Association of an ACSL1 gene variant with polyunsaturated fatty acids in bovine skeletal muscle

  • Philipp Widmann1,

    Affiliated with

    • Karin Nuernberg2,

      Affiliated with

      • Christa Kuehn1 and

        Affiliated with

        • Rosemarie Weikard1Email author

          Affiliated with

          BMC Genetics201112:96

          DOI: 10.1186/1471-2156-12-96

          Received: 6 June 2011

          Accepted: 11 November 2011

          Published: 11 November 2011

          Abstract

          Background

          The intramuscular fat deposition and the fatty acid profiles of beef affect meat quality. High proportions of unsaturated fatty acids are related to beef flavor and are beneficial for the nutritional value of meat. Moreover, a variety of clinical and epidemiologic studies showed that particularly long-chain omega-3 fatty acids from animal sources have a positive impact on human health and disease.

          Results

          To screen for genetic factors affecting fatty acid profiles in beef, we initially performed a microsatellite-based genome scan in a F2 Charolais × German Holstein resource population and identified a quantitative trait locus (QTL) for fatty acid composition in a region on bovine chromosome 27 where previously QTL affecting marbling score had been detected in beef cattle populations. The long-chain acyl-CoA synthetase 1 (ACSL1) gene was identified as the most plausible functional and positional candidate gene in the QTL interval due to its direct impact on fatty acid metabolism and its position in the QTL interval. ACSL1 is necessary for synthesis of long-chain acyl-CoA esters, fatty acid degradation and phospholipid remodeling. We validated the genomic annotation of the bovine ACSL1 gene by in silico comparative sequence analysis and experimental verification. Re-sequencing of the complete coding, exon-flanking intronic sequences, 3' untranslated region (3'UTR) and partial promoter region of the ACSL1 gene revealed three synonymous mutations in exons 6, 7, and 20, six noncoding intronic gene variants, six polymorphisms in the promoter region, and four variants in the 3' UTR region. The association analysis identified the gene variant in intron 5 of the ACSL1 gene (c.481-233A>G) to be significantly associated with the relative content of distinct fractions and ratios of fatty acids (e.g., n-3 fatty acids, polyunsaturated, n-3 long-chain polyunsaturated fatty acids, trans vaccenic acid) in skeletal muscle. A tentative association of the ACSL1 gene variant with intramuscular fat content indicated that an indirect effect on fatty acid composition via modulation of total fat content of skeletal muscle cannot be excluded.

          Conclusions

          The initial QTL analysis suggested the ACSL1 gene as a positional and functional candidate gene for fatty acid composition in bovine skeletal muscle. The findings of subsequent association analyses indicate that ACSL1 or a separate gene in close proximity might play a functional role in mediating the lipid composition of beef.

          Background

          In recent decades, the continuing accumulation of knowledge and the increasing number of reports providing evidence regarding the beneficial health effects of polyunsaturated fatty acids (PUFA) have attracted the attention of the medical and public community. Consumers are becoming increasingly aware of the relationships between diet and health and also of the importance of the diet for general physical and mental wellbeing [1, 2]. Many clinical and epidemiologic studies have indicated a positive impact of long-chain omega-3 fatty acids (n-3 long-chain polyunsaturated fatty acids, n-3 LC-PUFA) on human health and disease. Beneficial effects of n-3 LC-PUFA are described in infant development, cancer, and cardiovascular diseases (e.g., [36]), lipid and glucose metabolism (e.g., [710]), inflammation (e.g., [11, 12]), and more recently, in various mental illnesses including depression, attention-deficit hyperactivity disorder, and dementia (e.g.,[13]). It has been demonstrated that diets containing higher levels of n-3 LC-PUFA [namely DHA (docosahexaenoic acid; C22:6n-3) and EPA (eicosapentaenoic acid; C20:5n-3)], may reduce cardiovascular risk in diabetes by inhibiting platelet aggregation, improving lipid profiles, and reducing cardiovascular mortality. Thus, n-3 LC-PUFA were particularly recommended to people with diabetes and metabolic disorders associated to obesity [5, 14]. Their beneficial health effects may be mediated through multiple distinct mechanisms, including alterations in cell membrane composition and function, gene expression, or eicosanoid biosynthesis [15, 16]. It is known that n-3 LC-PUFA can exert important metabolic effects due to their ability to modulate the transcription of regulatory genes with function in lipid metabolism [1721].

          The n-3 LC-PUFA, like DHA and EPA, are particularly abundant in oily cold-water fish and seafood, however, they are also present in other animal products (e.g., ruminant meat and milk) but in lower concentrations. Increases of n-3 LC-PUFA content in the human diet can be achieved by dietary supplementation, but there is also a potential to alter the natural fatty acid (FA) profile in food from animals. FA composition of meat and milk reflects both, FA biosynthesis in the respective animal tissue and FA composition of ingested nutrients. A recent study showed that cattle and lambs fed grass-diet in the period before slaughter had an increased content of beneficial FAs in meat, and that subsequent moderate consumption of the respective meat had resulted in increased plasma and platelet n-3 LC-PUFA concentrations in healthy human individuals [22]. A ruminant diet on grass, which is rich in α-linolenic acid (C18:3n-3, ALA) compared to cereal-based concentrate diet can influence the FA profile of meat in the desired direction and improve its nutritional value [2325]. However, the link between nutritional intake of FAs and its subsequent concentration in skeletal muscle is stronger in monogastric animals (pigs, poultry) than in ruminants due to hydrogenation of dietary FAs in the rumen (e.g., [26]).

          In addition to the environmental conditions, genetic factors may also have a substantial effect on the variability of FA composition in animal products, especially for ruminants [27]. Consequently, genetic selection and breeding of animals with favorably enriched n-3 LC-PUFA content in skeletal muscle can provide a rich source of the desired beneficial FAs for the human diet. Therefore, it is necessary to elucidate the molecular-genetic background of fatty acid composition in bovine skeletal muscle for identifying the genes or gene variants favorable for human nutrition.

          Numerous quantitative trait loci (QTL) affecting meat quality traits in cattle like marbling and FA composition have been identified on a variety of bovine chromosomes (http://​www.​animalgenome.​org/​cgi-bin/​gbrowse/​bovine/​), which enabled subsequent identification of positional candidate genes, which are located in the vicinity of identified QTL and have putative physiological functions regarding FA synthesis in skeletal muscle. These candidate genes for lipid-associated traits have been studied for their possible role regarding phenotypic variation observed between and within breeds. DNA variants in a variety of genes involved in lipid synthesis and FA metabolism have been found to influence FA composition in bovine muscle tissue and carcass (SCD1, [2834], SREBP-1 [29], FASN [29, 3437], FABP4 and LXRα [38], GH [29], ACACA [39], myostatin [40, 41], leptin [33]).

          However, the biochemical processes and the molecular background affecting the genetic variability of the complex polygenic trait of FA composition are not yet completely understood, particularly with regard to European cattle breeds, because the majority of recent studies have been performed on the very specific genetic background of Japanese Black cattle.

          Therefore, the aim of this study was to identify genetic factors affecting the variation of FA composition in bovine skeletal muscle. For our study, we took advantage of a unique F2 resource population generated from the major European cattle breeds Charolais and German Holstein by means of embryo transfer and foster mothers [42]. In previous studies, this population had been shown to segregate for two major loci (NCAPG and MSTN) associated with prenatal and pubertal growth, postnatal body composition and general lipid deposition [43, 44].

          Results and discussion

          The animals from our resource cross population were kept and fed at standardized uniform conditions and slaughtered at the same age. Therefore, we can exclude exogenous factors due to differences in herd, age, feeding and gender. Consequently, differences in skeletal muscle fatness or FA composition should be due to differences in endogenous factors of the animals like the genetic background. The primary focus of our study was to discover phenotypic differences of FA composition in skeletal muscle between the individual animals of the resource population due to genetic variation.

          QTL analysis and identification of ACSL1 as a positional and functional candidate gene

          An initial QTL analysis in the Charolais × German Holstein cross population identified a QTL for FA composition on bovine chromosome 27 (BTA27) as exemplified for n-3 LC-PUFA in Figure 1. In our study, the trait n-3 LC-PUFA represents n-3 PUFA exceeding a carbon chain length of C18. The QTL interval corresponded to a region, where previously QTL affecting marbling had been detected in a Bos indicus × Bos taurus cross and two commercial US Angus populations [45, 46]. The QTL explained 20.5% variance in the model calculated as the relative reduction of the residual variance due to including the QTL in the model [47].
          http://static-content.springer.com/image/art%3A10.1186%2F1471-2156-12-96/MediaObjects/12863_2011_959_Fig1_HTML.jpg
          Figure 1

          QTL for the relative content of n-3 long chain PUFA (n-3 LC PUFA) on BTA27. Solid boxes: ACSL1 c.481-233A>G effect not included in the model, open boxes: ACSL1 c.481-233A>G included in the model as a fixed effect. LRT significance threshold is indicated by a dashed line (α = 0.05: 7.23).

          Furthermore, QTL for FA composition, myristic acid, (C14:0) and oleic acid (C18:1) content, have been reported in this chromosomal region in a Jersey × Limousin back-cross cattle population [48]. In our study, the QTL interval affecting FA composition in skeletal muscle displayed a peak between 15 and 16 cM on our genetic map of BTA27 corresponding to a genomic position at approximately 16 Mb on the current bovine genome assembly of the chromosome (NCBI mapviewer, build 5.2, http://​www.​ncbi.​nlm.​nih.​gov/​projects/​mapview/​map_​search.​cgi?​taxid=​9913).

          Based on its chromosomal position and integration in biochemical pathways of lipid metabolism, we identified the acyl-CoA synthetase long-chain family member 1 (ACSL1) gene as the most plausible positional and functional candidate gene underlying the QTL with effect on FA composition on BTA27. The ACSL1 gene is located exactly under the peak of the QTL interval. Its protein, the ACSL1 enzyme, is known to catalyze the first step of activation of long-chain (LC) FAs by converting them into LC acyl CoA thioesters for channeling towards chain elongation, triacylglyceride synthesis or FA oxidation [49]. ACSL1 has a key function in both the synthesis of cellular lipids and FA degradation, and is also necessary for phospholipid remodeling [50]. Due to its physiological biochemical function, it can be suggested that ACSL1 plays an important role in lipid metabolism, insulin resistance and obesity. Recently, a study in humans reported that a gene variant located in intron 1 of the ACSL1 gene can influence the metabolic syndrome risk (characterized by insulin resistance, dyslipidaemia, abdominal obesity and hypertension associated to type 2 diabetes), and that this ACSL1 genotype-dependent effect can be modulated by dietary PUFA intake suggesting a gene-nutrient interaction [51].

          Structure analysis and screening for polymorphisms of the ACSL1 gene

          Although sequences for the ACSL1 gene and protein were deposited in the bovine genome databases, we found inconsistencies regarding the structural annotation of the gene in the bovine genome assemblies. A correct and conclusive structural gene annotation is a prerequisite for subsequent screening for gene variants and analysis of their functional relevance. Therefore, the first step of our study focused on the experimental confirmation of the structure of the ACSL1 gene on the genomic and cDNA level. Experimental verification by RT-PCR, re-sequencing and comparative sequence analyses confirmed the genomic annotation of the bovine ACSL1 gene in the alternate UMD_3.1 genome assembly (Figure 2), which is in contrast to the reference genome assembly Btau4.2 (http://​www.​ncbi.​nlm.​nih.​gov/​projects/​mapview/​map_​search.​cgi?​taxid=​9913).
          http://static-content.springer.com/image/art%3A10.1186%2F1471-2156-12-96/MediaObjects/12863_2011_959_Fig2_HTML.jpg
          Figure 2

          Structure of the bovineACSL1gene and detection of polymorphic sites. Reference mRNA sequence: NM_001076085.1. SNPs included in the association analysis are bold framed.

          Re-sequencing of DNA from pools and individuals differing in IMF content and Δ9 desaturase activity index included a total of 8.5 Kb of genomic DNA. Comparative sequence analysis revealed a total of 19 single nucleotide polymorphisms (SNPs) in the targeted gene regions (Table 1). Three synonymous exonic (exons 6, 7 and 20), six intronic (introns 5, 6, 9, 13, 16 and 20), six SNPs in the promoter region and four SNPs in the 3'UTR of the bovine ACSL1 gene were detected (Figure 2, Table 1). Eleven out of these SNPs identified in our study were novel and not previously represented in the SNP database (version 133) at NCBI.
          Table 1

          Identified SNPs within the ACSL1 locus and positions on the bovine genome assemblies

          SNP ID

          relative to coding sequence*

          Gene region

          Variation relative to reference sequence

          Position on NW_001494406.2 (Btau4.2)

          Position on NW_003104605.1 (UMD_3.1)

          Allele

          frequency

          SNP accession number (dbSNP, NCBI ss#)

          c.-569_570del AC

          Promoter

          Indel TG

          1918795

          389858

          Not analyzed

          ss469271165

          c.-224_225del GG

          Promoter

          Indel (C)5-7

          1918451

          389615

          Not analyzed

          ss469271166

          c.-196G>A

          Promoter

          C>T

          1918422

          3894586

          Not analyzed

          ss469271167

          c.-167G>C

          Promoter

          C>G

          1918393

          3894557

          Not analyzed

          ss469271168

          c.-151G>C

          Promoter

          C>G

          1918377

          3894541

          Not analyzed

          ss469271169

          c.-122G>A

          Promoter

          C>T

          1918348

          3894512

          0.67 (G)/0.33 (A)

          ss469271170

          c.481-233A>G

          Intron 5

          T>C

          1876389

          3852106

          0.73 (A)/0.27 (G)

          ss469271171

          c.516C>G

          Exon 6

          G>C

          1876121

          3852284

          0.57 (C)/0.43 (G)

          ss469271172

          c.580+114C>G

          Intron 6

          G>C

          1875943

          3852552

          0.33 (C)/0.67 (G)

          ss469271173

          c.584A>G

          Exon 7

          T>C

          1875838

          3852001

          0.07 (G)/0.94 (A)

          ss469271174

          c.845-58T>G

          Intron 9

          A>C

          1871919

          3848082

          0.75 (T)/0.21 (G)5

          ss469271175

          c.1267-100C>T

          Intron 13

          G>A

          1864210

          3840373

          0.24 (T)/0.76 (C)

          ss469271176

          c.1525-131C>T

          Intron 16

          G>A

          1859370

          3835533

          Not analyzed

          ss469271177

          c.1938T>G

          Exon 20

          A>C

          Not annotated

          3831586

          0.75 (T)/0.25 (G)

          ss469271178

          c.1959+56G>A

          Intron 20

          C>T

          Not annotated

          3831509

          0.24 (A)/0.76 (G)

          ss469271179

          c.2099+1023del A

          3'UTR

          Indel A

          1853870

          3829944

          Not analyzed

          ss469271180

          c.2099+1030 C>A

          3'UTR

          C>A

          1853863

          3829937

          Not analyzed

          ss469271181

          c.2099+1032 A>C

          3'UTR

          A>C

          1853861

          3829935

          Not analyzed

          ss469271182

          c.2099+1034 C>A

          3'UTR

          C>A

          1853859

          3829933

          Not analyzed

          ss469271183

          *SNP nomenclature according to the translation start codon ATG, reference sequence NM_001076085.1. SNPs marked in bold were included in the association analysis. Genomic positions of the SNPs were inferred from the current versions of the refererence and alternative bovine genome assemblies Btau4.2 and UMD_3.1 available at NCBI (http://​www.​ncbi.​nlm.​nih.​gov/​genome/​guide/​cow/​index.​html).

          Association of ACSL1 gene variants with PUFA profile in skeletal muscle

          The association analysis included all exonic and intronic ACSL1 gene variants (except for the one in intron 16) and one SNP in the promoter region, which were identified by re-sequencing and validated by genotyping in the Charolais × German Holstein resource population. The nine SNPs analyzed in the Holstein × Charolais cross bred population showed a minor allele frequency ≥ 0.2 in the analyzed data set (Table 1). Intragenic linkage disequilibrium (LD) analysis revealed a strong LD between the SNPs in intron 20, exon 20, intron 13 and intron 9 (r2 >0.9), whereas there was only a moderate LD (0.5 < r2 <0.6) between these SNPs and the one in intron 5.

          The association analysis with intragenic ACSL1 SNPs revealed that the SNP located in intron 5 of the ACSL1 gene (c.481-233A>G) showed the most significant associations with FA composition in skeletal muscle. The gene variant ACSL1 c.481-233A>G was significantly associated with the relative content of distinct fractions of unsaturated FAs, n-3 FA, PUFA, n-3 LC-PUFA and docosapentaenoic fatty acid (DPA) as well as with the absolute content of total FA, MUFA, and trans vaccenic acid (C18:1trans-11) in M. longissimus dorsi (Table 2). The results revealed that the c.481-233A allele of this gene variant is strongly associated with a higher relative level of n-3 FA, PUFA, DPA, and n-3 LC-PUFA. In contrast, the c.481-233A allele showed a decreasing effect on content of C18:1trans-11, total FA, and MUFA, and tended to be associated with a lower IMF content in skeletal muscle compared to the c.481-233G allele. The c.481-233A allele had a higher freqeuncy (73%) in the analyzed population compared to the alternative allele (27%).
          Table 2

          Association of the SNP in intron 5 of the ACSL1 gene (c.481-233A>G) with variation in intramuscular fatty acid composition and fat content

           

          Model without IMF as covariate

          Model with IMF as covariate

          Trait*

          LRT

          p-value

          Effect allele A

          SE

          Effect allele G

          SE

          Var [%]**

          LRT

          p-value

          Effect allele A

          SE

          Effect allele G

          SE

          Total FA [mg]* &

          6.2

          0.0130

          3.70

          0.07

          3.88

          0.07

           

          3.8

          0.0507

              

          MUFA [mg]* &

          5.9

          0.0154

          3.29

          0.08

          3.48

          0.09

           

          2.9

          0.0874

              

          n-3 FA [%]* #

          9.7

          0.0018a

          0.16

          0.05

          0.01

          0.06

          11.4

          5.8

          0.0159

          0.42

          0.04

          0.36

          0.04

          PUFA [%]* #

          7.1

          0.0079b

          1.12

          0.05

          0.98

          0.06

          3.5

          3.9

          0.0477

              

          n-3 LC PUFA [%]#

          6.7

          0.0099b

          0.24

          0.03

          0.16

          0.04

          3.4

          3.5

          0.0628

              

          C18:1trans-11 [mg]* &

          10.5

          0.0012a

          1.31

          0.10

          1.63

          0.12

          6.5

          8.1

          0.0045a

          0.86

          0.09

          1.07

          0.10

          C22:5n-3 [%]#

          7.2

          0.0071 b

          0.16

          0.02

          0.11

          0.03

          3.6

          5.9

          0.0150

          0.27

          0.02

          0.23

          0.02

          PUFA/SFA*

          7.3

          0.0069b

          -0.79

          0.06

          -0.94

          0.07

          3.6

          4.2

          0.0407

              

          P/S*

          6.7

          0.0099b

          -1.02

          0.05

          -1.15

          0.06

          3.2

          3.2

          0.0758

              

          LA/ALA*

          4.9

          0.0265

          1.03

          0.03

          0.97

          0.03

           

          1.9

          0.1720

              

          IMF [%]

          3.1

          0.0776

          1.11

          0.18

          1.42

          0.21

          1.7

                

          *Trait data log-transformed, &absolute content of fatty acids (mg/100 g of skeletal muscle), #relative content of fatty acids (percentage of the respective fatty acid fraction relative to total fatty acid amount)

          LTR: likelihood ratio test, p: significancy of allelic effects, Var: variance explained, SE: standard error, aq-value <0.05, bq-value <0.1, **% variance in the model calculated as the relative reduction of the residual variance due to including the SNP in the model [47].

          Allelic effects of the ACSL1 SNP (c.481-233A>G) on different FA fractions: n-3 fatty acids (n-3 FA = C18:3n-3 + C18:4n-3 + C20:5n-3 + C22:5n-3 + C22:6n-3), poly-unsaturated fatty acids (PUFA = n-3 FA + n-6 FA [C18:2n-6 + C18:3n-6 + C20:2n-6 + C20:3n-6 + C20:4n-6 + C22:2n-6 + C22:4n-6]), n-3 long-chain PUFA (n-3 LC-PUFA = C20:3n-3 + C22:6n-3 + C22:5n-3 + C20:5n-3), total FA, mono-unsaturated fatty acids (MUFA), docosapentaenoic fatty acid (DPA, C22:5n-3), trans vaccenic acid (TVA, C18:1trans-11) and the ratios: PUFA/SFA (saturated fatty acids = C12:0 + C14:0 + C16:0 + C17:0 + C18:0 + C20:0 + C24:0), P/S (C18:2 n-6 + C18:3 n-3/C14:0 + C16:0 + C18:0), LA/ALA (C18:2 n-6/C18:3 n-3), and the intramuscular fat content (IMF).

          Although the c.481-233A allele tends to be associated with a slightly lower total IMF content, the relative content of the FA fractions, n-3 FA, PUFA, DPA, and n-3 LC-PUFA, known to exert health-beneficial effects in humans is highly increased indicating a higher nutritional value for beef originating from animals with the favorable ACSL1 allele.

          The strongest allelic effect of the ACSL1 c.481-233A>G locus was observed for n-3 FA content. This trait also includes the polyunsaturated C18 fatty acids, α-linolenic acid (ALA, C18:3n-3) and stearidonic acid (C18:4n-3). The n-3-FA content is different to the trait n-3 LC-PUFA, which exclusively comprises n-3 FA with a chain length > C18. As an essential FA, ALA cannot be synthesized by mammalian species and must be obtained from the diet. The ALA concentration in skeletal muscle, therefore, could be linked to the dietary absorption. However, the standardized concentrate-based feeding regimen in our study provides uniform feeding conditions for the animals. ALA is the precursor for the n-3 FA pathway [52] by serving as parent FA for the synthesis of stearidonic acid and n-3 LC-PUFA (EPA, DPA, and DHA) via sequential steps of desaturation and/or chain-elongation. The association of ACSL1 c.481-233A>G with DPA and with n-3 LC-PUFA (containing n-3 FA exceeding a chain length of C18) could suggest that a substantial proportion of their precursor ALA might be activated and channeled to chain elongation processes.

          The trait PUFA comprises both FA types, the n-6 and n-3 FA. The ACSL1 c.481-233A>G variant showed no significant impact on n-6 FA content and thus, its association with PUFA could be due to its effect on the trait's component n-3 FA.

          Interestingly, the ACSL1 gene variant c.481-233A>G that affected FA profiles in bovine skeletal muscle had no significant influence on the ratio n-6/n-3 FA in this tissue. Considering the standardized uniform feeding regimen in our study, this result could support the findings from other studies, which indicate that the n-6/n-3 FA ratio may be affected more by feeding than by genetics [53, 54]. In contrast, we found the ACSL1 gene variant c.481-233A>G to be associated with the LA/ALA (C18:2 n-6/C18:3 n-3) ratio. Furthermore, we observed significant associations of this gene variant with the ratios PUFA/SFA and P/S in our study, both representing characteristics of meat quality and widely used to evaluate the nutritional value of meat fat content. Again, the c.481-233A allele revealed an increasing effect on these ratios compared to the c.481-233G allele.

          In contrast to the increasing effect associated with the c.481-233A allele on the relative content of the FA fractions, n-3 FA, PUFA, DPA, and n-3 LC-PUFA, and the PUFA/SFA and P/S ratios, we observed a decreasing effect of this allele on the absolute content of the trans vaccenic acid C18:1trans-11 in skeletal muscle in our study. This effect was in concert with the associated parallel decrease in total FA and MUFA content in the tissue. The effect on C18:1trans-11 is of particular interest, because trans vaccenic acid is a precursor of conjugated linoleic acid (CLAcis-9, trans-11) generation. CLAs are believed to have several important physiological functions, including anti-carcinogenic, anti-atherogenic, immunomodulating, growth and lean body mass promoting effects [55]. Thus, targeted selection of cattle carrying the homozygous c.481-233A/c.481-233A genotype in the ACSL1 gene would possibly be accompanied by detrimental effects on the CLA profile in skeletal muscle.

          There is the open question, whether the significant effects of the ACSL1 gene variant c.481-233A>G on FA composition were due to general fatness differences in skeletal muscle, which is supported by several QTL for marbling in the targeted chromosomal region, or whether the effects were associated with the ACSL1 gene variant c.481-233A>G. Alternatively, the effects of this gene variant might modulate the accumulation of specific FAs in skeletal muscle. To address this issue, we extended our association analysis and fitted IMF as a covariate in the model. When adjusting for IMF (Table 2), the association of the ACSL1 gene variant c.481-233A>G with absolute content of trans vaccenic acid in skeletal muscle remained significant, whereas the other associations dropped below a stringent threshold of statistical significance (Bonferroni q < 0.1) and were only tentatively significant (e.g., for relative content of n-3 FA and DPA). Thus, we cannot exclude that variants in the bovine ACSL1 gene may exert a substantial effect on total intramuscular fat content, which indirectly affects intramuscular composition of specific FA fractions. However, as the results for trans vaccenic acid demonstrate, it is suggested that there are also direct effects associated with the ACSL1 gene variant c.481-233A>G on intramuscular content of specific FAs.

          Conclusions

          Due to our observation that the c.481-233A>G SNP in intron 5 of the ACSL1 gene cannot fully explain the QTL variance (Figure 1), we conclude that this gene variant is presumably not causal, but in LD to another not yet detected polymorphism in its close vicinity affecting FA composition in bovine skeletal muscle. Presumably, these effects are not exclusively the consequence of variation in intramuscular fat content, but due to effects on specific FA. Prior to selective breeding of cattle carrying the desired genotype of the ACSL1 gene variant c.481-233A>G in order to produce meat with specific FA profiles, the association between c.481-233A>G and FA composition has to be confirmed in the particular target cattle population.

          Nevertheless, our results indicate that the ACSL1 gene might play a functional role in mediating the FA composition in bovine skeletal muscle and provide a basis to further elucidate the function of the ACSL1 gene and its coordinated network with genes integrated in FA metabolism to dissect the molecular background of lipid composition of beef.

          Methods

          Animals and phenotypes

          The generation of the Charolais × German Holstein resource cross population (SEGFAM), details regarding feeding and housing of the animals analyzed in our study, have been previously described [43, 44]. The animals were kept under standardized environmental and feeding conditions in barn facilities at the Leibniz Institute for Farm Animal Biology (FBN). After birth, the calves were fed a milk/replacer/hay/concentrate diet ad libitum until day 121. Thereafter, the animals received a feed ration of concentrates and chaffed hay with a hay to concentrate ratio of 1:3 and an energy content of 12.7 MJ ME/kg dry matter fed ad libitum until slaughter. The animals were kept in a tight stall barn with individual daily feed recording. At the age of 18 months (547 days of age), the male animals were slaughtered, and a detailed dissection of the carcass was performed. A wide range of phenotypic data related to beef production and beef quality including FA composition were recorded including FA composition of selected skeletal muscles.

          Analysis of FA composition of lipids involving 26 different FAs in skeletal muscle (M. longissimus dorsi) was determined for 156 F2 bulls using capillary gas chromatography as described previously [56]. The absolute amount of FAs in skeletal muscle was determined from 2 g of skeletal muscle and calculated as mg/100 g tissue. The relative content of individual fatty acids was calculated as percentage of the total amount of FAs extracted. Based on the data obtained for individual fatty acids, sums of specific fatty acid fractions were calculated: saturated fatty acids (SFA), unsaturated fatty acids (UFA), monounsaturated fatty acids (MUFA), trans fatty acids (TFA), n-3 fatty acids (n-3 FA), n-6 fatty acids (n-6 FA), polyunsaturated fatty acids (PUFA) and n-3 long-chain PUFA (n-3 LC-PUFA). Furthermore, the ratios n-6/n-3 FA, MUFA/SFA, PUFA/SFA, P/S and LA/ALA as well as four different Δ9 desaturase indices [57] were calculated. Intramuscular fat (IMF) content (percentage in 100 g tissue) was ascertained in M. longissimus dorsi by FoodScan Lab (FOSS) as described previously [56]. The phenotypic traits for FA composition of IMF included in our study are summarized in Table 3.
          Table 3

          Phenotypic traits characterizing fatty acid composition in skeletal muscle

          Trivial name

          Abbreviation

          Mean of absolute

          content (mg/100 g)

          SD

          Mean of relative

          content (%)

          SD

          Lauric acid

          C12:0

          2.83*

          1.80

          0.10

          0.04

          Myristoleic acid

          C14:1cis-9

          18.53

          17.85

          0.62

          0.31

          Myristic acid

          C14:0

          92.12*

          65.50

          3.10*

          0.66

          Palmitoleic acid

          C16:1cis-9

          109.33*

          76.59

          3.73

          0.83

          Palmitic acid

          C16:0

          823.94*

          490.88

          28.77

          1.86

          Heptadecenoic acid

          C17:1cis-10

          23.48*

          12.51

          0.85

          0.18

          Margaric acid

          C17:0

          34.94*

          18.13

          1.26*

          0.25

          Stearic acid

          C18:0

          373.40*

          199.95

          4.96*

          1.80

          Oleic acid

          C18:1cis-9

          981.37*

          578.52

          34.35

          2.60

          Vaccenic acid

          C18:1cis-11

          43.60*

          30.60

          13.41

          1.65

          trans Vaccenic acid

          C18:1trans-11

          28.40*

          20.18

          1.52*

          0.33

          Linoleic acid (LA)

          C18:2n-6

          121.45*

          29.94

          0.99*

          0.43

          Linolelaidic acid

          C18:2trans-9, trans-12

          4.11*

          3.39

          0.11

          0.13

          Conjugated linoleic acid

          CLAcis-9, trans-11

          5.99*

          4.73

          0.20

          0.09

          α-Linolenic acid (ALA)

          C18:3n-3

          12.99

          4.97

          0.50*

          0.14

          Stearidonic acid (SDA)

          C18:4n-3

          2.70

          3.36

          0.15

          0.10

          Arachidic acid

          C20:0

          2.94

          1.90

          0.11

          0.06

          Eisosenoic acid

          C20:1n-9

          4.21*

          2.80

          0.35

          0.15

          Eisosatrienoic acid (ETE)

          C20:3n-3

          8.15*

          1.86

          0.11*

          0.05

          Arachidonic acid (AA)

          C20:4n-6

          33.89

          7.60

          1.48*

          0.74

          Timnodonic acid, EPA

          C20:5n-3

          2.41*

          0.70

          0.14*

          0.03

          Erucic acid

          C22:1n-9

          0.46*

          0.24

          0.02*

          0.01

          Adrenic acid

          C22:4n-6

          6.20

          1.53

          0.28

          0.13

          Clupadonic acid, DPA

          C22:5n-3

          6.51*

          1.34

          0.26*

          0.11

          Cervonic acid, DHA

          C22:6n-3

          0.92

          0.45

          0.04

          0.03

          Lignoceric acid

          C24:0

          0.82

          0.44

          0.03*

          0.02

          ∑ Saturated fatty acids

          SFA

          1352.06*

          777.93

          47.55

          2.38

          ∑ Unsaturated fatty acids

          UFA

          1463.62*

          777.61

          52.45

          2.38

          ∑ Polyunsaturated fatty acids

          PUFA

          208.34*

          44.62

          8.57*

          3.02

          ∑ Monounsaturated fatty acids

          MUFA

          1208.85*

          726.67

          42.19*

          3.16

          ∑ trans fatty acids

          TFA

          43.92*

          24.70

          1.58

          0.47

          ∑ n-3 fatty acids

          n-3FA

          24.75

          6.42

          1.01*

          0.35

          ∑ n-3 long-chain PUFA

          n-3 LCPUFA

          9.58

          2.21

          0.42*

          0.20

          ∑ n-6 fatty acids

          n-6FA

          167.28*

          34.88

          6.94

          2.64

          ∑ n-6 long-chain PUFA

          n-6 LCPUFA

          40.09

          8.62

          1.78

          0.85

          ∑ Total fatty acids

          FA

          2743.81*

          1524.08

            

          Ratio n-6/n-3

          n-6/n-3

          6.96

          1.42

            

          Ratio MUFA/SFA

          MUFA/SFA

          0.89

          0.09

            

          Ratio PUFA/SFA

          PUFA/SFA

          0.18*

          0.07

            

          Ratio P/S

          P/S

          0.12*

          0.05

            

          Ratio C18:2n-6/C18:3n-3

          LA/ALA

          9.86*

          2.51

            

          Δ9-desaturase index MUFA

          Δ9MUFA

          46.39

          2.56

            

          Δ9-desaturase index C14

          Δ9C14

          16.31

          6.65

            

          Δ9-desaturase index C16

          Δ9C16

          11.40

          2.08

            

          Δ9-desaturase index C18

          Δ9C18

          72.16

          3.34

            

          Intramuscular fat content

          IMF

            

          2.56

          1.13

          SD: standard deviation

          *Data displaying distributions significantly different from normality (p < 0.01) were log-transformed.

          SFA = C12:0 + C14:0 + C16:0 + C17:0 + C18:0 + C20:0 + C24:0

          MUFA = C14:1 + C16:1 + C17:1 + C18:1 + C20:1 + C22:1 + C18:1cis-9 + C18:1cis-11 + C18:1trans-11

          UFA = MUFA + PUFA

          Total FA = sum of all fatty acids determined

          n-3FA = C18:3n-3 + C18:4n-3 + C20:3n-3 + C20:5n-3 + C22:5n-3 + C22:6n-3

          n-6FA = C18:2n-6 + C18:3n-6 + C20:2n-6 + C20:3n-6 + C20:4n-6 + C22:2n-6 + C22:4n-6

          PUFA = n-3FA + n-6FA

          n-3 LC-PUFA = C20:3n-3 + C22:6n-3 + C22:5n-3 + C20:5n-3

          TFA = C18:1trans-11 + C18:2trans-9, trans-12

          LA/ALA = C18:2n-6/C18:3n-3

          P/S = C18:2 n-6 + C18:3 n-3/C14:0 + C16:0 + C18:0

          Δ9MUFA = [(C14:1 + C16:1 + C17:1 + C18:1cis-9 + CLAcis-9, trans-11)/(C14:1 + C16:1 + C17:1 + C18:1cis-9 +

          C18:1trans-11 + C14:0 + C16:0 + C17:0 + C18:0 + CLAcis-9, trans-11)] × 100

          Δ9C14 = [C14:1/(C14:0 + C14:1)] × 100

          Δ9C16 = [C16:1/(C16:0 + C16:1)] × 100

          Δ9C18 = [(C18:1cis-9 + CLAcis-9, trans-11/(C18:0 + C18:1cis-9 + C18:1trans-11 + CLAcis-9, trans-11)] × 100

          QTL analysis

          An initial QTL scan comprising 244 microsatellite markers [58] for variation of FA composition in skeletal muscle had pinpointed a region on bovine chromosome 27 (BTA27) with effect on n-3 PUFA content in skeletal muscle. Five microsatellite markers located on BTA27 (BM3507, RM209, BMS689, BM1857, BM203) had been genotyped in all 733 P0, F1, and F2 individuals of the Charolais × German Holstein resource population.

          The respective QTL interval pointed to a chromosomal region on BTA27 harboring the acyl-CoA synthetase long-chain family member 1 (ACSL1) gene according to the sequence assembly of the chromosome. Therefore, in a second step of our analysis, nine intragenic ACSL1 SNPs (Figure 1) were added to the initial marker set. All microsatellite markers and all genotyped ACSL1 SNPs were included to calculate a genetic map using CRIMAP Version 2.50 [59], incorporating modifications by Ian Evans and Jill Maddox (University of Melbourne). The resulting genetic map was applied in the QTL analyses with a variance component QTL model as implemented in Qxpak [60] and essentially as described previously [43]:
          http://static-content.springer.com/image/art%3A10.1186%2F1471-2156-12-96/MediaObjects/12863_2011_959_Equa_HTML.gif

          where y is a vector of phenotypes, b is a vector of the fixed effects (slaughter year, NCAPG I442M genotype), u is the vector of individual infinitesimal polygenic effects, g is a vector of the additive QTL effects not fixed within founder breeds; F, Z and Q represent the incidence matrices for the fixed, polygenic and the QTL effect, respectively, and e is the vector of random residuals. An MCMC algorithm was used to calculate identity-by-descent probabilities as implemented in Qxpak. The NCAPG I442M mutation was included in the model, because previous analyses had shown a major effect of the mutation on carcass lipid deposition and growth in the resource population [44].

          Statistical significance of the QTL analyses was tested by a likelihood-ratio test (LRT). Significance thresholds for the LRT were determined according to [61], considering one chromosome with a length of 0.6 M and an average marker density of 0.1 M. The significance thresholds for false positive results with α = 0.05 and α = 0.01 correspond to LRT values > 7.2 and LRT > 10.2, respectively.

          Structural analysis of the ACSL1 gene

          The coding sequence of the bovine ACSL1 gene is represented by the reference mRNA sequence NM_001076085.1, which spans 3690 bp and is located on BTA27.

          At the beginning of our study, the previous bovine genome assembly Btau4.0 and the current reference assembly Btau4.2 available at NCBI (http://​blast.​ncbi.​nlm.​nih.​gov/​Blast.​cgi?​PAGE_​TYPE=​BlastSearch&​PROG_​DEF=​blastn&​BLAST_​PROG_​DEF=​megaBlast&​SHOW_​DEFAULTS=​on&​BLAST_​SPEC=​OGP_​_​9913_​_​10708, [62]) annotated the bovine ACSL1 gene with a total of 19 protein-coding exons. In silico sequence analysis of the respective mRNA and protein sequences (NM_001076085.1 and NP_001069553) revealed that parts of the sequences could not be aligned to the bovine genome reference assembly Btau4.2. This indicated an incomplete annotation of the bovine ACSL1 gene. However, in the alternative bovine genome assembly Bos_taurus_UMD3.1 (ftp://​ftp.​cbcb.​umd.​edu/​pub/​data/​assembly/​Bos_​taurus/​Bos_​taurus_​UMD_​3.​1/​, [63]) integrated into the recent bovine genome assembly, Build 5.2, at NCBI (http://​www.​ncbi.​nlm.​nih.​gov/​projects/​mapview/​map_​search.​cgi?​taxid=​9913), the bovine ACSL1 gene was annotated with a total of 21 protein-coding exons, which is also in agreement with the earlier bovine genome assembly, version Btau3.1. Comparative sequence analysis between gene and protein sequences of the bovine ACSL1 gene and those of the orthologous human counterparts (NM_001995.2 and NP_001986.2) and the current human genome assembly Hsa37.2 (http://​blast.​ncbi.​nlm.​nih.​gov/​Blast.​cgi?​PAGE_​TYPE=​BlastSearch&​PROG_​DEF=​blastn&​BLAST_​PROG_​DEF=​megaBlast&​SHOW_​DEFAULTS=​on&​SHOW_​DEFAULTS=​on&​BLAST_​SPEC=​OGP_​_​9606_​_​9558) showed that the mRNA and amino acid sequences of both species display a high similarity (88% and 91% identity, respectively), which supported the annotation of the current Bos_taurus_UMD3.1 and the earlier Btau3.1 assemblies.

          An experimental confirmation of the bovine ACSL1 gene structure was required because of the inconsistent annotation of the ACSL1 gene. Therefore, fragments completely covering the coding region of the gene and the 5' und 3' UTRs, including the respective critical gene fragments with discordant structure annotation, were validated in our study. Exon-flanking primers (Table 4) were derived from the sequence contigs NW_001494406.2 and NW_930554.1 and used for PCR-amplification with genomic DNA and cDNA. Genomic DNA was isolated from blood leucocytes using standard methods. The cDNA was prepared from liver tissue of a lactating cow. Total RNA extraction and cDNA synthesis by reverse transcription were performed as described recently [43]. To amplify cDNA fragments of the ACSL1 gene, PCR was performed with cDNA using gene-fragment specific primers (Table 4). The PCR-amplicons were isolated from agarose gels using the NucleoSpin® Extract II kit (Macherey & Nagel) and sequenced with PCR primers using BigDye© sequencing chemistry on a capillary sequencer (MEGABACE, GE Healthcare).
          Table 4

          Primer sequences for the bovine ACSL1 gene applied for annotation confirmation, screening for polymorphisms and genotyping

          Primer

          Sequence (5' → 3')

          Gene region

          Amplicon (bp)

          Position in reference sequence

          AccNo. of reference sequence

          Application*

          ACSL1_F1

          ACSL1_R1

          CCGAGCCCCAACCGAGAC

          TGGACGCTGTTCTTGAGTGGTG

          intron 1 -promoter

          844

          1918181 - 1918198

          1919003 - 1919024

          NW_001494406.2

          SNP

          ACSL1_E1_F3

          ACSL1_E1SF

          GACCCGAGCCCCAACCGAG

          GTTGAGCCACCACAATTTACTC

          intron 1 -promoter

          497

          1918178 - 1918196

          1918674 - 1918653

          NW_001494406.2

          SNP

          ACSL1_E1SR

          ACSL1_R1

          GGACTGCCCTGGATTTCACAAG

          TGGACGCTGTTCTTGAGTGGTG

          promoter

          413

          1918612 - 1918633

          1919003 - 1919024

          NW_001494406.2

          SNP

          ACSL1_F2

          ACSL1_R2

          TCGCTGCTGAAGTCCTGTCTG

          GCTCTAATGCCCCCGTTGATG

          exon 2

          501

          1897290 - 1897310

          1897770 - 1897790

          NW_001494406.2

          SNP

          ACSL1_F3

          ACSL1_R3

          TTGCGTGGGAGAGAGTTGTG

          TCAGGTGGAGGATTTATGTCAG

          exon 3

          384

          1882758 - 1882777

          1883120 - 1883141

          NW_001494406.2

          SNP

          ACSL1_F4

          ACSL1_R4

          GCATCCACACTCCATAGAAAC

          AATAAAGAAGCAAAACTCAGACC

          exon 4

          345

          1881998 - 1882018

          1882320 - 1882342

          NW_001494406.2

          SNP

          ACSL1_F5

          ACSL1_R5

          ATGAAAGGGAAAAGTGAAAGTG

          CTTGAGTTGGACCTGATGCTG

          exon 5

          457

          1878288 - 1878309

          1878724 - 1878744

          NW_001494406.2

          SNP

          ACSL1_F6

          ACSL1_R6

          CGGCTGGAAGTAAAGAGACAC

          TTGTGTTCTTCATCCTCCTTTC

          exon 6

          574

          1875840 - 1875860

          1876392 - 1876413

          NW_001494406.2

          SNP

          ACSL1_F7

          ACSL1_R7

          GTTCTCTTTTACAGGACCAG

          CAGGGATGCTTTACTTACTC

          exon 7

          600

          1875542 - 1875561

          1876122 - 1876141

          NW_001494406.2

          SNP

          ACSL1_F8_9

          ACSL1_R8_9

          TGGGTGATGTAAATGTGTGAGG

          ATGATAGGAATGGCAGTGGAGAC

          exons

          8-9

          750

          1872567 - 1872588

          1873294 - 1873316

          NW_001494406.2

          SNP

          ACSL1_F10

          ACSL1_R10

          ATCTGTATTTCAGGTACTGTTTC

          GTTTATGGGCTTCTCTCACG

          exon 10

          287

          1871656 - 1871678

          1871923 - 1871942

          NW_001494406.2

          SNP

          ACSL1_F11

          ACSL1_R11

          TACACACTTGAACTTACCAG

          TGTGCTCTGAAATAAATGG

          exon 11

          314

          1869171 - 1869190

          1869466 - 1869484

          NW_001494406.2

          SNP

          ACSL1_F12

          ACSL1_R12

          TCTGTATTGTGCCTTCTGATG

          GGAAACTGGGCTGAAATGC

          exon 12

          371

          1866801 - 1866821

          1867153 - 1867171

          NW_001494406.2

          SNP

          ACSL1_F13

          ACSL1_R13

          TCTCACACAATAAAGGGGTAGG

          TCCACATCTTCACCAACACTC

          exon 13

          516

          1864669 - 1864690

          1865164 - 1865184

          NW_001494406.2

          SNP

          ACSL1_F14

          ACSL1_R14

          AAGCCGCCCAGGAATAACAC

          TGCCACAAACCCACGACACT

          exon 14

          516

          1863888 - 1863907

          1864384 - 1864403

          NW_001494406.2

          SNP

          ACSL1_F15

          ACSL1_R15

          GACTTGTGTTTATTTCTGCCTG

          TGGGCTGAGGTTTCTAATCC

          exon 15

          524

          1862774 - 1862795

          1863278 - 1863297

          NW_001494406.2

          SNP

          ACSL1_F16

          ACSL1_R16

          TGCTGAGAAGTGGCTGGTTAC

          CATGAGAACAGGGCTTATTGG

          exon 16

          247

          1860135 - 1860155

          1860361 - 1860381

          NW_001494406.2

          SNP

          ACSL1_F17

          ACSL1_R17

          ATGCGAGGGAGAAAGAGG

          CCGCTAACAAAAAGAACAGTG

          exon 17

          427

          1859039 - 1859056

          1859445 - 1859465

          NW_001494406.2

          SNP

          ACSL1_F18

          ACSL1_R18

          GGCAAACTTCCCATTACACTG

          GACTCCTTCATCCCTTCTCTG

          exon 18

          512

          1857386 - 1857406

          1857877 - 1857897

          NW_001494406.2

          SNP

          ACSL1_F19_20

          ACSL1_R19_20

          GCCAAAGCACACCACTCTC

          CGAAGCAGATAATAAGGAACTAC

          exons 19-20

          517

          139425 - 139443

          139919 - 139941

          NW_930554.1

          SNP

          ACSL1_F21

          ACSL1_R21

          CACCCGCCTTTGTAACTG

          GTCCTGATTCTGTCCTGATGTC

          exon 21

          548

          138819 - 138836

          139345 - 139366

          NW_930554.1

          SNP

          ACSL1_UTR_F31

          ACSL1_UTR_R3

          AAACCCTCTGGTCCTCTTGCG

          CAATGGCAGGAAGGGAGGGAG

          exon 21

          404

          138633 - 138653

          139016 - 139036

          NW_930554.1

          SNP

          ACSL1_UTR_F2

          ACSL1_UTR_R21

          GAGTTTTCCAGATTCCTATGTCC

          CCTGTTACCCTCCCTTCCCTG

          exon 21

          650

          137966 - 137988

          138595 - 138615

          NW_930554.1

          SNP

          ACSL1_UTR_F11

          ACSL1_UTR_R1

          ATGCGACTGCTGACATGAAAAAC

          AAATAAATGCTCTTCTGTCGTAATG

          exon 21

          527

          137530 - 137552

          138032 - 138056

          NW_930554.1

          SNP

          ACSL1_E1_F3

          ACSL1_E1_R2

          GACCCGAGCCCCAACCGAG

          GCTCGTAGGCTGCAGCGAG

          intron 1-promoter

          220

          1918178 - 1918196

          1918379 - 1918397

          NW_001494406.2

          GT

          ACSL1_F7

          ACSL1_R7

          GTTCTCTTTTACAGGACCAG

          CAGGGATGCTTTACTTACTC

          exon 7

          600

          1875542 - 1875561

          1876122 - 1876141

          NW_001494406.2

          GT

          (PCR-RFLP)

          ACSL1_E1_F5

          ACSL1_E1_R3

          ACSL1_E1_F7_T

          ACSL1_E1_R8_C

          GGAGGGAACTCGGGGAGCC

          AGGGCGGGGCTGAGACGG

          GCTATTTAAGGGTGCCGCCGT

          GCAGCCAGCTCTCGGAAGTAG

          promoter

          451

          316

          175

          1918052 - 1918070

          1918485 - 1918502

          1918328 - 1918348

          1918348 - 1918368

          NW_001494406.2

          GT

          (Tetra-ARMS PCR)

          ACSL1_E1_F2

          ACSL1_E5_R1

          CGGAGGAGACTGTGGCTTAG

          CTGAGCGAAGATGCCAATAAAC

          exons

          1-5

          505

          38 - 58

          521 - 543

          NM_001076085.1

          cDNA

          ACSL1_E5_F1

          ACSL1_E12_R2

          CAGTTTATTGGCATCTTCGCTC

          GGAAGATGGTGGGTTGAAGG

          exons

          5-12

          649

          519 - 541

          1148 - 1168

          NM_001076085.1

          cDNA

          ACSL1_E11_F2

          ACSL1_E18_R1

          CCATATGTTTGAGAGAGTTGTAG

          ATGTACTCCCCCTGTGCCAG

          exons 11-18

          735

          1046-1069

          1761 - 1781

          NM_001076085.1

          cDNA

          ACSL1_E17_F2

          ACSL1_E21_R2

          CTGGATAAAGACGGCTGGTTG

          GAGTTCAGGGTGGAGATAGATG

          exons 17-21

          399

          1665 - 1686

          2042 - 2064

          NM_001076085.1

          cDNA

          ACSL1_E21_R3

          GTCAAACTCCCCTCCGCTTC

          exons 17-21

          540

          2185 - 2205

          NM_001076085.1

          cDNA, RT

          ACSL1_E21_R4

          CAGAAAGAGCAAAGTCCTAACC

            

          2454 - 2476

          NM_001076085.1

          cDNA, RT

          * cDNA: analysis of cDNA structure, RT: reverse transcription, GT: genotyping, SNP: screening for polymorphisms

          Screening for polymorphisms in the ACSL1 gene

          Screening for polymorphisms was carried out by re-sequencing and covered the complete coding sequence, exon-flanking intronic regions, the 5' and 3' UTRs and 724 bp of the promoter of the ACSL1 gene. DNA primer pairs for PCR amplification and sequencing were designed based on genomic contig sequences (NW_001494406.2 and NW_930554.1) and the mRNA sequence (NM_001076085.1), respectively (Table 4).

          Four genomic DNA pools consisting of selected animals from the Charolais × Holstein resource population differing in their intramuscular fat content and index of delta 9-desaturase were established and subjected to screening for gene variants by comparative re-sequencing. The IMF pools contained DNA from sampling time- and pedigree-matched animals with high (n = 5, 4.93 ± 1.73%) and low (n = 7, 1.78 ± 0.21%) IMF. The Δ9 desaturase index pools consisted of DNA from sampling time- and pedigree-matched animals with a high (n = 7; 50.87 ± 0.89) or low (n = 6, 43.86 ± 0.95) Δ9 desaturase index. Furthermore, two genomic DNA samples from control individuals and two individual DNA samples originating from extreme animals displaying the lowest (1.63%) and highest (6.09%) IMF were included to validate the results received from the pools.

          Genomic DNA was isolated from blood leucocytes using standard methods. PCR with exon-flanking primers (Table 4) was performed with a total of 60 ng genomic DNA as described above. The generated PCR products were purified using the peqGOLD Cycle-Pure Kit (PEQLAB) according to the manufacturer's instructions and sequenced. Sequencing was performed on a capillary sequencer (MEGABACE, GE Healthcare) with primers used for targeted PCR amplification. To identify variable DNA positions, the sequences were analyzed meticulously by visual inspection of the sequencing profiles from DNA-pools and individuals' DNA and by sequence alignment to the reference cDNA sequence (NM_001076085.1) as well as to the respective bovine genome sequences. All SNPs identified by sequencing of DNA pools were verified by single sample re-sequencing.

          SNP Genotyping

          Out of the identified 19 ACSL1 SNPs (see Table 3, Figure 1), nine were genotyped in the Charolais × German Holstein resource population: Two exonic SNPs (c.516C>G, c.1938T>G) and five intronic SNPs (c.481-233A>G, c.580+114C>G, c.845-58T>G, c.1267-100C>T, c.1959+56G>A) were genotyped on an Illumina Beadstation [64] as part of a targeted 384 SNP GoldenGate assay. The SNP in exon 7 (c.584A>G) was analyzed using a PCR-RFLP assay with primers for amplification of the targeted region (Table 4) and the restriction enzyme SacI (Fermentas). The promoter SNP c.-122G>A was genotyped by a Tetra-ARMS PCR assay [65] and validated by direct sequencing. The respective primers are given in Table 4. The NCAPG I442M mutation was genotyped by PCR-RFLP [43].

          Association analysis

          Prior to association analysis, we tested whether the phenotypic data of the individual traits were normally distributed using the Shapiro Wilk test. For those data displaying distributions significantly different from normality (P < 0.01), we performed natural log (ln) transformation, and the log- transformed data were subjected to association analysis. The respective data are indicated in Tables 2 and 3.

          The BTA27 marker haplotypes of the individuals of the resource population were estimated by a Markov chain Monte Carlo (MCMC) algorithm implemented in Qxpak [60]. The corresponding haplotypes were submitted to pairwise LD analysis calculating r2 values using PowerMarker V3.25 [66].

          Subsequently to the QTL analyses, association analyses were performed between ACSL1 gene SNPs and the absolute and relative FA composition traits in M. longissimus dorsi. The following model testing for LD as implemented in Qxpak [60] was applied:
          http://static-content.springer.com/image/art%3A10.1186%2F1471-2156-12-96/MediaObjects/12863_2011_959_Equb_HTML.gif

          where yi is the record of individual i, ap is the fixed effect of slaughter year p, λihk is an indicator variable for the NCAPG I442M locus, which is 1 when the allele at the hth haplotype (1 or 2) of the ith individual is 1 and otherwise 0, λimn is a respective indicator variable for the specific ACSL1 SNP, ui is the infinitesimal genetic effect of individual i, gk and gm are the respective allelic effects for NCAPG I442M and the ACSL1 SNP, and eihkmnp is the residual. Analogous to the QTL analyses, the NCAPG I442M mutation was included in the model, because previous analyses had shown a major effect of the mutation on carcass lipid deposition and growth in the resource population [44]. A likelihood-ratio test (likelihood of model with both loci vs. likelihood of model with NCAPG I442M) was applied to test for statistical significance. In order to dissect whether the association of the respective ACSL1 variant with intramuscular FA composition is solely due to indirect effects on IMF or a consequence of direct effects on the specific FA accumulation, we extended the model and fitted IMF as an additional covariate. A Bonferroni correction was calculated (q-value) to account for testing several SNPs in order to avoid false positive associations. The q-values thresholds of 0.05 and 0.1, respectively, indicate an experiment-wise significant or suggestive association, respectively. Finally, an additive fixed effect of the SNP in intron 5 was added in the QTL model described above to test whether this SNP might explain the QTL variance at the identified position on BTA27.

          Abbreviations

          (SCD1): 

          stearoyl-Coenzyme A desaturase 1

          (SREBP-1): 

          sterol regulatory element binding protein 1

          (FASN): 

          fatty acid synthase

          (FABP4): 

          fatty acid binding protein 4

          (LXRα): 

          liver X receptor alpha

          (GH): 

          growth hormone

          (ACACA): 

          acetyl-CoA carboxylase alpha

          (NCAPG): 

          non-SMC condensin I complex

          subunit G: 

          (MSTN): myostatin.

          Declarations

          Acknowledgements and Funding

          Skillful technical assistance of Annett Eberlein, Astrid Kühl, Marlies Fuchs, Birgit Jentz, Maria Dahm, Antje Lehmann and Simone Wöhl is thankfully acknowledged. We thank the German Federal Ministry of Education and Research (BMBF) for the financial support of this work within the scope of the FUGATO QUALIPID project (FKZ 0313391C). Also, we thank our colleagues at the FBN Dummerstorf involved in the generation and care of the SEGFAM F2 resource population for their continuous support of our work and Jill Maddox (University of Melbourne, Australia) for providing the modified CRIMAP version 2.50.

          Authors’ Affiliations

          (1)
          Research Unit Molecular Biology, Leibniz Institute for Farm Animal Biology (FBN)
          (2)
          Research Unit Muscle Biology and Growth, Leibniz Institute for Farm Animal Biology (FBN)

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