Telomeres-end+problem+of+replication
端粒和端粒酶telomeres and telomerase
Every chromosome has to contains one centromere, two telomeres, and multiple origins of replication
Blue = chromosomes
White = Telomere protein
Telomeres
Repeated G rich sequence on one strand in humans: (TTAGGG)n Repeats can be several thousand basepairs long. In humans, telomeric repeats average 5-15 kilobases Telomere specific proteins, eg. TRF1 & TRF2 bind to the repeat sequence and protect the ends
But…tumor cells often lack p53
Sensed as DNA damage by the p53 checkpoint
Cell division continues without telomeres leading to chromosomal rearrangements This genomic instability can promote tumorigenesis
Telomerase and Cancer
Could turning off telomerase in cancer cells cause them to senesce and thereby stop progression of the disease? Maybe Studies in an important model system, Telomerase deficient mice indicate that it will probably depend on the type of tumor.
DNA的生物合成(基因信息传递)
复制的基本规律(重点) ➢ 复制的方式 —半保留复制 (semi-conservative replication) ➢ 双向复制 (bidirectional replication) ➢ 半不连续复制 (semi-discontinuous replication)
复制中不连续的两条单链
切断、整理后的两链
结果 (dNTP)n+1
不连续→连续链 改变拓扑状态
第三节 DNA生物合成过程
The Process of DNA Replication
一、原核生物的DNA生物合成
（一）复制起始：DNA解链形成引发体
需要解决两个问题： 1. DNA解开成单链，提供模板。 2. 形成引发体，合成引物，提供3-OH末端。
二、DNA聚合酶催化核苷酸之间聚合
➢全称：依赖DNA的DNA聚合酶 (DNA-dependent
DNA polymerase，DNA-pol)
➢ 活性： 1. 53 的聚合活性 2. 核酸外切酶活性
①3 5外切酶活性: 能辨认错配的碱基对，并将其水解
②5 3外切酶活性: 能切除突变的 DNA片段。
CG
AT
AT
CG
CG
TA
TA
GC
GC
GC
GC
子代DNA
二、DNA复制从起始点向两个方向延伸
➢ 原核生物复制时，DNA从起始点(origin)向两个方向解链， 形成两个延伸方向相反的复制叉，称为双向复制。
ori
ter
A
B
A. 环状双链DNA及复制起始点
C
B. 复制中的两个复制叉
C. 复制接近终止点(termination, ter)
chapter 28-DNA replication
28.1 How is DNA replicated?
1. DNA replication is semiconservative 2. DNA replication is bidirectional 3. DNA replication is semidiscontinuous
How is DNA replicated?-I
site through base-pairing with the corresponding base in the template strand 2. Chain growth is in the 5->3 direction antiparallel to the template strand 3. DNA polymerases cannot initiate DNA synthesis de novo —all require a primer with a free 3-OH to build upon.
In prokaryotes, replicons are usually closed circles of DNA that have no ends. In most bacteria, linear molecules of DNA are degraded by exonucleases. Consequently, linear segments of DNA that enter a bacterial cell during conjugation or transformation will eventually be degraded.
E.coli DNA polymerase III holoenzyme-replicates chromosome
科技英语：科学家成功将人体衰老细胞转换成年轻细胞
Eternal youth could be one step closer following the successful transformation1 of old human cells into young ones.随着科学家成功地将人体衰老细胞转换成年轻的细胞，人类距离青春永驻的梦想将更近一步。
The process increases the length of the 'telomeres', which are the protective caps on the end of chromosomes2 that impact ageing and disease.Researchers in the US say the technique could extend human life and provide new hope for battling diseases that arise from old age.Telomeres - often described as being like the plastic caps on the end of shoelaces –help keep DNA3 healthy.These protective end caps become shorter with each DNA replication, and eventually are no longer able to protect DNA from sustaining damage and mutations, causing people to age.In young people, telomeres are about 8,000-10,000 organic molecules4, or nucleotides, long.'Now we have found a way to lengthen5 human telomeres by as much as 1,000 nucleotides, turning back the internal clock in these cells by the equivalent of many years of human life,' said Helen Blau of Stanford University.To make the discovery, researchers used modified messenger RNA to extend the telomeres.RNA carries instructions from genes6 in the DNA to the cell's protein-making factories.The RNA used in this experiment contained the coding sequence for TERT - the active component7 of a naturally occurring enzyme8 called telomerase.When the cells are treated, they behave as if they are younger and multiply quickly rather than dying.'One day it may be possible to target muscle stem cells in a patient with Duchenne muscular dystrophy, for example, to extend their telomeres,' said Dr Blau.'There are also implications for treating conditions of aging, such as diabetes9 and heart disease.'This has really opened the doors to consider all types of potential uses of this therapy.'The researchers also hope that the method will be able to allow scientists to generate large numbers of cells that could someday lead to an effective anti-aging drug.词汇解析：1 transformationn.变化；改造；转变参考例句：Going to college brought about a dramatic transformation in her outlook.上大学使她的观念发生了巨大的变化。
细胞生物学名词解释
1、细胞cell细胞是由膜包被的能独立进行繁殖的原生质团，是一切生物体结构和功能的基本单位，也是生命活动的基本单位。
2、构件分子building block molecules细胞内的各种元素构成的30种的小分子化合物，它们是构成生物大分子的基本单位，所以把它们称为构件分子。
3、生物大分子biological macromolecure细胞内的大分子物质主要包括核酸，蛋白质，糖类，脂类以及它们的复合体，其分子质量巨大，结构复杂，功能多样，称为生物大分子。
它们是细胞生命活动的重要物质基础。
4、肽键peptide bond一个氨基酸的a-氨基与另一个氨基酸的羧基在体外加热或体内由酶催化，可以脱水缩合成多肽，此新生成的酰胺键被称为肽键5、肽peptide氨基酸通过肽键相连的化合物6、蛋白质的一级结构primary structure蛋白质肽链中氨基酸残基的排列顺序，包括生成二硫键的两个Cys残基的位置。
7、DNA的一级结构DNA中脱氧核糖核苷酸残基的序列8、特定化学物质的区室化分布(compartmentalization )真核细胞有复杂的内膜系统，将细胞内环境分隔成许多功能不同的区室。
区室化使每一种细胞器都有其特有的酶系统和其他大分子物质，行使不同的代谢和生理功能，不同代谢过程既相互联系又互不干扰，充分发挥各自在生命活动中的特殊作用。
内膜系统。
真核细胞中，在结构、功能或发生上相关的，由膜围绕而成的细胞器或细胞结构，如核膜、内质网、高尔基体、线粒体、叶绿体、溶酶体等。
9、核酸nucleic acid由核苷酸聚合而成的生物大分子10、脱氧核苷酸deoxyribonucleic acid,DNA由dAMP、dGMP、dCMP和dTMP四种脱氧核糖核苷酸聚合而成的生物大分子。
11、3’,5’磷酸二酯键核酸链内的前一个核苷酸的3’羟基和下一个核苷酸的5’磷酸形成3’,5’磷酸二酯键12、二级结构secondary structure多肽链中相邻氨基酸残基形成的局部肽链空间结构，是其主链各原子的局部空间排布主要形式:α螺旋、β折叠、β转角、π螺旋、随意卷曲主要化学键：氢键13、超二级结构(supersecondary structure)蛋白质多肽链上的一些二级结构单元，可有规律地聚集起来，形成ααα，βββ，βαβ等结构称为超二级结构。
21世纪是生命科学的世纪20世纪后叶分子生物学的突破性...
第一章绪论一简答题1. 21世纪是生命科学的世纪。
20世纪后叶分子生物学的突破性成就，使生命科学在自然科学中的位置起了革命性的变化。
试阐述分子生物学研究领域的三大基本原则，三大支撑学科和研究的三大主要领域？答案：（1）研究领域的三大基本原则：构成生物大分子的单体是相同的；生物遗传信息表达的中心法则相同；生物大分子单体的排列（核苷酸，氨基酸）导致了生物的特异性。
（2）三大支撑学科：细胞学，遗传学和生物化学。
（3）研究的三大主要领域：主要研究生物大分子结构与功能的相互关系，其中包括DNA和蛋白质之间的相互作用；激素和受体之间的相互作用；酶和底物之间的相互作用。
2. 分子生物学的概念是什么？答案：有人把它定义得很广：从分子的形式来研究生物现象的学科。
但是这个定义使分子生物学难以和生物化学区分开来。
另一个定义要严格一些，因此更加有用：从分子水平来研究基因结构和功能。
从分子角度来解释基因的结构和活性是本书的主要内容。
3 二十一世纪生物学的新热点及领域是什么？答案：结构生物学是当前分子生物学中的一个重要前沿学科，它是在分子层次上从结构角度特别是从三维结构的角度来研究和阐明当前生物学中各个前沿领域的重要学科问题，是一个包括生物学、物理学、化学和计算数学等多学科交叉的，以结构（特别是三维结构）测定为手段，以结构与功能关系研究为内容，以阐明生物学功能机制为目的的前沿学科。
这门学科的核心内容是蛋白质及其复合物、组装体和由此形成的细胞各类组分的三维结构、运动和相互作用，以及它们与正常生物学功能和异常病理现象的关系。
分子发育生物学也是当前分子生物学中的一个重要前沿学科。
人类基因组计划，被称为―21世纪生命科学的敲门砖‖。
“人类基因组计划”以及“后基因组计划”的全面展开将进入从分子水平阐明生命活动本质的辉煌时代。
目前正迅速发展的生物信息学，被称为“21世纪生命科学迅速发展的推动力”。
尤应指出，建立在生物信息基础上的生物工程制药产业，在21世纪将逐步成为最为重要的新兴产业；从单基因病和多基因病研究现状可以看出，这两种疾病的诊断和治疗在21世纪将取得不同程度的重大进展；遗传信息的进化将成为分子生物学的中心内容‖的观点认为，随着人类基因组和许多模式生物基因组序列的测定，通过比较研究，人类将在基因组上读到生物进化的历史，使人类对生物进化的认识从表面深入到本质；研究发育生物学的时机已经成熟。
第十一章 端粒端粒酶与肿瘤
(四)、function Allow cells to distinguish the chromosome ends from double strand DNA breaks Prevent the degradation or fusion of chromosome ends, and is essential for maintaining the integrity and stability of eukaryotic genomes Indirctly influence gene expression The clock of life
Crisis or mortality mechanism2(M2) After disruption of the cell-cycle control pathways( and M0 and M1) by, for example, DNA tumor viruses, the telomeres shorten still further, until one or more becomes dysfunctional. At this time, as a consequence of telomeric fusions, many dicentric chromosomes and anaphase bridges form and result in much cell death. This checkpoint on the pathway to immortality is known as crisis or mortality mechanism 2.
Two states: A closed, protected form An open, unprotected form If no telomerase, cell may sense the open form as a dysfunctional telomere. The dysfunctional telomere may then signal a senescence arrest or cell death, depending on the integrity of genes that control and implement the senescence/telomere checkpoint.
细胞凋亡(12级英文班)1127
Theory of senescence
Genetic control theory aging-associated gene: WRN, Sirtuins, Bcl-2 et al. Free radical theory Telomere theory Accumulation of metabolic wastes theory Cumulative damage theory mtDNA mutation theory
Section 1 Cellular Aging (cell senescence)
Cellular aging namely senescence, is defined as progressive deterioration in physiological functions and metabolic processes of a cell or organism. It is the universal, gradually irreversible changes in structure and function of a cell. Almost all living organisms pass through a sequence of changes: characterized by growth, development, maturation and senescence. Normal human somatic cells lose their dividing potential and become senescent after about 50 to 60 divisions.
Young cells after 20 population doublings (PDs)
【转】Isoform
【转】Isoform expre...Exon-centric DEDSGseq summary:This programs uses gapped alignments to the genome to generate differential splicing for groups of technical and biological replicates in two treatments. You can't compare just two samples, two samples per group is the minimum.It generates a ranking of differentially spliced genes using their negative binomial statistic which focuses of difference in expression. The NB statistic is provided per gene and per exon. A threshold used in the paper is NB > 5. The program doesn't support reconstruction of isoforms or quantification of specific isoforms, which apparently is computationally harder.I found it easy to get it to run using the example data provided and the instructions. You need to run a preparation step on the gene annotation. Starting from BAM files, you also need to run two preparation steps on each library, first to convert it to BED, and then to get the counts.While the paper clearly says that transcript annotation information is not necessary for the algorithm, you do need to provide a gene annotation file in refFlat format, which the output is based on.The developers are unresponsive so no help is at hand if you get stuck.DEXseq summaryThis is similar to DSGseq and Diffsplice insofar as the isoform reconstruction and quantification are skipped and differential exon expression is carried out. Whereas the other two tools say that they don't need an annotation for their statistics, this program is based on only annotated exons, and uses the supplied transcript annotation in the form of a GFF file.It also needs at least two replicates per group.I found the usage of this program extremely tedious (as a matlab person). To install it you need to also install numpy and HTSeq. For preparing the data (similarly to DSGseq) you need to do a preparation step on the annotations, and another preparation step for every sample separately which collects the counts (both using python scripts). Then you switch to R, where you need to prepare something called an ExonCountSet object. To do this you need to first make a data.frame R object with the files that come out of the counting step. Yo also need to define a bunch of parameters in the R console. Then you can finally run the analysis. Despite the long instructional PDF, all this is not especially clear, and it's a rather tedious process compared to the others I've tried so far. In the end, I ran makeCompleteDEUAnalysis, and printed out a table of the results. I tried to plot some graphics too, but couldn't because "semi-transparency is not supported on this device". However, there's an extremely useful function that creates a browsable HTML directory with the graphics for all the significant genes. If anyone wants a copy of the workflow I used, send me a message, trying to figure it out might take weeks, but after you get the hang of it, this program is really useful.DiffSplice summaryThis is a similar approach for exon-centric differential expression to DEXseq and DSGseq (no attempt to reconstruct or quantify specific isoforms). Also supports groups of treatments, minimum 2 samples per group. The SAM inputs and various rather detailed parameters are supplied in two config files. I found this very convenient. In the data config file you can specify treatment group ID, individual IDs, and sample IDs, which determine how the shuffling in their permuation test is done. It was unclear to me what the sample IDs are (as opposed to the individual ID).DiffSplice prefers alignments that come from TopHat or MapSplice because it looks for the XS (strand) tag which BWA doesn't create. There's no need to do a separate preparation step on the alignments. However, if you want you can separate the three steps of the analysis using parameters for selective re-running. This program is user friendly and the doc page makes sense.On the downside, when the program has bad inputs or stops in the middle there's no errors or warnings - it just completes in an unreasonably short time and you get no results.Diffsplice appears to be sensitive to rare deviations from the SAM spec, because while I'm able to successfully run it on mini datasets, the whole datasets are crashing it. I ran Picard's FixMateInformation and ValidateSamFile tools to see if they will make my data acceptable (mates are fine, and sam files are valid! woot), but no dice. It definitely isn't due to the presence of unaligned reads.SplicingCompass summary:SplicingCompass would be included together with DEXseq, DiffSplice, and DSGseq, insofar as it's an exon-centric differential expression tool. However, unlike DEXseq and DSGseq, it provides novel junctions as well. Unlike DiffSplice, it does use an annotation. The annotation + novel detection feature of this program is pretty attractive.This is an R package, though as far as i can tell, it's not included in bioconductor. Personally I find it tedious to type lines upon lines of commands into R, and would much prefer to supply a configuration file and run one or a few things on the command line. Alas. Here, at least the instructions are complete, step by step, and on a "for dummies" level. Great.This tool is based on genome alignments. You basically have to run Tophat, because the inputs are both bam files and junction.bed files which Tophat provides. A downside is that you basically have to use the GTF annotation that they provide which is based on UCSC ccds genes. If you want to use ensembl or something else, you meed to email the developer for an untested procedure that might get you a useable annotation at the end (directly using an ensembl GTF doesn't work).Another problem is that I got no significant exons at the end of the analysis:>sc=initSigGenesFromResults(sc,adjusted=TRUE,threshold=0.1)Error in order(df[, pValName]) : argument 1 is not a vectorI'm still unsure as to whether this is due to some mistake or because this tool is extremely conservative.Transcriptome based reconstruction and quantificationeXpress summary:This program can take a BAM file in a stream, or a complete SAM or BAM file.It produces a set of isoforms and a quantification of said isoforms. There is no built in differential expression function (yet) so they recommend inputting the rounded effective counts that eXpress produces into EdgeR or DEGSeq. No novel junctions or isoforms are assembled.I used bowtie2 for the alignments to the transcriptome. Once you have those, using eXpress is extremely simple and fun. There's also a cloud version available on Galaxy, though running from the command line is so simple in this case I don't see any advantage to that. Definite favorite!SailFish summary:This program is unique insofar as it isn't based on read alignment to the genome or the transcriptome. It is based on k-mer alignment, which is based on a k-merized reference transcriptome. It is extremely fast. The first, indexing step took about 20 minutes. This step only needs to be run once per reference transcriptome for a certain k-mer size. The second, quant step took from 15 minutes to 1.5 hours depending on the library. The input for the quant step is fastq's as opposed to bam files. No novel junctions or isoforms are assembled.Like eXpress, there is no built in differential expression function. I used the counts from the non-bias-corrected (quant.sf) output file as inputs for DESeq and got reasonable results.The method is published on arXiv, and has been discussed in Lior Pachter's blog. According to the website the manuscript has been submitted for publication. The program is quite user friendly.RSEM +EBSeq summary:This also generates isoforms and quantifies them. It also needs to be followed by an external cont-based DE tool - they recommend EBSeq, which is actually included in the latest RSEM release, and can be run from the command line easily.RSEM can't tolerate any gaps in your transcriptome alignment, including the indels bowtie2 supports. Hence, you either need to align ahead of time with bowtie and input a SAM/BAM, or use the bowtie that's built into the RSEM call and input a fsta/fastq. For me this was unfortunate because we don't keep fastq files on hand (only illumina qseq files) which bowtie doesn't take as inputs. However, it does work! I successfully followed the instructions to execute EBSeq, which is conveniently included as an RSEM function, and gives intelligible results. Together, this workflow is complete.An advantage of RSEM is that it supplies expression relative to the whole transcriptome (RPKM, TPM) and, if supplied with a transcript-to-gene mapping, it also supplies relative expression of transcripts within genes (PSI). ie. transcript A comprises 70% of the expression of gene X, transcript B comprises 20 %, etc. MISO is the only other transcript-based program, as far as I know, that provides this useful information.BitSeq summary:This, like DEXSeq, is an R bioconductor package. I found the manual a lot easier to understand than DEXSeq.They recalculate the probability of each alignment, come up with a set of isoforms, quantify them, and also provide a DE function. In this way, it is the most complete tool I've tried so far, since all the other tools have assumed, skipped, or left out at least one of these stages. Also, BitSeq automatically generates results files, which is useful for people that don't know R. One annoying thing is that (as far as I know) you have to use sam files.For running BitSeq I used the same bowtie2 alignments to the transcriptome as for eXpress. You need to run the function getExpression on each sample separately. Then you make a list of the result objects in each treatment group and run the function getDE on those.Genome based reconstruction and quantificationiReckon summary:iReckon generates isoforms and quantifies them. However, this is based on gapped alignment to the genome (unlike eXpress, RSEM and BitSeq which are based on alignments to the transcriptome). It doesn't have a built in DE function, so each sample is run separately.This tool is a little curious because it requires both a gapped alignment to the genome, and the unaligned reads in fastq or fasta format with a reference genome. Since it requires a BWA executable, it's doing some re-alignment. iReckon claims to generate novel isoforms with low false positives by taking into consideration a whole slew of biological and technical biases.One irritating thing in getting the program running is that you need to re-format your refgene annotation file using an esoteric indexing tool from the Savant genome browser package. If you happen to use IGV, this is a bit tedious. Apparently, this will change in the next version. Also, iReckon takes up an enormous amount of memory and scratch space. For a library with 350 million reads, you would need about 800 G scratch space. Apparently everything (run time, RAM, and space) is linear to the number of reads, so this program would be a alright for a subset of the library or for lower coverage libraries.Cufflinks + cuffdiff2 summary:This pipeline, like iReckon, is based on gapped alignment to the genome. It requires the XS tag, so if you're not using tophat to align your RNA, you need to add that tag. I also found out that our gapped aligner introduces some pesky 0M and 0N's in the cigars, since cufflinks doesn't tolerate these. But with these matters sorted out, it's pretty easy to use.I like the versatility. You can run cufflinks for transcriptome reconstruction and isoform quantification in a variety of different modes. For example, with annotations and novel transcript discovery, with annotations and no novel discovery, with no annotations, and with annotations to be ignored in the output. For differential expression, cuffdiff 2 can be run with the results of the transcript quantification from cufflinks to include novel transcripts, or, it can be run directly from the alignment bam files with an annotation. Unlike the exon-based approaches, you don't need to have more than one library in each treatment group, (ie. you can do pairwise comparisons) though if you do it's better to keep them separate than to merge them. The problem here is that the results of cuffdiff are so numerous that it's not easy to figure out what you need in the end. Also, not all the files include the gene/transcript names so you need to do a fair bit of command line munging. There's also cummeRbund, which is a visualization package in R that so far seems to work ok.。
ON THE “HOT SPOTS ” CONJECTURE OF J. RAUCH
where c1 and c2 = 0 are constants depending on the initial condition, µ2 is the second eigenvalue for the Neumann problem in D, ϕ2 (x) is a corresponding eigenfunction, and R(t, x) goes to 0 faster than e−µ2 t , as t → ∞. We will make this precise below in Proposition 2.1. The eigenfunction expansion (1.2) leads to a version of the “hot spots” conjecture which involves the second eigenfunction. We will state several versions of the conjecture, with varying strength of the analytic condition and for various classes of domains. Consider the following statements for a domain D. (HS1) For every eigenfunction ϕ2 (x) corresponding to µ2 which is not identically 0, and all y ∈ D, we have inf x∈∂D ϕ2 (x) < ϕ2 (y ) < supx∈∂D ϕ2 (x). (HS2) For every eigenfunction ϕ2 (x) corresponding to µ2 and all y ∈ D, we have inf x∈∂D ϕ2 (x) ≤ ϕ2 (y ) ≤ supx∈∂D ϕ2 (x). (HS3) There exists an eigenfunction ϕ2 (x) corresponding to µ2 which is not identically 0, and such that for all y ∈ D, we have inf x∈∂D ϕ2 (x) ≤ ϕ2 (y ) ≤ supx∈∂D ϕ2 (x). The strongest statement (HS1) asserts that the inequalities are strict, while the other two statements involve weaker assertions. Note that all statements (HS1)(HS3) make assertions about both “hot spots” and “cold spots” of eigenfunctions. This is because if ϕ is an eigenfunction, so is −ϕ and so maxima and minima are indistinguishable in the context of this problem. Conjecture R2 . (Rauch) The statement (HS1) is true for every domain D ⊂ Rd . The “hot spots” conjecture was made, as we recently learned from Rauch, in 1974 in a lecture he gave at a Tulane University PDE conference. Despite the
植物表观遗传学
CG
CNG CHH
Me Me Me
MET1? DRM2
Me
Me
Me
Specific DNA methylation loci in Arabidopsis
(pathogen related)
Chan et al., Nat Rev Genet. 2005 6:351-60.
Arabidopsis Wassilewskija strain
RNA dependent RNA Pol IV
Dorweiler et al, Plant cell, 2000 Alleman et al., Nature, 2006, 442:295-8.
853-bp repeats
In B-I: more methylation, but more open chromatin structure
Me Me Me
promoter Marker gene
外源沉默基因: 带有标记基因的T-DNA插 入；在基因组的某处产生dsRNA, 沉默基 因组同源序列。 内源沉默基因：PAI, Superman
Four classes of DNA methyltransferase in Arabidopsis thaliana
tryptophan enzyme phosphoribosylanthranilate isomerase (PAI)
PAI1-4: 350bp+ORF: hypermethylation hypomethylation
hypomethylation
S15a promoter+ first exon
3.遗传学方法
Me Me Me
promoter Marker gene
端粒酶
Telomeres, Eternal Life, and CancerResearch has discovered that regions of repetitive DNA stretches called telomeres found on the ends of our DNA strands are cut shorter every time they are copied. Eventually the telomeres are worn away and genes near the end of the chromosomes are lost which contain protein instructions the body desperately needs to survive. The discoveries in this area will have a huge impact on more than just showing the way to a possible fountain of youth. Cancer research and cloning may also hinge on developments in the field of telomere research.Telomeres exist as the body’s way of solving a problem with DNA replication. DNA is replicated by the use of an enzyme called DNA polymerase. DNA polymerase functions to copy our chromosomal DNA, using an existing DNA "parental" strand as a template. There are two main problems with the capabilities of the DNA polymerase.The first is that it can’t start from scratch. There must be a segment of the new strand from which the polymerase can begin attaching new nucleotides. The use of primers easily solves this problem. These primers are RNA fragments that bind by random assortment complementary to sites on the parent strand of DNA, and must be in place before the DNA polymerase can begin copying the parent strand.The second problem caused by DNA polymerase during replication is much more difficult for cells to surpass. DNA polymerase can only work in a 5’ to 3’ direction. The polymerase can therefore only work from the direction of the previousl y attached 5’ carbon to the 3’ carbon, which has the –OH group available for the attachment of the next nucleotide. The problem with this unidirectional movement lies with the primers, for they can’t stay in the new strand because they are RNA, and not DNA. Removal of these RNA primers is really not a problem when they are located in the middle of the new daughter strand. There will be a 5’ carbon available for a DNA polymerase to fill in the gap that remained after primer removal. However, the problem lies at the beginning each chromosome. A primer was necessary to provide a 5’ carbon for the beginning of synthesis, yet once it is removed, an upstream 5’ carbon is not available from which a polymerase can attach nucleotides and fill in the gap. Therefore, because the nucleotides are not replaced after removal of the first primer at the beginning of every chromosome, every time the chromosome replicates the daughter strand will be shorter than the parental strand. Studies have shown that the length of a chromosome shortens by about 50 nucleotides every time it replicates. The damage isn’t huge compared to the overall length of a chromosome, but it does mean the chromosome is mortal in that it is slowly being eaten away at the ends with every celldivision. If any of these 50 nucleotides contains the instruction to begin the transcription of a gene, that gene and the protein it encodes will never be usable by the body again.The body’s natural cure to this dilemma is the production of expendable nucleotides at t he 3’ end of every chromosome. These "cannon fodder" nucleotides are called telomeres. Telomeres are repetitive hexameric (6 base pair) sequences of DNA. In humans this repeated G-rich sequence is AGGGTT. These sequences are 1000-1700 base pairs long at the beginning of a mammalian life.Oddly, these telomeres are not encoded in the initial DNA resulting from egg fertilization. What this means is that the telomeres must be added later in development. In 1985 Elizabeth Blackburn and Carol Greider discovered a new DNA polymerase which can add telomeres to DNA. This polymerase, called telomerase, is a ribonucleoprotein present in the very early stages of development. Telomerase activity stops in later development, as it is only required to put the telomeres in place once. Ribonucleoproteins contain RNA, which telomerase uses as a template to synthesize the hexameric DNA telomeres. Because telomerase is a polymerase that copies an RNA template (its own) into DNA, it is a reverse transcriptase.A reverse transcriptase is so named because it is capable of writing codes of DNA from an RNA template which is the reverse of transcription. Reverse transcriptases have gained a lot of fame because they are used by retroviruses, notably HIV, for viral replication.Telomer ase binds to the 3’ end of a chromosome and lines its own RNA template so that a few of its RNA base pairs are complementary to that of the strand. Another segment of the ribozyme hangs over the edge providing a template for the synthesis of the telomeres (CCUAAC). Telomerase synthesizes the hexomeric sequence and then translocates to a new 3’ recognition site, which is within the hexanucleotide it just produced, and repeats the procedure. A normal DNA polymerase and primer can then complete the complementary strand’s 5’ end with all of the new hexomeric repeats--all except the last bit of course. The exact details of telomerase function are currently under research, but its currently understood mechanism as a DNA polymerase that carries its own template appears quite unique and phenomenal.Could the "Fountain of Youth," simply be a shot of telomerase?Some research hints that this might be a good start to combat aging. For example, recent studies have shown that mice deficient in the gene for encoding telomerase RNA (mTR) developed liver cirrhosis (肝硬化) sooner and regenerated much slower than normal mice.These same mice also showed improved liver function upon receiving gene delivery of telomerase.However, in most cases the addition of telomerase into somatic cells late in development would be a death sentence. Cell death (apoptosis) is often a good thing in the body. If some cells didn’t die, some tissues would never stop growing. Apoptosis is a crucial tool used by the body to maintain proper development. Certain cells must die at certain times or else the entire organism will perish.Cloning researchers have found that unfortunately the telomeres of cloned animals (such as the famed cloned sheep named "Dolly") are much shorter than a counterpart of the same developmental "age". Even though cloning technology has attained successful birth rates as high as 80%, most of these clones die before even reaching adulthood. Shortened telomeres appear to be the most likely cause of these deaths. Research seeks to uncover a means of safely extending the telomeres of the clones. Some may hope that the solution to the clone problem will eventually bring about a magic youth potion to humanity.Besides the prevention of age-related health problems, another motivating drive for telomerase research is to develop effective cancer treatments. Scientists are attempting to destroy the telomeres by removing telomerase activity in cancer cells. The purpose is to limit the number of divisions possible in these cells. Normal somatic cells have no telomerase present in them because the expression of the telomerase gene is shut down early in life. Because these cells live a long time in the body, the telomeres created early in life are long enough to serve them for the number of divisions they need to make during the lifetime of the organism. However, cancer cells are defined by unbridled cell division, and therefore it is the telomerase which allows cancer cells to continue their unhindered proliferation and subsequent immortality (永生化). One of the mutations that leads to a cell becoming cancerous is one that disrupts the cells ability to shut down telomerase expression. Cancer researchers have become very interested in designing drugs that target and inactivate telomerase, for if telomerase could be inactivated this would lead to cancer cells becoming mortal again and stop them in their tracks.Although using telomere research for finding a treatment for cancer is a popular concept that everyone supports, the idea of significantly extending life is much more controversial. With the population of Earth bulging proudly over 6 billion souls one has to ponder if human immortality would be a blessing at this point in time. Endless life could be to society what cell immortality is to the body.。
DNA replication(07-6)改
Bidirectional DNA Replication
DNA synthesis occurs in replicons consisting of an origin of replication and two diverging replication forks (bidirectional)
Fork movement
Fork movement
Replication of Circular Chromosome
• Replication begins from a single origin of replication • Replication is bidirectional
–intermediate is called a theta structure
Rolling Circle Replication Mode of replication
used by some plasmids and some phage
One strand remains circular and acts as template for continuous synthesis
DNA Replication
PART I AN OVERVIEW
DNA Replication
1) Semi-conservative mechanism（半保留机制） 2）Replicons (复制子), origins（复制起点）, and termini （复制终点） 3）Semi-discontinuous replication（半不连续复制） 4）RNA priming（引导）
Lagging strand synthesis
Must supply a primer (i.e. 3’-OH) to start DNA synthesis This is the function of primase which makes RNA primers
Replication1A
Pulse with radiolabeled nucleotide; chase with cold nucleotide. Then do autoradiography
5. The final product does not have any gaps in the DNA that result from the removal of the RNA primer. These are filled in by the 5’ to 3’ polymerase action of DNA Polymerase I.
The second two activities of DNA Pol I are important for replication, but DNA Polymerase III (Pol III) is the enzyme that performs the 5'-3' polymerase function. 5. Primase - The requirement for a free 3' hydroxyl group is fulfilled by the RNA primers that are synthesized at the initiation sites by these enzymes. 6. DNA Ligase - Nicks occur in the developing molecule because the RNA primer is removed and synthesis proceeds in a discontinuous manner on the lagging strand. The final replication product does not have any nicks because DNA ligase forms a covalent phosphodiester linkage between 3'-hydroxyl and 5'-phosphate groups.
Telomeres and Telomerase
Without a telomere…
• Telemeres also can:
– Protect open ends of chromosomes from enzymatic digestion – Anchor chromosomes to nuclear membrane (important for chromosome transcription) – Prevent clumping of chromosomes during anaphase • Open ends of chromosomes are “sticky”; therefore, without telemeres capping the ends, several linear chromosomes may clump together. • All mammals have TTAGGG as the repeating telomere sequence
• telomerase in action
Telomerase
Telomerase and cancer cells
• Active telomerase found in 90% of human tumors. • Telomerase does NOT cause cancer; it only allows cancer cells to
(aging) Internal “clock” for cellular aging? Telomerase would essentially reset the “clock”
Telomerase as anti-aging treatment anti• Abnormally reactive in cancer cells • Maintaining telomere length with telomerase in normal • •
端粒与细胞衰老
Ｋｅｙ Ｗｏｒ ｄｓ： Ｔｅｌｏｍｅｒｅｓ； ｃｅｌｌｕｌａｒ ｓｅｎｅｓｃｅｎｃｅ
／（ 编审： 徐元宏）
（ 上接第 ８３ 页）
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２５（３）：１８６￣１８３ １０ ｄｅ Ｗｉｔ Ｒ， ｖａｎ Ａｌｐｈｅｎ ＭＭ． Ｎｅｗ ｄｅｖｅｌｏｐｍｅｎｔｓ ｉｎ ｔｈｅ ｔｒｅａｔｍｅｎｔ ｏｆ ｎａｕｓｅａ ａｎｄ ｖｏｍｉｔｉｎｇ ｃａｕｓｅｄ ｂｙ ｃｈｅｍｏｔｈｅｒａｐｙ． Ｎｅｄ Ｔｉｊｄｓｃｈｒ Ｇｅｎｅｅｓｋｄ，２００３， １４７（１５）： ６９０￣６９４ １１ Ｐｏｌｉ － Ｂｉｇｅｌｉ Ｓ， Ｒｏｄｒｉｇｕｅｓ － Ｐｅｒｅｉｒａ Ｊ，Ｃａｒｉｄｅｓ ＡＤ， ｅｔ ａｌ． Ａｄｄｉｔｉｏｎ ｏｆ ｔｈｅ ｎｅｕｒｏｋｉｎｉｎ １ ｒｅｃｅｐｔｏｒ ａｎｔａｇｏｎｉｓｔ ａｐｒｅｐｉｔａｎｔ ｔｏ ｓｔａｎｄａｒｄ ａｎｔｉｅｍｅｔｉｃ ｔｈｅｒａｐｙ ｉｍｐｒｏｖｅｓ ｃｏｎｔｒｏｌ ｏｆ ｃｈｅｍｏｔｈｅｒａｐｙ－ ｉｎｄｕｃｅｄ ｎａｕｓｅａ ａｎｄ ｖｏｍｉｔ－ ｉｎｇ． Ｒｅｓｕｌｔｓ ｆｒｏｍ ａ ｒａｎｄｏｍｉｚｅｄ， ｄｏｕｂｌｅ－ ｂｌｉｎｄ， ｐｌａｃｅ－ ｂｏ－ ｃｏｎｔｒｏｌｌｅｄ ｔｒｉａｌ ｉｎ Ｌａｔｉｎ Ａｍｅｒｉｃａ． Ｃａｎｃｅｒ，２００３，９７ （１２）：３０９０￣３０９８ １２ ２００６ 年美国临床肿瘤 学 会（ＡＳＣＯ）止 吐 药 应 用 指南［Ｊ］．Ｊ Ｃｈｉｎ Ｏｎｉｃｏｌ，２００６，２４（１８）：２９３２
constant sequences基因组
constant sequences基因组
基因组中的恒定序列通常指的是在整个基因组中重复出现、序列不变的DNA片段。
这些序列可能包括：
端粒（Telomeres）：位于染色体末端，保护染色体免于退化和融合。
着丝粒（Centromeres）：位于染色体中心附近，是细胞分裂时纺锤丝附着的地方。
复制起点（Origins of replication）：启动DNA复制的特定区域。
转座元件（Transposable elements）：可以在基因组内移动的DNA序列，有时也称为跳跃基因。
在人类基因组研究中，Telomere-to-Telomere (T2T) Consortium提出了一个包含30亿5500万碱基对的完整人类基因组序列T2T-CHM13，该序列填补了除Y染色体外所有染色体的间隙，并纠正了先前参考序列中的错误。
此外，重复的DNA序列（repeats）在真核生物和原核生物的基因组中都占有一定比例，它们在基因组结构和功能中起着重要作用。
《计算机网络(第四版)》习题答案
计算机网络(第四版) 习题答案第1 章概述1-3 The performance of a client-server system is influenced by two network factors: the bandwidth of the network (how many bits/sec it can transport) and the latency (how many seconds it takes for the first bit to get from the client to the server). Give an example of a network that exhibits high bandwidth and high latency. Then give an example of one with low bandwidth and low latency.客户-服务器系统的性能会受到两个网络因素的影响：网络的带宽（每秒可以传输多少位数据）和延迟（将第一个数据位从客户端传送到服务器端需要多少秒时间）。
请给出一个网络的例子，它具有高带宽和高延迟。
然后再给出另一个网络的例子，它具有低带宽和低延迟。
答：横贯大陆的光纤连接可以有很多千兆位/秒带宽，但是由于光速度传送要越过数千公里，时延将也高。
相反，使用56 kbps调制解调器呼叫在同一大楼内的计算机则有低带宽和较低的时延。
1-4 Besides bandwidth and latency, what other parameter is needed to give a good characterization of the quality of service offered by a network used for digitized voice traffic?除了带宽和延迟以外，针对数字化的语音流量，想要让网络提供很好的服务质量，还需要哪个参数？声音的传输需要相应的固定时间，因此网络时隙数量是很重要的。