Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data
Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the f...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Muñoz, María [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Anmerkung: |
© Muñoz et al.; licensee BioMed Central Ltd. 2013 |
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| Übergeordnetes Werk: |
Enthalten in: BMC genomics - London : BioMed Central, 2000, 14(2013), 1 vom: 02. Dez. |
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| Übergeordnetes Werk: |
volume:14 ; year:2013 ; number:1 ; day:02 ; month:12 |
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| DOI / URN: |
10.1186/1471-2164-14-845 |
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| Katalog-ID: |
SPR027084205 |
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| 245 | 1 | 0 | |a Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data |
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| 520 | |a Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. | ||
| 650 | 4 | |a Fatty acid composition |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Pleiotropic effects |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a QTL scan |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a eQTL |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Rodríguez, M Carmen |4 aut | |
| 700 | 1 | |a Alves, Estefânia |4 aut | |
| 700 | 1 | |a Folch, Josep María |4 aut | |
| 700 | 1 | |a Ibañez-Escriche, Noelia |4 aut | |
| 700 | 1 | |a Silió, Luis |4 aut | |
| 700 | 1 | |a Fernández, Ana Isabel |4 aut | |
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10.1186/1471-2164-14-845 doi (DE-627)SPR027084205 (SPR)1471-2164-14-845-e DE-627 ger DE-627 rakwb eng Muñoz, María verfasserin aut Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Muñoz et al.; licensee BioMed Central Ltd. 2013 Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 Rodríguez, M Carmen aut Alves, Estefânia aut Folch, Josep María aut Ibañez-Escriche, Noelia aut Silió, Luis aut Fernández, Ana Isabel aut Enthalten in BMC genomics London : BioMed Central, 2000 14(2013), 1 vom: 02. Dez. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:14 year:2013 number:1 day:02 month:12 https://dx.doi.org/10.1186/1471-2164-14-845 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2013 1 02 12 |
| spelling |
10.1186/1471-2164-14-845 doi (DE-627)SPR027084205 (SPR)1471-2164-14-845-e DE-627 ger DE-627 rakwb eng Muñoz, María verfasserin aut Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Muñoz et al.; licensee BioMed Central Ltd. 2013 Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 Rodríguez, M Carmen aut Alves, Estefânia aut Folch, Josep María aut Ibañez-Escriche, Noelia aut Silió, Luis aut Fernández, Ana Isabel aut Enthalten in BMC genomics London : BioMed Central, 2000 14(2013), 1 vom: 02. Dez. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:14 year:2013 number:1 day:02 month:12 https://dx.doi.org/10.1186/1471-2164-14-845 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2013 1 02 12 |
| allfields_unstemmed |
10.1186/1471-2164-14-845 doi (DE-627)SPR027084205 (SPR)1471-2164-14-845-e DE-627 ger DE-627 rakwb eng Muñoz, María verfasserin aut Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Muñoz et al.; licensee BioMed Central Ltd. 2013 Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 Rodríguez, M Carmen aut Alves, Estefânia aut Folch, Josep María aut Ibañez-Escriche, Noelia aut Silió, Luis aut Fernández, Ana Isabel aut Enthalten in BMC genomics London : BioMed Central, 2000 14(2013), 1 vom: 02. Dez. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:14 year:2013 number:1 day:02 month:12 https://dx.doi.org/10.1186/1471-2164-14-845 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2013 1 02 12 |
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10.1186/1471-2164-14-845 doi (DE-627)SPR027084205 (SPR)1471-2164-14-845-e DE-627 ger DE-627 rakwb eng Muñoz, María verfasserin aut Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Muñoz et al.; licensee BioMed Central Ltd. 2013 Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 Rodríguez, M Carmen aut Alves, Estefânia aut Folch, Josep María aut Ibañez-Escriche, Noelia aut Silió, Luis aut Fernández, Ana Isabel aut Enthalten in BMC genomics London : BioMed Central, 2000 14(2013), 1 vom: 02. Dez. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:14 year:2013 number:1 day:02 month:12 https://dx.doi.org/10.1186/1471-2164-14-845 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2013 1 02 12 |
| allfieldsSound |
10.1186/1471-2164-14-845 doi (DE-627)SPR027084205 (SPR)1471-2164-14-845-e DE-627 ger DE-627 rakwb eng Muñoz, María verfasserin aut Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data 2013 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Muñoz et al.; licensee BioMed Central Ltd. 2013 Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 Rodríguez, M Carmen aut Alves, Estefânia aut Folch, Josep María aut Ibañez-Escriche, Noelia aut Silió, Luis aut Fernández, Ana Isabel aut Enthalten in BMC genomics London : BioMed Central, 2000 14(2013), 1 vom: 02. Dez. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:14 year:2013 number:1 day:02 month:12 https://dx.doi.org/10.1186/1471-2164-14-845 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 14 2013 1 02 12 |
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Enthalten in BMC genomics 14(2013), 1 vom: 02. Dez. volume:14 year:2013 number:1 day:02 month:12 |
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Fatty acid composition Pleiotropic effects QTL scan eQTL |
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Muñoz, María @@aut@@ Rodríguez, M Carmen @@aut@@ Alves, Estefânia @@aut@@ Folch, Josep María @@aut@@ Ibañez-Escriche, Noelia @@aut@@ Silió, Luis @@aut@@ Fernández, Ana Isabel @@aut@@ |
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Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. 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Muñoz, María |
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Muñoz, María misc Fatty acid composition misc Pleiotropic effects misc QTL scan misc eQTL Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data |
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Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data Fatty acid composition (dpeaa)DE-He213 Pleiotropic effects (dpeaa)DE-He213 QTL scan (dpeaa)DE-He213 eQTL (dpeaa)DE-He213 |
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Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data |
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Muñoz, María Rodríguez, M Carmen Alves, Estefânia Folch, Josep María Ibañez-Escriche, Noelia Silió, Luis Fernández, Ana Isabel |
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genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data |
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Genome-wide analysis of porcine backfat and intramuscular fat fatty acid composition using high-density genotyping and expression data |
| abstract |
Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. © Muñoz et al.; licensee BioMed Central Ltd. 2013 |
| abstractGer |
Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. © Muñoz et al.; licensee BioMed Central Ltd. 2013 |
| abstract_unstemmed |
Background Porcine fatty acid composition is a key factor for quality and nutritive value of pork. Several QTLs for fatty acid composition have been reported in diverse fat tissues. The results obtained so far seem to point out different genetic control of fatty acid composition conditional on the fat deposits. Those studies have been conducted using simple approaches and most of them focused on one single tissue. The first objective of the present study was to identify tissue-specific and tissue-consistent QTLs for fatty acid composition in backfat and intramuscular fat, combining linkage mapping and GWAS approaches and conducted under single and multitrait models. A second aim was to identify powerful candidate genes for these tissue-consistent QTLs, using microarray gene expression data and following a targeted genetical genomics approach. Results The single model analyses, linkage and GWAS, revealed over 30 and 20 chromosomal regions, 24 of them identified here for the first time, specifically associated to the content of diverse fatty acids in BF and IMF, respectively. The analyses with multitrait models allowed identifying for the first time with a formal statistical approach seven different regions with pleiotropic effects on particular fatty acids in both fat deposits. The most relevant were found on SSC8 for C16:0 and C16:1(n-7) fatty acids, detected by both linkage and GWAS approaches. Other detected pleiotropic regions included one on SSC1 for C16:0, two on SSC4 for C16:0 and C18:2, one on SSC11 for C20:3 and the last one on SSC17 for C16:0. Finally, a targeted eQTL scan focused on regions showing tissue-consistent effects was conducted with Longissimus and fat gene expression data. Some powerful candidate genes and regions were identified such as the PBX1, RGS4, TRIB3 and a transcription regulatory element close to ELOVL6 gene to be further studied. Conclusions Complementary genome scans have confirmed several chromosome regions previously associated to fatty acid composition in backfat and intramuscular fat, but even more, to identify new ones. Although most of the detected regions were tissue-specific, supporting the hypothesis that the major part of genes affecting fatty acid composition differs among tissues, seven chromosomal regions showed tissue-consistent effects. Additional gene expression analyses have revealed powerful target regions to carry the mutation responsible for the pleiotropic effects. © Muñoz et al.; licensee BioMed Central Ltd. 2013 |
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| score |
7.3995934 |