally, the RNA integrity was checked using a Bioanalyzer 2100 RNA 6000 Nano Kit (Agilent Technologies, CA, USA). Library preparation and RNA sequencing The RNA sequencing libraries were constructed according to the manufacturer’s instructions of the NEBNext^® Ultra^™ RNA Library Prep Kit for Illumina^® (NEB, MA, USA). Index codes were added, so as to attribute sequences to each sample. Next, mRNA was isolated using poly-T oligo-attached magnetic beads and fragmented by divalent cations in a NEB Next First Strand Synthesis Reaction Buffer (5X) under increased temperature. Subsequently, the first and second strand cDNA were synthesized using random hexamer primer. The 3’ ends of DNA fragments were adenylated, followed by ligation with a NEBNext Adaptor. cDNA fragments of 150~200 bp were selected with an AMPure XP system (Beckman Coulter, CA, USA). PCR was performed with Universal PCR primers and an Index (X) Primer. The library quality was checked by an Agilent Bioanalyzer 2100 system. TruSeq PE Cluster Kit v3-cBot-HS (Illumina, CA, USA) was used for cluster generation. The final RNA-seq libraries were constructed using an Illumina Hiseq 2500 platform (Illumina, CA, USA), which generated 125 bp/150 bp paired-end reads. Sequencing data analysis In order to obtain clean data, raw data (fastq format) were processed through in-house perl scripts. In this step, clean data were obtained by removing reads containing adapters, low quality reads (the proportion of the read bases with Phred quality score≤20 is over 50% of the reads), and reads with proportion of N greater than 10%. Subsequently, the Q20 (the percentage of read bases with Phred quality score >20), Q30 (the percentage of read bases with Phred quality score >30), and GC contents of the clean data were calculated. The downstream study analyzed the clean data with high quality. The paired-end clean reads were mapped to the reference genome of Bos taurus UMD 3.1.1 ([54]https://www.ncbi.nlm.nih.gov/genome/82?genome_assembly_id=214974) using TopHat v2.0.12. The index of the reference genome was built using Bowtie v2.2.3. Gene expression quantification and differential expression analysis The gene expression level was estimated as fragments per kilobase of transcript per millions fragments mapped reads (FPKM), which was calculated based on the length of the gene and reads count mapped to this gene. HTSeq v0.6.1 was utilized for counting the read numbers mapped to each gene. Differential expression analysis of Holstein bulls and steers was performed using the DESeq R package (1.18.0). Benjamini and Hochberg’s approach was applied to correct the resulting P-values to control the false discovery rate. Genes with a corrected P-value <0.05 were considered as differentially expressed genes (DEGs). Gene Ontology (GO) and pathway enrichment analysis of DEGs Gene Ontology (GO) of DEGs was implemented using the GOseq R package. KOBAS software was applied to calculate the statistical enrichment of DEGs in the KEGG pathways ([55]http://www.genome.jp/kegg/). QTL-SNP screening analysis of DEGs To associate the DEGs with beef quality traits, a QTL-SNP screening analysis was performed to determine the candidate genes [[56]26,[57]27]. Firstly, the DEGs with the physical position located within the region of reported QTLs related with beef quality traits ([58]https://www.animalgenome.org/cgi-bin/QTLdb/BT/index) were selected. The genetic distance between the DEGs and QTL peak was calculated. Secondly, we created a pool of SNPs related with beef quality traits reported by previous GWAS. Physical position of the DEGs and the reported SNPs were compared, and the DEGs with distance to significant SNPs less than 5 Mb were selected. Finally, combining the QTL and SNP screening results, the overlapped DEGs those were both located inside of QTLs and near significant SNPs were selected as candidate genes associated with beef quality traits. qRT-PCR To confirm the sequencing results, nine DEGs were randomly selected for qRT-PCR. The total RNA (1 μg) was reverse transcribed into first strand cDNA by a Quantitect^® reverse transcription kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. Primers for qPCR were designed using the primer-BLAST tool on the NCBI website ([59]S2 Table). The transcript levels of the tested genes were normalized to β-actin and GAPDH in qRT-PCR, and calculated using the 2^-△△ct method. The qPCR reactions were performed in triplicates using iQ SYBR Green Supermix (BioRad, CA, USA). The amplified conditions were as follows: 95°C for 3 min; 40 cycles of 95°C for 15 s, 60°C for 15 s and 72°C for 20 s; 72°C for 10 min. Statistical analysis The data of the growth and beef quality characteristics from the steers’ group and the bulls’ group obeyed normal distribution with the Kolmogorov-Smirnov test, followed by analysis with the Independent-Sample T test using SPSS 19.0 software. The results were shown as mean value ± standard error. A probability of P ≤0.05 was considered as significant, while P≤0.01 was highly significant, and 0.05 0.05) comparing steers and bulls. Table 2. Forty annotated differentially expressed genes in LL muscle identified between Holstein steers and bulls. Gene ID Official Full Name Gene Symbol Chr Position log[2] Fold Change (steers/bulls) P-Value ENSBTAG00000000448 3-hydroxybutyrate dehydrogenase 1 BDH1 1 72572941–72608810 1.8192 6.45E-04 ENSBTAG00000002151 ankyrin repeat and SOCS box containing 15 ASB15 4 88697392–88729365 1.7126 6.98E-05 ENSBTAG00000002527 zinc finger SWIM-type containing 4 ZSWIM4 7 12959854–12977638 -1.7474 4.06E-04 ENSBTAG00000003403 peptidyl arginine deiminase 2 PADI2 2 136049644–136103406 1.88 1.06E-05 ENSBTAG00000005847 Rho associated coiled-coil containing protein kinase 2 ROCK2 11 86501577–86583652 -1.534 4.61E-04 ENSBTAG00000005857 solute carrier family 6 member 1 SLC6A1 22 55695783–55714644 1.716 1.53E-04 ENSBTAG00000006754 D-box binding PAR bZIP transcription factor DBP 18 55722336–55729578 1.4405 4.62E-03 ENSBTAG00000007062 insulin like growth factor binding protein 5 IGFBP5 2 105378991–105397646 2.7936 1.53E-02 ENSBTAG00000007131 glutamate decarboxylase like 1 GADL1 22 5258463–5452369 1.7586 2.44E-02 ENSBTAG00000007635 phospholipase C like 1 PLCL1 2 86718341–87086748 1.4057 9.02E-03 ENSBTAG00000008103 aldehyde dehydrogenase 1 family member A1 ALDH1A1 8 49354207–49408166 1.3273 2.22E-02 ENSBTAG00000008353 cyclin dependent kinase inhibitor 1A CDKN1A 23 10560499–10568780 -2.2471 6.56E-09 ENSBTAG00000008807 F-box and leucine rich repeat protein 22 FBXL22 10 46461587–46466076 1.8751 3.71E-03 ENSBTAG00000008866 glucosidase alpha, neutral C GANC 10 37754445–37817713 1.8652 4.84E-05 ENSBTAG00000008940 neuronal pentraxin 1 NPTX1 19 52679104–52685498 -2.0194 4.61E-04 ENSBTAG00000009148 glycoprotein A33 GPA33 3 1726504–1779667 -2.1275 1.30E-02 ENSBTAG00000010389 starch binding domain 1 STBD1 6 92967767–92971371 2.2268 7.38E-09 ENSBTAG00000010419 cytochrome P450 family 2 subfamily R member 1 CYP2R1 15 38420926–38445583 -1.913 9.68E-04 ENSBTAG00000011381 solute carrier family 30 member 3 SLC30A3 11 72364682–72373190 -2.2679 3.70E-04 ENSBTAG00000011548 adenosine monophosphate deaminase 1 AMPD1 3 28756908–28768496 1.8424 6.75E-06 ENSBTAG00000011808 Growth/differentiation factor 8 MSTN 2 6213566–6220196 2.034 2.22E-02 ENSBTAG00000046587 cystatin E/M CST6 29 44766936–44768173 1.8718 1.13E-02 ENSBTAG00000015018 fibronectin type III and SPRY domain-containing protein 2 FSD2 21 23501906–23537791 1.4181 2.39E-03 ENSBTAG00000015402 protein GREB1 GREB1 11 86199420–86268193 -3.9542 4.65E-15 ENSBTAG00000016269 malic enzyme 2 ME2 24 50870262–50928290 -1.622 4.65E-02 ENSBTAG00000016444 reticulophagy regulator 1 RETREG1 20 56709603–56758641 -1.2271 4.16E-02 ENSBTAG00000017765 glutathione S-transferase M2 GSTM2 3 33824401–33834874 1.6982 8.71E-03 ENSBTAG00000016591 RAB11 family interacting protein 3 RAB11FIP3 25 404964–464143 -1.1768 4.52E-02 ENSBTAG00000016676 phosphotriesterase related PTER 13 31202455–31278293 1.3723 1.40E-02 ENSBTAG00000018088 SET binding protein 1 SETBP1 24 45025456–45141793 1.4051 1.53E-02 ENSBTAG00000018204 myosin heavy chain 1 MYH1 19 30110728–30134757 1.988 2.52E-04 ENSBTAG00000019065 endonuclease/exonuclease/phosphatase family domain containing 1 EEPD1 4 61354648–61476979 1.2436 4.40E-02 ENSBTAG00000019954 abhydrolase domain containing 2 ABHD2 21 20998719–21106763 -1.6449 2.11E-02 ENSBTAG00000021151 myosin heavy chain 10 MYH10 19 28680825–28800880 -1.1847 4.97E-02 ENSBTAG00000034411 shisa family member 3 SHISA3 6 62877287–62880849 -1.9731 3.54E-02 ENSBTAG00000037794 myosin heavy chain 4 MYH4 19 30080604–30103436 2.2376 2.03E-05 ENSBTAG00000038584 olfactomedin 1 OLFM1 11 106675880–106712955 1.5765 1.91E-02 ENSBTAG00000039574 nephrocan NEPN 9 33595874–33619430 2.4845 1.53E-04 ENSBTAG00000040126 desmoglein 4 DSG4 24 26038529–26078704 -2.6521 4.61E-04 ENSBTAG00000040398 KIAA1211 ortholog KIAA1211 6 73368358–73396166 2.0568 1.44E-02 [71]Open in a new tab Validation of RNA-seq by qRT-PCR In order to verify the RNA-seq results, we randomly selected 9 genes from the 41 annotated DEGs for qRT-PCR, namely IGFBP5, MYH1, PLCL1, SLC6A1, BDH1, MYH4, SLC30A3, PETREG1 and ME2. The comparisons of transcript abundance detected by qRT-PCR and RNA-Seq are illustrated in [72]Fig 2, showing the correlated gene expression levels using these two approaches. Consequently, it was shown that the RNA-seq data of this study are reproducible and convincible. Fig 2. Correlations of mRNA expression levels of 9 random DEGs in LL muscle of steers versus bulls by qRT-PCR and RNA-seq. [73]Fig 2 [74]Open in a new tab The x-axis indicates the log[2] (ratio of mRNA levels) using RNA-seq, and the y-axis displays the log[2] (ratio of mRNA level) measured by qRT-PCR. The blue dots represent the tested genes. The red line indicates the scatterplot of qPCR vs RNA seq. GO and pathway analysis of the DEGs In order to further investigate the physiological characteristics that were affected by castration in the LL muscle, 56 DEGs were analyzed for their functions via Gene Ontology (GO). Most of the GO categories were associated with muscle development, cell division, various enzymatic activities and nucleotide metabolism ([75]Fig 3). Specifically, the most enriched cellular components were myosin filament, cleavage furrow, cell surface furrow and myosin complex, most of which relate to muscle growth and development. The most highly enriched molecular functions include deaminase activities, oxidoreductase activities, vitamin D[3] 25-hydroxylase activity and hydrolase activities, all of which either directly or indirectly participated in fatty acid metabolism. An additional GO term clearly associated with fatty acid synthesis in the top 30 enriched categories is a response to ketones. Meanwhile, the top biological processes consist of IMP salvage, purine nucleotide salvage, purine-containing compound salvage and nucleotide salvage, which were all related with the purine nucleotide cycle, which is the ultimate function in muscle energy production. Fig 3. Most highly enriched GO terms of DEGs between Holstein steers and bulls. [76]Fig 3 [77]Open in a new tab The x-axis displays the number of DEGs, and the y-axis represents the GO terms. The bar colors correspond to different GO categories, with yellow for molecular function, red for biological process and blue for cellular component. ^1Hydrolase activity, acting on carbon-nitrogen (but not peptide) bonds, in cyclic amidines. ^2Oxidoreductase activity, acting on the CH-OH group of donors, NAD or NADP as acceptor. To discover the metabolic pathways associated with beef quality, we performed metabolic pathway analysis on the DEGs. The details of the top 12 enriched pathways in the LL muscle by comparing bulls and steers are listed in [78]Table 3. The pathways which were related with fatty acids metabolism were synthesis and degradation of ketone bodies, butanoate metabolism, purine metabolism, galactose metabolism, linoleic acid metabolism, and pyruvate metabolism. Other pathways were involved in muscle cell growth, such as tight junction, oxytocin signaling pathway and proteoglycans in cancer. Table 3. Most highly enriched KEGG pathways of DEGs between Holstein steers and bulls. KEGG Terms Input number P-Value Gene name Tight junction (cell polarity; muscle cell development) 3 0.006 MYH4, MYH1, MYH10 GABAergic synapse 2 0.025 SLC6A1, PLCL1 Synthesis and degradation of ketone bodies (ketone bodies degraded to acetyl-CoA for fatty acids synthesis) 1 0.032 BDH1 Oxytocin signaling pathway (cell proliferation; contraction) 2 0.067 ROCK2, CDKN1A Butanoate metabolism (Acetyl-CoA for fatty acids synthesis) 1 0.076 BDH1 Purine metabolism 2 0.086 ENSBTAG00000045889 (pseudogene), AMPD1 Galactose metabolism (glycerol for fatty acids synthesis) 1 0.087 GANC Linoleic acid metabolism (fatty acid metabolism) 1 0.094 CYP2R1 Pyruvate metabolism (linked to fatty acid biosynthesis through Malonyl-CoA 1 0.101 ME2 Bladder cancer (X) 1 0.101 CDKN1A Proteoglycans in cancer (cell growth) 2 0.107 ROCK2, CDKN1A Metabolic pathways 6 0.125 ALDH1A1, AMPD1, ENSBTAG00000045889 (pseudogene), GANC, CYP2R1, BDH1 [79]Open in a new tab Candidate genes associated with beef quality traits by QTL-SNP screening In order to further screen the DEGs for the candidate genes related with beef quality traits, we analyzed the DEGs in the animal QTL database ([80]https://www.animalgenome.org/cgi-bin/QTLdb/index). By comparing the gene position of the DEGs on the chromosome with the QTLs region, 9 out of 40 annotated DEGs were discovered ([81]S6 Table). In addition, we created a genome-wide association studies (GWAS) database by pooling the published SNPs related with meat quality traits for further analysis. The differentially expressed genes are considered as related to the specific SNP associated traits only if the position of the gene on the chromosome is at a distance of less than 5 Mb from that of the SNP ([82]S7 Table). A total of 39 out of 40 annotated DEGs were found as potential genes related to beef quality. Taken together, seven overlapping DEGs, namely GADL1, CYP2R1, MYH1, EEPD1, MYH10, SHISA3 and MYH4, are considered as promising candidate genes responsible for the differences in LL muscle qualities between Holstein bulls and steers ([83]Table 4). Table 4. Candidate DEGs associated with meat quality traits. Gene Information Reported QTLs Reported SNPs Gene Symbol Chr[84]^1 Position (bp)[85]^2 QTL ID[86]^3 Distance to QTL peak (cM) Traits[87]^4 Ref[88]^5 SNP Name Distance to SNP (Mb) Traits[89]^4 Ref[90]^5 EEPD1 4 61354648–61476979 20355 0.6 CW [[91]28] Hapmap42645-BTA-70875 1.84 CC [[92]29] 20368 0.6 FT12R [[93]28] MYH10 19 28680825–28800880 22873 -22.3 IMF [[94]30] UA-IFASA-9813 3.92 CW [[95]29] ARS-BFGL-NGS-88422 0.82 CC [[96]29] 22872 -2.6 IMF [[97]30] CYP2R1 15 38420926–38445583 24706 -6.7 LDMA [[98]31] ARS-BFGL-NGS-117790 2.12 CC [[99]29] GADL1 22 5258463–5452369 37164 -2.0 LMY [[100]29] ARS-BFGL-NGS-27027 0.06 CC [[101]29] MYH1 19 30110728–30134757 22873 -19.9 IMF [[102]30] UA-IFASA-9813 2.58 CW [[103]29] ARS-BFGL-NGS-88422 2.25 CC [[104]29] SHISA3 6 62877287–62880849 20764 -0.8 SF [[105]33] BTA-76543-no-rs 1.13 IMFP [[106]32] MYH4 19 30080604–30103436 22873 -19.9 IMF [[107]30] UA-IFASA-9813 2.61 CW [[108]29] ARS-BFGL-NGS-88422 2.22 CC [[109]29] [110]Open in a new tab ^1 Chromosome in B. taurus. ^2 Gene position on the UMD3.1.1 bovine genome assembly. ^3 QTL information retrieved on the Animal Quantitative Trait Loci (QTL) Database (Animal QTLdb) ([111]https://www.animalgenome.org/cgi-bin/QTLdb/index). ^4 CW: carcass weight; IMF: intramuscular fat; FT12R: fat thickness at the 12th rib; LMY: lean meat yield; SF: shear force; CC: carcass conformation; IMFP: intramuscular fat percentage. ^5 References reported indicating QTLs or SNPs.