Apoa2 Gene Detail

Summary

• Symbol
  Apoa2
• Name
  apolipoprotein A-II
• Synonyms
  Alp-2, Apoa-2, ApoA-II, Hdl-1

• Feature Type
  protein coding gene
• IDs
  MGI:88050
  NCBI Gene: 11807
• Alliance
  gene page
• Transcription Start Sites
  7 TSS
• Candidate for QTL
  11 QTL

Location &
Maps

• Sequence Map
  Chr1:171052623-171053948 bp, + strand

  From Ensembl annotation of GRCm39
  

• View this region in JBrowse
  
  

• Genome Browsers
  Ensembl | UCSC | NCBI

• Genetic Map
  Chromosome 1, 79.22 cM
• Mapping Data
  77 experiments

Strain
Comparison

• SNPs within 2kb
  110 from dbSNP Build 142
• Strain Annotations
  18
• PCR
  1
• RFLP
  11

Strain	Gene Model ID	Feature Type	Coordinates
C57BL/6J	MGI_C57BL6J_88050	protein coding gene	Chr1:171049133-171053948 (+)
129S1/SvImJ	MGP_129S1SvImJ_G0016747	protein coding gene	Chr1:177005836-177007160 (+)
A/J	MGP_AJ_G0016727	protein coding gene	Chr1:169806490-169807817 (+)
AKR/J	MGP_AKRJ_G0016693	protein coding gene	Chr1:174892267-174893592 (+)
BALB/cJ	MGP_BALBcJ_G0016688	protein coding gene	Chr1:170288996-170290320 (+)
C3H/HeJ	MGP_C3HHeJ_G0016511	protein coding gene	Chr1:175137087-175138411 (+)
C57BL/6NJ	MGP_C57BL6NJ_G0017149	protein coding gene	Chr1:182889449-182890774 (+)
CAROLI/EiJ	MGP_CAROLIEiJ_G0014857	protein coding gene	Chr1:161486859-161488164 (+)
CAST/EiJ	MGP_CASTEiJ_G0016092	protein coding gene	Chr1:174761338-174762663 (+)
CBA/J	MGP_CBAJ_G0016486	protein coding gene	Chr1:189404691-189406010 (+)
DBA/2J	MGP_DBA2J_G0016593	protein coding gene	Chr1:168645504-168646823 (+)
FVB/NJ	MGP_FVBNJ_G0016589	protein coding gene	Chr1:166994363-166995687 (+)
LP/J	MGP_LPJ_G0016664	protein coding gene	Chr1:178126940-178128264 (+)
NOD/ShiLtJ	MGP_NODShiLtJ_G0016616	protein coding gene	Chr1:196688166-196689486 (+)
NZO/HlLtJ	MGP_NZOHlLtJ_G0017186	protein coding gene	Chr1:174763228-174764555 (+)
PWK/PhJ	MGP_PWKPhJ_G0015878	protein coding gene	Chr1:167868472-167869800 (+)
SPRET/EiJ	MGP_SPRETEiJ_G0015662	protein coding gene	Chr1:173547578-173548899 (+)
WSB/EiJ	MGP_WSBEiJ_G0016154	protein coding gene	Chr1:174881658-174883023 (+)

Homology

• Human Ortholog
  APOA2, apolipoprotein A2

• Vertebrate Orthologs
  3

Vertebrate Orthology Source

Alliance of Genome Resources

• Human Ortholog
  APOA2, apolipoprotein A2
  
• Synonyms
  apoAII, Apo-AII, ApoA-II
• Links
  HGNC:601

  NCBI Gene ID: 336

  neXtProt AC: NX_P02652

  UniProt: P02652

  
  
• Chr Location
  1q23.3; chr1:161222293-161223628 (-)  GRCh38.p7

---

• Alliance of Genome Resources
  Apoa2 stringent orthology
  1 human;1 mouse;1 rat;1 zebrafish
  
• HCOP
  vertebrate homology predictions: APOA2
• Gene Tree
  Apoa2
  

Human Diseases

• Diseases
  1 with human APOA2 associations

				Human Disease	Mouse Models
				familial hypercholesterolemia IDs familial hypercholesterolemia       DOID:13810 ICD10CM:E78.01 MESH:D006938 NCI:C34704 OMIM:143890 ORDO:406 UMLS_CUI:C0020445

Click on a disease name to see all genes associated with that disease.

Mutations,
Alleles, and
Phenotypes

• Phenotype Summary
  14 phenotypes from 5 alleles in 7 genetic backgrounds
  10 phenotypes from multigenic genotypes
  43 phenotype references
  

• All Mutations and Alleles
  23
• Chemically induced (other)
  2
• Endonuclease-mediated
  1
• Gene trapped
  6
• Targeted
  6
• Transgenic
  2
• Genomic Mutations
  2 involving Apoa2
• Incidental Mutations
  Mutagenetix , APF
• Find Mice (IMSR)
  13 strains or lines available
• Comparison Matrix
  Gene Expression + Phenotype

Homozygous null mutation of this gene results in a reduction of total cholesterol, HDL cholesterol, free fatty acids, insulin, and glucose levels in both the fasted and unfasted states. Strain specific alleles have been associated with varying degrees of amyloidosis.

Gene Ontology
(GO)
Classifications

• All GO Annotations
  81
• GO References
  15

Expression

• Assay Results
  865
• Tissues
  103
• cDNA Data
  429
• Literature Summary
  13

Images

Tissue x Stage Matrix

Comparison Matrix

Gene Expression + Phenotype

• Other Mouse Links
  Allen Institute
  GEO
  Expression Atlas

Interactions

• Apoa2 interacts with 6 markers (Mir93, Mir194-2, Mir325, ...) View All

Sequences &
Gene Models

• All Sequences
  54
• RefSeq
  9
• UniProt
  2
• CCDS
  CCDS35773.1

• Ensembl
  ENSMUSG00000005681 (Evidence)
• NCBI Gene
  11807

Representative Sequences			Length	Strain/Species
genomic	ENSMUSG00000005681	Ensembl Gene Model | MGI Sequence Detail	1326	C57BL/6J
transcript	ENSMUST00000111321	Ensembl | MGI Sequence Detail	518	Not Applicable
polypeptide	ENSMUSP00000106953	Ensembl | MGI Sequence Detail	102	Not Applicable

Protein
Information

• UniProt
  2 Sequences
• Protein Ontology
  PR:000004142 apolipoprotein A-II
  (term hierarchy)
• InterPro Domains
  IPR006801 Apolipoprotein A-II (ApoA-II)
  IPR036172 Apolipoprotein A-II (ApoA-II) superfamily

Molecular
Reagents

• All nucleic 442

  Genomic 5

  cDNA 431

  Primer pair 4

  Other 2

  
  

  Microarray probesets 3

Other
Accession IDs

MGD-MRK-10688, MGD-MRK-1289, MGD-MRK-1365, MGD-MRK-1368

References

• Summaries
  All 158

  Developmental Gene Expression 13

  Gene Ontology 15

  Phenotypes 43
• Earliest
  J:7017 Lusis AJ, et al., Genetic control of lipid transport in mice. II. Genes controlling structure of high density lipoproteins. J Biol Chem. 1983 Apr 25;258(8):5071-8
• Latest
  J:322813 Cui X, et al., Exercise suppresses mouse systemic AApoAII amyloidosis through enhancement of the p38 MAPK signaling pathway. Dis Model Mech. 2022 Mar 1;15(3):dmm049327

TSS for Apoa2:

(View these features in JBrowse)

Transcription Start Site	Location	Distance from Gene 5'-end
Tssr9986	Chr1:171052646-171052669 (+)	35 bp
Tssr9987	Chr1:171052839-171052901 (+)	247 bp
Tssr9988	Chr1:171053231-171053279 (+)	632 bp
Tssr9989	Chr1:171053280-171053320 (+)	677 bp
Tssr9990	Chr1:171053322-171053336 (+)	706 bp
Tssr9991	Chr1:171053729-171053751 (+)	1,117 bp
Tssr9992	Chr1:171053842-171053866 (+)	1,231 bp

Apoa2 is Candidate Gene for:

QTL	Genetic Location*	Genome Location (GRCm39)	Reference	QTL Note
Cq2	Chr1, 81.08 cM	Chr1:174456299-174456436	J:99474	Linkage analysis was performed on 3 separate F2 crosses in 3 previous studies: J: 54322, J:87328 and J:94251 to map QTLs associated with plasma cholesterol levels. Cq1, Cq2, and Cq6 mapped to mouse Chromosome 1, Cq3 mapped to mouse Chromosome 3, and Cq4 and Cq5 mapped to mouse Chromosome 9. Cq2 and Cq6 map to the same location on distal mouse Chromosome 1 at approximately 100 cM. Cq2 was identified in a (C57BL/6J x KK-A)F2 intercross and Cq6 was identified in a (C57BL/6J x RR)F2 intercross. Apoa2 wasinvestigated as a possible candidate gene. The Apoa2 allele is found in KK and RR strains and is associated with increased cholesterol levels while inbred strain C57BL/6J carries the Apoa2 allele. It is thought that the Apoa2 allele may be responsible for the QTL effects of Cq2 and Cq6. Inbred strains A/J and SM/J carry the Apoa2 allele. It was previously unknown whether the Apoa2 and Apoa2 alleles had the same or different influences on plasma cholesterol level. An F2 intercross between congenic strains C57BL/6J-Apoa2 and C57BL/6J-Apoa2 revealed no physiological differences between the Apoa2 and Apoa2 alleles. Therefore, the Apoa2 allele confers increased plasma cholesterol compared to the Apoa2 and Apoa2 alleles. Cq4 and Cq5 map to the same location on mouse Chromosome 9 at approximately 27 cM and Apoa1 and Apoa4 were investigated as possible candidate genes. Cq4 was identified in a (C57BL/6J x KK-A)F2 intercross and Cq5 was identified in a (KK x RR)F2 intercross. Sequence analysis of Apoa1 revealed that polymorphic differences between the involved strains did not correlate to cholesterol phenotype. Analysis of Apoa4 revealed a silent polymorphism (C771T) that exhibits complete correlation to cholesterol phenotype. Inbred strain KK carries the T allele whereas inbred strain C57BL/6J and RR carry the C allele. Another polymorphism in Apoa4 was detected involving a 12 nucleotide insertion encoding Glu-Gln-Ala/Val-Gln. Inbred strain KK carries 3 repeats, inbred strain C57BL/6J carries 4 repeats, and inbred strain RR carries 5 repeats. However, it could not be determined if this particular polymorphism explains the QTL effect of Cq4 and Cq5 on cholesterol levels.
Cq6	Chr1, 80.33 cM		J:99474	Linkage analysis was performed on 3 separate F2 crosses in 3 previous studies: J: 54322, J:87328 and J:94251 to map QTLs associated with plasma cholesterol levels. Cq1, Cq2, and Cq6 mapped to mouse Chromosome 1, Cq3 mapped to mouse Chromosome 3, and Cq4 and Cq5 mapped to mouse Chromosome 9. Cq2 and Cq6 map to the same location on distal mouse Chromosome 1 at approximately 100 cM. Cq2 was identified in a (C57BL/6J x KK-A)F2 intercross and Cq6 was identified in a (C57BL/6J x RR)F2 intercross. Apoa2 wasinvestigated as a possible candidate gene. The Apoa2 allele is found in KK and RR strains and is associated with increased cholesterol levels while inbred strain C57BL/6J carries the Apoa2 allele. It is thought that the Apoa2 allele may be responsible for the QTL effects of Cq2 and Cq6. Inbred strains A/J and SM/J carry the Apoa2 allele. It was previously unknown whether the Apoa2 and Apoa2 alleles had the same or different influences on plasma cholesterol level. An F2 intercross between congenic strains C57BL/6J-Apoa2 and C57BL/6J-Apoa2 revealed no physiological differences between the Apoa2 and Apoa2 alleles. Therefore, the Apoa2 allele confers increased plasma cholesterol compared to the Apoa2 and Apoa2 alleles. Cq4 and Cq5 map to the same location on mouse Chromosome 9 at approximately 27 cM and Apoa1 and Apoa4 were investigated as possible candidate genes. Cq4 was identified in a (C57BL/6J x KK-A)F2 intercross and Cq5 was identified in a (KK x RR)F2 intercross. Sequence analysis of Apoa1 revealed that polymorphic differences between the involved strains did not correlate to cholesterol phenotype. Analysis of Apoa4 revealed a silent polymorphism (C771T) that exhibits complete correlation to cholesterol phenotype. Inbred strain KK carries the T allele whereas inbred strain C57BL/6J and RR carry the C allele. Another polymorphism in Apoa4 was detected involving a 12 nucleotide insertion encoding Glu-Gln-Ala/Val-Gln. Inbred strain KK carries 3 repeats, inbred strain C57BL/6J carries 4 repeats, and inbred strain RR carries 5 repeats. However, it could not be determined if this particular polymorphism explains the QTL effect of Cq4 and Cq5 on cholesterol levels.
Hdlq20	Chr1, 88.97 cM		J:133501	SNP analysis, mRNA microarray analysis and protein expression difference analysis were used to narrow the QTL intervals of 9 previously identified QTLs for HDL cholesterol (Hdlq1, Hdlq20, Hdlq24), gallstone susceptibility (Lith17, Lith19, Lith21) and obesity (Obwq3, Obwq4, Obwq5). This methodology identified a manageable list of potential candidate genes for each QTL. A panel of 130,000 SNPs for SM/J and NZB/BlNJ reduced the QTL intervals by 40%-72%. Liver mRNA analysis identified 10 genes differentially expressed between SM/J and NZB/BlNJ strains and this finding was confirmed using TaqMan RT-PCR assays. Mass spectrometry analysis of liver proteins identified 45 proteins displaying differential expression between SM/J andNZB/BlNJ. On mouse Chromosome 1, Apoa2 (92.6 cM), Fh1, and Hsd11b1 were identified as potential candidate genes for Hdlq20 at 96 cM. Apoa2 was identified based on protein expression and SNP coding sequence differences. Apoa2 displays up-regulation in NZB/BlNJ liver proteins comparedto SM/J. Fh1 displays gene coding sequence differences and decreased protein expression in NZB/BlNJ livers compared to SM/J. Hsd11b1 was identified based on decreased protein expression in NZB/BlNJ. On mouse Chromosome 5, Acads (65 cM) and Scarb1 (68 cM)were identified as potential candidate genes for Hdlq1 (70 cM) and Lith17 (60 cM). Acads was identified on the basis of decreased protein expression in NZB/BlNJ livers compared to SM/J, as well as coding sequence differences. Scarb1 displays coding regionsequence differences and decreased liver mRNA expression in NZB/BlNJ. Scarb1 is located more closely to Hdlq1 and decreased Scarb1 mRNA expression was observed for this QTL. On mouse Chromosome 6, Pparg (52.7 cM), Rassf4 and Adipor2 (60.7 cM) were identified as potential candidate genes for Hdlq24 (66 cM) and Obwq3 (42 cM). Pparg displays coding sequences differences between NZB/BlNJ and SM/J while Rassf4 displays decreased liver mRNA expression in NZB/BlNJ animals. Adipor2 displays increased liver mRNAexpression in NZB/BlNJ and gene coding sequence differences. Ndufa9 was identified as a QTL for Hdlq24 on the basis of decreased liver protein expression in NZB/BlNJ and coding sequence differences. On mouse Chromosome 8,Slc10a2 (2 cM) was identifiedas a potential candidate gene for Lith19 (0 cM) on the basis of increased liver mRNA expression in NZB/BlNJ animals compared to SM/J. On mouse Chromosome 10, Ctgf (17 cM) was identified as a potential candidate gene for Lith21 (24 cM)on the basis of decreased liver mRNA expression in NZB/BlNJ animals compared to SM/J and gene coding sequences differences. On mouse Chromosome 17, Pgc (30 cM) was identified as a potential candidate for Obwq4 (32 cM).Pgc displays coding sequence differences between NZB/BlNJ and SM/J. Atrnl1 was identified as a candidate for Obwq5 (52 cM) on chromosome 19. Atrnl1 displays increased liver mRNA expression in NZB/BlNJ animals compared to SM/J.
Insq2	Chr1, syntenic		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Insq6	Chr1, 38.01 cM	Chr1:73726922-73727077	J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Nidd6	Chr1, 65.11 cM		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Obq2	Chr1, 6.50 cM	Chr1:20941620-20941887	J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Obq7	Chr1, 33.31 cM		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Obq9	Chr1, 74.68 cM		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Wt6q1	Chr1, syntenic		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.
Wt6q2	Chr1, syntenic		J:99477	Authors used novel data mining tool ExQuest to identify novel candidate genes for existing diabesity QTLs. Next, candidate gene expression in the liver, adipose, and pancreas of diabesity-prone Tally Ho mice and diabesity-resistant C57BL/6J mice was assessed by quantitative PCR analysis. Several potential candidate genes, some with no previous association to diabesity QTLs, were identified. Since QTL intervals may be large and could contain hundreds or thousands of potential candidate genes, this method allows researchers to focus on those with strong potential as well as identify novel candidate genes. A potential candidate gene for Obq2 at 15 cM on mouse Chromosome 1 as identified by ExQuest is Gsta3. For QTLs Obq7 (28.7 cM), Wt6q1 (27 cM), Insq2 (36cM), and Insq6 (37 cM), potential candidate genes Aox1 (23.2 cM), Fn1 (36.1 cM), Pecr, Igfbp2 (36.1 cM), Plcd4 (39.2 cM), Scg2 (43.6 cM), Irs1, and Inpp5d (57 cM) were identified. For QTL Nidd6 (77 cM), potential candidate gene Qscn6 was identified. For QTL Obq9 (88.4 cM), potential candidate genes Fmo1, Fmo3, and Apoa2 (92.6 cM) were identified. For QTL Wt6q2 (108 cM), potential candidate gene Hsd11b1 was identified.

*cM position of peak correlated region/marker