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Generation of Longer cDNA Fragments from SAGE Tags for Gene Identification

February 2003
Methods in molecular biology (Clifton, N.J.) 221:207-22

February 2003
221:207-22

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PubMed

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When a cell is destined for apoptosis, will its genome reprogram its transcriptional machinery to overcome the life-threatening chal-lenge? To address this issue, we performed a genome-wide transcriptome analysis in EPO (erythropoietin) deprivation-induced apoptotic erythroid cells using the SAGE method. The results show that the transcript contents for the majority of the genes remain unchanged in the apoptotic cells, including the apoptotic genes and the heat shock genes. Of the small number of genes with an altered expression, they are mainly associated with cellular structure. Our study reveals that there is no genetic reprogramming for the transcriptional machinery in the apoptotic genome. Apoptosis, as defined by programmed cell death, is not a crisis but a peaceful physiological process.

Expression level of classical apoptotic genes in the apoptotic BFU-E cells

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Heat shock gene expression between the control and apoptotic cells

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SAGE tags statistically different between the control and the apoptotic cells (A) SAGE tags different between the control and apoptotic cells

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Stable transcriptional status in the apoptotic erythroid genome

Sanggyu Lee

, Junmo Hwang

, Jodie Ulaszek

, Yeong C. Kim

, Hui Dong

Hyung Soo Kim

, Ji Woong Seok

, Bo Kyung Suh

, So Jeong Yim

Debra Johnson

, Nong Hoon Choe

, Kyu Tae Chang

, Zae Young Ryoo

Charles C. Tseng

, Amittha Wickrema

, San Ming Wang

School of Life Science and Biotechnology, Kyungpook National University, Daegu, Republic of Korea

Department of Medicine, University of Chicago, IL 60637, USA

Center for Functional Genomics, ENH Research Institute, Northwestern University, 1001 University Place, Evanston, IL 60201, USA

Department of Biological Sciences, Purdue University Calumet, Hammond, IN 46323, USA

College of Veterinary Medicine, Konkuk University, Seoul, Republic of Korea

National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea

Received 18 May 2007

Available online 4 June 2007

Abstract

When a cell is destined for apoptosis, will its genome reprogram its transcriptional machinery to overcome the life-threatening chal-

lenge? To address this issue, we performed a genome-wide transcriptome analysis in EPO (erythropoietin) deprivation-induced apoptotic

erythroid cells using the SAGE method. The results show that the transcript contents for the majority of the genes remain unchanged in

the apoptotic cells, including the apoptotic genes and the heat shock genes. Of the small number of genes with an altered expression, they

are mainly associated with cellular structure. Our study reveals that there is no genetic reprogramming for the transcriptional machinery

in the apoptotic genome. Apoptosis, as deﬁned by programmed cell death, is not a crisis but a peaceful physiological process.

Keywords: Transcription; Gene expression; SAGE; Apoptosis; Erythroid; Genome

Apoptosis is an important biological process in main-

taining the proper progression during development and cel-

lular diﬀerentiation. With extensively analysis using

biochemical approaches, the general machinery of apopto-

sis has been elucidated with the identiﬁcation of many

genes that are directly involved in apoptosis pathways. This

information provides a solid basis for our understanding of

apoptotic molecular machinery.

Besides the genes directly involved in the apoptosis

pathways, it is not clear that when a cell is destined for

apoptosis, will the apoptotic genome react drastically by

reprogramming its gene expression machinery to make a

large-scale change of gene expression? We investigated this

issue by analyzing the contents of the transcript in the

apoptotic erythroid cells. Erythroid diﬀerentiation starts

from the hematopoietic stem cells to the erythroid lineage

committed BFU-E, and goes through the stages of CFU-E,

pronormoblast, orthochromatophilic erythroblast, poly-

chromatophilic erythroblast, reticulocyte, and the mature

red blood cells [1]. Cytokines including EPO (erythropoie-

tin) play critical roles in initiating erythroid lineage com-

mitment and in driving erythroid diﬀerentiation [2–6].

Without EPO, erythroid cells rapidly undergo apoptosis

[7]. Our study focused on the analysis of the transcriptional

status in primary apoptotic erythroid cells to closely reﬂect

their physiological conditions. In this study, we used the

SAGE method for the analysis [8], in an aim to provide

quantitative measure for both known and unknown

transcripts.

doi:10.1016/j.bbrc.2007.05.168

Corresponding authors. Fax: +82 53 943 6925 (S. Lee), +1 224 364

5003 (S.M. Wang).

E-mail addresses: slee@knu.ac.kr (S. Lee), swang1@northwestern.edu

(S.M. Wang).

www.elsevier.com/locate/ybbrc

Biochemical and Biophysical Research Communications 359 (2007) 556–562

Materials and methods

Primary erythroid cell isolation and culture. Primary human erythroid

progenitor cells were generated from CD34

early hematopoietic cells as

previously described [9]. Brieﬂy, CD34

uncommitted hematopoietic cells

were isolated from mobilized peripheral blood (All Cells, Berkeley, CA)

using the Isolex 300i cell selection device. Subsequently, CD34

cells were

cultured in IMDM containing 15% human AB serum, 15% fetal bovine

serum, erythropoietin (Epo), stem cell factor (SCF), and interleukin-3 (IL-

3). During subsequent feedings starting on day 3, no new IL-3 was added to

the cultures. On day 6 of being cultured (Late BFU-E/Early CFU-E), cells

were further puriﬁed by glycophorin A selection using paramagnetic beads

coated with anti-glycophorin A antibody (Miltenyi Biotec, Aurban, CA).

After selection, glycophorin A positive cells were re-cultured for 24 h in the

same culture media with growth factors. The cells were then washed

extensively with IMDM and cultured in two separate dishes: one in the

presence of Epo (2 U/ml) and the other in the absence of Epo in serum-

containing media. During the culture, cells were stained with benzidine and

hematoxylin, and analyzed by ﬂow cytometry with annexin and propidium

iodide. Total RNA was isolated from cells with Trizolä reagent.

SAGE library construction and SAGE tag collection. SAGE libraries

were constructed following the SAGE protocol [10]. Brieﬂy, total RNA

and mRNA were puriﬁed from the control cells and apoptotic cells.

Double-strand cDNA were synthesized, and 3

cDNA were puriﬁed using

NlaIII digestion. SAGE tags were released from 3

cDNA for cancate-

merization and cloning into the pZero vector. Sequencing reactions for

SAGE clones were performed with ABI Big-Dye 3.1 kit. Sequences were

collected using a Megabace DNA sequencer (Amersham, Piscataway, NJ).

Sequences passed Phred20 were used for SAGE tag extraction.

SAGE data analysis. SAGE tags were extracted from sequences using

SAGE 300 software. To identify the gene origins, SAGE tags were

matched to SAGEmap database (http://www.ncbi.nlm.nih.gov/SAGE/).

For the SAGE tags shared by multiple genes, the most likely gene for

these SAGE tags was identiﬁed through matching these SAGE tags to a

tissue-speciﬁc tag to the gene database under the tissue type ‘‘Blood’’

(http://basic.northwestern.edu). The Audic and Claverie method [11,12,

http://telethon.bio.unipd.it/bioinfo/IDEG6/] was used to identify the

statistically diﬀerent SAGE tags between the control and apoptotic cells.

Two pre-conditions were set to determine the diﬀerentially expressed genes

in the control and apoptotic cells, including p values <0.05 and fold

Fig. 1. Induction of apoptosis in primary human erythroid progenitors deprived of growth factors. Primary erythroid progenitor cells were collected

beginning on day 7 of being cultured in the presence (A) or absence (B–D) of EPO for (B) 6 h, (C) 8 h, or (D) 24 h. The extent of apoptosis was determined

by a ﬂow cytometry assay to ascertain the percentages of cells positive for annexin and propidium iodide.

S. Lee et al. / Biochemical and Biophysical Research Communications 359 (2007) 556–562 557

Table 1

Comparison between control and apoptotic cells

(A) Total SAGE tag comparison between the control and apoptotic cells

Control Apoptosis

Total tags 37,279 40,009

Unique tags 20,162 20,690

Total:unique 1.8:1 1.9:1

Match 12,154 (60) 12,558 (61)

Novel 8008 (40) 8132 (39)

(B) Quantitative distribution of SAGE tag between control and apoptotic cells

>50 49 to 10 9 to 5 4 to 2 1 Total

Tags matched to known genes

Apoptosis 50 250 419 2141 9698 12,558

Control 45 253 376 2151 9329 12,154

Tags without match to known genes

Apoptosis 6 27 71 599 7429 8132

Control 4 19 50 557 7378 8008

Table 2

Expression level of classical apoptotic genes in the apoptotic BFU-E cells

Gene UniGene ID SAGE tag

SAGE tag copy Fold change p value

Control Apoptosis

BAX Hs.159428 GGCATTTTTC 6 0 6.0 0.007

AAGACAGGGG 1 0 1.0 0.250

BAK1 Hs.93213 ACTCCCAAGG 0 1 1.0 0.268

BID Hs.300825 TCAACAGCGT 3 3 1.0 0.161

GCACAGAGAT 0 1 1.0 0.268

CTGGTGCTGG 0 1 1.0 0.268

GTCTCTTTGG 0 2 2.0 0.139

CASP2 Hs.433103 ATCCACCCAC 4 2 2.0 0.113

CASP8 Hs.243491 AACCTGCTGG 0 1 1.0 0.268

GGGAAACAGA 1 0 1.0 0.250

CASP9 Hs.329502 ATCCTGTGTT 0 1 1.0 0.268

GATCCCTGTG 1 1 1.0 0.258

CASP3 Hs.141125 GGCGTGTTCC 0 1 0.0 0.268

CASP6 Hs.3280 CCTGCAATCC 15 24 1.6 0.032

GAGAAGCCCC 3 1 3.0 0.120

GAAGATGCTG 0 1 1.0 0.268

CASP7 Hs.9216 CAAAAGTTCT 1 0 1.0 0.250

CYCS Hs.437060 TTCATTTGCC 3 2 1.5 0.156

FADD Hs.86131 TGAGGATTAT 1 0 1.0 0.250

CCACTCACCC 0 1 1.0 0.268

GGAAACTCTG 0 1 1.0 0.268

IKBKG Hs.43505 TGCAAGTTCC 1 0 1.0 0.250

NFKB1 Hs.160557 GACCCGGGGG 0 1 1.0 0.268

TTTGCTGCTG 1 0 1.0 0.250

ATTATGGGCA 1 0 1.0 0.250

RELA Hs.132594 CAACAGCACT 1 2 2.0 0.201

GAATTCCAGT 2 0 2.0 0.120

RIPK1 Hs.390758 AAGCTCTGCT 0 1 1.0 0.268

TNF

TNFSF10 Hs.387871 CCACTACACT 29 20 1.5 0.018

TNF Hs.241570 TAGCCCCCTG 0 1 1.0 0.268

TNF receptor

TNFRSF1A Hs.159 CCCGTTTTGG 0 1 1.0 0.268

GGCCTCTCCA 0 1 1.0 0.268

GGGCCTTCAG 0 1 1.0 0.268

TNFRSF1B Hs.256278 GTAAAACCCC 31 24 1.3 0.027

GGTGACTCAG 1 0 1.0 0.250

ATGGAGCGCA 0 3 3.0 0.072

GCCAGTGTGA 1 0 1.0 0.250

TRADD Hs.89862 AAGCACCTTG 1 0 1.0 0.250

Diﬀerent SAGE tags for the same gene reﬂect the transcript isoforms expressed from the same gene.

558 S. Lee et al. / Biochemical and Biophysical Research Communications 359 (2007) 556–562

change P4. The Gene Ontology (GO) ‘‘Biological Process’’ term (http://

www.geneontology.org) was used to classify the alternatively expressed

genes in the apoptotic cells into functional categories.

Semi-quantitative PCR. A semi-quantitative PCR assay was used to

conﬁrm the SAGE results. For each reaction, a set of sense and anti-

sense primers was designed based on the tag-matched sequences (Sup-

plementary Table 2). Total RNA samples from the control and

apoptotic cells were used as the templates for PCR. b-Actin was used as

the internal control. Amplicons were aliquoted and loaded on 2%

agarose gel for visualization.

Results and discussion

Erythroid progenitors rapidly progress to apoptosis upon Epo

deprivation

Several studies have been performed in addressing the

genome response to apoptosis [13,14]. These studies were

largely performed using transformed cell lines using

microarray-based approaches. Although the results are

informative, it can not be certain that the observation

will be the same in the primary cells. In addition, micro-

array-based approaches can only detect the known genes

or transcripts. It is not certain whether there are novel

genes or novel trans cripts present in the apoptotic cells.

In this study, we analyzed the apoptotic primary human

erythroid progenitors derived from normal hematopoietic

stem/progenitor cells, in an aim to provide the informa-

tion close to the primary cells. These cells, derived from

early-uncommitted CD34

hematopoietic stem/progeni-

tor cells, are absolutely dependent on Epo for growth.

Following Epo deprivation, cells rapidly undergo the

apoptotic stage (Fig. 1). Although the rate of apoptotic

cells is higher in longer time frame, the RNA in the

apoptotic cells becomes degraded. To obtain a balanced

level of apoptotic cells and good RNA quality for the

analysis, we used the cells after an 8-h EPO deprivation

that contained about 55% apoptotic cells. We used the

SAGE method to detect the transcripts in an aim to pro-

vide a quantitative measurement of gene expression, not

only for transcripts from known genes but also from

novel transcripts/novel genes.

Transcription status in the apoptotic erythroid genome

We collected 40,009 SAGE tags from the control

cells and 37,295 SAGE tags from the apoptotic cells.

From these SAGE tags, we identiﬁed 20,162 unique

SAGE tags for the control cells and 20,690 unique

SAGE tags for the apoptotic cells. We performed the

following analyses using the data from the control and

apoptotic cells.

We compared the ratio between the total tags and the

unique tags identiﬁed from the total tags. This ratio

reﬂected the general abundance of transcripts expressed

in the cells. A higher ratio indicated lower number of

expressed transcripts and vice versa. The ratio was similar

between the two sets of data, with 1.9:1 in the apoptotic

cells and 1.8:1 in the control cells. We compared the ratio

between the SAGE tags matched to known genes and the

novel SAGE tags without matches. This ratio was also sim-

ilar between the control cells and apoptotic cells, with 60%

matched tags and 40% novel tags in the control cells and

61% matched tags and 39% novel tags in the apoptotic cells

(Table 1A and Supple mentary Table 1). We further com-

pared the quantitative distribution of the matched SAGE

tags and novel SAGE tags between the control and

apoptotic cells. The distribution provided a measure for

large-scale quantitative changes of the known genes and

Fig. 2. Semi-quantitative RT-PCR conﬁrmation. (A) Conﬁrmation for

Bax gene expression. Speciﬁc sense and antisense primers for Bax

transcripts were designed. RNA samples extracted from cells in the

presence or absence of EPO were used as the templates for the analysis. (B)

12 SAGE tags that diﬀered between the control and apoptotic cells were

chosen. Sense and antisense primers were designed using the SAGE tag-

matched sequences. Reactions No. 7 and 8 were negative (not shown).

b-Actin was used as the internal control for semi-quantitative PCR.

Amplicons at diﬀerent PCR cycles were loaded on gels. See Supplementary

Table 2 for detailed information.

S. Lee et al. / Biochemical and Biophysical Research Communications 359 (2007) 556–562 559

Table 3

Heat shock gene expression between the control and apoptotic cells

Heat shock gene UniGene ID Common tag Diﬀerent tags Tag copy

Control Apoptosis Control Apoptosis

Heat shock 27 kDa protein 1 Hs.76067 CCCAATCTAG 1 1

ACCCTCCCCT 1 n.d.

AGTGCCGGTG 1 n.d.

CCAAGCTTGG 1 n.d.

CCCAAGCTAG 1 n.d.

CCCCAAGCTA 1 n.d.

GCAACAACAG 1 n.d.

ATTGCAGCAC n.d. 3

TTCCCTCCCT n.d. 2

Heat shock 60 kDa protein 1 Hs.79037 TACCAGTGTA 12 3

TACCCAGTGT 2 n.d.

TTCTAACTCC 2 n.d.

AACTTTAGGG 1 n.d.

AAGACAGCTG 1 n.d.

TTACTGGACT 1 n.d.

Heat shock 70 kDa protein 1A Hs.75452 CGCTCGATCT 2 1

CAGAGATGAA 2 n.d.

Heat shock 70 kDa protein 5 Hs.310769 TGCATCTGGT 12 7

CAGGTGGTAG 1 n.d.

GAAACAGCTG 1 n.d.

GAACACTTCA 1 n.d.

AACCAAACTG n.d. 1

Heat shock 70 kDa protein 8 Hs.180414 CCAGGAGGAA 26 7

CAGGAGGAAT 1 n.d.

CCCAAGGTCC 1 n.d.

CTTGTGAACG 1 n.d.

GGATACTCAA 1 n.d.

TTCACACATT 1 n.d.

AACTCTCAAA n.d. 1

ACAAAAGGAT n.d. 1

AGCCAACTGC n.d. 1

GCTTAAATGT n.d. 1

TTGGTGATAC n.d. 1

Heat shock 70 kDa protein 9B Hs.184233 AGTGAAACCC 18 10

TTTGTAGATG 1 n.d.

AGCCCACCGG n.d. 1

GCACTTCAGA n.d. 1

GGCACTTTCC n.d. 1

Heat shock 90 kDa protein 1, a Hs.446579 GAAGCTTTGC 34 8

TACTAGTCCT 26 5

Heat shock 90 kDa protein 1, b Hs.74335 TGATTTCACT 54 76

GGCTCCCACT 25 10

ATTCAAGCTT 13 22

GTGAGCCCAT 15 6

GGCTCCACTG 2 n.d.

GGTGAAGCCC 2 n.d.

GTTGAGCCCA 2 n.d.

AAGCCCAGCA 1 n.d.

AGGCAGGATG 1 n.d.

ATCAAGTAGG 1 n.d.

AAAAGAAATC n.d. 1

ATTGGGCAGT n.d. 1

CCGAAACAGA n.d. 1

GAGAGGAGGA n.d. 1

GGCTCCCATT n.d. 1

Heat shock 105/110 kDa protein 1 Hs.36927 TGAACCCGTT 6 n.d.

TTGTTGACTA 1 n.d.

n.d., not detected.

560 S. Lee et al. / Biochemical and Biophysical Research Communications 359 (2007) 556–562

the novel transcripts in the apoptotic cells. The distribution

patterns showed no signiﬁcant diﬀerences between the con-

trol and the apoptotic cells (Table 1B).

We then compared the genes detected in both the control

and apoptotic cells (Table 1B). There were 12,154 and

12,558 SAGE tags matc hed to known genes in the control

and apoptotic cells correspondingly. Comparing these two

sets of data showed that the 3718 matched tags were present

in both cell popul ations. This result indicated that the

majority of known genes expressed in both control and

the apoptotic cells were similar. We then compared the

novel SAGE tags shared between these two cell types. 949

novel SAGE tags were present in both cell types. The rate

was lower than the matched SAGE tags. This may relate

with several possibilities: the novel SAGE tags were mostly

at low copy numbers, representing the low abundant tran-

scripts. The present coverage of the SAGE tag collection

did not reach the saturated coverage of the transcripts,

but tended more to random detection that lead to lower

overlapping between the control and apoptotic cells. In

addition, there were certain portions of novel SAGE tags

that were related with sequencing errors. But the high rate

overlapping between the control and apoptotic cells implied

the constant gene expression between these two cell types.

We next compared the expression of the classical apop-

totic genes between the control and the apoptotic cells

(Table 2). Of these apoptotic genes, all except Bax gene

remained stably expressed in the apoptotic cells, such as

TNF, BID, and CASP 2 genes. The stable expression of

these apoptotic genes implied that there were no regulatory

changes for their expression in the apoptotic cells. Interest-

ingly, the BAX gene changed from six copies detected in

the control cells to unde r a detection level in the apoptotic

cells. This observation was conﬁrmed by semi-quantitative

PCR (Fig. 2A). BAX is an important apoptosis regulator

that promotes apoptosis by releasing cytochrome c from

the mitochondrion. Expression of the BAX gene would

be expected to have increased in the apoptotic cell [15].

The unexpected turn-oﬀ of BAX gene expression in the

apoptotic cells might be because BAX transcripts are

needed at an earlier stage of apoptosis for protein synthe-

sis. After the initiation of apoptosis, the continued presence

of BAX transcripts may not be required. The unique

expression of the BAX gene provides a potential target

for intervention of erythroid apoptosis.

We analyzed the expression of classical heat shock genes

in the apoptotic cells. Heat shock genes are molecular

chaperones involved in maintaining the protein structures

for cells. When a cell is under external and internal stress

conditions, these genes will rapidly increa se their expres-

sion level to protect the cells. We compared the SAGE tags

that represented the major transcripts and the alternatively

spliced/adenylated isoforms of each heat sh ock genes.

Compared with those in the control cells, we saw no signs

Table 4

SAGE tags statistically diﬀerent between the control and the apoptotic cells

(A) SAGE tags diﬀerent between the control and apoptotic cells

Presence Absence Increase Decrease Total

Matched SAGE tags 73 59 44 68 244

Novel SAGE tags 24 10 14 5 53

Total 97 69 58 73 297

(B) Functional classiﬁcation of genes alternatively expressed in the apoptotic cells

Functional categories Number of grouped genes

Decreased in the apoptotic cells

Biosynthesis 12

Carboxylic acid biosynthesis 3

Fatty acid biosynthesis 3

Nitric oxide biosynthesis 2

Organic acid biosynthesis 3

Ribonucleotide biosynthesis 3

Energy metabolism 5

Cell cycle and proliferation 10

Protein folding 6

Transport 14

Increased in the apoptotic cells

Actin cytoskeleton organization 4

Cell organization and biogenesis 9

Lipid metabolism 7

Macromolecule biosynthesis 8

Organelle organization and biogenesis 5

Regulation of cell cycle 6

Regulation of metabolism 14

Regulation of physiological process 14

S. Lee et al. / Biochemical and Biophysical Research Communications 359 (2007) 556–562 561

of increased expression of heat shock genes in the apoptotic

cells. In fact, several genes decreased their expression in the

apoptotic cells (Table 3). The stable expression of heat

shock genes implied that the apoptotic cells were not in

the state of stress.

The limited number of genes alternatively expressed in the

apoptotic genome

Although a large-scale alternation of gene expression

was not observed in the apoptotic cells, there were 297

SAGE tags statistically diﬀerent between the apoptotic

cells and the control cells, representing 244 known genes

and 53 novel transcripts (Table 4A and Supplementary

Table 3). The diﬀerences were veriﬁed by semi-quantitative

RT-PCR for a group of the SAGE tags (Fig. 2B and Sup-

plementary Table 2). Using the Gene Ontology ‘‘biologic al

process’’ term, 128 of the known genes were grouped into

several functional categories. The genes that showed

decreased expression were large ly involved in biosynthesis

of smal l molecular blocks such as carboxylic acid, fatty

acid, organic acid, and ribonucleotides; the genes that

showed increased expression were mostly involved in

cellular organization (Table 4B and Supplemen tary

Table 4).

In summary, our study shows that there are no large-

scale alternations of gene expression in the apoptotic ery-

throid cells, including the apoptosis genes and heat shock

genes. The small numbers of alternated genes are related

with the synthes is of basic bio-block molecules and cellular

structure. Our study indicates that there is no genetic

reprogramming for gene expression in the apoptotic

erythroid genome. From the gene expression point of view,

apoptosis is not a crisis but a peaceful physiological pro-

cess, as precisely deﬁned as ‘‘the programmed cell death’’.

Acknowledgments

The authors thank Dr. Janet D. Rowley for her support

for this project. This study was supported by the National

Institute of Heal th and the Daniel F., Ada L. Rice Founda-

tion (S.M.W.) and Kyungpook National University

Research Fund, 2005 (S.L.).

Appendix A. Supplementary data

Supplementary data associated with this article can be

found, in the online version, at doi:10.1016/j.bbrc.

2007.05.168.

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Article

Matthias Bernhard Wahl

Um die molekularen Mechanismen, welche Knorpelentwicklung und Somitogenese steuern, aufzuklären, wurde eine globale quantitative Genexpressions-analyse unter Verwendung von SAGE (Serial Analysis of Gene Expression) an der knorpelbildenden Zelllinie ATDC5 und an somitischem Gewebe, präpariert von E10.5 Mäusen, durchgeführt. Unter insgesamt 43,656 von der murinen knorpelbildenden Zelllinie ATDC5 gewonnenen SAGE Tags (21,875 aus uninduzierten Zellen und 21,781 aus Zellen, die für 6h mit BMP4 induziert wurden) waren 139 Transkripte unterschiedlich in den beiden Bibliotheken repräsentiert (P >= 0.05). 95 Tags konnten einzelnen UniGene Einträgen zugeordnet werden (77 bekannte Gene und 18 ESTs), aber überraschenderweise wurden viele davon bisher nicht mit der Differenzierung von Knorpel in Verbindung gebracht. Interessanterweise wurde von einer signifikanten Fraktion dieser Gene Gruppen physikalischer Verknüpfung gebildet. Für die Untersuchung der Somitogenese wurden Expressionsprofile von vier verschiedenen Teilen des caudalen bereiches von E10.5 Maus Embryonen verglichen: Schwanzknospe (A), die caudalen zwei Drittel (B) und das rostrale Drittel (C) des präsomitischen Mesoderms und zwei Paare werdender Somiten. Insgesamt wurden 171,639 LongSAGE Tags (A: 21,595; B: 50,699; C: 49,732; D: 49,613) generiert, wodurch 1007 Transcripte identifiziert wurden, welche zumindest zwischen zwei Bibliotheken unterschiedlich repräsentiert waren (P >= 0.05). Alle LongSAGE Tags, die mindestens zwei Mal in dem gesamten Datensatz vorkamen, wurden mit der momentanen EnsEMBL Genom- Annotierung verglichen. Die Analyse von LongSAGE Tags ohne entsprechendem EnsEMBL Gen führte zur Identifikation von 1872 Gene, welche bisher noch nicht an das Genom annotiert wurden, aber durch einen UniGene Cluster repräsentiert sind. Zusätzlich konnten 2348 GeneScan Vorhersagen verifiziert und 547 Antisense- Gene identifiziert werden. Eine Analyse von öffentlich zugänglichen SAGE Bibliotheken zeigte, dass Zielgene von anderen Signaltransduktionswegen als BMP4 auch Cluster im Genom bilden. Desweiteren wurden die beobachteten Veränderungen in der Genexpression von ribosomalen Proteinen in verschiedenen Geweben unter unterschiedlichen Bedingungen untersucht. Erstaunlicherweise zeigte eine Cluster- Analyse, dass verschiedene Gewebetypen eindeutig abgegrenzte Genexpressionsprofile ribosomaler Proteine haben. Zusammenfassend bietet die Transkriptiom- Analyse von BMP- induzierter Knorpelentwicklung sowie Somitogenese einen Einblick auf die molekularen Ereignisse, welche beide Entwicklungsprozesse steuern. Generell sind mehrere Signaltransduktionswege sowie eine vielzahl zellulärer Prozesse involviert. Weitere Studien werden zeigen, wie diese Veränderungen in der Genexpression hervorgerufen werden und wie sie in die fein abgestimmten zellul\"aren Ereignisse von Knorpel- und Somitenentwicklung organisiert werden.

Application of Serial Analysis of Gene Expression to the Study of the Gene Expression Profile of Leishmania infantum chagasi Promastigote

Article

Full-text available

Apr 2012
J BIOMED BIOTECHNOL

This study describes the application of the LongSAGE methodology to study the gene expression profile in promastigotes of Leishmania infantum chagasi. A tag library was created using the LongSAGE method and consisted of 14,208 tags of 17 bases. Of these, 8,427 (59.3%) were distinct. BLAST research of the 1,645 most abundant tags showed that 12.8% of them identified the coding sequences of genes, while 82% (1,349/1,645) identified one or more genomic sequences that did not correspond with open reading frames. Only 5.2% (84/1,645) of the tags were not aligned to any position in the L. infantum genome. The UTR size of Leishmania and the lack of CATG sites in some transcripts were decisive for the generation of tags in these regions. Additional analysis will allow a better understanding of the expression profile and discovering the key genes in this life cycle.

Quantitative Analysis of Nucleic Acids - the Last Few Years of Progress

Article

Feb 2004
J BIOCHEM MOL BIOL

DNA and RNA quantifications are widely used in biological and biomedical research. In the last ten years, many technologies have been developed to enable automated and high-throughput analyses. In this review, we first give a brief overview of how DNA and RNA quantifications are carried out. Then, five technologies (microarrays, SAGE, differential display, real time PCR and real competitive PCR) are introduced, with an emphasis on how these technologies can be applied and what their limitations are. The technologies are also evaluated in terms of a few key aspects of nucleic acids quantification such as accuracy, sensitivity, specificity, cost and throughput.

Breeding and Field Performance of Novel Soft and Waxy Transgenic Rice Lines Without Selectable Marker

Article

Jun 2009

Amylose content is one of the important factors affecting rice cooking and eating quality, and is controlled by Waxy (Wx) gene encoding a granule-bound starch synthase. High amylose level is usually associated with poor cooking and eating quality. Several homozygous transgenic lines with soft or waxy grain property were selected from the offspring of selectable marker-free (SMF) transformants containing the antisense Wx gene. The results from Northern blotting analysis indicated that the levels of both Wx mature mRNA and pre-mRNA were reduced in the endosperm of different transgenic lines. The Wx protein content in mature seeds of the transgenic lines also decreased. The amylose contents of 2 transgenic lines were reduced to that of the soft rice (about 10%), and one of them was even reduced to the level of waxy rice (lower than 2%). The gel consistency of these transgenic lines was softer than that of the wild type. The variance of gelatinization temperature between the transgenic lines and the wild type was significant. Most of the main agronomic traits of these transgenic lines were similar to those of the wild type. Therefore, the 3 SMF transgenic homozygous lines with improved quality were successfully developed.

Serielle Analyse der Genexpression (SAGE)

Article

Jan 2006

S Castell

Die vorliegende Arbeit ist im Rahmen eines Projektes zur Untersuchung der Genexpression bei Tiermodellen neurologischer Erkrankungen entstanden. Mit herkömmlichen Kandidatenansätzen ist eine Genexpressionsanalyse nur in beschränktem Umfang zu realisieren. Ziel war daher die Etablierung eines Verfahrens wie SAGE (serielle Analyse der Genexpression), das die Analyse des gesamten Transkriptoms zuläßt. Wie die Arbeit zeigt, ist SAGE in einem Standardlabor durchführbar. Es wurden geringfügige Abwandlungen der Orginalmethode eingeführt. Zur Sequenzfehlerkorrektur wurde ein spezielles Computerprogramm entwickelt und evaluiert. Zur Evaluierung der statistischen Auswertung von SAGE wurde zusätzlich zu einer Darstellung des gesamten statistischen Entscheidungsprozesses explorativ die Situation statistischer Entscheidungen wie sie im Rahmen üblicher SAGE Experimente auftreten mit vier Tests nachgeahmt. Es wurde eine Testvariante (modifizierter Z-Test) angewandt und evaluiert, die bis dato noch nicht zur Auswertung von SAGE benutzt worden war. Um die Reliabilität von SAGE abschätzen zu können, wurde von vier Mäusegroßhirnen die Gesamt-RNS vereinigt. Diese Transkriptgrundpopulation wurde zweigeteilt und parallel untersucht. Die beiden Gruppen wurden anhand eines statistischen Tests, der die gesamte Verteilungen der beiden Profile prüft, auf Homogenität untersucht. Zusätzlich wurde das Zusammenhangsmaß ermittelt. Dies ergab, daß die Reliabilität von SAGE im vorliegenden Kontext (relativ geringe Stichprobe und ein komplexes Gewebe) nicht optimal ist. Es kann jedoch keine Aussage dazu gemacht werden, ob dies der Methode selbst, das heißt ihrer molekularbiologischen Praxis und der Datenaufbereitung, anzulasten ist oder einer großen Stichprobenvariabilität. Dies bedeutet, daß in der vorliegenden Arbeit keine endgültige Aussage zur Reliabilität von SAGE möglich ist. Es werden Möglichkeiten dargestellt mit einer suboptimale Reliabilität im Rahmen von zukünftigen Projekten umzugehen.

A Partial Transcriptome of Human Epidermis

Article

Jun 2002

Serial analysis of gene expression (SAGE) is a powerful technique for global expression profiling without prior knowledge of the genes of interest. We carried out SAGE analysis of purified keratinocytes derived from human skin biopsy specimens, resulting in a partial transcriptome of human epidermis. We identified 7645 unique SAGE tags with quantitative information from 15,131 collected SAGE tags obtained from approximately 3 x 10(6) epidermal cells. This catalog contains a large number of genes that were not previously known to be expressed by human epidermis. Comparison with the databases of all known human SAGE tags allowed us to identify a number of keratinocyte-specific tags that putatively correspond to formerly unknown genes. Surprisingly, human epidermal keratinocytes in vivo show relatively low expression levels of genes typically associated with epidermal differentiation, whereas the expression levels of housekeeping genes are considerably higher than in cultured keratinocytes. This study provides a first step toward a transcriptome of human epidermis and, as such, harbors a wealth of information to identify genes involved in skin function, and candidate genes for genetic skin disorders.

Genomic convergence: Identifying candidate genes for Parkinson's disease by combining serial analysis of gene expression and genetic linkage

Article

Full-text available

Apr 2003

We present a multifactorial, multistep approach called genomic convergence that combines gene expression with genomic linkage analysis to identify and prioritize candidate susceptibility genes for Parkinson's disease (PD). To initiate this process, we used serial analysis of gene expression (SAGE) to identify genes expressed in two normal substantia nigras (SN) and adjacent midbrain tissue. This identified over 3700 transcripts, including the three most abundant SAGE tags, which did not correspond to any known genes or ESTs. We developed high-throughput bioinformatics methods to map the genes corresponding to these tags and identified 402 SN genes that lay within five large genomic linkage regions, previously identified in 174 multiplex PD families. These genes represent excellent candidates for PD susceptibility alleles and further genomic convergence and analyses.

Generation of longer 3' cDNA fragments from massively parallel signature sequencing tags

Article

Full-text available

Feb 2004
NUCLEIC ACIDS RES

Massively Parallel Signature Sequencing (MPSS) is a powerful technique for genome-wide gene expression analysis, which, similar to SAGE, relies on the production of short tags proximal to the 3′end of transcripts. A single MPSS experiment can generate over 107 tags, providing a 10-fold coverage of the transcripts expressed in a human cell. A significant fraction of MPSS tags cannot be assigned to known transcripts (orphan tags) and are likely to be derived from transcripts expressed at very low levels (∼1 copy per cell). In order to explore the potential of MPSS for the characterization of the human transcriptome, we have adapted the GLGI protocol (Generation of Longer cDNA fragments from SAGE tags for Gene Identification) to convert MPSS tags into their corresponding 3′ cDNA fragments. GLGI-MPSS was applied to 83 orphan tags and 41 cDNA fragments were obtained. The analysis of these 41 fragments allowed the identification of novel transcripts, alternative tags generated from polymorphic and alternatively spliced transcripts, as well as the detection of artefactual MPSS tags. A systematic large-scale analysis of the genome by MPSS, in combination with the use of GLGI-MPSS protocol, will certainly provide a complementary approach to generate the complete catalog of human transcripts.

Genomic representations using concatenates of Type IIB restriction endonuclease digestion fragments

Article

Full-text available

Feb 2004
NUCLEIC ACIDS RES

We have developed a method for genomic representation using Type IIB restriction endonucleases. Representation by concatenation of restriction digests, or RECORD, is an approach to sample the fragments generated by cleavage with these enzymes. Here, we show that the RECORD libraries may be used for digital karyotyping and for pathogen identification by computational subtraction.

Prediction, Annotation, and Analysis of Human Promoters

Article

Feb 2003

Michael Zhang

Excerpt Since the celebrated discovery of the Watson-Crickdouble-helix structure of DNA, it has taken 50 years forthe human genome to be sequenced. It may very welltake another 50 years for the functional information to befully decoded. Until recently, genome research hasmainly focused on coding regions, and the immediatequestions have been, "Where are the protein coding regions?" and "What are the functions of the gene products?" Increasingly, the field is advancing toward noncoding regions, where the central questions become,"Where are the regulatory regions?" and "How do theycontrol gene expressions?" In 1961, Jacob and Monodpublished "On the regulation of gene activity" at the 26thCold Spring Harbor Symposium on Quantitative Biology, in which some of the fundamental concepts of generegulation were first elegantly formulated. Regulatoryregions are most fundamental, because all the gene structures are defined by and recognized through the cis elements in such regions; furthermore, what a gene does invivo is intimately related to when, where, and how muchit is expressed. A phenotype, upon which the selectionforce is acting, is the integrated result of gene functionand regulation. It is argued that animal diversity ismainly due to evolutionary expansion in regulatory complexity (Levine and Tjian 2003). Most regulations occurat the transcriptional level, and the initiation of transcription is largely determined by the promoter located atthe beginning of each gene; identification of promotersand cis regulatory elements within them has become theprerequisite for understanding of gene regulation. For afew model organisms with compact genomes (such asphage, bacteria, and yeast), many of the gene regulatorypathways or networks have been worked out. But formammalian systems, such as human, systematic identification of regulatory regions and gene networks hasturned out to be extremely difficult, largely due to thesize and complexity of the genomes (hence, as a result,the diversity of the cell/tissue types and the complicationof developmental stages)...

Generation of longer cDNA fragments from serial analysis of gene expression tags for gene identification

Article

Full-text available

Jan 2000

We have developed a technique called the generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI), to convert SAGE tags of 10 bases into their corresponding 3' cDNA fragments covering hundred bases. A primer containing the 10-base SAGE tag is used as the sense primer, and a single base anchored oligo(dT) primer is used as an antisense primer in PCR, together with Pfu DNA polymerase. By using this approach, a cDNA fragment extending from the SAGE tag toward the 3' end of the corresponding sequence can be generated. Application of the GLGI technique can solve two critical issues in applying the SAGE technique: one is that a longer fragment corresponding to a SAGE tag, which has no match in databases, can be generated for further studies; the other is that the specific fragment corresponding to a SAGE tag can be identified from multiple sequences that match the same SAGE tag. The development of the GLGI method provides several potential applications. First, it provides a strategy for even wider application of the SAGE technique for quantitative analysis of global gene expression. Second, a combined application of SAGE/GLGI can be used to complete the catalogue of the expressed genes in human and in other eukaryotic species. Third, it can be used to identify the 3' cDNA sequence from any exon within a gene. It can also be used to confirm the reality of exons predicted by bioinformatic tools in genomic sequences. Fourth, a combined application of SAGE/GLGI can be applied to define the 3' boundary of expressed genes in the genomic sequences in human and in other eukaryotic genomes.

Serial microanalysis of renal transcriptomes

Article

Full-text available

Dec 1999

Large-scale gene expression studies can now be routinely performed on macroamounts of cells, but it is unclear to which extent current methods are valuable for analyzing complex tissues. In the present study, we used the method of serial analysis of gene expression (SAGE) for quantitative mRNA profiling in the mouse kidney. We first performed SAGE at the whole-kidney level by sequencing 12,000 mRNA tags. Most abundant tags corresponded to transcripts widely distributed or enriched in the predominant kidney epithelial cells (proximal tubular cells), whereas transcripts specific for minor cell types were barely evidenced. To better explore such cells, we set up a SAGE adaptation for downsized extracts, enabling a 1, 000-fold reduction of the amount of starting material. The potential of this approach was evaluated by studying gene expression in microdissected kidney tubules (50,000 cells). Specific gene expression profiles were obtained, and known markers (e.g., uromodulin in the thick ascending limb of Henle's loop and aquaporin-2 in the collecting duct) were found appropriately enriched. In addition, several enriched tags had no databank match, suggesting that they correspond to unknown or poorly characterized transcripts with specific tissue distribution. It is concluded that SAGE adaptation for downsized extracts makes possible large-scale quantitative gene expression measurements in small biological samples and will help to study the tissue expression and function of genes not evidenced with other high-throughput methods.

Serial Analysis of Gene Expression

Article

Full-text available

Nov 1995

The characteristics of an organism are determined by the genes expressed within it. A method was developed, called serial analysis of gene expression (SAGE), that allows the quantitative and simultaneous analysis of a large number of transcripts. To demonstrate this strategy, short diagnostic sequence tags were isolated from pancreas, concatenated, and cloned. Manual sequencing of 1000 tags revealed a gene expression pattern characteristic of pancreatic function. New pancreatic transcripts corresponding to novel tags were identified. SAGE should provide a broadly applicable means for the quantitative cataloging and comparison of expressed genes in a variety of normal, developmental, and disease states.

Survival or death of individual proerythroblasts results from differing erythropoietin sensitivities: A mechanism for controlled rates of erythrocyte production

Article

Full-text available

Nov 1993

Murine erythroid progenitors infected with the anemia-inducing strain of Friend virus (FVA cells) undergo apoptosis when deprived of erythropoietin (EPO). When cultured with EPO, they survive and complete terminal differentiation. Although cell volume is decreased and nuclear chromatin is condensed during both apoptosis and terminal differentiation, morphologic and biochemical distinctions between these two processes were observed. In apoptosis, homogeneous nuclear condensation with nuclear envelope loss occurred in cells that had not reached the stage of hemoglobin synthesis. In terminal erythroid differentiation, nuclear condensation with heterochromatin, euchromatin, and nuclear envelope preservation occurred simultaneously with hemoglobin synthesis. Cells with apoptotic morphology appeared asynchronously in EPO-deprived cultures, indicating that only a portion of the cells were undergoing apoptosis at any given time. The percentages of apoptotic cells and cleaved DNA increased with time in EPO-deprived cultures. Inhibition of DNA cleavage was directly proportional to EPO concentration over a wide physiologic range, demonstrating a heterogeneity in susceptibility to apoptosis based on variability in the EPO sensitivity of individual cells. A subpopulation of FVA cells with increased EPO sensitivity (decreased EPO requirement) was isolated from EPO-deprived cultures. This increased EPO sensitivity did not result from differences in EPO receptor number, affinity, or structure, suggesting that the differences are in the signal transduction pathway. These results indicate that control of red blood cell production involves both prevention of apoptosis by EPO and heterogeneity in the EPO requirement of individual progenitor cells.

Gene Expression Profiles in Normal and Cancer Cells

Article

Full-text available

Jun 1997

As a step toward understanding the complex differences between normal and cancer cells in humans, gene expression patterns were examined in gastrointestinal tumors. More than 300,000 transcripts derived from at least 45,000 different genes were analyzed. Although extensive similarity was noted between the expression profiles, more than 500 transcripts that were expressed at significantly different levels in normal and neoplastic cells were identified. These data provide insight into the extent of expression differences underlying malignancy and reveal genes that may prove useful as diagnostic or prognostic markers.

Differentiation and erythropoietin receptor gene expression in human erythroid progenitor cells [see comments]

Article

Oct 1992

Partially purified human burst-forming unit-erythroid (BFU-E) cells from peripheral blood were cultured for 6 to 8 days to obtain colony- forming unit-erythroid (CFU-E) cells. When these BFU-E-derived CFU-E were further purified and recultured in liquid suspension cultures with erythropoietin (EPO), they matured and differentiated into reticulocytes in vitro. A maximum rate of hemoglobin synthesis was observed at day 10 of cumulative culture time by measuring 59Fe incorporation into heme. Withdrawal of EPO from erythroblast cultures at various times during development showed that between day 10 and day 11 (when the majority of the cells are in the polychromatic erythroblast stage), these cells became independent of EPO. The timing of the disappearance of the EPO requirement in these cells coincided with the marked decline in proliferation. Measurement of EPO receptor messenger RNA (mRNA) levels by Northern analysis showed that there is a slight decline during the day 8 to day 10 time period, followed by a rapid decline between days 10 and 14. Binding of 125I-EPO to erythroblasts also showed a steady decline of the cell surface binding during maturation and terminal differentiation. The half-life of the human EPO receptor was 90 minutes in the presence of the transcriptional inhibitor actinomycin D and the half-life measured at two different times during the 8- to 14-day culture period remained constant. These results indicate that human EPO receptor mRNA must be transcribed continuously to maintain the levels seen by Northern analysis. The human cell system described here is well suited for the study of a wide variety of biochemical events during late erythroid differentiation.

Erythropoietin

Article

Feb 1991

SB Krantz

Wickrema A, Krantz SB, Winkelmann JC, Bondurant MC.. Differentiation and erythropoietin receptor gene expression in human erythroid progenitor cells. Blood 80: 1940-1949

Article

Nov 1992

Partially purified human burst-forming unit-erythroid (BFU-E) cells from peripheral blood were cultured for 6 to 8 days to obtain colony-forming unit-erythroid (CFU-E) cells. When these BFU-E-derived CFU-E were further purified and recultured in liquid suspension cultures with erythropoietin (EPO), they matured and differentiated into reticulocytes in vitro. A maximum rate of hemoglobin synthesis was observed at day 10 of cumulative culture time by measuring 59Fe incorporation into heme. Withdrawal of EPO from erythroblast cultures at various times during development showed that between day 10 and day 11 (when the majority of the cells are in the polychromatic erythroblast stage), these cells became independent of EPO. The timing of the disappearance of the EPO requirement in these cells coincided with the marked decline in proliferation. Measurement of EPO receptor messenger RNA (mRNA) levels by Northern analysis showed that there is a slight decline during the day 8 to day 10 time period, followed by a rapid decline between days 10 and 14. Binding of 125I-EPO to erythroblasts also showed a steady decline of the cell surface binding during maturation and terminal differentiation. The half-life of the human EPO receptor was 90 minutes in the presence of the transcriptional inhibitor actinomycin D and the half-life measured at two different times during the 8- to 14-day culture period remained constant. These results indicate that human EPO receptor mRNA must be transcribed continuously to maintain the levels seen by Northern analysis. The human cell system described here is well suited for the study of a wide variety of biochemical events during late erythroid differentiation.

Quantitation of specific binding of erythropoietin to human erythroid colony-forming cells

Article

Nov 1988

Highly purified human erythroid colony-forming cells (ECFC), which consist predominately of colony-forming units-erythroid (CFU-E), were prepared from human blood and used to study the binding and processing of erythropoietin (Ep). When radioiodinated human recombinant Ep (125I-rEp) was incubated with these cells, binding was specific and saturable. Specific binding was directly proportional to cell concentration and did not occur with other human cells. Saturation of specific binding at 3 degrees C occurred at 1 nM (3.9/U/ml), and Scatchard analysis revealed two classes of binding sites on the cell surface. Of a total of 1,050 binding sites per ECFC, one-fifth had a Kd of 0.10 nM, while the remainder had a Kd of 0.57 nM. Specific binding was twofold greater at 37 degrees C than at 3 degrees C, and removal of surface-bound Ep with acid indicated that 125I-rEp was internalized into the cells after incubation at 37 degrees C. Further incubation at this temperature showed a decline of cellular radioactivity, with a release of small molecular weight degradation fragments into the medium. These studies demonstrate two classes of receptors for Ep on normal human ECFC. Internalization and degradation of EP occur, and the biologic effect of the hormone is produced by a small number of Ep molecules, as demonstrated in murine erythroid progenitor cells.

Tumor-suppressor P53 is a direct transcriptional activator of the human bax gene

Article

Feb 1995
CELL

The bax gene promoter region contains four motifs with homology to consensus p53-binding sites. In cotransfection assays using p53-deficient tumor cell lines, wild-type but not mutant p53 expression plasmids transactivated a reporter gene plasmid that utilized the bax gene promoter to drive transcription of chloramphenicol acetyltransferase. In addition, wild-type p53 transactivated reporter gene constructs containing a heterologous minimal promoter and a 39-bp region from the bax gene promoter in which the p53-binding site consensus sequences reside. Introduction of mutations into the consensus p53-binding site sequences abolished p53 responsiveness of reporter gene plasmids. Wild-type but not mutant p53 protein bound to oligonucleotides corresponding to this region of the bax promoter, based on gel retardation assays. Taken together, the results suggest that bax is a p53 primary-response gene, presumably involved in a p53-regulated pathway for induction of apoptosis.

Generation of Longer cDNA Fragments from SAGE Tags for Gene Identification

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