This gene set describes genes that are up-regulated in blood of children with COVID-19, the disease caused by SARS-CoV2, versus healthy controls using RNAseq analysis. These children did not have MIS-C. The genes were filtered for a p-value < 0.05 and a log fold-change of greater than 1.0 given in supplemental table 7. Genes were entered into GeneWeaver using the reported EnsEMBL identifiers. Values are log-fold change.
Authors:
Noam D Beckmann, Phillip H Comella, Esther Cheng, Lauren Lepow, Aviva G Beckmann, Scott R Tyler, Konstantinos Mouskas, Nicole W Simons, Gabriel E Hoffman, Nancy J Francoeur, Diane Marie Del Valle, Gurpawan Kang, Anh Do, Emily Moya, Lillian Wilkins, Jessica Le Berichel, Christie Chang, Robert Marvin, Sharlene Calorossi, Alona Lansky, Laura Walker, Nancy Yi, Alex Yu, Jonathan Chung, Matthew Hartnett, Melody Eaton, Sandra Hatem, Hajra Jamal, Alara Akyatan, Alexandra Tabachnikova, Lora E Liharska, Liam Cotter, Brian Fennessy, Akhil Vaid, Guillermo Barturen, Hardik Shah, Ying-Chih Wang, Shwetha Hara Sridhar, Juan Soto, Swaroop Bose, Kent Madrid, Ethan Ellis, Elyze Merzier, Konstantinos Vlachos, Nataly Fishman, Manying Tin, Melissa Smith, Hui Xie, Manishkumar Patel, Kai Nie, Kimberly Argueta, Jocelyn Harris, Neha Karekar, Craig Batchelor, Jose Lacunza, Mahlet Yishak, Kevin Tuballes, Ieisha Scott, Arvind Kumar, Suraj Jaladanki, Charuta Agashe, Ryan Thompson, Evan Clark, Bojan Losic, Lauren Peters, , Panagiotis Roussos, Jun Zhu, Wenhui Wang, Andrew Kasarskis, Benjamin S Glicksberg, Girish Nadkarni, Dusan Bogunovic, Cordelia Elaiho, Sandeep Gangadharan, George Ofori-Amanfo, Kasey Alesso-Carra, Kenan Onel, Karen M Wilson, Carmen Argmann, Supinda Bunyavanich, Marta E Alarcón-Riquelme, Thomas U Marron, Adeeb Rahman, Seunghee Kim-Schulze, Sacha Gnjatic, Bruce D Gelb, Miriam Merad, Robert Sebra, Eric E Schadt, Alexander W Charney
This gene set describes genes that are up-regulated in children with Multisystem inflammatory Syndrome in Children (MISC-C) versus healthy controls using RNAseq analysis. The genes were filtered for a p-value < 0.05 and a log fold-change of greater than 1.0 given in supplemental table 7. Genes were entered into GeneWeaver using the reported EnsEMBL identifiers. Values are log-fold change.
Authors:
Noam D Beckmann, Phillip H Comella, Esther Cheng, Lauren Lepow, Aviva G Beckmann, Scott R Tyler, Konstantinos Mouskas, Nicole W Simons, Gabriel E Hoffman, Nancy J Francoeur, Diane Marie Del Valle, Gurpawan Kang, Anh Do, Emily Moya, Lillian Wilkins, Jessica Le Berichel, Christie Chang, Robert Marvin, Sharlene Calorossi, Alona Lansky, Laura Walker, Nancy Yi, Alex Yu, Jonathan Chung, Matthew Hartnett, Melody Eaton, Sandra Hatem, Hajra Jamal, Alara Akyatan, Alexandra Tabachnikova, Lora E Liharska, Liam Cotter, Brian Fennessy, Akhil Vaid, Guillermo Barturen, Hardik Shah, Ying-Chih Wang, Shwetha Hara Sridhar, Juan Soto, Swaroop Bose, Kent Madrid, Ethan Ellis, Elyze Merzier, Konstantinos Vlachos, Nataly Fishman, Manying Tin, Melissa Smith, Hui Xie, Manishkumar Patel, Kai Nie, Kimberly Argueta, Jocelyn Harris, Neha Karekar, Craig Batchelor, Jose Lacunza, Mahlet Yishak, Kevin Tuballes, Ieisha Scott, Arvind Kumar, Suraj Jaladanki, Charuta Agashe, Ryan Thompson, Evan Clark, Bojan Losic, Lauren Peters, , Panagiotis Roussos, Jun Zhu, Wenhui Wang, Andrew Kasarskis, Benjamin S Glicksberg, Girish Nadkarni, Dusan Bogunovic, Cordelia Elaiho, Sandeep Gangadharan, George Ofori-Amanfo, Kasey Alesso-Carra, Kenan Onel, Karen M Wilson, Carmen Argmann, Supinda Bunyavanich, Marta E Alarcón-Riquelme, Thomas U Marron, Adeeb Rahman, Seunghee Kim-Schulze, Sacha Gnjatic, Bruce D Gelb, Miriam Merad, Robert Sebra, Eric E Schadt, Alexander W Charney
Data from GEO GSE194368 and analyzed using GEO2R, only top gene shown. Authors identified transcriptional adaptations of GR signaling in the amygdala of humans with OUD. Thus, GRs, their coregulators and downstream systems may represent viable therapeutic targets to treat the “stress side” of OUD.
Authors:
Stephanie A Carmack, Janaina C M Vendruscolo, M Adrienne McGinn, Jorge Miranda-Barrientos, Vez Repunte-Canonigo, Gabriel D Bosse, Daniele Mercatelli, Federico M Giorgi, Yu Fu, Anthony J Hinrich, Francine M Jodelka, Karen Ling, Robert O Messing, Randall T Peterson, Frank Rigo, Scott Edwards, Pietro P Sanna, Marisela Morales, Michelle L Hastings, George F Koob, Leandro F Vendruscolo
This gene set comprises 239 genes that are differentially expressed within each of five brain regions (amygdala, hippocampus, nucleus accumbens, prefrontal cortex and ventral tegmental area) when chronic nicotine treatment is administered to C57BL/6J mice only. Background: Studies involving use of chronic nicotine treatment identify unique nicotine addiction genes and the biological processes they control in B6 and C3 mice. Results are obtained using gene expression profiling and gene ontology.
Authors:
Wang J, Gutala R, Hwang YY, Kim JM, Konu O, Ma JZ, Li MD
This gene set comprises 25 genes that are downregulated within each of five brain regions (amygdale (Amyg), hippocampus (HP), nucleus accumbens (NA), prefrontal cortex (PFC) and ventral tegmental area (VTA)) when chronic nicotine treatment is administered to C57BL/6J mice only. Background: Studies involving use of chronic nicotine treatment identify unique nicotine addiction genes and the biological processes they mediate in C3H/HeJ and C57BL/6J mice. Results are obtained using gene expression profiling via cDNA microarrays and gene ontology.
Authors:
Wang J, Gutala R, Hwang YY, Kim JM, Konu O, Ma JZ, Li MD
This gene set comprises 66 genes that are upregulated within each of five brain regions (amygdale, hippocampus, nucleus accumbens, prefrontal cortex and ventral tegmental area) when chronic nicotine treatment is administered to B6 mice only. Background: Studies involving chronic nicotine treatment identify unique nicotine addiction genes and the biological processes they mediate in C3 and B6 mice. Results are obtained using gene expression profiling via cDNA microarrays and gene ontology.
Authors:
Wang J, Gutala R, Hwang YY, Kim JM, Konu O, Ma JZ, Li MD
Neocortex Gene Expression Correlates for HIC_SCORE measured in BXD RI Males obtained using GeneNetwork Neocortex ILM6v1.1 (Feb08) RankInv. The HIC_SCORE measures Handling induced convulsion score under the domain Ethanol HIC. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
cocaine related behavior 14 (Cocrb14) spans 43.765096 - 93.765096 Mbp (NCBI Build 37) on Chr 15. Obtained from MGI (http://www.informatics.jax.org) by searching for QTLs containing the keyword .
cocaine related behavior 15 (Cocrb15) spans 70.807693 - 120.807693 Mbp (NCBI Build 37) on Chr 15. Obtained from MGI (http://www.informatics.jax.org) by searching for QTLs containing the keyword .
QTL for cocaine related behavior on Chr15 at D15Mit3 (83.88 Mbp , Build 37)
Description:
cocaine related behavior spans 58.88 - 108.88 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for alcohol consumption on Chr15 at D15Mit105 (87.33 Mbp , Build 37)
Description:
alcohol consumption spans 62.33 - 112.33 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
Authors:
Vadasz C, Saito M, Gyetvai B, Mikics E, Vadasz C 2nd
QTL for cocaine induced activation on Chr15 at NA (92.79 Mbp , Build 37)
Description:
cocaine induced activation spans 67.79 - 117.79 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for METH responses for home cage activity on Chr15 at D15Mit1 (93.20 Mbp , Build 37)
Description:
METH responses for home cage activity spans 68.20 - 118.20 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for cocaine related behavior on Chr15 at D15Ncvs29 (95.81 Mbp , Build 37)
Description:
cocaine related behavior spans 70.81 - 120.81 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for METH responses for home cage activity on Chr15 at Spt1 (102.87 Mbp , Build 37)
Description:
METH responses for home cage activity spans 77.87 - 127.87 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for cocaine seizure on Chr15 at D15Mit48 (105.10 Mbp , Build 37)
Description:
cocaine seizure spans 80.10 - 130.10 Mbp (NCBI Build 37) on Chr15. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
Chronic cocaine - Cocaine-paired (conditioned place preference) vs. Control (saline or cocaine-non-paired) DNA microarray All genes on microarray presented After the pre-conditioning phase where animals were allowed access to either compartment for 15 minutes for 4 consecutive days, the conditioning phase for the cocaine-paired groups and cocaine non-paired groups began, consisting of eight subsequent daily sessions. For both groups, cocaine (10 mg / kg) or saline injections were administered on alternate days. For the cocaine-paired groups, rats were immediately placed in one of the two compartments for 30 min with the door in place restricting a z transformation followed by z test and anova followed by Student-Newman-Keuls' post hoc test. Gene expression profile was assessed 24 h after the last conditioning session that corresponded to 48 h after last cocaine exposure, when drug has been eliminated from the body and transient transcriptional changes are likely to be minimal. Therefore, changes in gene expression at this time-point are likely to reflect longer lasting adaptations that may account for maintenance of cocaine-induced memories. The complete lists of normalized gene expression values for the hippocampus of saline-treated, cocaine non-paired and cocaine-paired groups are presented. Analyses revealed that 214 transcripts were differentially regulated in the hippocampus of cocaine-paired rats vs. non-paired and saline-treated controls. Cocaine-induced conditioned place preference caused significant increases in the expression of 151 genes and caused decreases in the expression of 63 genes. (NIF Table ID 130.1 [83])
Authors:
Krasnova IN, Li SM, Wood WH, McCoy MT, Prabhu VV, Becker KG, Katz JL, Cadet JL
Chronic cocaine - Cocaine-paired (conditioned place preference) vs. Control (saline or cocaine-non-paired) DNA microarray All genes on microarray presented After the pre-conditioning phase where animals were allowed access to either compartment for 15 minutes for 4 consecutive days, the conditioning phase for the cocaine-paired groups and cocaine non-paired groups began, consisting of eight subsequent daily sessions. For both groups, cocaine (10 mg / kg) or saline injections were administered on alternate days. For the cocaine-paired groups, rats were immediately placed in one of the two compartments for 30 min with the door in place restricting a z transformation followed by z test and anova followed by Student-Newman-Keuls' post hoc test. Gene expression profile was assessed 24 h after the last conditioning session that corresponded to 48 h after last cocaine exposure, when drug has been eliminated from the body and transient transcriptional changes are likely to be minimal. Therefore, changes in gene expression at this time-point are likely to reflect longer lasting adaptations that may account for maintenance of cocaine-induced memories. The complete lists of normalized gene expression values for the frontal cortex of saline-treated, cocaine non-paired and cocaine-paired groups are presented. Differences in the expression of 39 transcripts in the frontal cortex were related to the conditioned place preference paradigm. These include increases in the level of 22 genes and decreases in 17 genes. (NIF Table ID 130.3 [83.5])
Authors:
Krasnova IN, Li SM, Wood WH, McCoy MT, Prabhu VV, Becker KG, Katz JL, Cadet JL
Acute and chronic alcohol exposure was analyzed in 534 (C57BL/6J x C3H/HeJ)F2 mice. Behavioral testing was done using 5 traits, acute drug effect, forced ethanol drinking, withdrawal studies ethanol preference and stress induced ethanol drinking. The following QTL were found in a genome wide scan: Following the QTL is the Chromosome , cM location, and LOD score, Eih1 (Chr 1, 85 cM, LOD 6.6), Eih2 (Chr 7, 10 cM, LOD 3.6), Ceih1 (Chr 3, 55 cM, LOD 4.1), Ceih2 (Chr 6, 24.7 cM, LOD 4.1), Ceih3 (Chr 13, 39 cM, LOD 4.1), Eia1(Chr 1, 65 cM, LOD 10.3 and 10.4), Eiwa1 (Chr 7, 50 cM, LOD 4.4), Eiwa2(Chr 11, 43.1 cM, LOD 4.1),Aldd1(Chr 5, 42 cM, LOD 13.2), Aldd2(Chr 12, 18 cM, LOD 5.3),Eiwax1(Chr 1, 79 cM, LOD 6.5), Eiwax2(Chr 5, 59 cM, LOD 15.0), Eiwax3(Chr 12, 21 cM, LOD 3.6), Methp1(Chr 16, 31.4 cM, LOD 4.3), Mec1(Chr 16, 19.4 cM, LOD 5.1), Epbs1(Chr 16, 33 cM, LOD 4.1), Ecbs1(Chr 16, 29.4 cM, LOD 4.8), Mec2(Chr 1, 109 cM, LOD 3.9), Mec3(Chr 2, 109 cM, LOD 4.3), Mec4(Chr 5, 29 cM, LOD 3.9), Mec5(Chr 10, 2 cM, LOD 5.0), Mec6(Chr 15, 49 cM, LOD 5.2, 95% CI 6.7–56.7).
Authors:
Drews E, Rcz I, Lacava AD, Barth A, Bilkei-Gorz A, Wienker TF, Zimmer A
Ethanol Preference from BXD lines span 58586243-108586243. This interval was obtained by using an arbitrary interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org). Marker Loci associated with 10% Ethanol Preferences Drinking at p<0.05 (Two Tailed) in the BXD RI set and the Correlation Coefficient, p and Estimated LOD. D15Mit33 (83586243 NCBI 37) p=0.05, LOD=0.08 overall LOD BXD & Select Line 2.4.
QTL for Voluntary Ethanol Consumption on LS x SS RI lines spans 43765164-93765164 .This interval was obtained by using an arbitrary interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org). Chr 15 D15Mit3 39 cM VEC (females) 0.02
Authors:
Gehle VM, Erwin VG
Add Selected GeneSets to Project(s)
Warning: You are not signed in. Adding these genesets to a project will create a guest account for you.
Guest accounts are temporary, and will be removed within 24 hours of creation. Guest accounts can be registered as full accounts, but you cannot associate a guest account with an existing account.
If you already have an account, you should sign into that account before proceeding.