PMC:1359071 / 2823-6158 JSONTXT

{"project":"2_test","denotations":[{"id":"16462940-11861025-86014481","span":{"begin":131,"end":132},"obj":"11861025"},{"id":"16462940-14596945-86014482","span":{"begin":133,"end":134},"obj":"14596945"},{"id":"16462940-11328966-86014483","span":{"begin":1364,"end":1365},"obj":"11328966"},{"id":"16462940-12925895-86014483","span":{"begin":1364,"end":1365},"obj":"12925895"},{"id":"16462940-12646919-86014483","span":{"begin":1364,"end":1365},"obj":"12646919"},{"id":"16462940-15514660-86014484","span":{"begin":1643,"end":1644},"obj":"15514660"},{"id":"16462940-14634638-86014485","span":{"begin":2103,"end":2104},"obj":"14634638"},{"id":"16462940-12646919-86014486","span":{"begin":2112,"end":2113},"obj":"12646919"},{"id":"16462940-15514893-86014487","span":{"begin":2114,"end":2115},"obj":"15514893"},{"id":"16462940-11923494-86014488","span":{"begin":2130,"end":2131},"obj":"11923494"},{"id":"16462940-15299141-86014488","span":{"begin":2130,"end":2131},"obj":"15299141"},{"id":"16462940-15687266-86014488","span":{"begin":2130,"end":2131},"obj":"15687266"},{"id":"16462940-15711547-86014488","span":{"begin":2130,"end":2131},"obj":"15711547"},{"id":"16462940-15711545-86014488","span":{"begin":2130,"end":2131},"obj":"15711545"},{"id":"16462940-15711544-86014488","span":{"begin":2130,"end":2131},"obj":"15711544"},{"id":"16462940-15269782-86014488","span":{"begin":2130,"end":2131},"obj":"15269782"},{"id":"16462940-12415114-86014488","span":{"begin":2130,"end":2131},"obj":"12415114"},{"id":"T54173","span":{"begin":131,"end":132},"obj":"11861025"},{"id":"T38470","span":{"begin":133,"end":134},"obj":"14596945"},{"id":"T34552","span":{"begin":1364,"end":1365},"obj":"11328966"},{"id":"T49441","span":{"begin":1364,"end":1365},"obj":"12925895"},{"id":"T29806","span":{"begin":1364,"end":1365},"obj":"12646919"},{"id":"T42793","span":{"begin":1643,"end":1644},"obj":"15514660"},{"id":"T65566","span":{"begin":2103,"end":2104},"obj":"14634638"},{"id":"T6696","span":{"begin":2112,"end":2113},"obj":"12646919"},{"id":"T30843","span":{"begin":2114,"end":2115},"obj":"15514893"},{"id":"T59192","span":{"begin":2130,"end":2131},"obj":"11923494"},{"id":"T9450","span":{"begin":2130,"end":2131},"obj":"15299141"},{"id":"T64174","span":{"begin":2130,"end":2131},"obj":"15687266"},{"id":"T72429","span":{"begin":2130,"end":2131},"obj":"15711547"},{"id":"T25873","span":{"begin":2130,"end":2131},"obj":"15711545"},{"id":"T67278","span":{"begin":2130,"end":2131},"obj":"15711544"},{"id":"T90746","span":{"begin":2130,"end":2131},"obj":"15269782"},{"id":"T76675","span":{"begin":2130,"end":2131},"obj":"12415114"}],"text":"Introduction\nFemales and males share nearly identical genetic information, but vary widely with respect to disease susceptibility [1,2]. Apart from the obvious gender-specific diseases such as cervical or prostate cancer, sex influences susceptibility to nearly all highly prevalent diseases that affect both women and men, including atherosclerosis and diabetes and their precursor conditions of hyperlipidemia, obesity, and insulin resistance. These are multifactorial in their pathogenesis, encompassing environmental and behavioral aspects, as well as significant genetic determination, on which these other factors interact. The genetic component is multigenic, with the heritability embedded in the genetic variation intrinsic to our population. Although the sex differences in disease susceptibility are recognized, the interplay between sex and gene expression that is at the basis of these differences is not well understood. Females and males inherit (on average) the same genes that may be risk factors, but their expression and effect on disease risk varies significantly. An understanding and recognition of the significance of specific disease-associated polymorphisms/mutations in the context of sex is therefore of critical clinical importance.\nWe have utilized the mouse as a model system to study the genetics of metabolic and vascular diseases [3–5]. Rather than focus initially on natural or induced mutants of single genes, we utilize the complex endogenous genetic variation between strains in genetic crosses to identify causative genetic loci and ultimately the underlying variations responsible for trait differences [6]. This design more closely reflects the situation faced when studying human populations. The genetic composition of each individual mouse is restricted to that of the two parental strains and is defined at every locus across the genome. The application of quantitative trait locus (QTL) analysis allows the identification of those chromosomal regions that contain a genetic variation that influences trait expression (for a comprehensive review on QTLs see [7]). We [5,8], and others [9–17], have recently extended the power of this approach by incorporating genome-wide gene expression array analysis, which allows us to model the “genetics of gene expression” using similar methods. An immediate extension of this approach is toward dissecting the genetic regulation of complex phenotypes, which would greatly improve the progression from candidate locus to candidate gene.\nHere we report the application of this integrated approach to study the significance of sex on the genetic determinants of obesity and the associated regulation of liver gene expression in an F2 intercross derived from the inbred strains C57BL/6J (B6) and C3H/HeJ (C3H) on an apolipoprotein E null (ApoE−/−) background. The BXH.ApoE−/− population was designed to recapitulate several of the phenotypes associated with the so-called metabolic syndrome. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of QTLs on sex. We detected several thousand gene expression QTLs (eQTLs), a significant proportion of which were sex-biased. We used these analyses to dissect the genetic regulation of the gonadal fat mass trait and to identify genes associated with the trait."}

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Apart from the obvious gender-specific diseases such as cervical or prostate cancer, sex influences susceptibility to nearly all highly prevalent diseases that affect both women and men, including atherosclerosis and diabetes and their precursor conditions of hyperlipidemia, obesity, and insulin resistance. These are multifactorial in their pathogenesis, encompassing environmental and behavioral aspects, as well as significant genetic determination, on which these other factors interact. The genetic component is multigenic, with the heritability embedded in the genetic variation intrinsic to our population. Although the sex differences in disease susceptibility are recognized, the interplay between sex and gene expression that is at the basis of these differences is not well understood. Females and males inherit (on average) the same genes that may be risk factors, but their expression and effect on disease risk varies significantly. An understanding and recognition of the significance of specific disease-associated polymorphisms/mutations in the context of sex is therefore of critical clinical importance.\nWe have utilized the mouse as a model system to study the genetics of metabolic and vascular diseases [3–5]. Rather than focus initially on natural or induced mutants of single genes, we utilize the complex endogenous genetic variation between strains in genetic crosses to identify causative genetic loci and ultimately the underlying variations responsible for trait differences [6]. This design more closely reflects the situation faced when studying human populations. The genetic composition of each individual mouse is restricted to that of the two parental strains and is defined at every locus across the genome. The application of quantitative trait locus (QTL) analysis allows the identification of those chromosomal regions that contain a genetic variation that influences trait expression (for a comprehensive review on QTLs see [7]). We [5,8], and others [9–17], have recently extended the power of this approach by incorporating genome-wide gene expression array analysis, which allows us to model the “genetics of gene expression” using similar methods. An immediate extension of this approach is toward dissecting the genetic regulation of complex phenotypes, which would greatly improve the progression from candidate locus to candidate gene.\nHere we report the application of this integrated approach to study the significance of sex on the genetic determinants of obesity and the associated regulation of liver gene expression in an F2 intercross derived from the inbred strains C57BL/6J (B6) and C3H/HeJ (C3H) on an apolipoprotein E null (ApoE−/−) background. The BXH.ApoE−/− population was designed to recapitulate several of the phenotypes associated with the so-called metabolic syndrome. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of QTLs on sex. We detected several thousand gene expression QTLs (eQTLs), a significant proportion of which were sex-biased. We used these analyses to dissect the genetic regulation of the gonadal fat mass trait and to identify genes associated with the trait."}

{"project":"craft-ca-core-ex-dev","denotations":[{"id":"T1918","span":{"begin":13,"end":20},"obj":"PATO_UBERON_EXT:female_or_bearer_of_femaleness"},{"id":"T1919","span":{"begin":25,"end":30},"obj":"PATO_UBERON_EXT:male_or_bearer_of_maleness"},{"id":"T1920","span":{"begin":54,"end":61},"obj":"SO_EXT:0000704"},{"id":"T1921","span":{"begin":193,"end":201},"obj":"UBERON:0000002"},{"id":"T1922","span":{"begin":205,"end":213},"obj":"UBERON:0002367"},{"id":"T1923","span":{"begin":309,"end":314},"obj":"NCBITaxon_UBERON_EXT:woman"},{"id":"T1924","span":{"begin":426,"end":433},"obj":"PR_EXT:000045358"},{"id":"T1925","span":{"begin":525,"end":535},"obj":"GO_PATO_EXT:biological_behavior"},{"id":"T1926","span":{"begin":568,"end":575},"obj":"SO_EXT:0000704"},{"id":"T1927","span":{"begin":634,"end":641},"obj":"SO_EXT:0000704"},{"id":"T1928","span":{"begin":660,"end":665},"obj":"SO_EXT:0000704"},{"id":"T1929","span":{"begin":705,"end":712},"obj":"SO_EXT:0000704"},{"id":"T1930","span":{"begin":713,"end":722},"obj":"SO_EXT:sequence_variation_entity_or_quality"},{"id":"T1931","span":{"begin":853,"end":857},"obj":"SO_EXT:0000704"},{"id":"T1932","span":{"begin":853,"end":868},"obj":"GO:0010467"},{"id":"T1933","span":{"begin":935,"end":942},"obj":"PATO_UBERON_EXT:female_or_bearer_of_femaleness"},{"id":"T1934","span":{"begin":947,"end":952},"obj":"PATO_UBERON_EXT:male_or_bearer_of_maleness"},{"id":"T1935","span":{"begin":983,"end":988},"obj":"SO_EXT:0000704"},{"id":"T1936","span":{"begin":1025,"end":1035},"obj":"GO:0010467"},{"id":"T1937","span":{"begin":1169,"end":1182},"obj":"SO_EXT:polymorphism"},{"id":"T1938","span":{"begin":1183,"end":1192},"obj":"SO_EXT:sequence_alteration_entity_or_process"},{"id":"T1939","span":{"begin":1282,"end":1287},"obj":"NCBITaxon:10088"},{"id":"T1940","span":{"begin":1319,"end":1327},"obj":"OBI_SO_EXT:gene_or_genetic_investigation_or_genetic_process"},{"id":"T1941","span":{"begin":1331,"end":1340},"obj":"GO:0008152"},{"id":"T1942","span":{"begin":1345,"end":1353},"obj":"UBERON_EXT:vascular_system_or_vasculature_or_vessel"},{"id":"T1943","span":{"begin":1420,"end":1427},"obj":"SO_EXT:sequence_altered_entity"},{"id":"T1944","span":{"begin":1438,"end":1443},"obj":"SO_EXT:0000704"},{"id":"T1945","span":{"begin":1479,"end":1486},"obj":"SO_EXT:0000704"},{"id":"T1946","span":{"begin":1487,"end":1496},"obj":"SO_EXT:sequence_variation_entity_or_quality"},{"id":"T1947","span":{"begin":1516,"end":1523},"obj":"SO_EXT:0000704"},{"id":"T1948","span":{"begin":1554,"end":1566},"obj":"SO_EXT:0000704"},{"id":"T1949","span":{"begin":1597,"end":1607},"obj":"SO_EXT:sequence_variation_entity_or_quality"},{"id":"T1950","span":{"begin":1715,"end":1720},"obj":"NCBITaxon:9606"},{"id":"T1951","span":{"begin":1738,"end":1745},"obj":"SO_EXT:0000704"},{"id":"T1952","span":{"begin":1777,"end":1782},"obj":"NCBITaxon:10088"},{"id":"T1953","span":{"begin":1874,"end":1880},"obj":"SO_EXT:0001026"},{"id":"T1954","span":{"begin":1901,"end":1925},"obj":"SO_EXT:0000771"},{"id":"T1955","span":{"begin":1927,"end":1930},"obj":"SO_EXT:0000771"},{"id":"T1956","span":{"begin":1976,"end":1995},"obj":"GO_SO_EXT:chromosomal_part_or_position_or_region_or_site"},{"id":"T1957","span":{"begin":2011,"end":2018},"obj":"SO_EXT:0000704"},{"id":"T1958","span":{"begin":2019,"end":2028},"obj":"SO_EXT:sequence_variation_entity_or_quality"},{"id":"T1959","span":{"begin":2093,"end":2097},"obj":"SO_EXT:0000771"},{"id":"T1960","span":{"begin":2204,"end":2210},"obj":"SO_EXT:0001026"},{"id":"T1961","span":{"begin":2216,"end":2220},"obj":"SO_EXT:0000704"},{"id":"T1962","span":{"begin":2216,"end":2231},"obj":"GO:0010467"},{"id":"T1963","span":{"begin":2278,"end":2286},"obj":"OBI_SO_EXT:gene_or_genetic_investigation_or_genetic_process"},{"id":"T1964","span":{"begin":2290,"end":2294},"obj":"SO_EXT:0000704"},{"id":"T1965","span":{"begin":2290,"end":2305},"obj":"GO:0010467"},{"id":"T1966","span":{"begin":2395,"end":2402},"obj":"SO_EXT:0000704"},{"id":"T1967","span":{"begin":2403,"end":2413},"obj":"GO:0065007"},{"id":"T1968","span":{"begin":2515,"end":2519},"obj":"SO_EXT:0000704"},{"id":"T1969","span":{"begin":2620,"end":2627},"obj":"SO_EXT:0000704"},{"id":"T1970","span":{"begin":2671,"end":2684},"obj":"_FRAGMENT"},{"id":"T1971","span":{"begin":2691,"end":2706},"obj":"GO:0010468"},{"id":"T1972","span":{"begin":2685,"end":2690},"obj":"UBERON:0002107"},{"id":"T1973","span":{"begin":2691,"end":2695},"obj":"SO_EXT:0000704"},{"id":"T1974","span":{"begin":2797,"end":2811},"obj":"CHEBI:39015"},{"id":"T1975","span":{"begin":2797,"end":2813},"obj":"PR_EXT:000004155"},{"id":"T1976","span":{"begin":2814,"end":2818},"obj":"SO_EXT:sequence_nullness"},{"id":"T1977","span":{"begin":2820,"end":2824},"obj":"PR_EXT:000004155"},{"id":"T1978","span":{"begin":2824,"end":2825},"obj":"SO_EXT:sequence_nullness_or_absence"},{"id":"T1979","span":{"begin":2826,"end":2827},"obj":"SO_EXT:sequence_nullness_or_absence"},{"id":"T1980","span":{"begin":2849,"end":2853},"obj":"PR_EXT:000004155"},{"id":"T1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and males share nearly identical genetic information, but vary widely with respect to disease susceptibility [1,2]. Apart from the obvious gender-specific diseases such as cervical or prostate cancer, sex influences susceptibility to nearly all highly prevalent diseases that affect both women and men, including atherosclerosis and diabetes and their precursor conditions of hyperlipidemia, obesity, and insulin resistance. These are multifactorial in their pathogenesis, encompassing environmental and behavioral aspects, as well as significant genetic determination, on which these other factors interact. The genetic component is multigenic, with the heritability embedded in the genetic variation intrinsic to our population. Although the sex differences in disease susceptibility are recognized, the interplay between sex and gene expression that is at the basis of these differences is not well understood. Females and males inherit (on average) the same genes that may be risk factors, but their expression and effect on disease risk varies significantly. An understanding and recognition of the significance of specific disease-associated polymorphisms/mutations in the context of sex is therefore of critical clinical importance.\nWe have utilized the mouse as a model system to study the genetics of metabolic and vascular diseases [3–5]. Rather than focus initially on natural or induced mutants of single genes, we utilize the complex endogenous genetic variation between strains in genetic crosses to identify causative genetic loci and ultimately the underlying variations responsible for trait differences [6]. This design more closely reflects the situation faced when studying human populations. The genetic composition of each individual mouse is restricted to that of the two parental strains and is defined at every locus across the genome. The application of quantitative trait locus (QTL) analysis allows the identification of those chromosomal regions that contain a genetic variation that influences trait expression (for a comprehensive review on QTLs see [7]). We [5,8], and others [9–17], have recently extended the power of this approach by incorporating genome-wide gene expression array analysis, which allows us to model the “genetics of gene expression” using similar methods. An immediate extension of this approach is toward dissecting the genetic regulation of complex phenotypes, which would greatly improve the progression from candidate locus to candidate gene.\nHere we report the application of this integrated approach to study the significance of sex on the genetic determinants of obesity and the associated regulation of liver gene expression in an F2 intercross derived from the inbred strains C57BL/6J (B6) and C3H/HeJ (C3H) on an apolipoprotein E null (ApoE−/−) background. 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and males share nearly identical genetic information, but vary widely with respect to disease susceptibility [1,2]. Apart from the obvious gender-specific diseases such as cervical or prostate cancer, sex influences susceptibility to nearly all highly prevalent diseases that affect both women and men, including atherosclerosis and diabetes and their precursor conditions of hyperlipidemia, obesity, and insulin resistance. These are multifactorial in their pathogenesis, encompassing environmental and behavioral aspects, as well as significant genetic determination, on which these other factors interact. The genetic component is multigenic, with the heritability embedded in the genetic variation intrinsic to our population. Although the sex differences in disease susceptibility are recognized, the interplay between sex and gene expression that is at the basis of these differences is not well understood. Females and males inherit (on average) the same genes that may be risk factors, but their expression and effect on disease risk varies significantly. An understanding and recognition of the significance of specific disease-associated polymorphisms/mutations in the context of sex is therefore of critical clinical importance.\nWe have utilized the mouse as a model system to study the genetics of metabolic and vascular diseases [3–5]. Rather than focus initially on natural or induced mutants of single genes, we utilize the complex endogenous genetic variation between strains in genetic crosses to identify causative genetic loci and ultimately the underlying variations responsible for trait differences [6]. This design more closely reflects the situation faced when studying human populations. The genetic composition of each individual mouse is restricted to that of the two parental strains and is defined at every locus across the genome. The application of quantitative trait locus (QTL) analysis allows the identification of those chromosomal regions that contain a genetic variation that influences trait expression (for a comprehensive review on QTLs see [7]). We [5,8], and others [9–17], have recently extended the power of this approach by incorporating genome-wide gene expression array analysis, which allows us to model the “genetics of gene expression” using similar methods. An immediate extension of this approach is toward dissecting the genetic regulation of complex phenotypes, which would greatly improve the progression from candidate locus to candidate gene.\nHere we report the application of this integrated approach to study the significance of sex on the genetic determinants of obesity and the associated regulation of liver gene expression in an F2 intercross derived from the inbred strains C57BL/6J (B6) and C3H/HeJ (C3H) on an apolipoprotein E null (ApoE−/−) background. The BXH.ApoE−/− population was designed to recapitulate several of the phenotypes associated with the so-called metabolic syndrome. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of QTLs on sex. We detected several thousand gene expression QTLs (eQTLs), a significant proportion of which were sex-biased. We used these analyses to dissect the genetic regulation of the gonadal fat mass trait and to identify genes associated with the trait."}