Miro-Dependent Mitochondrial Pool of CENP-F and Its Farnesylated C-Terminal Domain Are Dispensable for Normal Development in Mice
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Y-Chromosome Short Tandem Repeat, Typing Technology, Locus Information and Allele Frequency in Different Population: a Review
Vol. 14(27), pp. 2175-2178, 8 July, 2015 DOI:10.5897/AJB2015.14457 Article Number: 2E48C3F54052 ISSN 1684-5315 African Journal of Biotechnology Copyright © 2015 Author(s) retain the copyright of this article http://www.academicjournals.org/AJB Review Y-Chromosome short tandem repeat, typing technology, locus information and allele frequency in different population: A review Muhanned Abdulhasan Kareem1, Ameera Omran Hussein2 and Imad Hadi Hameed2* 1Babylon University, Centre of Environmental Research, Hilla City, Iraq. 2Department of Molecular Biology, Babylon University, Hilla City, Iraq. Received 29 January, 2015; Accepted 29 June, 2015 Chromosome Y microsatellites seem to be ideal markers to delineate differences between human populations. They are transmitted in uniparental and they are very sensitive for genetic drift. This review will highlight the importance of the Y- Chromosome as a tool for tracing human evolution and describes some details of Y-chromosomal short tandem repeat (STR) analysis. Among them are: microsatellites, amplification using polymerase chain reaction (PCR) of STRs, separation and detection and advantages of X-chromosomal microsatellites. Key words: Forensic, population, review, STR, Y- chromosome. INTRODUCTION Microsatellites are DNA regions with repeat units that are microsatellite, but repeats of five (penta-) or six (hexa-) 2 to 7 bp in length or most generally short tandem nucleotides are usually classified as microsatellites as repeats (STRs) or simple sequence repeats (SSRs) well. DNA can be used to study human evolution. (Ellegren, 2000; Imad et al., 2014). The classification of Besides, information from DNA typing is important for the DNA sequences is determined by the length of the medico-legal matters with polymorphisms leading to more core repeat unit and the number of adjacent repeat units. -
Combinatorial Genomic Data Refute the Human Chromosome 2 Evolutionary Fusion and Build a Model of Functional Design for Interstitial Telomeric Repeats
The Proceedings of the International Conference on Creationism Volume 8 Print Reference: Pages 222-228 Article 32 2018 Combinatorial Genomic Data Refute the Human Chromosome 2 Evolutionary Fusion and Build a Model of Functional Design for Interstitial Telomeric Repeats Jeffrey P. Tomkins Institute for Creation Research Follow this and additional works at: https://digitalcommons.cedarville.edu/icc_proceedings Part of the Biology Commons, and the Genomics Commons DigitalCommons@Cedarville provides a publication platform for fully open access journals, which means that all articles are available on the Internet to all users immediately upon publication. However, the opinions and sentiments expressed by the authors of articles published in our journals do not necessarily indicate the endorsement or reflect the views of DigitalCommons@Cedarville, the Centennial Library, or Cedarville University and its employees. The authors are solely responsible for the content of their work. Please address questions to [email protected]. Browse the contents of this volume of The Proceedings of the International Conference on Creationism. Recommended Citation Tomkins, J.P. 2018. Combinatorial genomic data refute the human chromosome 2 evolutionary fusion and build a model of functional design for interstitial telomeric repeats. In Proceedings of the Eighth International Conference on Creationism, ed. J.H. Whitmore, pp. 222–228. Pittsburgh, Pennsylvania: Creation Science Fellowship. Tomkins, J.P. 2018. Combinatorial genomic data refute the human chromosome 2 evolutionary fusion and build a model of functional design for interstitial telomeric repeats. In Proceedings of the Eighth International Conference on Creationism, ed. J.H. Whitmore, pp. 222–228. Pittsburgh, Pennsylvania: Creation Science Fellowship. COMBINATORIAL GENOMIC DATA REFUTE THE HUMAN CHROMOSOME 2 EVOLUTIONARY FUSION AND BUILD A MODEL OF FUNCTIONAL DESIGN FOR INTERSTITIAL TELOMERIC REPEATS Jeffrey P. -
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. -
Microdeletion of the Azfc Locus with High Frequency of Mosaicism 46,XY/47XYY in Cases of Non Obstructive Azoospermia in Eastern Population of India
Microdeletion of the AZFc locus with high frequency of mosaicism 46,XY/47XYY in cases of non obstructive azoospermia in eastern population of India A.K. Saxena and K. Aniket Department of Pathology/Lab Medicine, Molecular Cytogenetics Laboratory, All India Institute of Medical Sciences, Patna (Bihar), India Corresponding author: A.K. Saxena E-mail: [email protected] Genet. Mol. Res. 18 (2): gmr18349 Received May 07, 2019 Accepted June 06, 2019 Published June 18, 2019 DOI http://dx.doi.org/10.4238/gmr18349 ABSTRACT. The etiopathology of male infertility is highly complex, involving gene - environment interactions to regulate spermatogenesis. Consequently, genetic analysis becomes imperative for cases of non-obstructive azoospermia (NOA) to identify the causative factors. Cases (n = 111) of NOA referred to the cytogenetics and molecular genetics laboratory of the All India Institute of Medical Sciences in -Patna from 2013-2018 were subjected to 1) karyotyping using GTG bandings techniques, 2) fluorescence in situ hybridization (FISH) for the sex determining region (SRY), and 3) PCR based analysis of STS markers based on microdeletion of the Y- chromosome after isolation of genomic DNA from whole blood. A flow cytometer was used for a cell- kinetic and DNA methylation study after incorporation of 5-azacytidine (5- AzaC) (1.0 ug/mL) in lymphocyte culture. PCR products were analyzed on an agarose gel (1.5%) and bands were visualized on Gel Doc after ethidium bromide staining. Chromosomal abnormalities, including structural numerical variations, were observed in 14 of the karyotypes. Eight cases showed a 46,XY/47,XYY i.e. mosaic pattern; two cases 46, XY/45/XO; a single case with 47,XY +16; two cases with 46,X+ ring Y; a single case with 46,XY+dicentric in Genetics and Molecular Research 18 (2): gmr18349 ©FUNPEC-RP www.funpecrp.com.br A.K. -
A Genetic Map of Chromosome 11 Q. Including the Atopy Locus
Original Paper EurJ Hum Genet 1995;3:188-194 A.J. Sandforda A Genetic Map of Chromosome M.F. Moffat t* S.E. Danielsa 11 q. Including the Atopy Locus Y. Nakamura'0 GM. Lathropc J.M. Hopkind W.O.CM. Cooksona 1608202 a Nuffield Department of Medicine, John Radcliffe Hospital, Oxford, UK; b Division of Biochemistry, Abstract Cancer Institute, Tokyo, Japan; Atopy is a common and genetically heterogeneous syndrome c CEPHB, Paris, France; and predisposing to allergic asthma and rhinitis. A locus linked to d Osier Chest Unit, Churchill Hospital, Oxford, UK the atopy phenotype has been shown to be present on chromo some llql2-13. Linkage has only been seen in maternally derived alleles. We have constructed a genetic linkage map of Key Words the region, using 15 markers to span approximately 27 cM, Atopy and integrate previously published maps. Under a model of Genetic map maternal inheritance, the atopy locus is placed within a 7-cM Linkage analysis interval between D11S480 and D11S451. The interval con Chromosome 11 tains the important candidate gene FCERIB. Introduction The linkage has been replicated in nuclear families [3], and has been independently con Atopy is a common familial syndrome firmed in extended Japanese families [4], and which underlies allergic asthma and rhinitis. Dutch asthmatic sib pairs [5]. All these posi It is characterised by immunoglobulin E re tive linkage results were seen in families with sponses to common aero-allergens such as severe symptomatic atopy. Linkage at this grass pollens or house dust mite. An atopy- locus is made more difficult because it is seen associated phenotype may be defined by mea predominately through maternal meioses [3- suring prick skin test responses to these aller 7], Linkage is also confounded by a high pop gens, by measuring specific IgE responses and ulation prevalence, and low penetrance in ear by estimating the total serum IgE. -
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. -
Glossary/Index
Glossary 03/08/2004 9:58 AM Page 119 GLOSSARY/INDEX The numbers after each term represent the chapter in which it first appears. additive 2 allele 2 When an allele’s contribution to the variation in a One of two or more alternative forms of a gene; a single phenotype is separately measurable; the independent allele for each gene is inherited separately from each effects of alleles “add up.” Antonym of nonadditive. parent. ADHD/ADD 6 Alzheimer’s disease 5 Attention Deficit Hyperactivity Disorder/Attention A medical disorder causing the loss of memory, rea- Deficit Disorder. Neurobehavioral disorders character- soning, and language abilities. Protein residues called ized by an attention span or ability to concentrate that is plaques and tangles build up and interfere with brain less than expected for a person's age. With ADHD, there function. This disorder usually first appears in persons also is age-inappropriate hyperactivity, impulsive over age sixty-five. Compare to early-onset Alzheimer’s. behavior or lack of inhibition. There are several types of ADHD: a predominantly inattentive subtype, a predomi- amino acids 2 nantly hyperactive-impulsive subtype, and a combined Molecules that are combined to form proteins. subtype. The condition can be cognitive alone or both The sequence of amino acids in a protein, and hence pro- cognitive and behavioral. tein function, is determined by the genetic code. adoption study 4 amnesia 5 A type of research focused on families that include one Loss of memory, temporary or permanent, that can result or more children raised by persons other than their from brain injury, illness, or trauma. -
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. -
A Genetic Locus on Chromosome 2Q24 Predicting Peripheral Neuropathy Risk in Type 2 Diabetes: Results from the ACCORD and BARI 2D Studies
Page 1 of 53 Diabetes A genetic locus on chromosome 2q24 predicting peripheral neuropathy risk in type 2 diabetes: results from the ACCORD and BARI 2D studies. Yaling Tang, M.D.1,2, Petra A. Lenzini, M.S.3, Rodica Pop Busui, M.D., Ph.D.4, Pradipta R. Ray, Ph.D5, Hannah Campbell, M.P.H3,6 , Bruce A. Perkins, M.D., M.P.H.7, Brian Callaghan, M.D., M.S.8, Michael J. Wagner, Ph.D.9, Alison A. Motsinger-Reif, Ph.D.10, John B. Buse, M.D., Ph.D.11, Theodore J. Price, Ph.D.5, Josyf C. Mychaleckyj, DPhil.12, Sharon Cresci, M.D.3,6, Hetal Shah, M.D., M.P.H.1,2*, Alessandro Doria, M.D., Ph.D., M.P.H.1,2* 1: Research Division, Joslin Diabetes Center, Boston, Massachusetts 2: Department of Medicine, Harvard Medical School, Boston, Massachusetts 3: Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 4: Department of Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, Michigan 5: School of Behavioral and Brain Sciences and Center for Advanced Pain Studies, The University of Texas at Dallas, Richardson, Texas 6: Department of Medicine, Washington University School of Medicine, St. Louis, Missouri 7: Leadership Sinai Centre for Diabetes, Sinai Health System and Division of Endocrinology & Metabolism, University of Toronto, Toronto, Canada 8: Department of Neurology, University of Michigan, Ann Arbor, Michigan 9: Center for Pharmacogenomics and Individualized Therapy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 10: Bioinformatics Research Center, and Department of Statistics, North Carolina State University, Raleigh, North Carolina 11: Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina 12: Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia * These authors contributed equally to this work and are co-senior authors. -
Cells Exhibiting Strong P16ink4a Promoter Activation in Vivo Display Features of Senescence
INK4a Cells exhibiting strong p16 promoter activation in vivo display features of senescence Jie-Yu Liua,b, George P. Souroullasc, Brian O. Diekmanb,d,e, Janakiraman Krishnamurthyb, Brandon M. Hallf, Jessica A. Sorrentinob, Joel S. Parkerb,g, Garrett A. Sessionsd, Andrei V. Gudkovf,h, and Norman E. Sharplessa,b,i,j,1 aCurriculum in Genetics and Molecular Biology, University of North Carolina School of Medicine, Chapel Hill, NC 27599; bThe Lineberger Comprehensive Cancer Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599; cDepartment of Medicine, Washington University School of Medicine, St. Louis, MO 63110; dThurston Arthritis Research Center, University of North Carolina School of Medicine, Chapel Hill, NC 27599; eJoint Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 and, North Carolina State University, Raleigh, NC 27695; fResearch Division, Everon Biosciences, Inc., Buffalo, NY 14203; gDepartment of Genetics, University of North Carolina School of Medicine, Chapel Hill, NC 27599; hDepartment of Cell Stress Biology, Roswell Park Cancer Institute, Buffalo, NY 14263; iDepartment of Medicine, University of North Carolina School of Medicine, Chapel Hill, NC 27599; and jOffice of the Director, The National Cancer Institute, Bethesda, MD 20892 Edited by Scott W. Lowe, Memorial Sloan Kettering Cancer Center, New York, NY, and approved December 17, 2018 (received for review October 31, 2018) The activation of cellular senescence throughout the lifespan has proven to be one of the most useful in vivo markers of se- INK4a promotes tumor suppression, whereas the persistence of senescent nescence. As a cell cycle regulator, p16 limits G1 to S-phase cells contributes to aspects of aging.