"Wow! I've never seen anything like that before," my colleague Chao-Qiang Lai exclaimed when examining output from his analysis of genome-wide association (GWAS) data. He was looking for genetic markers influencing the level of triglyceride in serum as part of the GOLDN study. GOLDN is looking at the genetics of the response to lipid-lowering medication. The result of Chao's preliminary analysis indicated that SNP rs2880301 associated with TG levels with a p-value of 10-218. He showed me some data from the scan of the Affymetrix 6.0 genotyping chip and we postulated that we could be looking at some type of CNV (copy number variant) or deletion, but the lack of minor allele homozygotes troubled us.
What intrigued us right from the start was our colleagues at other institutions who are also analysis the GOLDN GWAS data did not report this SNP in their initial findings. The dbSNP entry for rs2880301 indicates a C to T variant with an allele frequency of 0.24 in the four primary HapMap populations from USA, Nigeria, China and Japan. No differences in allele frequency means no chance of positive (or negative) selection on this variant. No, none indeed as we were to learn later.
So, Chao dug deeper into his data and he and I shot ideas back and forth. After my suggestion to look at sex, he saw that when the SNP and sex are together in the same model, the analysis did not complete. Then, looking at the individual genotypes, he saw that all the men had genotype CT and all the women CC. This is from a total of just over 800 subjects.
OK, time for me to step in and see where this "SNP" maps in the genome. My first query was the flanking sequence supplied by Affymetrix. This 33-bp segment maps nearly perfectly to both chromosome 13, within intron 1 of the TPTE2 gene and agreeing with both dbSNP and Affyemtrix's annotation of the SNP, and curiously to a spot on the Y chromosome. (TPTE2 is a membrane-associated phosphatase which acts on the 3-position phosphate of inositol phospholipids and could be argues as relevant to TG biology.) The only residue not matching is the "polymorphic" base of the "SNP." A C is found on chr13 and a T is found on Y. Thus, the SNP becomes a marker of sex and Chao was right - it is a type of deletion (females carry no Y chromosome) - but a deletion he had not envisioned.
Is rs2880301 then a marker for gender? Not really. I compared the genomic regions where the homologous SNP sequences were found on both chromosomes, extending over 6 kbp in each direction. I saw a large region of sequence identity between 13 and Y - over 96% - for a ~5 kbp segment. Running RepeatMasker indicated that rs2880301 falls within an L1 LINE, a common repeat element. Thus, while it is intriguing that an array of repeats (70% of the 13-kbp segment of chr13 is masked by RepeatMasker) are conserved between chromosomes 13 and Y, and in order, SNP rs2880301 is not really a SNP. All subjects are C on chr13 and all Y chromosomes are T.
What we then had in our data were five genotypes: CC on chr13 for all women, CC on chr13 for all men and T on Y. Thus, the "allele frequencies" of C between 0.75 and 0.80 and T between 0.20 and 0.25 seen by us and others, including the HapMap data, roughly correspond to populations that are half to slightly more than half women.
Wednesday, October 26, 2011
Tuesday, September 13, 2011
Genetics of hypertension
An important paper describing genetic factors involved in blood pressure and heart disease was published this week. 29 loci were identified - 16 of these novel. This is impressive, but not so surprising as both diastolic and systolic blood pressure are complex, heritable traits. Many, many factors are at play here. In fact, the authors describe a risk score based on genotypes at 29 genome-wide significant variants, which was associated with hypertension, left ventricular wall thickness, stroke and coronary artery disease, but not kidney disease or kidney function.
Some time ago, I wrote about the genome of the SHR (spontaneous hypertensive rat). This rat and the FHH strain are models for hypertension. The genome of the SHR strain showed that 788 genes contained variants with respect to the reference rat genome. Whether any or all of those variants function in producing the hypertension phenotype is not clear, but reasoning went that these variants would be a logical place from which to build list of candidate genes.
Well, I thought it would be a fun and quick exercise to see how many of these 29 loci detected by genome-wide associations in nearly 70,000 individuals of European ancestry (with validation of top signals in up to 133,000 additional individuals of European descent) compare to those genes that possess genetic variants in either the FHH or SHR rat strains. This may give insight into the applicability of sequencing the genomes of specific model organism strains and into how many or how often genes are identified by both GWAS and whole-genome sequencing. To do this, I used the Rat Genome Browser hosted by the Medical College of Wisconsin.
Of the 29 human loci, 23 map in the rat genome within a QTL for blood pressure. This looks good, but consider that there are numerous blood pressure (BP) QTL mapped throughout the rat genome. In fact, the rat Adm gene maps within 27 different BP QTL and three other gene regions, Furin - Fes, Plekha7 and Mov10, map within more than 20 different BP QTL. Some of these QTL are large, spanning many genes, which means that fine-mapping is needed - such as a GWAS - to identify more precisely candidate loci.
Only 18 of the human BP genes identified in the paper contain SNPs in either the FHH or SHR strains. Often, the variants are shared in both strains. Both synonymous and nonsynonymous SNPs were noted, but synonymous far outnumbered those variants that altered the underlying amino acid sequence. No SNPs in gene control regions were noted, which may indeed be the case or a limitation of the data sources used here.
The human genes whose rat versions contain SNPs in the hypertensive-susceptible strains are:
SLC39A8
ATP2B1
GNAS - EDN3
MTHFR - NPPB
FGF5
CYP1A1 - ULK3
FURIN - FES
FLJ32810 - TMEM133
NPR3 - C5orf23
EBF1
PLCE1
BAT2-BAT5
ZNF652
TBX5 - TBX3
JAG1
GUCY1A3 - GUCY1B3
MECOM
ULK4
SNPs altering gene expression still need to be added to this analysis. Nonetheless, the numbers and types of genes that share genetic variation in hypertensive mammals (human, rat) is revealing. It is likely that the 788 identified genes with variation in the SHR rat are not all important for hypertension, but that strain does carry variants in 17 of these new BP genes. Or is that just 17?
Some time ago, I wrote about the genome of the SHR (spontaneous hypertensive rat). This rat and the FHH strain are models for hypertension. The genome of the SHR strain showed that 788 genes contained variants with respect to the reference rat genome. Whether any or all of those variants function in producing the hypertension phenotype is not clear, but reasoning went that these variants would be a logical place from which to build list of candidate genes.
Well, I thought it would be a fun and quick exercise to see how many of these 29 loci detected by genome-wide associations in nearly 70,000 individuals of European ancestry (with validation of top signals in up to 133,000 additional individuals of European descent) compare to those genes that possess genetic variants in either the FHH or SHR rat strains. This may give insight into the applicability of sequencing the genomes of specific model organism strains and into how many or how often genes are identified by both GWAS and whole-genome sequencing. To do this, I used the Rat Genome Browser hosted by the Medical College of Wisconsin.
Of the 29 human loci, 23 map in the rat genome within a QTL for blood pressure. This looks good, but consider that there are numerous blood pressure (BP) QTL mapped throughout the rat genome. In fact, the rat Adm gene maps within 27 different BP QTL and three other gene regions, Furin - Fes, Plekha7 and Mov10, map within more than 20 different BP QTL. Some of these QTL are large, spanning many genes, which means that fine-mapping is needed - such as a GWAS - to identify more precisely candidate loci.
Only 18 of the human BP genes identified in the paper contain SNPs in either the FHH or SHR strains. Often, the variants are shared in both strains. Both synonymous and nonsynonymous SNPs were noted, but synonymous far outnumbered those variants that altered the underlying amino acid sequence. No SNPs in gene control regions were noted, which may indeed be the case or a limitation of the data sources used here.
The human genes whose rat versions contain SNPs in the hypertensive-susceptible strains are:
SLC39A8
ATP2B1
GNAS - EDN3
MTHFR - NPPB
FGF5
CYP1A1 - ULK3
FURIN - FES
FLJ32810 - TMEM133
NPR3 - C5orf23
EBF1
PLCE1
BAT2-BAT5
ZNF652
TBX5 - TBX3
JAG1
GUCY1A3 - GUCY1B3
MECOM
ULK4
SNPs altering gene expression still need to be added to this analysis. Nonetheless, the numbers and types of genes that share genetic variation in hypertensive mammals (human, rat) is revealing. It is likely that the 788 identified genes with variation in the SHR rat are not all important for hypertension, but that strain does carry variants in 17 of these new BP genes. Or is that just 17?
Tuesday, May 24, 2011
More on microRNAs - a nutrition connection
The landscape at the intersection of microRNA (miR) expression and diet is sparse. This is even more so concerning the consequence of bioactive food components in affecting the physical aspects of the miR-mRNA interaction.
Nonetheless, evidence has been reported to suggest that miRs are key metabolic regulators. In adipose of mice, expression of miRs was shown to be sensitive to conjugated linoleic acid in the diet. In rats fed a diet of corn oil/fish oil with pectin/cellulose and in which colonic tumors were induced, a number of miRs, including miR-16, miR-19b, miR-21, miR-26b, miR-27b, miR-93 and miR-203, exhibited altered expression and were linked to oncogenic signaling pathways. Also in rats, downregulation in the liver of three miRs (miR-122, miR-451 and miR-27) and upregulation of miR-200a, miR-200b and miR-429 was noted after feeding of either a high-fat or high-fructose diet with consequences of diet-induced nonalcoholic fatty liver disease.
In mice, pregnant and lactating dams fed a high-fat diet displayed reduced expression of miR-26a, miR-122, miR-192, miR-194, miR-709 and the let-7 family with a common predicted target of methyl-CpG binding protein 2 (Mecp2).
A comparison of miR expression profiles in subcutaneous adipose of women highlighted eleven miRNAs as significantly deregulated in obese subjects with and without type 2 diabetes. Many of the same miRs also showed significant deregulation during adipocyte differentiation. The role of diet in regulating miR expression in prostate cancer has been reviewed. MiR-33, encoded in an intron of SERBF1/SREBF2, cooperatively regulates cholesterol homeostasis via targeting of ABCA1 and NPC1. The FXR/SHP signaling cascade regulates miR-34a and its target SIRT1, which likely functions as either a regulator of epigenetic gene silencing or an intracellular regulatory protein with mono-ADP-ribosyltransferase activity.
Using a mouse diet-induced obesity model, it was shown that hepatic expression of miR-107 decreases while its target FASN, encoding fatty acid synthase, increases.
In summary, there is a growing body of evidence to strongly implicate microRNAs as having significant functions in regulating the metabolic-based response of a number of cell types.
Nonetheless, evidence has been reported to suggest that miRs are key metabolic regulators. In adipose of mice, expression of miRs was shown to be sensitive to conjugated linoleic acid in the diet. In rats fed a diet of corn oil/fish oil with pectin/cellulose and in which colonic tumors were induced, a number of miRs, including miR-16, miR-19b, miR-21, miR-26b, miR-27b, miR-93 and miR-203, exhibited altered expression and were linked to oncogenic signaling pathways. Also in rats, downregulation in the liver of three miRs (miR-122, miR-451 and miR-27) and upregulation of miR-200a, miR-200b and miR-429 was noted after feeding of either a high-fat or high-fructose diet with consequences of diet-induced nonalcoholic fatty liver disease.
In mice, pregnant and lactating dams fed a high-fat diet displayed reduced expression of miR-26a, miR-122, miR-192, miR-194, miR-709 and the let-7 family with a common predicted target of methyl-CpG binding protein 2 (Mecp2).
A comparison of miR expression profiles in subcutaneous adipose of women highlighted eleven miRNAs as significantly deregulated in obese subjects with and without type 2 diabetes. Many of the same miRs also showed significant deregulation during adipocyte differentiation. The role of diet in regulating miR expression in prostate cancer has been reviewed. MiR-33, encoded in an intron of SERBF1/SREBF2, cooperatively regulates cholesterol homeostasis via targeting of ABCA1 and NPC1. The FXR/SHP signaling cascade regulates miR-34a and its target SIRT1, which likely functions as either a regulator of epigenetic gene silencing or an intracellular regulatory protein with mono-ADP-ribosyltransferase activity.
Using a mouse diet-induced obesity model, it was shown that hepatic expression of miR-107 decreases while its target FASN, encoding fatty acid synthase, increases.
In summary, there is a growing body of evidence to strongly implicate microRNAs as having significant functions in regulating the metabolic-based response of a number of cell types.
Friday, April 1, 2011
CDKN2A and its response to diet
Although it is April 1st here, there is some serious business taking place on my desktop: Cleanup day. I'm reading through an electronic pile of papers and news items that have gathered over the last weeks.
Here's an interesting bit about human gene CDKN2A. This gene encodes cyclin-dependent kinase inhibitor 2A and is also known as p16INK4a. Suppression of CDKN2A by glucose restriction in human cells (fetal lung fibroblasts) was shown by Li & Tollefsbol to contribute to lifespan extension via epigenetic and genetic mechanisms that were mediated by SIRT1.
A year ago, we published a paper showing the effects on gene expression in mononuclear cells in metabolic syndrome subjects after intake of phenol-rich virgin olive oil. We noted repressed expression of several pro-inflammatory genes. Interestingly, CDKN2A was also significantly repressed. Thus, two dietary conditions - low glucose and phenol-rich olive oil - repress expression of this gene, albeit in different cell types and under different circumstances.
Here's an interesting bit about human gene CDKN2A. This gene encodes cyclin-dependent kinase inhibitor 2A and is also known as p16INK4a. Suppression of CDKN2A by glucose restriction in human cells (fetal lung fibroblasts) was shown by Li & Tollefsbol to contribute to lifespan extension via epigenetic and genetic mechanisms that were mediated by SIRT1.
A year ago, we published a paper showing the effects on gene expression in mononuclear cells in metabolic syndrome subjects after intake of phenol-rich virgin olive oil. We noted repressed expression of several pro-inflammatory genes. Interestingly, CDKN2A was also significantly repressed. Thus, two dietary conditions - low glucose and phenol-rich olive oil - repress expression of this gene, albeit in different cell types and under different circumstances.
Monday, March 28, 2011
MicroRNAs and glucose metabolism
A noteworthy article released yesterday in Nature Cell Biology reports that in mice, in liver, microRNA miR-143 induces the down-regulation of oxysterol binding protein-like 8 (OSBPL8, ORP8). This leads to an impaired ability of insulin to induce AKT activation. AKT is a protein kinase. What is most interesting about this work is the presentation of evidence that microRNA-based regulation of gene activity is important in glucose homeostasis and perhaps onset of type 2 diabetes.
Before I get into what else is known about miR-143/MIRN143, it is interesting to note that OSBPL8 suppresses ABCA1 expression and cholesterol efflux from macrophages, as reported by Yan et al. (2008). ABCA1 is itself regulated, in part, by microRNA MIR33A encoded within SREBF2 to regulate both HDL biogenesis in the liver and cellular cholesterol efflux.
MIRN143:
MIRN143 is frequently observed to be downregulated in colorectal (Ng Sung 2009 Br J Cancer 101:699) and gastric cancers (Takagi Akao 2009 Oncology 77:12)
MIRN143 is frequently downregulated in pancreatic cancer cells (Kent Mendell 2009 Cancer Biol Ther 8:2013)
MIRN143 was a transcriptional target of myocardin and other transcriptional factors involved in smooth muscle cell fate (Cordes Srivastava 2009 Nature 460:705)
MIRN143 has also been found to play a role in adipocyte differentiation (Xie Lodish 2009 Dibetes 58:1050, Walden Cannon 2009 J Cell Physiol 218:444, Takanabe Hasegawa 2008 Biochem Biophys Res Commun 376:728, Esau Griffey 2004 J Biol Chem 279:52361))
Expression of MIRN143 was elevated in differentiating adipocytes and inhibition of MIRN143 could suppress differentiation of adipocytes (Esau Griffey 2004 J Biol Chem 279:52361)
Ectopically expressed MIRN143 in preadipocyte 3T3-L1 cells has been found to accelerate adipogenesis (Xie Lodish 2009 Diabetes 58:1050)
In addition, MIRN145, neighboring MIRN143 in the human genome is also a participant to this regulatory network:
IRS1 translation is downregulated by MIRN145 (Shi B, Baserga R, et al J. Biol. Chem. 282:32582-32590, 2007)
MIRN145 regulates actin cytoskeletal dynamics (Xin 2009 Genes Dev 23:2166)
stem cell pluripotency is regulated by MIRN145 (Xu 2009 Cell 137:647)
Before I get into what else is known about miR-143/MIRN143, it is interesting to note that OSBPL8 suppresses ABCA1 expression and cholesterol efflux from macrophages, as reported by Yan et al. (2008). ABCA1 is itself regulated, in part, by microRNA MIR33A encoded within SREBF2 to regulate both HDL biogenesis in the liver and cellular cholesterol efflux.
MIRN143:
MIRN143 is frequently observed to be downregulated in colorectal (Ng Sung 2009 Br J Cancer 101:699) and gastric cancers (Takagi Akao 2009 Oncology 77:12)
MIRN143 is frequently downregulated in pancreatic cancer cells (Kent Mendell 2009 Cancer Biol Ther 8:2013)
MIRN143 was a transcriptional target of myocardin and other transcriptional factors involved in smooth muscle cell fate (Cordes Srivastava 2009 Nature 460:705)
MIRN143 has also been found to play a role in adipocyte differentiation (Xie Lodish 2009 Dibetes 58:1050, Walden Cannon 2009 J Cell Physiol 218:444, Takanabe Hasegawa 2008 Biochem Biophys Res Commun 376:728, Esau Griffey 2004 J Biol Chem 279:52361))
Expression of MIRN143 was elevated in differentiating adipocytes and inhibition of MIRN143 could suppress differentiation of adipocytes (Esau Griffey 2004 J Biol Chem 279:52361)
Ectopically expressed MIRN143 in preadipocyte 3T3-L1 cells has been found to accelerate adipogenesis (Xie Lodish 2009 Diabetes 58:1050)
In addition, MIRN145, neighboring MIRN143 in the human genome is also a participant to this regulatory network:
IRS1 translation is downregulated by MIRN145 (Shi B, Baserga R, et al J. Biol. Chem. 282:32582-32590, 2007)
MIRN145 regulates actin cytoskeletal dynamics (Xin 2009 Genes Dev 23:2166)
stem cell pluripotency is regulated by MIRN145 (Xu 2009 Cell 137:647)
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