Additional file 6: of A modular analysis of microglia gene expression, insights into the aged phenotype

Additional file 1: Figure S1. of Transcriptome sequencing reveals that LPS-triggered transcriptional responses in established microglia BV2 cell lines are poorly representative of primary microglia

Amitabh Das (712672)
Sun Kim (28274)
Sarder Arifuzzaman (3455846)
Taeho Yoon (3329025)
Jin Chai (183630)
Young Lee (101856)
Kyoung Park (3455837)
Kyoung Jung (3455843)
Young Chai (3455840)

July 2016

Morphology and quantification of CD11b-positive microglial cells. (A) Photomicrographs are represent...

Additional file 6: of Genetic risk for Alzheimer’s disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Figure S1. Open chromatin regions (OCRs) identified in macrophages and microglia at Alzheimer’s dise...

Additional file 3: of Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma

Verena Haage (6339722)
Marcus Semtner (249048)
Ramon Vidal (2619952)
Daniel Hernandez (3952946)
Winnie Pong (6339725)
Zhihong Chen (38223)
Dolores Hambardzumyan (206665)
Vincent Magrini (55436)
Amy Ly (277577)
Jason Walker (469626)
Elaine Mardis (816997)
Philipp Mertins (554706)
Sascha Sauer (271148)
Helmut Kettenmann (214707)
David Gutmann (6339728)

February 2019

Figure S3. Validation of SGmic and SGmac genes in microglia and peripheral monocytes/macrophages fre...

Additional file 5: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Figure S1 Flow cytometry shows enrichment of CD45low cells in Cd11b-MACS samples. (A) Flow cytometry...

Additional file 1: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S1 List of conditions used in microglia stimulus panel. Table containing stimulus identity, su...

Additional file 2: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S2 Number of replicates in each stimulus condition. Table showing the number of biological rep...

Additional file 3: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S3 Lists of genes in each module. Each column shows the full list of genes in a given module. ...

Additional file 2: of RNAseq analysis of hippocampal microglia after kainic acid-induced seizures

Dale Bosco (5431751)
Jiaying Zheng (5431754)
Zhiyan Xu (1945468)
Jiyun Peng (4686358)
Ukpong Eyo (5431757)
Ke Tang (39453)
Cheng Yan (406565)
Jun Huang (127297)
Lijie Feng (3412118)
Gongxiong Wu (5431748)
Jason Richardson (232863)
Hui Wang (30400)
Long-Jun Wu (47043)

June 2018

Figure S1. Expression profiles of microglia specific markers. The expression of microglia specific m...

Additional file 1: of Genome-wide RNAseq study of the molecular mechanisms underlying microglia activation in response to pathological tau perturbation in the rTg4510 tau transgenic animal model

Hong Wang (13528)
Yupeng Li (507508)
John Ryder (6092906)
Justin Hole (6092909)
Philip Ebert (6092912)
David Airey (513432)
Hui-Rong Qian (18854)
Benjamin Logsdon (3491201)
Alice Fisher (6092915)
Zeshan Ahmed (6092918)
Tracey Murray (5632871)
Annalisa Cavallini (6092921)
Suchira Bose (6092924)
Brian Eastwood (6092927)
David Collier (231300)
Jeffrey Dage (729068)
Bradley Miller (1869454)
Kalpana Merchant (6092930)
Michael O’Neill (2179246)
Ronald Demattos (6092933)

December 2018

Figure S1. Microglia isolation from adult mouse brain and validation by q-RT-PCR and FACS analysis. ...

Additional file 4: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S4 Gene Ontology (GO) terms associated with each module. Columns show the GO term and correspo...

Additional file 1: of Proteomic analysis of aged microglia: shifts in transcription, bioenergetics, and nutrient response

Antwoine Flowers (3999608)
Harris Bell-Temin (1964092)
Ahmad Jalloh (3999611)
Stanley Stevens (2496859)
Paula Bickford (46386)

May 2017

Table S1. Differentially expressed proteins used for bioinformatic analysis (Studentâs t test only...

Additional file 1: of TMEM106B haplotypes have distinct gene expression patterns in aged brain

Yingxue Ren (5107256)
Marka van Blitterswijk (119410)
Mariet Allen (160001)
Minerva Carrasquillo (417900)
Joseph Reddy (1742365)
Xue Wang (102830)
Thomas Beach (559420)
Dennis Dickson (417904)
Nilüfer Ertekin-Taner (160094)
Yan Asmann (217921)
Rosa Rademakers (85403)

July 2018

Table S1. Tissue samples available and selected for inclusion in this study. Table S2. DEGS in TCX. ...

Additional file 1: of Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma

Verena Haage (6339722)
Marcus Semtner (249048)
Ramon Vidal (2619952)
Daniel Hernandez (3952946)
Winnie Pong (6339725)
Zhihong Chen (38223)
Dolores Hambardzumyan (206665)
Vincent Magrini (55436)
Amy Ly (277577)
Jason Walker (469626)
Elaine Mardis (816997)
Philipp Mertins (554706)
Sascha Sauer (271148)
Helmut Kettenmann (214707)
David Gutmann (6339728)

February 2019

Figure S1.. Expression levels of selected differentially expressed macrophage marker genes after hie...

Additional file 5: of Development and validation of a simplified method to generate human microglia from pluripotent stem cells

Amanda McQuade (6113636)
Morgan Coburn (6113639)
Christina Tu (6113642)
Jonathan Hasselmann (6113645)
Hayk Davtyan (86332)
Mathew Blurton-Jones (3537701)

December 2018

Table S2. Differential expression analysis of iPS-microglia versus iPS-microglia2.0. (XLSX 80 kb

Additional file 6: of Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimerâs disease

Srikant Rangaraju (4174204)
Eric Dammer (4174213)
Syed Raza (4174210)
Priyadharshini Rathakrishnan (5245535)
Hailian Xiao (36120)
Tianwen Gao (262800)
Duc Duong (4174198)
Michael Pennington (1343655)
James Lah (3504050)
Nicholas Seyfried (3504065)
Allan Levey (3504062)

May 2018

Table S6. Top AD risk genes in Blue, Magenta and Yellow AD-associated microglial modules. (XLSX 22Â ...

Additional file 1: Figure S1. of Transcriptome sequencing reveals that LPS-triggered transcriptional responses in established microglia BV2 cell lines are poorly representative of primary microglia

Amitabh Das (712672)
Sun Kim (28274)
Sarder Arifuzzaman (3455846)
Taeho Yoon (3329025)
Jin Chai (183630)
Young Lee (101856)
Kyoung Park (3455837)
Kyoung Jung (3455843)
Young Chai (3455840)

July 2016

Morphology and quantification of CD11b-positive microglial cells. (A) Photomicrographs are represent...

Additional file 6: of Genetic risk for Alzheimer’s disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Figure S1. Open chromatin regions (OCRs) identified in macrophages and microglia at Alzheimer’s dise...

Additional file 3: of Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma

Verena Haage (6339722)
Marcus Semtner (249048)
Ramon Vidal (2619952)
Daniel Hernandez (3952946)
Winnie Pong (6339725)
Zhihong Chen (38223)
Dolores Hambardzumyan (206665)
Vincent Magrini (55436)
Amy Ly (277577)
Jason Walker (469626)
Elaine Mardis (816997)
Philipp Mertins (554706)
Sascha Sauer (271148)
Helmut Kettenmann (214707)
David Gutmann (6339728)

February 2019

Figure S3. Validation of SGmic and SGmac genes in microglia and peripheral monocytes/macrophages fre...

Additional file 5: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Figure S1 Flow cytometry shows enrichment of CD45low cells in Cd11b-MACS samples. (A) Flow cytometry...

Additional file 1: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S1 List of conditions used in microglia stimulus panel. Table containing stimulus identity, su...

Additional file 2: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S2 Number of replicates in each stimulus condition. Table showing the number of biological rep...

Additional file 3: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S3 Lists of genes in each module. Each column shows the full list of genes in a given module. ...

Additional file 2: of RNAseq analysis of hippocampal microglia after kainic acid-induced seizures

Dale Bosco (5431751)
Jiaying Zheng (5431754)
Zhiyan Xu (1945468)
Jiyun Peng (4686358)
Ukpong Eyo (5431757)
Ke Tang (39453)
Cheng Yan (406565)
Jun Huang (127297)
Lijie Feng (3412118)
Gongxiong Wu (5431748)
Jason Richardson (232863)
Hui Wang (30400)
Long-Jun Wu (47043)

June 2018

Figure S1. Expression profiles of microglia specific markers. The expression of microglia specific m...

Additional file 1: of Genome-wide RNAseq study of the molecular mechanisms underlying microglia activation in response to pathological tau perturbation in the rTg4510 tau transgenic animal model

Hong Wang (13528)
Yupeng Li (507508)
John Ryder (6092906)
Justin Hole (6092909)
Philip Ebert (6092912)
David Airey (513432)
Hui-Rong Qian (18854)
Benjamin Logsdon (3491201)
Alice Fisher (6092915)
Zeshan Ahmed (6092918)
Tracey Murray (5632871)
Annalisa Cavallini (6092921)
Suchira Bose (6092924)
Brian Eastwood (6092927)
David Collier (231300)
Jeffrey Dage (729068)
Bradley Miller (1869454)
Kalpana Merchant (6092930)
Michael O’Neill (2179246)
Ronald Demattos (6092933)

December 2018

Figure S1. Microglia isolation from adult mouse brain and validation by q-RT-PCR and FACS analysis. ...

Additional file 4: of A modular analysis of microglia gene expression, insights into the aged phenotype

Christine Cho (1749574)
Sagar Damle (4766640)
Edward Wancewicz (6414020)
Swagatam Mukhopadhyay (434948)
Christopher Hart (6414023)
Curt Mazur (185224)
Eric Swayze (6414026)
Fredrik Kamme (6414029)

March 2019

Table S4 Gene Ontology (GO) terms associated with each module. Columns show the GO term and correspo...

Additional file 1: of Proteomic analysis of aged microglia: shifts in transcription, bioenergetics, and nutrient response

Antwoine Flowers (3999608)
Harris Bell-Temin (1964092)
Ahmad Jalloh (3999611)
Stanley Stevens (2496859)
Paula Bickford (46386)

May 2017

Table S1. Differentially expressed proteins used for bioinformatic analysis (Studentâs t test only...

Additional file 1: of TMEM106B haplotypes have distinct gene expression patterns in aged brain

Yingxue Ren (5107256)
Marka van Blitterswijk (119410)
Mariet Allen (160001)
Minerva Carrasquillo (417900)
Joseph Reddy (1742365)
Xue Wang (102830)
Thomas Beach (559420)
Dennis Dickson (417904)
Nilüfer Ertekin-Taner (160094)
Yan Asmann (217921)
Rosa Rademakers (85403)

July 2018

Table S1. Tissue samples available and selected for inclusion in this study. Table S2. DEGS in TCX. ...

Additional file 1: of Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma

Verena Haage (6339722)
Marcus Semtner (249048)
Ramon Vidal (2619952)
Daniel Hernandez (3952946)
Winnie Pong (6339725)
Zhihong Chen (38223)
Dolores Hambardzumyan (206665)
Vincent Magrini (55436)
Amy Ly (277577)
Jason Walker (469626)
Elaine Mardis (816997)
Philipp Mertins (554706)
Sascha Sauer (271148)
Helmut Kettenmann (214707)
David Gutmann (6339728)

February 2019

Figure S1.. Expression levels of selected differentially expressed macrophage marker genes after hie...

Additional file 5: of Development and validation of a simplified method to generate human microglia from pluripotent stem cells

Amanda McQuade (6113636)
Morgan Coburn (6113639)
Christina Tu (6113642)
Jonathan Hasselmann (6113645)
Hayk Davtyan (86332)
Mathew Blurton-Jones (3537701)

December 2018

Table S2. Differential expression analysis of iPS-microglia versus iPS-microglia2.0. (XLSX 80 kb

Additional file 6: of Identification and therapeutic modulation of a pro-inflammatory subset of disease-associated-microglia in Alzheimerâs disease

Srikant Rangaraju (4174204)
Eric Dammer (4174213)
Syed Raza (4174210)
Priyadharshini Rathakrishnan (5245535)
Hailian Xiao (36120)
Tianwen Gao (262800)
Duc Duong (4174198)
Michael Pennington (1343655)
James Lah (3504050)
Nicholas Seyfried (3504065)
Allan Levey (3504062)

May 2018

Table S6. Top AD risk genes in Blue, Magenta and Yellow AD-associated microglial modules. (XLSX 22Â ...

Additional file 1: Figure S1. of Transcriptome sequencing reveals that LPS-triggered transcriptional responses in established microglia BV2 cell lines are poorly representative of primary microglia

Amitabh Das (712672)
Sun Kim (28274)
Sarder Arifuzzaman (3455846)
Taeho Yoon (3329025)
Jin Chai (183630)
Young Lee (101856)
Kyoung Park (3455837)
Kyoung Jung (3455843)
Young Chai (3455840)

July 2016

Morphology and quantification of CD11b-positive microglial cells. (A) Photomicrographs are represent...

Additional file 6: of Genetic risk for Alzheimer’s disease is concentrated in specific macrophage and microglial transcriptional networks

Katherine Tansey (4889533)
Darren Cameron (4889530)
Matthew Hill (394308)

February 2018

Figure S1. Open chromatin regions (OCRs) identified in macrophages and microglia at Alzheimer’s dise...

Additional file 3: of Comprehensive gene expression meta-analysis identifies signature genes that distinguish microglia from peripheral monocytes/macrophages in health and glioma

Verena Haage (6339722)
Marcus Semtner (249048)
Ramon Vidal (2619952)
Daniel Hernandez (3952946)
Winnie Pong (6339725)
Zhihong Chen (38223)
Dolores Hambardzumyan (206665)
Vincent Magrini (55436)
Amy Ly (277577)
Jason Walker (469626)
Elaine Mardis (816997)
Philipp Mertins (554706)
Sascha Sauer (271148)
Helmut Kettenmann (214707)
David Gutmann (6339728)

February 2019

Figure S3. Validation of SGmic and SGmac genes in microglia and peripheral monocytes/macrophages fre...

Additional file 6: of A modular analysis of microglia gene expression, insights into the aged phenotype

Abstract

Extracted data

Additional file 6: of A modular analysis of microglia gene expression, insights into the aged phenotype

Abstract

Extracted data

Related items

Related items