DOCSLIB.ORG

Mouse Cct4 Conditional Knockout Project (CRISPR/Cas9)

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mouse Cct4 Conditional Knockout Project (CRISPR/Cas9) https://www.alphaknockout.com Mouse Cct4 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Cct4 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Cct4 gene (NCBI Reference Sequence: NM_009837 ; Ensembl: ENSMUSG00000007739 ) is located on Mouse chromosome 11. 14 exons are identified, with the ATG start codon in exon 1 and the TAA stop codon in exon 14 (Transcript: ENSMUST00000173867). Exon 2~3 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Cct4 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-214C7 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 2 starts from about 7.92% of the coding region. The knockout of Exon 2~3 will result in frameshift of the gene. The size of intron 1 for 5'-loxP site insertion: 2386 bp, and the size of intron 3 for 3'-loxP site insertion: 1542 bp. The size of effective cKO region: ~1621 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele 5' gRNA region gRNA region 3' 1 2 3 4 5 14 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Cct4 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. No significant tandem repeat is found in the dot plot matrix. So this region is suitable for PCR screening or sequencing analysis. Overview of the GC Content Distribution Window size: 300 bp Sequence 12 Summary: Full Length(8121bp) | A(28.83% 2341) | C(19.15% 1555) | T(30.23% 2455) | G(21.8% 1770) Note: The sequence of homologous arms and cKO region is analyzed to determine the GC content. Significant high GC-content regions are found. It may be difficult to construct this targeting vector. Page 3 of 8 https://www.alphaknockout.com BLAT Search Results (up) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 3000 1 3000 3000 100.0% chr11 + 22990018 22993017 3000 browser details YourSeq 109 621 853 3000 78.9% chr7 - 25443454 25443600 147 browser details YourSeq 79 2038 2155 3000 87.9% chr1 + 118408497 118738433 329937 browser details YourSeq 76 1954 2082 3000 83.7% chr7 - 127526490 127526616 127 browser details YourSeq 76 1993 2107 3000 91.5% chr12 - 91783131 91783247 117 browser details YourSeq 76 1955 2107 3000 94.3% chr2 + 29824786 29824938 153 browser details YourSeq 74 2031 2169 3000 93.2% chrX + 60422114 60422451 338 browser details YourSeq 74 2123 2237 3000 82.7% chr5 + 131412696 131412811 116 browser details YourSeq 72 1951 2079 3000 94.0% chr8 - 125879570 125879700 131 browser details YourSeq 72 1949 2082 3000 92.0% chr8 - 83734665 83734798 134 browser details YourSeq 72 1998 2149 3000 91.0% chr3 + 31577844 31578090 247 browser details YourSeq 71 1993 2118 3000 91.9% chr8 - 69745939 69746066 128 browser details YourSeq 69 1998 2117 3000 89.1% chr10 + 63119621 63119739 119 browser details YourSeq 67 1948 2075 3000 90.6% chr8 - 22494075 22494204 130 browser details YourSeq 67 2038 2324 3000 94.9% chr11 - 65091377 65091793 417 browser details YourSeq 67 1954 2079 3000 93.6% chr4 + 34626666 34626793 128 browser details YourSeq 66 2123 2329 3000 92.5% chrX + 99366565 99366774 210 browser details YourSeq 65 1955 2079 3000 92.4% chr5 - 125439671 125439797 127 browser details YourSeq 65 1993 2118 3000 85.4% chr18 - 66418270 66418393 124 browser details YourSeq 65 2118 2237 3000 77.5% chr1 - 69830511 69830631 121 Note: The 3000 bp section upstream of Exon 2 is BLAT searched against the genome. No significant similarity is found. BLAT Search Results (down) QUERY SCORE START END QSIZE IDENTITY CHROM STRAND START END SPAN ----------------------------------------------------------------------------------------------- browser details YourSeq 3000 1 3000 3000 100.0% chr11 + 22994639 22997638 3000 browser details YourSeq 300 1294 2513 3000 85.5% chr7 - 25443070 25443434 365 browser details YourSeq 244 421 1062 3000 93.0% chr1 - 58350035 58837847 487813 browser details YourSeq 209 409 1064 3000 91.7% chr2 + 33317596 33469222 151627 browser details YourSeq 203 450 1067 3000 82.6% chr7 + 142850392 142850812 421 browser details YourSeq 195 426 1064 3000 89.4% chr8 + 110987406 111109706 122301 browser details YourSeq 189 407 1032 3000 92.4% chr1 + 84870471 84926139 55669 browser details YourSeq 177 407 994 3000 88.4% chr13 - 62638356 62638937 582 browser details YourSeq 176 445 1063 3000 82.8% chr2 - 69872014 69872372 359 browser details YourSeq 175 432 1010 3000 94.5% chr1 + 20994699 21404096 409398 browser details YourSeq 138 447 1031 3000 82.1% chr9 - 86516284 86516764 481 browser details YourSeq 138 389 559 3000 94.9% chr16 + 65478609 65478795 187 browser details YourSeq 138 406 590 3000 92.6% chr1 + 68677761 68677955 195 browser details YourSeq 136 406 558 3000 94.8% chr16 - 30497807 30497960 154 browser details YourSeq 135 393 560 3000 90.2% chr4 - 133664073 133664234 162 browser details YourSeq 132 407 560 3000 90.7% chr1 - 52882608 52882756 149 browser details YourSeq 131 407 559 3000 90.6% chr1 - 72818255 72818402 148 browser details YourSeq 130 407 559 3000 90.0% chr3 + 113161739 113161887 149 browser details YourSeq 129 407 557 3000 93.4% chr14 - 40970005 40970157 153 browser details YourSeq 129 407 559 3000 92.2% chr11 - 114937019 114937171 153 Note: The 3000 bp section downstream of Exon 3 is BLAT searched against the genome. No significant similarity is found. Page 4 of 8 https://www.alphaknockout.com Gene and protein information: Cct4 chaperonin containing Tcp1, subunit 4 (delta) [ Mus musculus (house mouse) ] Gene ID: 12464, updated on 12-Aug-2019 Gene summary Official Symbol Cct4 provided by MGI Official Full Name chaperonin containing Tcp1, subunit 4 (delta) provided by MGI Primary source MGI:MGI:104689 See related Ensembl:ENSMUSG00000007739 Gene type protein coding RefSeq status VALIDATED Organism Mus musculus Lineage Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia; Eutheria; Euarchontoglires; Glires; Rodentia; Myomorpha; Muroidea; Muridae; Murinae; Mus; Mus Also known as A45; Cctd; C78323; 2610204B21Rik Expression Ubiquitous expression in CNS E11.5 (RPKM 82.4), placenta adult (RPKM 69.7) and 28 other tissues See more Orthologs human all Genomic context Location: 11 A3.2; 11 14.25 cM See Cct4 in Genome Data Viewer Exon count: 14 Annotation release Status Assembly Chr Location 108 current GRCm38.p6 (GCF_000001635.26) 11 NC_000077.6 (22990593..23003336) Build 37.2 previous assembly MGSCv37 (GCF_000001635.18) 11 NC_000077.5 (22890593..22903336) Chromosome 11 - NC_000077.6 Page 5 of 8 https://www.alphaknockout.com Transcript information: This gene has 9 transcripts Gene: Cct4 ENSMUSG00000007739 Description chaperonin containing Tcp1, subunit 4 (delta) [Source:MGI Symbol;Acc:MGI:104689] Gene Synonyms 2610204B21Rik, A45, Cctd, T complex protein 1, delta, TCP-1 delta Location Chromosome 11: 22,990,519-23,003,780 forward strand. GRCm38:CM001004.2 About this gene This gene has 9 transcripts (splice variants), 212 orthologues, 13 paralogues and is a member of 1 Ensembl protein family. Transcripts Name Transcript ID bp Protein Translation ID Biotype CCDS UniProt Flags Cct4- ENSMUST00000173867.7 2484 539aa ENSMUSP00000133523.1 Protein coding CCDS24474 P80315 TSL:1 204 Q564F4 GENCODE basic APPRIS P1 Cct4- ENSMUST00000020562.4 1634 509aa ENSMUSP00000020562.4 Protein coding - G5E839 TSL:5 201 GENCODE basic Cct4- ENSMUST00000174047.7 581 120aa ENSMUSP00000134248.1 Nonsense mediated - G3UYW5 TSL:5 205 decay Cct4- ENSMUST00000174659.1 489 47aa ENSMUSP00000133667.1 Nonsense mediated - G3UXF3 TSL:5 207 decay Cct4- ENSMUST00000173853.7 465 59aa ENSMUSP00000133677.1 Nonsense mediated - G3UXG2 TSL:3 203 decay Cct4- ENSMUST00000174244.7 1736 No - Retained intron - - TSL:1 206 protein Cct4- ENSMUST00000174746.1 627 No - Retained intron - - TSL:1 209 protein Cct4- ENSMUST00000174689.1 507 No - Retained intron - - TSL:2 208 protein Cct4- ENSMUST00000145912.1 596 No - lncRNA - - TSL:2 202 protein Page 6 of 8 https://www.alphaknockout.com 33.26 kb Forward strand 22.99Mb 23.00Mb 23.01Mb Genes (Comprehensive set... Cct4-204 >protein coding Fam161a-206 >protein coding Cct4-203 >nonsense mediated decay Cct4-202 >lncRNA Fam161a-205 >protein coding Cct4-206 >retained intron Cct4-208 >retained intron Fam161a-203 >protein coding Cct4-201 >protein coding Fam161a-208 >protein coding Cct4-205 >nonsense mediated decay Fam161a-201 >protein coding Cct4-207 >nonsense mediated decay Cct4-209 >retained intron Contigs BX001008.3 > Genes < Gm28048-201protein coding (Comprehensive set... < Commd1-204protein coding < Commd1-202protein coding < Commd1-203protein coding Regulatory Build 22.99Mb 23.00Mb 23.01Mb Reverse strand 33.26 kb Regulation Legend CTCF Open Chromatin Promoter Promoter Flank Transcription Factor Binding Site Gene Legend Protein Coding merged Ensembl/Havana Ensembl protein coding Non-Protein Coding processed transcript RNA gene Page 7 of 8 https://www.alphaknockout.com Transcript: ENSMUST00000173867 13.26 kb Forward strand Cct4-204 >protein coding ENSMUSP00000133... MobiDB lite TIGRFAM T-complex protein 1, delta subunit Superfamily GroEL-like apical domain superfamily GroEL-like equatorial domain superfamily TCP-1-like chaperonin intermediate domain superfamily Prints Chaperone tailless complex polypeptide 1 (TCP-1) Pfam Chaperonin Cpn60/TCP-1 family PROSITE patterns Chaperonin TCP-1, conserved site Chaperonin TCP-1, conserved site Chaperonin TCP-1, conserved site PANTHER PTHR11353:SF26 PTHR11353 Gene3D GroEL-like equatorial domain superfamily GroEL-like apical domain superfamily CDD T-complex protein 1, delta subunit All sequence SNPs/i..
Load more

Recommended publications
  • Analysis of Gene Expression Data for Gene Ontology
    ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins.
    [Show full text]
  • Transcriptional Regulation of RKIP in Prostate Cancer Progression
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr.
    [Show full text]
  • Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights Into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle
    animals Article Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle Masoumeh Naserkheil 1 , Abolfazl Bahrami 1 , Deukhwan Lee 2,* and Hossein Mehrban 3 1 Department of Animal Science, University College of Agriculture and Natural Resources, University of Tehran, Karaj 77871-31587, Iran; [email protected] (M.N.); [email protected] (A.B.) 2 Department of Animal Life and Environment Sciences, Hankyong National University, Jungang-ro 327, Anseong-si, Gyeonggi-do 17579, Korea 3 Department of Animal Science, Shahrekord University, Shahrekord 88186-34141, Iran; [email protected] * Correspondence: [email protected]; Tel.: +82-31-670-5091 Received: 25 August 2020; Accepted: 6 October 2020; Published: 9 October 2020 Simple Summary: Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest.
    [Show full text]
  • 1 Supporting Information for a Microrna Network Regulates
    Supporting Information for A microRNA Network Regulates Expression and Biosynthesis of CFTR and CFTR-ΔF508 Shyam Ramachandrana,b, Philip H. Karpc, Peng Jiangc, Lynda S. Ostedgaardc, Amy E. Walza, John T. Fishere, Shaf Keshavjeeh, Kim A. Lennoxi, Ashley M. Jacobii, Scott D. Rosei, Mark A. Behlkei, Michael J. Welshb,c,d,g, Yi Xingb,c,f, Paul B. McCray Jr.a,b,c Author Affiliations: Department of Pediatricsa, Interdisciplinary Program in Geneticsb, Departments of Internal Medicinec, Molecular Physiology and Biophysicsd, Anatomy and Cell Biologye, Biomedical Engineeringf, Howard Hughes Medical Instituteg, Carver College of Medicine, University of Iowa, Iowa City, IA-52242 Division of Thoracic Surgeryh, Toronto General Hospital, University Health Network, University of Toronto, Toronto, Canada-M5G 2C4 Integrated DNA Technologiesi, Coralville, IA-52241 To whom correspondence should be addressed: Email: [email protected] (M.J.W.); yi- [email protected] (Y.X.); Email: [email protected] (P.B.M.) This PDF file includes: Materials and Methods References Fig. S1. miR-138 regulates SIN3A in a dose-dependent and site-specific manner. Fig. S2. miR-138 regulates endogenous SIN3A protein expression. Fig. S3. miR-138 regulates endogenous CFTR protein expression in Calu-3 cells. Fig. S4. miR-138 regulates endogenous CFTR protein expression in primary human airway epithelia. Fig. S5. miR-138 regulates CFTR expression in HeLa cells. Fig. S6. miR-138 regulates CFTR expression in HEK293T cells. Fig. S7. HeLa cells exhibit CFTR channel activity. Fig. S8. miR-138 improves CFTR processing. Fig. S9. miR-138 improves CFTR-ΔF508 processing. Fig. S10. SIN3A inhibition yields partial rescue of Cl- transport in CF epithelia.
    [Show full text]
  • Supplemental Information
    Supplemental information Dissection of the genomic structure of the miR-183/96/182 gene. Previously, we showed that the miR-183/96/182 cluster is an intergenic miRNA cluster, located in a ~60-kb interval between the genes encoding nuclear respiratory factor-1 (Nrf1) and ubiquitin-conjugating enzyme E2H (Ube2h) on mouse chr6qA3.3 (1). To start to uncover the genomic structure of the miR- 183/96/182 gene, we first studied genomic features around miR-183/96/182 in the UCSC genome browser (http://genome.UCSC.edu/), and identified two CpG islands 3.4-6.5 kb 5’ of pre-miR-183, the most 5’ miRNA of the cluster (Fig. 1A; Fig. S1 and Seq. S1). A cDNA clone, AK044220, located at 3.2-4.6 kb 5’ to pre-miR-183, encompasses the second CpG island (Fig. 1A; Fig. S1). We hypothesized that this cDNA clone was derived from 5’ exon(s) of the primary transcript of the miR-183/96/182 gene, as CpG islands are often associated with promoters (2). Supporting this hypothesis, multiple expressed sequences detected by gene-trap clones, including clone D016D06 (3, 4), were co-localized with the cDNA clone AK044220 (Fig. 1A; Fig. S1). Clone D016D06, deposited by the German GeneTrap Consortium (GGTC) (http://tikus.gsf.de) (3, 4), was derived from insertion of a retroviral construct, rFlpROSAβgeo in 129S2 ES cells (Fig. 1A and C). The rFlpROSAβgeo construct carries a promoterless reporter gene, the β−geo cassette - an in-frame fusion of the β-galactosidase and neomycin resistance (Neor) gene (5), with a splicing acceptor (SA) immediately upstream, and a polyA signal downstream of the β−geo cassette (Fig.
    [Show full text]
  • Aneuploidy: Using Genetic Instability to Preserve a Haploid Genome?
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Science (Cancer Biology) Aneuploidy: Using genetic instability to preserve a haploid genome? Submitted by: Ramona Ramdath In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Science Examination Committee Signature/Date Major Advisor: David Allison, M.D., Ph.D. Academic James Trempe, Ph.D. Advisory Committee: David Giovanucci, Ph.D. Randall Ruch, Ph.D. Ronald Mellgren, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: April 10, 2009 Aneuploidy: Using genetic instability to preserve a haploid genome? Ramona Ramdath University of Toledo, Health Science Campus 2009 Dedication I dedicate this dissertation to my grandfather who died of lung cancer two years ago, but who always instilled in us the value and importance of education. And to my mom and sister, both of whom have been pillars of support and stimulating conversations. To my sister, Rehanna, especially- I hope this inspires you to achieve all that you want to in life, academically and otherwise. ii Acknowledgements As we go through these academic journeys, there are so many along the way that make an impact not only on our work, but on our lives as well, and I would like to say a heartfelt thank you to all of those people: My Committee members- Dr. James Trempe, Dr. David Giovanucchi, Dr. Ronald Mellgren and Dr. Randall Ruch for their guidance, suggestions, support and confidence in me. My major advisor- Dr. David Allison, for his constructive criticism and positive reinforcement.
    [Show full text]
  • MOCHI Enables Discovery of Heterogeneous Interactome Modules in 3D Nucleome
    Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome Dechao Tian1,# , Ruochi Zhang1,# , Yang Zhang1, Xiaopeng Zhu1, and Jian Ma1,* 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA #These two authors contributed equally *Correspondence: [email protected] Contact To whom correspondence should be addressed: Jian Ma School of Computer Science Carnegie Mellon University 7705 Gates-Hillman Complex 5000 Forbes Avenue Pittsburgh, PA 15213 Phone: +1 (412) 268-2776 Email: [email protected] 1 Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof-of-principle, to identify heterogeneous interactome modules (HIMs), each of which represents a cluster of gene loci that are in spatial contact more frequently than expected and that are regulated by the same group of transcription factors. HIM integrates transcription factor binding and 3D genome structure to reflect “transcriptional niche” in the nucleus. We develop a new algorithm MOCHI to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and exhibit distinct functional properties. Through integrative analysis, this work demonstrates the utility of MOCHI to identify HIMs, which may provide new perspectives on the interplay between transcriptional regulation and 3D genome organization.
    [Show full text]
  • Mechanisms Underlying Phenotypic Heterogeneity in Simplex Autism Spectrum Disorders
    Mechanisms Underlying Phenotypic Heterogeneity in Simplex Autism Spectrum Disorders Andrew H. Chiang Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2021 © 2021 Andrew H. Chiang All Rights Reserved Abstract Mechanisms Underlying Phenotypic Heterogeneity in Simplex Autism Spectrum Disorders Andrew H. Chiang Autism spectrum disorders (ASD) are a group of related neurodevelopmental diseases displaying significant genetic and phenotypic heterogeneity. Despite recent progress in ASD genetics, the nature of phenotypic heterogeneity across probands is not well understood. Notably, likely gene- disrupting (LGD) de novo mutations affecting the same gene often result in substantially different ASD phenotypes. We find that truncating mutations in a gene can result in a range of relatively mild decreases (15-30%) in gene expression due to nonsense-mediated decay (NMD), and show that more severe autism phenotypes are associated with greater decreases in expression. We also find that each gene with recurrent ASD mutations can be described by a parameter, phenotype dosage sensitivity (PDS), which characteriZes the relationship between changes in a gene’s dosage and changes in a given phenotype. Using simple linear models, we show that changes in gene dosage account for a substantial fraction of phenotypic variability in ASD. We further observe that LGD mutations affecting the same exon frequently lead to strikingly similar phenotypes in unrelated ASD probands. These patterns are observed for two independent proband cohorts and multiple important ASD-associated phenotypes. The observed phenotypic similarities are likely mediated by similar changes in gene dosage and similar perturbations to the relative expression of splicing isoforms.
    [Show full text]
  • Identifying Functions and Prognostic Biomarkers of Network Motifs Marked by Diverse Chromatin States in Human Cell Lines
    Oncogene (2020) 39:677–689 https://doi.org/10.1038/s41388-019-1005-1 ARTICLE Identifying functions and prognostic biomarkers of network motifs marked by diverse chromatin states in human cell lines 1 1 2 1 1 1 1 1 1 Li Wang ● Hongying Zhao ● Jing Li ● Yingqi Xu ● Yujia Lan ● Wenkang Yin ● Xiaoqin Liu ● Lei Yu ● Shihua Lin ● 3 1 1 1 Michael Yifei Du ● Xia Li ● Yun Xiao ● Yunpeng Zhang Received: 23 May 2019 / Revised: 30 July 2019 / Accepted: 15 August 2019 / Published online: 19 September 2019 © The Author(s) 2019. This article is published with open access Abstract Epigenetic modifications play critical roles in modulating gene expression, yet their roles in regulatory networks in human cell lines remain poorly characterized. We integrated multiomics data to construct directed regulatory networks with nodes and edges labeled with chromatin states in human cell lines. We observed extensive association of diverse chromatin states and network motifs. The gene expression analysis showed that diverse chromatin states of coherent type-1 feedforward loop (C1-FFL) and incoherent type-1 feedforward loops (I1-FFL) contributed to the dynamic expression patterns of targets. Notably, diverse chromatin state compositions could help C1- or I1-FFL to control a large number of distinct biological functions in human cell lines, such as four different types of chromatin state compositions cooperating with K562-associated C1-FFLs controlling “regulation of cytokinesis,”“G1/S transition of mitotic cell cycle,”“DNA recombination,” and “telomere maintenance,” respectively. Remarkably, we identified six chromatin state-marked C1-FFL instances (HCFC1- NFYA-ABL1, THAP1-USF1-BRCA2, ZNF263-USF1-UBA52, MYC-ATF1-UBA52, ELK1-EGR1-CCT4, and YY1- EGR1-INO80C) could act as prognostic biomarkers of acute myelogenous leukemia though influencing cancer-related biological functions, such as cell proliferation, telomere maintenance, and DNA recombination.
    [Show full text]
  • A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family
    Rockefeller University Digital Commons @ RU Student Theses and Dissertations 2018 A High-Throughput Approach to Uncover Novel Roles of APOBEC2, a Functional Orphan of the AID/APOBEC Family Linda Molla Follow this and additional works at: https://digitalcommons.rockefeller.edu/ student_theses_and_dissertations Part of the Life Sciences Commons A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY A Thesis Presented to the Faculty of The Rockefeller University in Partial Fulfillment of the Requirements for the degree of Doctor of Philosophy by Linda Molla June 2018 © Copyright by Linda Molla 2018 A HIGH-THROUGHPUT APPROACH TO UNCOVER NOVEL ROLES OF APOBEC2, A FUNCTIONAL ORPHAN OF THE AID/APOBEC FAMILY Linda Molla, Ph.D. The Rockefeller University 2018 APOBEC2 is a member of the AID/APOBEC cytidine deaminase family of proteins. Unlike most of AID/APOBEC, however, APOBEC2’s function remains elusive. Previous research has implicated APOBEC2 in diverse organisms and cellular processes such as muscle biology (in Mus musculus), regeneration (in Danio rerio), and development (in Xenopus laevis). APOBEC2 has also been implicated in cancer. However the enzymatic activity, substrate or physiological target(s) of APOBEC2 are unknown. For this thesis, I have combined Next Generation Sequencing (NGS) techniques with state-of-the-art molecular biology to determine the physiological targets of APOBEC2. Using a cell culture muscle differentiation system, and RNA sequencing (RNA-Seq) by polyA capture, I demonstrated that unlike the AID/APOBEC family member APOBEC1, APOBEC2 is not an RNA editor. Using the same system combined with enhanced Reduced Representation Bisulfite Sequencing (eRRBS) analyses I showed that, unlike the AID/APOBEC family member AID, APOBEC2 does not act as a 5-methyl-C deaminase.
    [Show full text]
  • Novel Targets of Apparently Idiopathic Male Infertility
    International Journal of Molecular Sciences Review Molecular Biology of Spermatogenesis: Novel Targets of Apparently Idiopathic Male Infertility Rossella Cannarella * , Rosita A. Condorelli , Laura M. Mongioì, Sandro La Vignera * and Aldo E. Calogero Department of Clinical and Experimental Medicine, University of Catania, 95123 Catania, Italy; [email protected] (R.A.C.); [email protected] (L.M.M.); [email protected] (A.E.C.) * Correspondence: [email protected] (R.C.); [email protected] (S.L.V.) Received: 8 February 2020; Accepted: 2 March 2020; Published: 3 March 2020 Abstract: Male infertility affects half of infertile couples and, currently, a relevant percentage of cases of male infertility is considered as idiopathic. Although the male contribution to human fertilization has traditionally been restricted to sperm DNA, current evidence suggest that a relevant number of sperm transcripts and proteins are involved in acrosome reactions, sperm-oocyte fusion and, once released into the oocyte, embryo growth and development. The aim of this review is to provide updated and comprehensive insight into the molecular biology of spermatogenesis, including evidence on spermatogenetic failure and underlining the role of the sperm-carried molecular factors involved in oocyte fertilization and embryo growth. This represents the first step in the identification of new possible diagnostic and, possibly, therapeutic markers in the field of apparently idiopathic male infertility. Keywords: spermatogenetic failure; embryo growth; male infertility; spermatogenesis; recurrent pregnancy loss; sperm proteome; DNA fragmentation; sperm transcriptome 1. Introduction Infertility is a widespread condition in industrialized countries, affecting up to 15% of couples of childbearing age [1]. It is defined as the inability to achieve conception after 1–2 years of unprotected sexual intercourse [2].
    [Show full text]
  • A Genomic View of Estrogen Actions in Human Breast Cancer Cells by Expression Profiling of the Hormone-Responsive Transcriptome
    719 A genomic view of estrogen actions in human breast cancer cells by expression profiling of the hormone-responsive transcriptome Luigi Cicatiello1, Claudio Scafoglio1, Lucia Altucci1, Massimo Cancemi1, Guido Natoli1, Angelo Facchiano2, Giovanni Iazzetti3, Raffaele Calogero4, Nicoletta Biglia6, Michele De Bortoli5,7, Christian Sfiligoi7, Piero Sismondi6,7, Francesco Bresciani1 and Alessandro Weisz1 1Dipartimento di Patologia generale, Seconda Università degli Studi di Napoli, Vico L. De Crecchio 7, 80138 Napoli, Italy 2Istituto di Scienze dell’Alimentazione del Consiglio Nazionale delle Ricerche, Avellino, Italy 3Dipartimento di Genetica, Biologia generale e molecolare, Università di Napoli ‘Federico II’, Napoli, Italy 4Dipartimento di Scienze cliniche e biologiche, Università degli Studi di Torino, Torino, Italy 5Dipartimento di Scienze oncologiche, Università degli Studi di Torino, Torino, Italy 6Dipartimento di Discipline ostetriche e ginecologiche, Università degli Studi di Torino, Torino, Italy 7Laboratorio di Ginecologia oncologica, Istituto per la Ricerca e la Cura del Cancro, Candiolo, Italy (Requests for offprints should be addressed to A Weisz; Email: [email protected]) Abstract Estrogen controls key cellular functions of responsive cells including the ability to survive, replicate, communicate and adapt to the extracellular milieu. Changes in the expression of 8400 genes were monitored here by cDNA microarray analysis during the first 32 h of human breast cancer (BC) ZR-75·1 cell stimulation with a mitogenic dose of 17-estradiol, a timing which corresponds to completion of a full mitotic cycle in hormone-stimulated cells. Hierarchical clustering of 344 genes whose expression either increases or decreases significantly in response to estrogen reveals that the gene expression program activated by the hormone in these cells shows 8 main patterns of gene activation/inhibition.
    [Show full text]