DOCSLIB.ORG

Supplementary Online Material Promoter-Anchored Chromatin

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Supplementary Online Material Promoter-Anchored Chromatin Supplementary Online Material Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data Wu et al. Contents Figure S1 to S8 Supplementary Note 1-2 References Figure S1 Schematic overview of this study. a b mean=3.7 mean=79 Kb median=2 median=23 Kb Count Count 0 1000 3000 5000 0 5000 10000 15000 0 5 10 15 20 25 >30 0 500 1000 1500 2000 No. interacting pairs Distance between interacting DNAm (Kb) Figure S2 Summary of the predicted PAIs. Panel a): distribution of the number of PIDSs (promoter interacting DNAm sites) for each bait probe (located in the promoter of a gene). Panel b): distribution of physical distances between pairwise interacting DNAm sites of the significant PAIs. Figure S3 Overlap of the predicted PAIs with TADs annotated from the Rao et al. 1 Hi-C data. Panel a): a heatmap of the predicted PAIs (red asterisks) and chromatin interactions with correlation score > 0.4 (blue dots) identified by Hi-C in a 1.38 Mb region on chromosome 6. Only 41.5% of the predicted PAIs in this region showed overlap with the TADs. This region harbours the RPS6KA2 locus as shown in Fig. 5. Panel b): a heatmap of the predicted PAIs (red asterisks) and chromatin interactions with correlation score > 0.4 (blue dots) identified by Hi-C in a 0.81 Mb region on chromosome 12. The predicted PAIs were highly consistent with the chromatin interactions identified by Hi-C. This region harbours the ABCB9 locus as shown in Fig. S4. The heatmap is asymmetric for the PAIs with the x- and y-axes representing the physical positions of “outcome” and “exposure” probes respectively. ) ) ) ) ) (ABCB9 (ABCB9 (ARL6IP4 (MPHOSPH9 (SBNO1 15 ILMN_2343048 ILMN_2343047 ILMN_2393144 ILMN_1654421 ILMN_1739943 ● ● ●● ● ● ● ●● SCZ ● ●● ● ● ● ●●●●●●●● ●●●●● ● ● ●● ●● ● ● ●● ● ● ● ●● ● ● ●● ●● ● ● ● ● ● 11 ● ●● ● ● ● ● ●● ●● ● ● ●●● ● ● ● ● ● ● ● ● ●●● ● ●● ●● ● ● ● ● ● ● ● ● ● ● ●● ●●● ● ●● ● ● ●● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ●● ● ● ● ● ● ●●●●●●●●●●●●●●●● ●●●●●● ●●● ●●●●●●●●●●●●● ● ● ● ●●●●●● ● ●● ●● ● ● ●● ●●● ●●● ●●●● ●●● ●●● ●● ● ● ● pMSMR = 5.52e−07 ● ● ● ●● ● ● ● ● ● ●●●●●●●●●●●● ●● ● ● ● 8 ● ● ●● ● ●●● ●●●●●●● ● ● ● ● ● ● ● ● ● ●●● ●● ● ● ● ● ● ●● ●●● ● ● ●●● ●●● ●● ● ● ●● ●●● ●● ●●● ●●●●● ●●● ●●●● ● ● ● ● ●● ● ●● ●●●●● ●●●●●●●●● ●● ●● ●●●● ●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●● ●●●●●●●●● ●●● ●●●●●●● ●● ● ● ●●● ● ●● ●● ● ● ● ● ●● ● ●● ●●●● ● ● ●● ● ●● ● ● ●●●● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ● ● ●● ● ● ● ● ● ● ●● ●● ●● ● ● ● ● ●●●●● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ● ●●●● ● ●● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ●● 4 ● ● ● ●● ● ● ● ●● ●● ●● ● ● ● ● ● ●● ● ● ● ●● ● ●● ● ●●● ●●●● ● ● ● ● ● ● ● ● ● ● ●● ● ● ●● ● ●● ●●● ●●● ●● ● ● ●● ● ● ● ●●●● ● ●●●●●● ●●● ● ●● ●●● ● ● pESMR● ● = 6.62e−05 ● ● ● ● ● ● ● ● ● ● ●●●●●●●● ●● ●● ●● ●● ●●●● ●●●● ● ●●● ● ●●●● ● ● ● ● ●●●●●● ● ●● ●● ●● ● ●● ● ● ●● ● ● ●● ● ● ● ●●●● ● ●●●●●●●●● ● ● ●● ●●● ●● ●● ●●●● ●●● ● ● ● ●● ●●●● ●●●●●●●●●●●● ●●●●●● ●● ●● ●●●●● ● ● ● ● ● ● ●● ●● ●● ● ●● ● ● ● ●●● ● ● ●● ● ● ●●●●●● ●●●●●●●●●● ●●●● ● ●●●●●● ●●● ●●●●●●●●●●●●●●●●●●●●●● ●●● ●●●● ●●●●●●●●●●●● ● ● ● ● ● ● ● ●●● ●● ●● ●●●●●● ●●●●● ●●●●●● ●● ●●●● ●●● ● ●● ●● ●● ● ●●●● ●●●● ● ●● ● ● ●● ● ● ● ● ● ●● ●● ● ● ● ●● ●●● ● ● ●● ●● ● ● ●●●● ●●●● ● ● ●● ● ●●● ● ● ●● ● ● ● ● ●● ● ● ● ● ●●●●●●● ●●●●● ●●●●●●●●● ●●●●●●●●●●●●●● ●●●● ●●● ●● ●● ● ● ●●● ●●●●● ● ●● ● ● ●●● ● ● ● ● ●● ●● ●● ● ● ● ●●● ● ● ●● ●● ● ●●● ● ● ● ● ● ●● ● ●● ●● ● ●● ● ●●●●●● ●●●●●●●●● ● ●●● ●●● ●●●●●●●●●●●●●●● 0 ●● ●● ● ● ● ● ● ●● ●● ● ● ● ● ● ● ● ●● ● ●●●● ●●●●●●●●●●● 17 GWAS or SMR) GWAS ●● ● ● ● ● ●● ●●● EY ●●●● ●●● ● ●●● ● ● ● ● ●● ● ●●● ● ● ● ● ● ● ●● ● ● ●●● ● ● ●● ● ●● ●●● ●● ● ●●●●●● ●●●● ●●●● ●● ● ● ●●●● ●● ● ● ● ●●● ● ● ●●●● ●●● ●● ●● ● P ● ● ●●●●●●●● ●● ●●●●●● ● ● ● ● ● ●● ● ●●●●● ●●● ●●●●●●● ●●● ●●●●●● ● ● ● ● ●● ● ● ●● ● ● ●●●● ●●● ● ● ( ●● ● ● ● ● ● ● ●● ●● ● ● ●● ● ● ● ● ●●● ● ● ● 13 ● ●●● ● ●●● ●● ● ● ●●● ● ● ● ● ●● ● ●● ● ● ● ●● ● ● ● ●●● ● ●●●●● ● ● ● ● ● ● ● ● 10 ● ● ● ●● ● ●●●● ● ● ● ● ● ●●● ●● ●● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ●●●● ● ● ● ● 8 ● ● ●● ● ●● ● ● pMSMR = 5.52e−07 ● ● ● ●● ● ● ● ● ● ● ●● ● ● ●● log ● ● ● ● ● ● ● ● ● ● ● ● − ● ● ● ● ● ● ● ● ● ● ● ● 4 ● ● ● ● ● ● ●●●●● ●●● ● ● ● ● ● ● ● ●● ●●● ● ● ● ● ● ● ● ●●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ●●● ● ● ● ● ●●● ● ● ● ● ● ●● ● ● ● ● ● ● ●●● ● ●● ● ● ● ● ● ●●●● ●●● ●●●●●●●● ●●● ●● ●●●●● ● ●● ● ● ● ●● ●● ●● ● ● ●●● ●●● ●● ●● ● ● ●●●● ● ●●● ● ● ● ● ● ● ● ● ●● ●● ● ● ●● ●●● ● ●●● ●●● ● ●●●●●●●● ●●● ●●●● ●●● ● ●● ● ●● ● ●●●●●●● ● ●● ●● ● ●●●● ● ● ●pESMR●●●●●●●● ●●● = 6.62e−05 ● ● ● ● ● ● ● ●●● ● ●● ● ●● ● ● ● ●● ● ● ●●● ●●● ●● ● ●● ● ● ● ● ● ● ●● ● ● ● ●●● ● ●● ● ● ●●●● ●●●●●●●●●●●●●●●●●● ●●● ● ●●●● ●● ●● ●● ●●●● ●●● ●●●● ●●● ●●●●●● ●●● ●● ●●●● ●●●●●●●● ●●●● ●●● ●●●●●●●●●●●●● ●●●● ●●● ●● ●●●●●●● ●●●●●●●●● ●●●●●●● ●●● ●● ●●● ●● ●●●● ●●● ● ●●● ●●●●●●●●●●● ●●●●●●●●●●●●●●● ● ●●●● ● ●●●●●● ●●● ● ● ●●● ● ● ● ● ● ●● ● ● ●● ● ● ●● ●● ● ●●● ●●● ● ● ● ●●●●●●●●● ●●●●●●●●● ●●●●● ●●●●●●●●●●●●●●● ●●●●●●●●● ●●●●●●●● ●●●●●●●●●● ●●●● ● ● ●● ●●●●●●●●● ● ●●●●● ● ●●●● ●● ●●●● 0 ●●●●●●●●●●●●●● ●● ●●● ● ●● ●●●●●●●● ●●●● ●●●●●●●●●●●●●●● ●●● ●●● ●●●●● ● ●● ●●●●● ●●●●●●● ● ●●● ● ●● ●● ●●● ●●●●● ● ●●●●● ●●●● ●●● ●●● ●●●●● ●●● ●●●●●● ●●●●● ●● ● ●●● ● ● ●● ●●● ● ● ●●● ●●●●●●● ●●● ● ●●● ●●●● ●● ● ●●●●●● ●●● ● ● ● ●●●●●●● ● ●●●● ● ●●● ● ●● ●●● ●●●●●●●●● ● ●●●●●●●●●●●●●●●● 35 ILMN_2343048 (ABCB9) 23 12 eQTL) 0 P 30 ( ILMN_2393144 (ARL6IP4) 10 20 10 log 0 − 30 ILMN_1654421 (MPHOSPH9) 20 10 206 ●● ●●●●● ●●● ●●● ● ● ●● ●●● ●●● ●● ● ● ●●●●● ● ●● ● ● ●● ● ● ● cg13010344 ● ● ●●● ●● ●●●● ● ●●●●●●●●●●● ● ●● ● ●● ●● ●●●●● ●● ●●● ● 137 ● ● ● ● ●●●●●● ● ●●●●● ● ● ● ● ● ●●●● meQTL) ● ●●● ● ●●● ●● ● ●● ●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●● ● ●●●●●●●●●●●●●●●●●●● ●●●●●● ●●●●●●●●●●●●●● ●● ●● ● ●●● ● ● ● ● ● ●●●●●●●●●●● ●●●●●● ● ●● ●●●● ● ●● ●● ●●● ● ● ●●●● ●●●●● ● ●●●●●●●●● ●●●●●●●● ●●●● ● ● ●●●● ● ●●●● ● ● ●●● ● ● ● P 69 ● ● ● ● ● ● ● ● ● ● ● ● ●●● ●● ●● ●● ● ●●●●●●●●●●●●●● ● ●●● ●●●● ● ● ●●●●●●●●●●●●● ●●● ●● ● ●● ● ●● ●●● ●●●●● ●●●●●●●●●●●●●● ●●● ●●●●●●●●●●●●●●● ●●●●●● ●●●●●●●●●●●●●●●● ●●●● ●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●● ●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●●● ( 0 ●●●●●●●●●●●●●●●●●● ●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●● ●●●● ●●● ●●●● ● ●● ● ● ● ● ●● ●● ● ● ●● ●●●●●●●● ● ● ● ●●●●● ● ● ●● ● ● ●●●●●●●●● 10 log − ESC TssA iPSC Prom ES−deriv Tx Blood & T−cell TxWk HSC & B−cell TxEn Mesenchymal EnhA Epithelial EnhW Brain Quies Muscle DNase Heart ZNF/Rpts Digestive Het Other PromP PromBiv ENCODE ReprPC VPS37B ABCB9 LOC100507091 KMT5A OGFOD2 MPHOSPH9 RILPL2 ARL6IP4 C12orf65 SNRNP35 MIR4304 CDK2AP1 MIR8072 RILPL1 PITPNM2 SBNO1 Hi-C loop 123.32 123.48 123.64 123.80 123.96 124.13 Chromosome 12 Mb Figure S4 A shared PIDS region with eQTLs predicted to interact with the promoters of multiple genes (i.e., ABCB9, ARL6IP4, MPHOSPH9). The top two plots show -log10(P values) of SNPs from the GWAS meta-analyses (grey dots) for schizophrenia (SCZ) and educational years (EY). Red diamonds and blue circles represent -log10(P values) from SMR tests for associations of gene expression and DNAm with SCZ and EY, respectively. Solid diamonds and circles are the probes not rejected by the HEIDI test. The following three plots show -log10(P values) of SNP associations for the gene expression probes ILMN_2343048 (tagging ABCB9), ILMN_2393144 (tagging ARL6IP4), and ILMN_1654421 (tagging MPHOSPH9) from the CAGE study. The sixth plot shows -log10(P values) of SNP associations for the DNAm probe cg13010344 from the mQTL meta-analysis. The heatmap-like panel on the bottom shows the 14 REMC annotations with the significant PAIs annotated by orange curved lines on the top (see Fig. S3b for the overlap of the predicted PAIs with Hi-C data) and the Hi-C loop identified by Rao et al.1 annotated on the x-axis (two orange bars connected by a red curved line). ESC TssA iPSC Prom ES−deriv Tx Blood & T−cell TxWk HSC & B−cell TxEn Mesenchymal EnhA Epithelial EnhW Brain Quies Muscle DNase Heart ZNF/Rpts Digestive Het Other PromP PromBiv ENCODE ReprPC SARS PSRC1 SORT1 SYPL2 CYB561D1 GPR61 CELSR2 MYBPHL PSMA5 ATXN7L2 AMIGO1 SARS PSMA5 SORT1 CYB561D1 PSMA5 109.74 109.83 109.92 110 110.09 Chromosome 1 (Mb) Figure S5 Predicted PAIs at the SORT1 locus. Shown are the 14 REMC chromatin state annotations with the significant PAIs labelled on the top. ENSG00000026297.11 Gene Expression 1,200 1,000 800 600 TPM 400 200 0 -200 LiverLung Testis Ovary Spleen UterusVagina Bladder PituitaryProstate Thyroid Pancreas Stomach Artery -Artery Aorta - Tibial Nerve - Tibial Whole Blood Adrenal Gland Brain - Cortex Fallopian Tube Colon - Sigmoid Kidney - Cortex Artery - CoronaryBrain - Amygdala Muscle - Skeletal Brain - Cerebellum CervixCervix - Ectocervix -Colon Endocervix - Transverse BrainBrain - Hippocampus - Hypothalamus Esophagus - MucosaHeart - Left VentricleMinor Salivary Gland Brain - Substantia nigra Esophagus - Muscularis Adipose - Subcutaneous Breast - Mammary Tissue Heart - Atrial Appendage Brain - Frontal Cortex (BA9) Adipose - Visceral (Omentum)Brain - Cerebellar Hemisphere Cells - Transformed fibroblasts Brain - Caudate (basal ganglia)BrainBrain - Putamen - Spinal (basalcord (cervical ganglia) c-1) SkinSmall - Sun Intestine Exposed - Terminal(Lower leg) Ileum Cells - EBV-transformed lymphocytes Skin - Not Sun Exposed (Suprapubic) Brain - Anterior cingulate cortex (BA24) Esophagus - Gastroesophageal Junction Brain - Nucleus accumbens (basal ganglia) Figure tissues S 6 E of
Load more

Recommended publications
  • ABCG1 (ABC8), the Human Homolog of the Drosophila White Gene, Is a Regulator of Macrophage Cholesterol and Phospholipid Transport
    ABCG1 (ABC8), the human homolog of the Drosophila white gene, is a regulator of macrophage cholesterol and phospholipid transport Jochen Klucken*, Christa Bu¨ chler*, Evelyn Orso´ *, Wolfgang E. Kaminski*, Mustafa Porsch-Ozcu¨ ¨ ru¨ mez*, Gerhard Liebisch*, Michael Kapinsky*, Wendy Diederich*, Wolfgang Drobnik*, Michael Dean†, Rando Allikmets‡, and Gerd Schmitz*§ *Institute for Clinical Chemistry and Laboratory Medicine, University of Regensburg, 93042 Regensburg, Germany; †National Cancer Institute, Laboratory of Genomic Diversity, Frederick, MD 21702-1201; and ‡Departments of Ophthalmology and Pathology, Columbia University, Eye Research Addition, New York, NY 10032 Edited by Jan L. Breslow, The Rockefeller University, New York, NY, and approved November 3, 1999 (received for review June 14, 1999) Excessive uptake of atherogenic lipoproteins such as modified low- lesterol transport. Although several effector molecules have been density lipoprotein complexes by vascular macrophages leads to proposed to participate in macrophage cholesterol efflux (6, 9), foam cell formation, a critical step in atherogenesis. Cholesterol efflux including endogenous apolipoprotein E (10) and the cholesteryl mediated by high-density lipoproteins (HDL) constitutes a protective ester transfer protein (11), the detailed molecular mechanisms mechanism against macrophage lipid overloading. The molecular underlying cholesterol export in these cells have not yet been mechanisms underlying this reverse cholesterol transport process are characterized. currently not fully understood. To identify effector proteins that are Recently, mutations of the ATP-binding cassette (ABC) trans- involved in macrophage lipid uptake and release, we searched for porter ABCA1 gene have been causatively linked to familial HDL genes that are regulated during lipid influx and efflux in human deficiency and Tangier disease (12–14).
    [Show full text]
  • Three Hundred Twenty-Six Genetic Variations in Genes Encoding Nine Members of ATP-Binding Cassette, Subfamily B (ABCB/MDR/TAP), in the Japanese Population
    4600/38J Hum Genet (2002) 47:38–50 N. Matsuda et al.: © Jpn EGF Soc receptor Hum Genet and osteoblastic and Springer-Verlag differentiation 2002 ORIGINAL ARTICLE Susumu Saito · Aritoshi Iida · Akihiro Sekine Yukie Miura · Chie Ogawa · Saori Kawauchi Shoko Higuchi · Yusuke Nakamura Three hundred twenty-six genetic variations in genes encoding nine members of ATP-binding cassette, subfamily B (ABCB/MDR/TAP), in the Japanese population Received: September 18, 2001 / Accepted: November 2, 2001 Abstract We screened DNAs from 48 Japanese individuals domain (Hyde et al. 1990). ABC proteins constitute a super- for single-nucleotide polymorphisms (SNPs) in nine genes family consisting of eight subfamilies: ABC1, MDR/TAP, encoding components of ATP-binding cassette subfamily CFTR/MRP, ALD, OABP, GCN20, WHITE, and ANSA B (ABCB/MDR/TAP) by directly sequencing the entire (Kerb et al. 2001; Human ABC gene nomenclature applicable genomic regions except for repetitive elements. committee, http://www.gene.ucl.ac.uk/nomenclature/ This approach identified 297 SNPs and 29 insertion/deletion genefamily/abc.html). polymorphisms among the nine genes. Of the 297 SNPs, 50 Members of the MDR/TAP subfamily include the were identified in the ABCB1 gene, 14 in TAP1, 35 in ATP-binding cassette, subfamily B (ABCB) and the TAP2, 48 in ABCB4, 13 in ABCB7, 21 in ABCB8, 21 in transporter associated with antigen processing (TAP). The ABCB9, 13 in ABCB10, and 82 in ABCB11. Thirteen were ABCB1 [ATP-binding cassette, subfamily B, member 1, located in 5Ј flanking regions, 237 in introns, 37 in exons, also called multidrug resistance (MDR)-1] gene encodes P- and 10 in 3Ј flanking regions.
    [Show full text]
  • Transcriptional and Post-Transcriptional Regulation of ATP-Binding Cassette Transporter Expression
    Transcriptional and Post-transcriptional Regulation of ATP-binding Cassette Transporter Expression by Aparna Chhibber DISSERTATION Submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Pharmaceutical Sciences and Pbarmacogenomies in the Copyright 2014 by Aparna Chhibber ii Acknowledgements First and foremost, I would like to thank my advisor, Dr. Deanna Kroetz. More than just a research advisor, Deanna has clearly made it a priority to guide her students to become better scientists, and I am grateful for the countless hours she has spent editing papers, developing presentations, discussing research, and so much more. I would not have made it this far without her support and guidance. My thesis committee has provided valuable advice through the years. Dr. Nadav Ahituv in particular has been a source of support from my first year in the graduate program as my academic advisor, qualifying exam committee chair, and finally thesis committee member. Dr. Kathy Giacomini graciously stepped in as a member of my thesis committee in my 3rd year, and Dr. Steven Brenner provided valuable input as thesis committee member in my 2nd year. My labmates over the past five years have been incredible colleagues and friends. Dr. Svetlana Markova first welcomed me into the lab and taught me numerous laboratory techniques, and has always been willing to act as a sounding board. Michael Martin has been my partner-in-crime in the lab from the beginning, and has made my days in lab fly by. Dr. Yingmei Lui has made the lab run smoothly, and has always been willing to jump in to help me at a moment’s notice.
    [Show full text]
  • Parkinson's Disease Is Associated with DNA Methylation Levels in Human
    Chuang et al. Genome Medicine (2017) 9:76 DOI 10.1186/s13073-017-0466-5 RESEARCH Open Access Parkinson’s disease is associated with DNA methylation levels in human blood and saliva Yu-Hsuan Chuang1, Kimberly C. Paul1, Jeff M. Bronstein4, Yvette Bordelon4, Steve Horvath2,3*† and Beate Ritz1,4,5*† Abstract Background: Several articles suggest that DNA methylation levels in blood relate to Parkinson’s disease (PD) but there is a need for a large-scale study that involves suitable population based controls. The purposes of the study were: (1) to study whether PD status is associated with DNA methylation levels in blood/saliva; (2) to study whether observed associations relate to blood cell types; and (3) to characterize genome-wide significant markers (“CpGs”) and clusters of CpGs (co-methylation modules) in terms of biological pathways. Methods: In a population-based case control study of PD, we studied blood samples from 335 PD cases and 237 controls and saliva samples from another 128 cases and 131 controls. DNA methylation data were generated from over 486,000 CpGs using the Illumina Infinium array. We identified modules of CpGs (clusters) using weighted correlation network analysis (WGCNA). Results: Our cross-sectional analysis of blood identified 82 genome-wide significant CpGs (including cg02489202 in LARS2 p = 8.3 × 10–11 and cg04772575 in ABCB9 p = 4.3 × 10–10). Three out of six PD related co-methylation modules in blood were significantly enriched with immune system related genes. Our analysis of saliva identified five significant CpGs. PD-related CpGs are located near genes that relate to mitochondrial function, neuronal projection, cytoskeleton organization, systemic immune response, and iron handling.
    [Show full text]
  • Whole-Exome Sequencing Identifies Novel Mutations in ABC Transporter
    Liu et al. BMC Pregnancy and Childbirth (2021) 21:110 https://doi.org/10.1186/s12884-021-03595-x RESEARCH ARTICLE Open Access Whole-exome sequencing identifies novel mutations in ABC transporter genes associated with intrahepatic cholestasis of pregnancy disease: a case-control study Xianxian Liu1,2†, Hua Lai1,3†, Siming Xin1,3, Zengming Li1, Xiaoming Zeng1,3, Liju Nie1,3, Zhengyi Liang1,3, Meiling Wu1,3, Jiusheng Zheng1,3* and Yang Zou1,2* Abstract Background: Intrahepatic cholestasis of pregnancy (ICP) can cause premature delivery and stillbirth. Previous studies have reported that mutations in ABC transporter genes strongly influence the transport of bile salts. However, to date, their effects are still largely elusive. Methods: A whole-exome sequencing (WES) approach was used to detect novel variants. Rare novel exonic variants (minor allele frequencies: MAF < 1%) were analyzed. Three web-available tools, namely, SIFT, Mutation Taster and FATHMM, were used to predict protein damage. Protein structure modeling and comparisons between reference and modified protein structures were performed by SWISS-MODEL and Chimera 1.14rc, respectively. Results: We detected a total of 2953 mutations in 44 ABC family transporter genes. When the MAF of loci was controlled in all databases at less than 0.01, 320 mutations were reserved for further analysis. Among these mutations, 42 were novel. We classified these loci into four groups (the damaging, probably damaging, possibly damaging, and neutral groups) according to the prediction results, of which 7 novel possible pathogenic mutations were identified that were located in known functional genes, including ABCB4 (Trp708Ter, Gly527Glu and Lys386Glu), ABCB11 (Gln1194Ter, Gln605Pro and Leu589Met) and ABCC2 (Ser1342Tyr), in the damaging group.
    [Show full text]
  • Structural Evolution of the ABC Transporter Subfamily B
    ORIGINAL RESEARCH Structural Evolution of the ABC Transporter Subfamily B Flanagan, J.U.1 and Huber, T.2 1ARC Special Research Centre for Functional and Applied Genomics, Level 5, Institute for Molecular Bioscience, The University of Queensland, St Lucia, QLD 4072, Australia. 2School of Molecular and Microbial Science, The University of Queensland, St Lucia, QLD 4072, Australia. Abstract: The ATP binding cassette containing transporters are a superfamily of integral membrane proteins that translocate a wide range of substrates. The subfamily B members include the biologically important multidrug resis- tant (MDR) protein and the transporter associated with antigen processing (TAP) complex. Substrates translocated by this subfamily include drugs, lipids, peptides and iron. We have constructed a comprehensive set of comparative models for the transporters from eukaryotes and used these to study the effects of sequence divergence on the sub- strate translocation pathway. Notably, there is very little structural divergence between the bacterial template struc- ture and the more distantly related eukaryotic proteins illustrating a need to conserve transporter structure. By contrast different properties have been adopted for the translocation pathway depending on the substrate type. A greater level of divergence in electrostatic properties is seen with transporters that have a broad substrate range both within and between species, while a high level of conservation is observed when the substrate range is narrow. This study represents the first effort towards understanding effect of evolution on subfamily B ABC transporters in the context of protein structure and biophysical properties. Abbreviations: A. thaliana, Arabidopsis thaliana; D. melanogaster, Drosophilia melanogaster; S. aureus, Staphylococcus aureus; ABC, ATP binding cassette; TAP, Transporter associated with antigen processing.
    [Show full text]
  • Anti-ABCB9 / TAPL Antibody (ARG63472)
    Product datasheet [email protected] ARG63472 Package: 100 μg anti-ABCB9 / TAPL antibody Store at: -20°C Summary Product Description Goat Polyclonal antibody recognizes ABCB9 / TAPL Tested Reactivity Hu Tested Application IHC-P Specificity This antibody is expected to recognise both human isoforms of this protein (as represented by NP_062570.1, NP_062571.1and NP_982269.1). Variants (NP_062571.1; NP_982269.1) encode the same isoform. Host Goat Clonality Polyclonal Isotype IgG Target Name ABCB9 / TAPL Antigen Species Human Immunogen C-GHNEPVANGSHKA Conjugation Un-conjugated Alternate Names hABCB9; TAP-like protein; ATP-binding cassette sub-family B member 9; EST122234; ATP-binding cassette transporter 9; ABC transporter 9 protein; TAPL Application Instructions Application table Application Dilution IHC-P 3 - 5 µg/ml Application Note IHC-P: Antigen Retrieval: Steam tissue section in Citrate buffer (pH 6.0). * The dilutions indicate recommended starting dilutions and the optimal dilutions or concentrations should be determined by the scientist. Calculated Mw 84 kDa Properties Form Liquid Purification Purified from goat serum by ammonium sulphate precipitation followed by antigen affinity chromatography using the immunizing peptide. Buffer Tris saline (pH 7.3), 0.02% Sodium azide and 0.5% BSA Preservative 0.02% Sodium azide Stabilizer 0.5% BSA Concentration 0.5 mg/ml Storage instruction For continuous use, store undiluted antibody at 2-8°C for up to a week. For long-term storage, aliquot www.arigobio.com 1/2 and store at -20°C or below. Storage in frost free freezers is not recommended. Avoid repeated freeze/thaw cycles. Suggest spin the vial prior to opening.
    [Show full text]
  • Regulation of Cholesterol Homeostasis in Macrophages and Consequences for Atherosclerotic Lesion Development
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector FEBS Letters 580 (2006) 5588–5596 Minireview Regulation of cholesterol homeostasis in macrophages and consequences for atherosclerotic lesion development Marieke Pennings, Illiana Meurs, Dan Ye, Ruud Out, Menno Hoekstra, Theo J.C. Van Berkel*, Miranda Van Eck Division of Biopharmaceutics, Leiden/Amsterdam Center for Drug Research, Gorlaeus Laboratories, Leiden University, P.O. Box 9502, 2300 RA Leiden, The Netherlands Received 19 June 2006; revised 28 July 2006; accepted 6 August 2006 Available online 23 August 2006 Edited by Gerrit van Meer 2. Macrophage cholesterol accumulation Abstract Foam cell formation due to excessive accumulation of cholesterol by macrophages is a pathological hallmark of athero- sclerosis. Macrophages cannot limit the uptake of cholesterol Cholesterol may enter macrophages via several different path- and therefore depend on cholesterol efflux pathways for prevent- ways. Macrophages express high levels of scavenger receptors, ing their transformation into foam cells. Several ABC-transport- which bind and internalize oxidatively modified lipoproteins. ers, including ABCA1 and ABCG1, facilitate the efflux of Furthermore, macrophages also contain several other types of cholesterol from macrophages. These transporters, however, also binding sites that are involved in the accumulation of unmodi- affect membrane lipid asymmetry which may have important fied lipoproteins and lipoprotein remnants, including the LDL implications for cellular endocytotic pathways. We propose that receptor (LDLr), LDL receptor-related protein (LRP), VLDL in addition to the generally accepted role of these ABC-trans- receptor (VLDLr), and proteoglycans (see Fig. 1). porters in the prevention of foam cell formation by induction An important receptor implicated in the accumulation of of cholesterol efflux from macrophages, they also influence the macrophage endocytotic uptake.
    [Show full text]
  • ABC Transporters and Scavenger Receptor BI: Important Mediators Of
    ABC transporters and scavenger receptor BI : important mediators of lipid metabolism and atherosclerosis Meurs, I. Citation Meurs, I. (2011, June 7). ABC transporters and scavenger receptor BI : important mediators of lipid metabolism and atherosclerosis. Retrieved from https://hdl.handle.net/1887/17686 Version: Corrected Publisher’s Version Licence agreement concerning inclusion of doctoral License: thesis in the Institutional Repository of the University of Leiden Downloaded from: https://hdl.handle.net/1887/17686 Note: To cite this publication please use the final published version (if applicable). Chapter 6 Transcriptional profiling of ABC transporters in murine foam cells and atherosclerotic lesions identifies putative novel targets for improving macrophage lipid homeostasis Illiana Meurs, Martine Bot, Bart Lammers, Theo J.C. Van Berkel, and Miranda Van Eck Division of Biopharmaceutics, Leiden/Amsterdam Center for Drug Research, Gorlaeus Laboratories, Leiden University, Leiden, The Netherlands Manuscript in preparation Chapter 6 ABSTRACT Objective- Excessive accumulation of cholesterol by macrophages leading to their transformation into foam cells is the earliest pathological hallmark of atherosclerosis. Key regulators of macrophage cholesterol and phospholipid efflux are the ATP-binding cassette (ABC) transporters ABCA1 and ABCG1. The objective of this study was to identify new ABC transporters that are differentially expressed during macrophage foam cell formation induced by the commonly used pro-atherogenic lipoproteins βVLDL and
    [Show full text]
  • Fitting and Visualising Row-Linear Models with Consensus
    Fitting and visualising row-linear models with consensus Tim Peters May 19, 2021 Summary This short vignette will demonstrate how to fit a set of row-linear mod- els in the form of an interlaboratory testing procedure (ASTM Standard E691) in a genomic context. This allows us to make comparisons of sensi- tivity and precision for each platform/condition the samples are measured under. We can then make broader inferences about the suitability of a given technology. In an ideal world we would like a set of \gold standards" to validate a new technology or laboratory protocol when quantifying various genomic character- istics. The problem with this is that all genomic measurements are estimates, even those that are seen as more reliable, such as qPCR. Stochastic sampling of individual molecules (and their subsequent amplification) is an inescapable part of most modern laboratory protocols, which means that, inevitably, there will always be error present in the measurement. Rather than ignore this error and defining a \gold standard" (thus biasing all subsequent measurements towards that standard), the aim of this package is to encourage an empirical approach to characterising the advantages and disadvantages of a suite of candidate tech- nological platforms, laboratory protocols or other various conditions that may influence the measurement. With this in mind, we start with some normalised gene expression data sourced from The Cancer Genome Atlas (TCGA) glioblas- toma multiforme (GBM) project[1]. Firstly, make sure the package is installed: if(!require("BiocManager")) install.packages("BiocManager") BiocManager::install("consensus") Then load package and data: library(consensus) data("TCGA") 1 We have 27 matched samples assayed across four different gene expres- sion measurement platforms: Affymetrix-HT-HG-U133A GeneChip, Affymetrix HuEx GeneChip, Custom Agilent 244,000 feature Gene Expression Microarray and a polyA selection RNA-Seq protocol.
    [Show full text]
  • Gene Expression Profiling of ABC Transporters in Dermal Fibroblasts Of
    Laboratory Investigation (2008) 88, 1303–1315 & 2008 USCAP, Inc All rights reserved 0023-6837/08 $30.00 Gene expression profiling of ABC transporters in dermal fibroblasts of pseudoxanthoma elasticum patients identifies new candidates involved in PXE pathogenesis Doris Hendig1, Thomas Langmann2,3, Sarah Kocken1, Ralf Zarbock1, Christiane Szliska4, Gerd Schmitz2, Knut Kleesiek1 and Christian Go¨tting1 Mutations in the ABCC6 gene, encoding the multidrug resistance-associated protein 6 (MRP6), cause pseudoxanthoma elasticum (PXE). This heritable disorder leads to pathological alterations in connective tissues. The implication of MRP6 deficiency in PXE is still unknown. Moreover, nothing is known about a possible compensatory expression of other ATP binding-cassette (ABC) transporter proteins in MRP6-deficient cells. We investigated the gene expression profile of 47 ABC transporters in human dermal fibroblasts of healthy controls (n ¼ 2) and PXE patients (n ¼ 4) by TaqMan low-density array. The analysis revealed the expression of 37 ABC transporter genes in dermal fibroblasts. ABCC6 gene expression was not quantifiable in fibroblasts derived from PXE patients. Seven genes (ABCA6, ABCA9, ABCA10, ABCB5, ABCC2, ABCC9 and ABCD2) were induced, whereas the gene expression of one gene (ABCA3) was decreased, comparing controls and PXE patients (with at least twofold changes). We reanalyzed the gene expression of selected ABC transporters in a larger set of dermal fibroblasts from controls and PXE patients (n ¼ 6, each). Reanalysis showed high interindividual variability between samples, but confirmed the results obtained in the array analysis. The gene expression of ABC transporter genes, as well as lineage markers of PXE, was further examined after inhibition of ABCC6 gene expression by using specific small-interfering RNA.
    [Show full text]
  • TP53 Target Genes from Chea NR3C1 Target Genes From
    TP53 target genes from ChEA NR3C1 target genes from ChEA RELA target genes from ChEA AARS2 AACS ABCA1 ABCB6 ABCD3 ABCB1 ABCB9 ABCG2 ABCB4 ABCF2 ABHD11 ABCB9 ABHD1 ABHD15 ABCC6 ABHD5 ABLIM3 ABHD2 ABL1 ACAA2 ABI1 ACAD11 ACACA ABR ACADVL ACAP2 ABTB2 ACAP1 ACBD6 ACHE ACBD6 ACHE ACSS1 ACSF2 ACSL5 ADAM19 ACTA2 ACSM3 ADCK3 ACTB ADAM10 ADCK4 ACTBL2 ADAMTSL2 ADORA1 ACTN4 ADAT2 ADRBK2 ADAM15 ADI1 AGER ADAM19 ADRA1A AGTRAP ADIPOR1 AGFG1 AHCTF1 ADPGK AGPAT3 AHNAK ADRB2 AGPAT5 AKAP13 AEBP2 AGTPBP1 AKR1B1 AEN AKAP12 AKR1C1 AGAP1 AKAP8 ALCAM AGL AKR1B1 ALDH3A1 AGPS ALDH18A1 ALOX12 AIMP1 ALDH1A1 ALOX12B AKAP10 ALDH7A1 ALOX5 AKAP13 ALOXE3 ALPK1 AKAP9 ANKRD28 AMACR ALAD ANKRD50 AMH ALDH3A1 APBB2 ANGPT1 ALOX5 APCDD1 ANKLE2 AMBRA1 APOL3 ANKRD28 AMZ2 APOL6 ANKRD9 ANKHD1 AQP1 ANXA7 ANKHD1-EIF4EBP3 ARFGEF2 AP1S3 ANKRD11 ARG2 AP2A1 ANKRD12 ARID1B AP2B1 ANKRD17 ARIH2 AP4M1 ANKZF1 ARL3 APBB2 AP4S1 ARL4A APOBEC3A APAF1 ARL4C APOBEC3B APBB2 ARL9 APOE APBB3 ARMC7 APP APITD1 ARRDC5 AR APOLD1 ASAP2 ARF1 ARCN1 ASXL2 ARFRP1 ARHGAP22 ATAD2B ARHGAP27 ARHGAP26 ATF1 ARHGEF2 ARHGEF3 ATIC ARHGEF40 ARID3A ATOH8 ARID1A ARID3B ATXN1 ARID2 ARL2 ATXN10 ARL4A ARL8B AZIN1 ARL5B ARSG AZU1 ARL6IP5 ASB16 B3GALT2 ARNT2 ASCC3 B4GALT1 ASAP1 ASTN2 B4GALT5 ASB6 ATAD2B B9D1 ASPH ATF3 BANP ASS1 ATG4A BBS2 ATG13 ATG9A BCAS4 ATG16L2 ATL1 BCAT1 ATOX1 ATN1 BCL6 ATP9A ATP2A2 BLK ATR ATRIP BOD1 ATXN2L ATXN7L3 BTBD11 AZIN1 AXL BTBD2 B2M B3GAT2 BTG1 B3GAT3 BACH1 BTN3A1 B4GALT5 BAI2 BTNL3 BACE1 BAX C1D BACH1 BBC3 CACNA1C BAIAP2L2 BBS9 CAMK1D BAX BCAS3 CAND1 BBC3 BCL2L1 CBR4 BCAT1 BEST4 CBS BCL2 BIN2
    [Show full text]