Clonal Evolution Patterns in Acute Myeloid Leukemia with NPM1 Mutation
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CEP41 As an ASD Gene Ashok Patowary 1,Soyeonwon2,Shinjioh2,Ryanrnesbitt1, Marilyn Archer1, Debbie Nickerson3, Wendy H
Patowary et al. Translational Psychiatry (2019) 9:4 https://doi.org/10.1038/s41398-018-0343-z Translational Psychiatry ARTICLE Open Access Family-based exome sequencing and case- control analysis implicate CEP41 as an ASD gene Ashok Patowary 1,SoYeonWon2,ShinJiOh2,RyanRNesbitt1, Marilyn Archer1, Debbie Nickerson3, Wendy H. Raskind1,4, Raphael Bernier1,JiEunLee2,5 and Zoran Brkanac1 Abstract Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a strong genetic component. Although next-generation sequencing (NGS) technologies have been successfully applied to gene identification in de novo ASD, the genetic architecture of familial ASD remains largely unexplored. Our approach, which leverages the high specificity and sensitivity of NGS technology, has focused on rare variants in familial autism. We used NGS exome sequencing in 26 families with distantly related affected individuals to identify genes with private gene disrupting and missense variants of interest (VOI). We found that the genes carrying VOIs were enriched for biological processes related to cell projection organization and neuron development, which is consistent with the neurodevelopmental hypothesis of ASD. For a subset of genes carrying VOIs, we then used targeted NGS sequencing and gene-based variant burden case-control analysis to test for association with ASD. Missense variants in one gene, CEP41, associated significantly with ASD (p = 6.185e−05). Homozygous gene-disrupting variants in CEP41 were initially found to be responsible for recessive Joubert syndrome. Using a zebrafish model, we evaluated the mechanism by which the 1234567890():,; 1234567890():,; 1234567890():,; 1234567890():,; CEP41 variants might contribute to ASD. We found that CEP41 missense variants affect development of the axonal tract, cranial neural crest migration and social behavior phenotype. -
Supporting Information for Proteomics DOI 10.1002/Pmic.200401283
Supporting Information for Proteomics DOI 10.1002/pmic.200401283 Laura Bianchi, Cristina Canton, Luca Bini, Rosaria Orlandi, Sylvie Mnard, Alessandro Armini, Monica Cattaneo, Vitaliano Pallini, Luigi Rossi Bernardi and Ida Biunno Protein profile changes in the human breast cancer cell line MCF-7 in response to SEL1L gene induction ª 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.proteomics-journal.de Probe Set ID UniGene ID Representative Public ID Gene Title Gene Symbol E+E- M+M- E+M+ E-M- 38591_at 397073 D38501 postmeiotic segregation increased 2-like 5 PMS2L5 D NC D NC 37611_at 81791 AB008822 tumor necrosis factor receptor superfamily, member 11b (osteoprotegerin) TNFRSF11B D NC D NC 40711_at 86405 AL049340 Splicing factor YT521-B YT521 D NC D NC 33540_at 378826 AL049233 Chromosome 10 open reading frame 18 C10orf18 D NC D NC 1298_at 510244 X86816 Estrogen receptor cDNA, 5' splice variant --- D NC D NC 38266_at 188553 W25798 retinoblastoma binding protein 6 RBBP6 D NC D NC 31665_s_at --- W27675 --- --- D NC D NC 40713_at 86998 AB020634 nuclear factor of activated T-cells 5, tonicity-responsive NFAT5 D NC D NC 33658_at 421238 S54641 zinc finger protein 124 (HZF-16) ZNF124 D NC D NC 1465_s_at 300592 S75881 V-myb myeloblastosis viral oncogene homolog (avian)-like 1 MYBL1 D NC D NC 36448_at --- X95677 --- --- D NC D NC 34777_at 441047 D14874 adrenomedullin ADM D NC D NC 32389_at 536594 W25892 Transcribed locus, weakly similar to XP_216369.2 similar to ORF2 consensus sequence encoding endonuclease and reverse--- transcriptase minus -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Profiling Data
Compound Name DiscoveRx Gene Symbol Entrez Gene Percent Compound Symbol Control Concentration (nM) JNK-IN-8 AAK1 AAK1 69 1000 JNK-IN-8 ABL1(E255K)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317I)-nonphosphorylated ABL1 87 1000 JNK-IN-8 ABL1(F317I)-phosphorylated ABL1 100 1000 JNK-IN-8 ABL1(F317L)-nonphosphorylated ABL1 65 1000 JNK-IN-8 ABL1(F317L)-phosphorylated ABL1 61 1000 JNK-IN-8 ABL1(H396P)-nonphosphorylated ABL1 42 1000 JNK-IN-8 ABL1(H396P)-phosphorylated ABL1 60 1000 JNK-IN-8 ABL1(M351T)-phosphorylated ABL1 81 1000 JNK-IN-8 ABL1(Q252H)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(Q252H)-phosphorylated ABL1 56 1000 JNK-IN-8 ABL1(T315I)-nonphosphorylated ABL1 100 1000 JNK-IN-8 ABL1(T315I)-phosphorylated ABL1 92 1000 JNK-IN-8 ABL1(Y253F)-phosphorylated ABL1 71 1000 JNK-IN-8 ABL1-nonphosphorylated ABL1 97 1000 JNK-IN-8 ABL1-phosphorylated ABL1 100 1000 JNK-IN-8 ABL2 ABL2 97 1000 JNK-IN-8 ACVR1 ACVR1 100 1000 JNK-IN-8 ACVR1B ACVR1B 88 1000 JNK-IN-8 ACVR2A ACVR2A 100 1000 JNK-IN-8 ACVR2B ACVR2B 100 1000 JNK-IN-8 ACVRL1 ACVRL1 96 1000 JNK-IN-8 ADCK3 CABC1 100 1000 JNK-IN-8 ADCK4 ADCK4 93 1000 JNK-IN-8 AKT1 AKT1 100 1000 JNK-IN-8 AKT2 AKT2 100 1000 JNK-IN-8 AKT3 AKT3 100 1000 JNK-IN-8 ALK ALK 85 1000 JNK-IN-8 AMPK-alpha1 PRKAA1 100 1000 JNK-IN-8 AMPK-alpha2 PRKAA2 84 1000 JNK-IN-8 ANKK1 ANKK1 75 1000 JNK-IN-8 ARK5 NUAK1 100 1000 JNK-IN-8 ASK1 MAP3K5 100 1000 JNK-IN-8 ASK2 MAP3K6 93 1000 JNK-IN-8 AURKA AURKA 100 1000 JNK-IN-8 AURKA AURKA 84 1000 JNK-IN-8 AURKB AURKB 83 1000 JNK-IN-8 AURKB AURKB 96 1000 JNK-IN-8 AURKC AURKC 95 1000 JNK-IN-8 -
De Novo EIF2AK1 and EIF2AK2 Variants Are Associated with Developmental Delay, Leukoencephalopathy, and Neurologic Decompensation
bioRxiv preprint doi: https://doi.org/10.1101/757039; this version posted September 16, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. De novo EIF2AK1 and EIF2AK2 variants are associated with developmental delay, leukoencephalopathy, and neurologic decompensation Dongxue Mao1,2, Chloe M. Reuter3,4, Maura R.Z. Ruzhnikov5,6, Anita E. Beck7, Emily G. Farrow8,9,10, Lisa T. Emrick1,11,12,13, Jill A. Rosenfeld12, Katherine M. Mackenzie5, Laurie Robak2,12,13, Matthew T. Wheeler3,14, Lindsay C. Burrage12,13, Mahim Jain15, Pengfei Liu12, Daniel Calame11,13, Sebastien Küry17,18, Martin Sillesen19, Klaus Schmitz-Abe20, Davide Tonduti21, Luigina Spaccini22, Maria Iascone23, Casie A. Genetti20, Madeline Graf16, Alyssa Tran12, Mercedes Alejandro12, Undiagnosed Diseases Network, Brendan H. Lee12,13, Isabelle Thiffault8,9,24, Pankaj B. Agrawal#,20, Jonathan A. Bernstein#,3,25, Hugo J. Bellen#,2,12,26,27,28, Hsiao- Tuan Chao#,1,2,11,12,13,28,27,29 #Correspondence should be addressed: [email protected] (P.A.), [email protected] (J.A.B.), [email protected] (H.J.B.), [email protected] (H.T.C.) 1Department of Pediatrics, Baylor College of Medicine (BCM), Houston, TX 2Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX 3Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA 4Stanford Center for Inherited Cardiovascular Disease, Division of Cardiovascular Medicine, -
Figure S1. HAEC ROS Production and ML090 NOX5-Inhibition
Figure S1. HAEC ROS production and ML090 NOX5-inhibition. (a) Extracellular H2O2 production in HAEC treated with ML090 at different concentrations and 24 h after being infected with GFP and NOX5-β adenoviruses (MOI 100). **p< 0.01, and ****p< 0.0001 vs control NOX5-β-infected cells (ML090, 0 nM). Results expressed as mean ± SEM. Fold increase vs GFP-infected cells with 0 nM of ML090. n= 6. (b) NOX5-β overexpression and DHE oxidation in HAEC. Representative images from three experiments are shown. Intracellular superoxide anion production of HAEC 24 h after infection with GFP and NOX5-β adenoviruses at different MOIs treated or not with ML090 (10 nM). MOI: Multiplicity of infection. Figure S2. Ontology analysis of HAEC infected with NOX5-β. Ontology analysis shows that the response to unfolded protein is the most relevant. Figure S3. UPR mRNA expression in heart of infarcted transgenic mice. n= 12-13. Results expressed as mean ± SEM. Table S1: Altered gene expression due to NOX5-β expression at 12 h (bold, highlighted in yellow). N12hvsG12h N18hvsG18h N24hvsG24h GeneName GeneDescription TranscriptID logFC p-value logFC p-value logFC p-value family with sequence similarity NM_052966 1.45 1.20E-17 2.44 3.27E-19 2.96 6.24E-21 FAM129A 129. member A DnaJ (Hsp40) homolog. NM_001130182 2.19 9.83E-20 2.94 2.90E-19 3.01 1.68E-19 DNAJA4 subfamily A. member 4 phorbol-12-myristate-13-acetate- NM_021127 0.93 1.84E-12 2.41 1.32E-17 2.69 1.43E-18 PMAIP1 induced protein 1 E2F7 E2F transcription factor 7 NM_203394 0.71 8.35E-11 2.20 2.21E-17 2.48 1.84E-18 DnaJ (Hsp40) homolog. -
Unique Integrated Stress Response Sensors Regulate Cancer Cell
RESEARCH ARTICLE Unique integrated stress response sensors regulate cancer cell susceptibility when Hsp70 activity is compromised Sara Sannino1*, Megan E Yates2,3,4, Mark E Schurdak5,6, Steffi Oesterreich2,3,7, Adrian V Lee2,3,7, Peter Wipf8, Jeffrey L Brodsky1* 1Department of Biological Sciences, University of Pittsburgh, Pittsburgh, United States; 2Women’s Cancer Research Center, UPMC Hillman Cancer Center, Magee- Women Research Institute, Pittsburgh, United States; 3Integrative Systems Biology Program, University of Pittsburgh, Pittsburgh, United States; 4Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, United States; 5Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, United States; 6University of Pittsburgh Drug Discovery Institute, Pittsburgh, United States; 7Department of Pharmacology and Chemical Biology, University of Pittsburgh School of Medicine, Pittsburgh, United States; 8Department of Chemistry, University of Pittsburgh, Pittsburgh, United States Abstract Molecular chaperones, such as Hsp70, prevent proteotoxicity and maintain homeostasis. This is perhaps most evident in cancer cells, which overexpress Hsp70 and thrive even when harboring high levels of misfolded proteins. To define the response to proteotoxic challenges, we examined adaptive responses in breast cancer cells in the presence of an Hsp70 inhibitor. We discovered that the cells bin into distinct classes based on inhibitor sensitivity. Strikingly, the most resistant cells have higher autophagy levels, and autophagy was maximally activated only in resistant cells upon Hsp70 inhibition. In turn, resistance to compromised Hsp70 *For correspondence: function required the integrated stress response transducer, GCN2, which is commonly associated [email protected] (SS); with amino acid starvation. In contrast, sensitive cells succumbed to Hsp70 inhibition by activating [email protected] (JLB) PERK. -
Relevance of Translation Initiation in Diffuse Glioma Biology and Its
cells Review Relevance of Translation Initiation in Diffuse Glioma Biology and its Therapeutic Potential Digregorio Marina 1, Lombard Arnaud 1,2, Lumapat Paul Noel 1, Scholtes Felix 1,2, Rogister Bernard 1,3 and Coppieters Natacha 1,* 1 Laboratory of Nervous System Disorders and Therapy, GIGA-Neurosciences Research Centre, University of Liège, 4000 Liège, Belgium; [email protected] (D.M.); [email protected] (L.A.); [email protected] (L.P.N.); [email protected] (S.F.); [email protected] (R.B.) 2 Department of Neurosurgery, CHU of Liège, 4000 Liège, Belgium 3 Department of Neurology, CHU of Liège, 4000 Liège, Belgium * Correspondence: [email protected] Received: 18 October 2019; Accepted: 26 November 2019; Published: 29 November 2019 Abstract: Cancer cells are continually exposed to environmental stressors forcing them to adapt their protein production to survive. The translational machinery can be recruited by malignant cells to synthesize proteins required to promote their survival, even in times of high physiological and pathological stress. This phenomenon has been described in several cancers including in gliomas. Abnormal regulation of translation has encouraged the development of new therapeutics targeting the protein synthesis pathway. This approach could be meaningful for glioma given the fact that the median survival following diagnosis of the highest grade of glioma remains short despite current therapy. The identification of new targets for the development of novel therapeutics is therefore needed in order to improve this devastating overall survival rate. This review discusses current literature on translation in gliomas with a focus on the initiation step covering both the cap-dependent and cap-independent modes of initiation. -
Strand Breaks for P53 Exon 6 and 8 Among Different Time Course of Folate Depletion Or Repletion in the Rectosigmoid Mucosa
SUPPLEMENTAL FIGURE COLON p53 EXONIC STRAND BREAKS DURING FOLATE DEPLETION-REPLETION INTERVENTION Supplemental Figure Legend Strand breaks for p53 exon 6 and 8 among different time course of folate depletion or repletion in the rectosigmoid mucosa. The input of DNA was controlled by GAPDH. The data is shown as ΔCt after normalized to GAPDH. The higher ΔCt the more strand breaks. The P value is shown in the figure. SUPPLEMENT S1 Genes that were significantly UPREGULATED after folate intervention (by unadjusted paired t-test), list is sorted by P value Gene Symbol Nucleotide P VALUE Description OLFM4 NM_006418 0.0000 Homo sapiens differentially expressed in hematopoietic lineages (GW112) mRNA. FMR1NB NM_152578 0.0000 Homo sapiens hypothetical protein FLJ25736 (FLJ25736) mRNA. IFI6 NM_002038 0.0001 Homo sapiens interferon alpha-inducible protein (clone IFI-6-16) (G1P3) transcript variant 1 mRNA. Homo sapiens UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 15 GALNTL5 NM_145292 0.0001 (GALNT15) mRNA. STIM2 NM_020860 0.0001 Homo sapiens stromal interaction molecule 2 (STIM2) mRNA. ZNF645 NM_152577 0.0002 Homo sapiens hypothetical protein FLJ25735 (FLJ25735) mRNA. ATP12A NM_001676 0.0002 Homo sapiens ATPase H+/K+ transporting nongastric alpha polypeptide (ATP12A) mRNA. U1SNRNPBP NM_007020 0.0003 Homo sapiens U1-snRNP binding protein homolog (U1SNRNPBP) transcript variant 1 mRNA. RNF125 NM_017831 0.0004 Homo sapiens ring finger protein 125 (RNF125) mRNA. FMNL1 NM_005892 0.0004 Homo sapiens formin-like (FMNL) mRNA. ISG15 NM_005101 0.0005 Homo sapiens interferon alpha-inducible protein (clone IFI-15K) (G1P2) mRNA. SLC6A14 NM_007231 0.0005 Homo sapiens solute carrier family 6 (neurotransmitter transporter) member 14 (SLC6A14) mRNA. -
Integrated Stress Response of Vertebrates Is Regulated by Four
www.nature.com/scientificreports OPEN Integrated stress response of vertebrates is regulated by four eIF2α kinases Received: 20 March 2016 Shusuke Taniuchi1,2,3, Masato Miyake1,2,3, Kazue Tsugawa1,2, Miho Oyadomari1,2 & Accepted: 16 August 2016 Seiichi Oyadomari1,2,3 Published: 16 September 2016 The integrated stress response (ISR) is a cytoprotective pathway initiated upon phosphorylation of the eukaryotic translation initiation factor 2 (eIF2α) residue designated serine-51, which is critical for translational control in response to various stress conditions. Four eIF2α kinases, namely heme- regulated inhibitor (HRI), protein kinase R (PKR), PKR-like endoplasmic reticulum kinase, (PERK) and general control non-depressible 2 (GCN2), have been identified thus far, and they are known to be activated by heme depletion, viral infection, endoplasmic reticulum stress, and amino acid starvation, respectively. Because eIF2α is phosphorylated under various stress conditions, the existence of an additional eIF2α kinase has been suggested. To validate the existence of the unidentified eIF2α kinase, we constructed an eIF2α kinase quadruple knockout cells (4KO cells) in which the four known eIF2α kinase genes were deleted using the CRISPR/Cas9-mediated genome editing. Phosphorylation of eIF2α was completely abolished in the 4KO cells by various stress stimulations. Our data suggests that the four known eIF2α kinases are sufficient for ISR and that there are no additional eIF2α kinases in vertebrates. The α subunit of eukaryotic translation initiation factor 2 (eIF2α ) is known to be phosphorylated by diverse stress stimuli1. There are several phosphorylation sites in eIF2α, but serine 51 is critical for translational control2. eIF2α phosphorylation causes transient attenuation of the translation of most mRNAs and transcriptional induc- tion by selective translation of transcription factors. -
Epigenetic Mechanisms Are Involved in the Oncogenic Properties of ZNF518B in Colorectal Cancer
Epigenetic mechanisms are involved in the oncogenic properties of ZNF518B in colorectal cancer Francisco Gimeno-Valiente, Ángela L. Riffo-Campos, Luis Torres, Noelia Tarazona, Valentina Gambardella, Andrés Cervantes, Gerardo López-Rodas, Luis Franco and Josefa Castillo SUPPLEMENTARY METHODS 1. Selection of genomic sequences for ChIP analysis To select the sequences for ChIP analysis in the five putative target genes, namely, PADI3, ZDHHC2, RGS4, EFNA5 and KAT2B, the genomic region corresponding to the gene was downloaded from Ensembl. Then, zoom was applied to see in detail the promoter, enhancers and regulatory sequences. The details for HCT116 cells were then recovered and the target sequences for factor binding examined. Obviously, there are not data for ZNF518B, but special attention was paid to the target sequences of other zinc-finger containing factors. Finally, the regions that may putatively bind ZNF518B were selected and primers defining amplicons spanning such sequences were searched out. Supplementary Figure S3 gives the location of the amplicons used in each gene. 2. Obtaining the raw data and generating the BAM files for in silico analysis of the effects of EHMT2 and EZH2 silencing The data of siEZH2 (SRR6384524), siG9a (SRR6384526) and siNon-target (SRR6384521) in HCT116 cell line, were downloaded from SRA (Bioproject PRJNA422822, https://www.ncbi. nlm.nih.gov/bioproject/), using SRA-tolkit (https://ncbi.github.io/sra-tools/). All data correspond to RNAseq single end. doBasics = TRUE doAll = FALSE $ fastq-dump -I --split-files SRR6384524 Data quality was checked using the software fastqc (https://www.bioinformatics.babraham. ac.uk /projects/fastqc/). The first low quality removing nucleotides were removed using FASTX- Toolkit (http://hannonlab.cshl.edu/fastxtoolkit/). -
1 Kinobead Profiling Reveals Reprogramming of B-Cell Receptor Signaling in Response to Therapy Within Primary CLL Cells. Linley
bioRxiv preprint doi: https://doi.org/10.1101/841312; this version posted November 14, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Kinobead profiling reveals reprogramming of B-cell receptor signaling in response to therapy within primary CLL cells. Linley AJ1, Griffin R2, Cicconi S2, D’Avola A3$, MacEwan DJ4, Pettit AR1, Kalakonda N1, Packham G3, Prior IA5, Slupsky JR1. 1. Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Sherrington Building, Ashton Street, Liverpool, UK. 2. CRUK Clinical Trials Unit, University of Liverpool, Waterhouse Building, Ashton Street, Liverpool. 3. Southampton Cancer Research UK Centre, Cancer Sciences Unit, Faculty of Medicine, University of Southampton, Southampton, UK. 4. Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Sherrington Building, Ashton Street, Liverpool, UK. 5. Department of Cellular and Molecular Physiology, Institute of Translational Medicine, University of Liverpool, Nuffield Wing, Crown Street, Liverpool, UK. $ Current Address: The Francis Crick Institute, 1 Midland Road, London, UK. Corresponding author: Dr Adam J Linley, Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Sherrington Building, Ashton Street, Liverpool, UK; [email protected]; +44(0)151 794 5310 Running head: Therapy brings about BCR signal changes. Key points 1. sIgM signaling patterns alter following in vivo therapy using either chemoimmunotherapy or ibrutinib. 2. Kinobeads provide a novel method for high-resolution investigation of signaling in primary CLL cells. 1 bioRxiv preprint doi: https://doi.org/10.1101/841312; this version posted November 14, 2019.