Assembly Principles and Stoichiometry of a Complete Human Kinetochore Module
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PDW CV March 2014
Curriculum Vitae Dr. ir. Peter De Wulf Contact information European Institute of Oncology Department of Experimental Oncology Via Adamello 16 20139 Milan, Italy E-mail: [email protected] Tel: (++39) 0294375036 Fax: (++39) 0294375990 Position 08/2005 - present Principal Investigator Director Kinetochore and Chromosome Segregation Research Unit Department of Experimental Oncology European Institute of Oncology Milan, Italy Education and training 11/1999 - 06/2005 Post-Doctoral Research in Yeast Kinetochore Biology Department of Biology Massachusetts Institute of Technology 77 Massachusetts Avenue 02139 Cambridge (MA), USA Mentor: Prof. Dr. Peter K. Sorger (now at Harvard Medical School, Department of Systems Biology) 07/1996 - 10/1999 Post-Doctoral Research in Bacterial Two-Component Signal Transduction Department of Microbiology and Molecular Genetics Harvard Medical School 210 Longwood Avenue 02115 Boston (MA), USA Mentor: Prof. Dr. Edmund C.C. Lin (deceased) 04-20/07/1999 Course in Protein Purification and Characterization Cold Spring Harbor Laboratory. Cold Spring Harbor (NY), USA Instructors: Dr. Richard Burgess, Dr. Albert Courey, Dr. Sue-Hwa Lin, Dr. Sheenah Mische 06-20/06/1997 Course in Advanced Bacterial Genetics Cold Spring Harbor Laboratory. Cold Spring Harbor (NY), USA Instructors: Dr. Bonnie Bassler, Dr. Colin Manoil, Dr. James Slauch 06/1995 - 06/1996 Training in Yeast Cell Biology Department of Applied Biochemistry University of Milan via Celoria 26 20133 Milan, Italy Mentor: Prof. Dr. Lilia Alberghina (now at the University of Milan-Bicocca, Department of Biotechnology and Biosciences) 1 01/1992-05/1995 Ph.D. in Industrial Microbiology and Biocatalysis Department of Biochemical and Microbial Technology School of Bioengineering University of Ghent Coupure Links 653 B-9000 Ghent, Belgium Mentor: Prof. -
CENPT (NM 025082) Human 3' UTR Clone – SC200995 | Origene
OriGene Technologies, Inc. 9620 Medical Center Drive, Ste 200 Rockville, MD 20850, US Phone: +1-888-267-4436 [email protected] EU: [email protected] CN: [email protected] Product datasheet for SC200995 CENPT (NM_025082) Human 3' UTR Clone Product data: Product Type: 3' UTR Clones Product Name: CENPT (NM_025082) Human 3' UTR Clone Vector: pMirTarget (PS100062) Symbol: CENPT Synonyms: C16orf56; CENP-T; SSMGA ACCN: NM_025082 Insert Size: 140 bp Insert Sequence: >SC200995 3’UTR clone of NM_025082 The sequence shown below is from the reference sequence of NM_025082. The complete sequence of this clone may contain minor differences, such as SNPs. Blue=Stop Codon Red=Cloning site GGCAAGTTGGACGCCCGCAAGATCCGCGAGATTCTCATTAAGGCCAAGAAGGGCGGAAAGATCGCCGTG TAACAATTGGCAGAGCTCAGAATTCAAGCGATCGCC AGTGGCAACTCTGTCTTCCCTGCCCAGTAGTGGCCAGGCTTCAACACTTTCCCTGTCCCCACCTGGGGA CTCTTGCCCCCACATATTTCTCCAGGTCTCCTCCCCACCCCCCCAGCATCAATAAAGTGTCATAAACAG AA ACGCGTAAGCGGCCGCGGCATCTAGATTCGAAGAAAATGACCGACCAAGCGACGCCCAACCTGCCATCA CGAGATTTCGATTCCACCGCCGCCTTCTATGAAAGG Restriction Sites: SgfI-MluI OTI Disclaimer: Our molecular clone sequence data has been matched to the sequence identifier above as a point of reference. Note that the complete sequence of this clone is largely the same as the reference sequence but may contain minor differences , e.g., single nucleotide polymorphisms (SNPs). RefSeq: NM_025082.4 Summary: The centromere is a specialized chromatin domain, present throughout the cell cycle, that acts as a platform on which the transient assembly of the kinetochore occurs during mitosis. All active centromeres are characterized by the presence of long arrays of nucleosomes in which CENPA (MIM 117139) replaces histone H3 (see MIM 601128). CENPT is an additional factor required for centromere assembly (Foltz et al., 2006 [PubMed 16622419]).[supplied by OMIM, Mar 2008] Locus ID: 80152 This product is to be used for laboratory only. Not for diagnostic or therapeutic use. -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
Gene Knockdown of CENPA Reduces Sphere Forming Ability and Stemness of Glioblastoma Initiating Cells
Neuroepigenetics 7 (2016) 6–18 Contents lists available at ScienceDirect Neuroepigenetics journal homepage: www.elsevier.com/locate/nepig Gene knockdown of CENPA reduces sphere forming ability and stemness of glioblastoma initiating cells Jinan Behnan a,1, Zanina Grieg b,c,1, Mrinal Joel b,c, Ingunn Ramsness c, Biljana Stangeland a,b,⁎ a Department of Molecular Medicine, Institute of Basic Medical Sciences, The Medical Faculty, University of Oslo, Oslo, Norway b Norwegian Center for Stem Cell Research, Department of Immunology and Transfusion Medicine, Oslo University Hospital, Oslo, Norway c Vilhelm Magnus Laboratory for Neurosurgical Research, Institute for Surgical Research and Department of Neurosurgery, Oslo University Hospital, Oslo, Norway article info abstract Article history: CENPA is a centromere-associated variant of histone H3 implicated in numerous malignancies. However, the Received 20 May 2016 role of this protein in glioblastoma (GBM) has not been demonstrated. GBM is one of the most aggressive Received in revised form 23 July 2016 human cancers. GBM initiating cells (GICs), contained within these tumors are deemed to convey Accepted 2 August 2016 characteristics such as invasiveness and resistance to therapy. Therefore, there is a strong rationale for targeting these cells. We investigated the expression of CENPA and other centromeric proteins (CENPs) in Keywords: fi CENPA GICs, GBM and variety of other cell types and tissues. Bioinformatics analysis identi ed the gene signature: fi Centromeric proteins high_CENP(AEFNM)/low_CENP(BCTQ) whose expression correlated with signi cantly worse GBM patient Glioblastoma survival. GBM Knockdown of CENPA reduced sphere forming ability, proliferation and cell viability of GICs. We also Brain tumor detected significant reduction in the expression of stemness marker SOX2 and the proliferation marker Glioblastoma initiating cells and therapeutic Ki67. -
1 AGING Supplementary Table 2
SUPPLEMENTARY TABLES Supplementary Table 1. Details of the eight domain chains of KIAA0101. Serial IDENTITY MAX IN COMP- INTERFACE ID POSITION RESOLUTION EXPERIMENT TYPE number START STOP SCORE IDENTITY LEX WITH CAVITY A 4D2G_D 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ B 4D2G_E 52 - 69 52 69 100 100 2.65 Å PCNA X-RAY DIFFRACTION √ C 6EHT_D 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ D 6EHT_E 52 - 71 52 71 100 100 3.2Å PCNA X-RAY DIFFRACTION √ E 6GWS_D 41-72 41 72 100 100 3.2Å PCNA X-RAY DIFFRACTION √ F 6GWS_E 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ G 6GWS_F 41-72 41 72 100 100 2.9Å PCNA X-RAY DIFFRACTION √ H 6IIW_B 2-11 2 11 100 100 1.699Å UHRF1 X-RAY DIFFRACTION √ www.aging-us.com 1 AGING Supplementary Table 2. Significantly enriched gene ontology (GO) annotations (cellular components) of KIAA0101 in lung adenocarcinoma (LinkedOmics). Leading Description FDR Leading Edge Gene EdgeNum RAD51, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, CENPW, HJURP, NDC80, CDCA5, NCAPH, BUB1, ZWILCH, CENPK, KIF2C, AURKA, CENPN, TOP2A, CENPM, PLK1, ERCC6L, CDT1, CHEK1, SPAG5, CENPH, condensed 66 0 SPC24, NUP37, BLM, CENPE, BUB3, CDK2, FANCD2, CENPO, CENPF, BRCA1, DSN1, chromosome MKI67, NCAPG2, H2AFX, HMGB2, SUV39H1, CBX3, TUBG1, KNTC1, PPP1CC, SMC2, BANF1, NCAPD2, SKA2, NUP107, BRCA2, NUP85, ITGB3BP, SYCE2, TOPBP1, DMC1, SMC4, INCENP. RAD51, OIP5, CDK1, SPC25, CCNB1, BIRC5, NCAPG, ZWINT, MAD2L1, SKA3, NUF2, BUB1B, CENPA, SKA1, AURKB, NEK2, ESCO2, CENPW, HJURP, TTK, NDC80, CDCA5, BUB1, ZWILCH, CENPK, KIF2C, AURKA, DSCC1, CENPN, CDCA8, CENPM, PLK1, MCM6, ERCC6L, CDT1, HELLS, CHEK1, SPAG5, CENPH, PCNA, SPC24, CENPI, NUP37, FEN1, chromosomal 94 0 CENPL, BLM, KIF18A, CENPE, MCM4, BUB3, SUV39H2, MCM2, CDK2, PIF1, DNA2, region CENPO, CENPF, CHEK2, DSN1, H2AFX, MCM7, SUV39H1, MTBP, CBX3, RECQL4, KNTC1, PPP1CC, CENPP, CENPQ, PTGES3, NCAPD2, DYNLL1, SKA2, HAT1, NUP107, MCM5, MCM3, MSH2, BRCA2, NUP85, SSB, ITGB3BP, DMC1, INCENP, THOC3, XPO1, APEX1, XRCC5, KIF22, DCLRE1A, SEH1L, XRCC3, NSMCE2, RAD21. -
Supplementary Table S1. Correlation Between the Mutant P53-Interacting Partners and PTTG3P, PTTG1 and PTTG2, Based on Data from Starbase V3.0 Database
Supplementary Table S1. Correlation between the mutant p53-interacting partners and PTTG3P, PTTG1 and PTTG2, based on data from StarBase v3.0 database. PTTG3P PTTG1 PTTG2 Gene ID Coefficient-R p-value Coefficient-R p-value Coefficient-R p-value NF-YA ENSG00000001167 −0.077 8.59e-2 −0.210 2.09e-6 −0.122 6.23e-3 NF-YB ENSG00000120837 0.176 7.12e-5 0.227 2.82e-7 0.094 3.59e-2 NF-YC ENSG00000066136 0.124 5.45e-3 0.124 5.40e-3 0.051 2.51e-1 Sp1 ENSG00000185591 −0.014 7.50e-1 −0.201 5.82e-6 −0.072 1.07e-1 Ets-1 ENSG00000134954 −0.096 3.14e-2 −0.257 4.83e-9 0.034 4.46e-1 VDR ENSG00000111424 −0.091 4.10e-2 −0.216 1.03e-6 0.014 7.48e-1 SREBP-2 ENSG00000198911 −0.064 1.53e-1 −0.147 9.27e-4 −0.073 1.01e-1 TopBP1 ENSG00000163781 0.067 1.36e-1 0.051 2.57e-1 −0.020 6.57e-1 Pin1 ENSG00000127445 0.250 1.40e-8 0.571 9.56e-45 0.187 2.52e-5 MRE11 ENSG00000020922 0.063 1.56e-1 −0.007 8.81e-1 −0.024 5.93e-1 PML ENSG00000140464 0.072 1.05e-1 0.217 9.36e-7 0.166 1.85e-4 p63 ENSG00000073282 −0.120 7.04e-3 −0.283 1.08e-10 −0.198 7.71e-6 p73 ENSG00000078900 0.104 2.03e-2 0.258 4.67e-9 0.097 3.02e-2 Supplementary Table S2. -
Greg's Awesome Thesis
Analysis of alignment error and sitewise constraint in mammalian comparative genomics Gregory Jordan European Bioinformatics Institute University of Cambridge A dissertation submitted for the degree of Doctor of Philosophy November 30, 2011 To my parents, who kept us thinking and playing This dissertation is the result of my own work and includes nothing which is the out- come of work done in collaboration except where specifically indicated in the text and acknowledgements. This dissertation is not substantially the same as any I have submitted for a degree, diploma or other qualification at any other university, and no part has already been, or is currently being submitted for any degree, diploma or other qualification. This dissertation does not exceed the specified length limit of 60,000 words as defined by the Biology Degree Committee. November 30, 2011 Gregory Jordan ii Analysis of alignment error and sitewise constraint in mammalian comparative genomics Summary Gregory Jordan November 30, 2011 Darwin College Insight into the evolution of protein-coding genes can be gained from the use of phylogenetic codon models. Recently sequenced mammalian genomes and powerful analysis methods developed over the past decade provide the potential to globally measure the impact of natural selection on pro- tein sequences at a fine scale. The detection of positive selection in particular is of great interest, with relevance to the study of host-parasite conflicts, immune system evolution and adaptive dif- ferences between species. This thesis examines the performance of methods for detecting positive selection first with a series of simulation experiments, and then with two empirical studies in mammals and primates. -
XBP1 Negatively Regulates CENPF Expression Via Recruiting Atf6α to the Promoter During ER Stress Tao Shen1* , Yan Li2,3, Shuang Liang4 and Zhiguang Chen1
Shen et al. Cancer Cell Int (2020) 20:459 https://doi.org/10.1186/s12935-020-01553-9 Cancer Cell International PRIMARY RESEARCH Open Access XBP1 negatively regulates CENPF expression via recruiting ATF6α to the promoter during ER stress Tao Shen1* , Yan Li2,3, Shuang Liang4 and Zhiguang Chen1 Abstract Background: Centromere protein F (CENPF) is a key component of the kinetochore complex involved in mitosis, cell diferentiation and cellular response to stresses. However, the alteration of CENPF in response to endoplasmic reticulum (ER) stress has not been well described. In the present study, we investigate CENPF regulation in response to ER stress. Methods: Quantitative real-time polymerase chain reaction and western blotting were used to determine CENPF expression under ER stress. Luciferase activity analysis was performed to investigate the promoter regions contribut- ing to CENPF transcription in response to TG. Chromatin immunoprecipitation (ChIP) and ChIP Re-IP assays were used to determine if X-box binding protein 1 (XBP1) and/or activating transcription factor 6α (ATF6α) bind in the CENPF promoter region. Cell apoptosis and proliferation were analyzed using TUNEL, cell growth and clonogenic assays. Results: CENPF expression is dramatically reduced under ER stress induced by thapsigargin (TG), brefeldin A (BFA), or tunicamycin (TM) and this downregulation of CENPF expression was dependent on XBP1 and ATF6α. Luciferase activity analysis of the truncated CENPF promoter indicates that regions from bases 679 to 488 and from 241 to 78 in the CENPF promoter were sensitive to TG treatment. Additionally, ChIP and− ChIP Re-IP− assays reveal −that XBP1− and ATF6α were assembled on the same regions of CENPF promoter. -
Birth, Evolution, and Transmission of Satellite-Free Mammalian Centromeric Domains
Downloaded from genome.cshlp.org on October 7, 2021 - Published by Cold Spring Harbor Laboratory Press Research Birth, evolution, and transmission of satellite-free mammalian centromeric domains Solomon G. Nergadze,1,6 Francesca M. Piras,1,6 Riccardo Gamba,1,6 Marco Corbo,1,6 † Federico Cerutti,1, Joseph G.W. McCarter,2 Eleonora Cappelletti,1 Francesco Gozzo,1 Rebecca M. Harman,3 Douglas F. Antczak,3 Donald Miller,3 Maren Scharfe,4 Giulio Pavesi,5 Elena Raimondi,1 Kevin F. Sullivan,2 and Elena Giulotto1 1Department of Biology and Biotechnology “Lazzaro Spallanzani,” University of Pavia, 27100 Pavia, Italy; 2Centre for Chromosome Biology, School of Natural Sciences, National University of Ireland, Galway, H91 TK33, Ireland; 3Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, New York 14850, USA; 4Genomanalytik (GMAK), Helmholtz Centre for Infection Research (HZI), 38124 Braunschweig, Germany; 5Department of Biosciences, University of Milano, 20122 Milano, Italy Mammalian centromeres are associated with highly repetitive DNA (satellite DNA), which has so far hindered molecular analysis of this chromatin domain. Centromeres are epigenetically specified, and binding of the CENPA protein is their main determinant. In previous work, we described the first example of a natural satellite-free centromere on Equus caballus Chromosome 11. Here, we investigated the satellite-free centromeres of Equus asinus by using ChIP-seq with anti-CENPA an- tibodies. We identified an extraordinarily high number of centromeres lacking satellite DNA (16 of 31). All of them lay in LINE- and AT-rich regions. A subset of these centromeres is associated with DNA amplification. The location of CENPA binding domains can vary in different individuals, giving rise to epialleles. -
Ribosomal DNA Copy Number Is Coupled with Gene Expression Variation and Mitochondrial Abundance in Humans
ARTICLE Received 12 Apr 2014 | Accepted 30 Jul 2014 | Published 11 Sep 2014 DOI: 10.1038/ncomms5850 Ribosomal DNA copy number is coupled with gene expression variation and mitochondrial abundance in humans John G. Gibbons1, Alan T. Branco1, Shoukai Yu1 & Bernardo Lemos1 Ribosomes are essential intracellular machines composed of proteins and RNA molecules. The DNA sequences (rDNA) encoding ribosomal RNAs (rRNAs) are tandemly repeated and give origin to the nucleolus. Here we develop a computational method for estimating rDNA dosage (copy number) and mitochondrial DNA abundance using whole-genome short-read DNA sequencing. We estimate these attributes across hundreds of human genomes and their association with global gene expression. The analyses uncover abundant variation in rDNA dosage that is coupled with the expression of hundreds of functionally coherent gene sets. These include associations with genes coding for chromatin components that target the nucleolus, including CTCF and HP1b. Finally, the data show an inverse association between rDNA dosage and mitochondrial DNA abundance that is manifested across genotypes. Our findings uncover a novel and cryptic source of hypervariable genomic diversity with global regulatory consequences (ribosomal eQTL) in humans. The variation provides a mechanism for cellular homeostasis and for rapid and reversible adaptation. 1 Program in Molecular and Integrative Physiological Sciences, Department of Environmental Health, Harvard School of Public Health, 665 Huntington Avenue, Building 2, Room 219, Boston, Massachusetts 02115, USA. Correspondence and requests for materials should be addressed to B.L. (email: [email protected]). NATURE COMMUNICATIONS | 5:4850 | DOI: 10.1038/ncomms5850 | www.nature.com/naturecommunications 1 & 2014 Macmillan Publishers Limited. -
Explorative Bioinformatic Analysis of Cardiomyocytes in 2D &3D in Vitro Culture System
EXPLORATIVE BIOINFORMATIC ANALYSIS OF CARDIOMYOCYTES IN 2D &3D IN VITRO CULTURE SYSTEM VERSION 2 Master Degree Project in Bioscience One years Level, 60 ECTS Sruthy Janardanan [email protected] Supervisor: Jane Synnergren [email protected] Examiner: Sanja Jurcevic [email protected] Abstract The in vitro cell culture models of human pluripotent stem cells (hPSC)-derived cardiomyocytes (CMs) have gained a predominant value in the field of drug discovery and is considered an attractive tool for cardiovascular disease modellings. However, despite several reports of different protocols for the hPSC-differentiation into CMs, the development of an efficient, controlled and reproducible 3D differentiation remains challenging. The main aim of this research study was to understand the changes in the gene expression as an impact of spatial orientation of hPSC-derived CMs in 2D(two-dimensional) and 3D(three-dimensional) culture conditions and to identify the topologically important Hub and Hub-Bottleneck proteins using centrality measures to gain new knowledge for standardizing the pre-clinical models for the regeneration of CMs. The above-mentioned aim was achieved through an extensive bioinformatic analysis on the list of differentially expressed genes (DEGs) identified from RNA-sequencing (RNA-Seq). Functional annotation analysis of the DEGs from both 2D and 3D was performed using Cytoscape plug-in ClueGO. Followed by the topological analysis of the protein-protein interaction network (PPIN) using two centrality parameters; Degree and Betweeness in Cytoscape plug-in CenTiScaPe. The results obtained revealed that compared to 2D, DEGs in 3D are primarily associated with cell signalling suggesting the interaction between cells as an impact of the 3D microenvironment and topological analysis revealed 32 and 39 proteins as Hub and Hub-Bottleneck proteins, respectively in 3D indicating the possibility of utilizing those identified genes and their corresponding proteins as cardiac disease biomarkers in future by further research. -
Rapid Molecular Assays to Study Human Centromere Genomics
Downloaded from genome.cshlp.org on September 26, 2021 - Published by Cold Spring Harbor Laboratory Press Method Rapid molecular assays to study human centromere genomics Rafael Contreras-Galindo,1 Sabrina Fischer,1,2 Anjan K. Saha,1,3,4 John D. Lundy,1 Patrick W. Cervantes,1 Mohamad Mourad,1 Claire Wang,1 Brian Qian,1 Manhong Dai,5 Fan Meng,5,6 Arul Chinnaiyan,7,8 Gilbert S. Omenn,1,9,10 Mark H. Kaplan,1 and David M. Markovitz1,4,11,12 1Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA; 2Laboratory of Molecular Virology, Centro de Investigaciones Nucleares, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay 11400; 3Medical Scientist Training Program, University of Michigan, Ann Arbor, Michigan 48109, USA; 4Program in Cancer Biology, University of Michigan, Ann Arbor, Michigan 48109, USA; 5Molecular and Behavioral Neuroscience Institute, University of Michigan, Ann Arbor, Michigan 48109, USA; 6Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109, USA; 7Michigan Center for Translational Pathology and Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan 48109, USA; 8Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA; 9Department of Human Genetics, 10Departments of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA; 11Program in Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA; 12Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan 48109, USA The centromere is the structural unit responsible for the faithful segregation of chromosomes. Although regulation of cen- tromeric function by epigenetic factors has been well-studied, the contributions of the underlying DNA sequences have been much less well defined, and existing methodologies for studying centromere genomics in biology are laborious.