Nielsen H. RNA: Methods and Protocols

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134 Meijer and de Moor

4. Notes

1. This protocol requires RNase-free handling. Gloves must

be worn at all times. Glassware, tubes and tips should be

sterile. All solutions have to be RNase-free. DEPC treat-

ment might be required.

2. The linearised plasmids should when transcribed result in

products slightly longer (up to about 400 nt extra) than

the probe used for the polyadenylation. Ideally they all

are transcribed using the same polymerase. Mix the tem-

plates, including the template used for the probe for the

polyadenylation and synthesise a mixed set of radiolabelled

transcripts which then can be used as a molecular weight

marker. If not all plasmids are transcribed using the same

polymerase, it is not possible to mix the templates and the

transcription reactions will have to be performed separately.

3. Handle phenol and chloroform in a fume hood.

P is a highly energetic radioactive isotope. Take precau-

tions not to expose yourself or others. If you have not han-

dled

P before, ask for instructions from someone who

has experience in handling

5. The choice of RNA polymerase is dependent on the plas-

mid used.

6. The polyadenylation reaction is very sensitive to tempera-

ture and timing. If the polyadenylation reaction does not

result in a range from A0 to A400 (length in excess over

unadenylated probe), then it is necessary to try different

dilutions of E-PAP until a full range is obtained. Alterna-

tively, it is possible to vary the incubation times.

7. Acrylamide is poisonous and needs to be handled with care.

8. Pour the gel immediately after adding the TEMED.

9. This protocol is optimised for the use of total RNA. How-

ever, the protocol has also been tested on crude lysates of

tissue culture cells (NIH3T3) and Xenopus laevis oocytes.

For tissue culture cells use a 10 cm diameter plate with 4

× 10

cells. Remove medium, wash cells in ice cold PBS

and remove as much of the PBS as possible. Lyse cells

in 500 μL GTC/BME per plate, scrape cells and transfer

440 μL of lysate to a 2-mL tube. For X. laevis oocytes use

ten oocytes per sample. Collect oocytes in tubes and freeze

on dry ice. Lyse the fr ozen oocytes in 416 μLGTC/BME.

These amounts are sufﬁcient for subsequent microarray

analysis. For detection of a speciﬁc mRNA by RT-qPCR the

Fractionation of mRNA Based on the Length of the Poly(A) Tail 135

procedure can be performed on smaller amounts of starting

material.

10. The amount of biotinylated oligo(dT) will have to be opti-

mised for each sample type to ensure efﬁcient binding

and elution. We tested biotinylated oligo(dT) from differ-

ent suppliers but the protocol only works efﬁciently with

biotinylated oligo(dT) from Promega.

11. This protocol can be adjusted to elute in fewer fractions. To

prepare samples for microarray analysis elute with 0.075×

SSC (oligoadenylated RNA) and water only (polyadeny-

lated RNA).

12. The amount loaded for total RNA and unbound is 20% of

starting material.

13. For examples of further analysis see Meijer et al. (3).

References

1. Piccioni, F., Zappavigna, V., Verrotti, A.

C. (2005) Translational regulation during

oogenesis and early development: the cap-

poly(A) tail relationship. C.R. Biol 328,

863–881.

2. Meyer, S., Temme, C. and Wahle, E. (2004)

Messenger RNA turnover in eukaryotes:

pathways and enzymes. Crit Rev Biochem Mol

Biolv 39, 197–216.

3. Meijer, H.A., Bushell, M., Hill, K., Gant,

T.W., Willis, A.E., Jones, P. and De

Moor, C.H. (2007) A novel method for

poly(A) fractionation reveals a large popu-

lation of mRNAs with a short poly(A) tail

in mammalian cells. Nucleic Acids Res 35,

e132.

4. Gorgoni, B., Gray, N.K. (2004) The roles of

cytoplasmic poly(A)-binding proteins in reg-

ulating gene expression: a developmental per-

spective. Brief Funct Genomics Proteomics 3,

125–141.

5. Zangar, R.C., Hernandez, M., Kocarek, T.A.

and Novak, R.F. (1995) Determination of

the poly(A) tail lengths of a single mRNA

species in total hepatic RNA. Biotechniques

18, 465–469.

6. Couttet, P., Fromont-Racine, M., Steel, D.,

Pictet, R. and Grange, T. (1997) Messen-

ger RNA deadenylation precedes decapping

in mammalian cells. Proc Natl Acad Sci USA

94, 5628–5633.

7. Sallés, F.J., Richards, W.G. and Strickland, S.

(1999) Assaying the polyadenylation state of

mRNAs. Methods 17, 38–45.

8. Rassa, J.C., Wilson, G.M., Brewer, G.A. and

Parks, G.D. (2000) Spacing constraints on

reinitiation of paramyxovirus transcription:

the gene end U tract acts as a spacer to sep-

arate gene end from gene start sites. Virology

274, 438–449.

9. Piqué, M., López, M. and Méndez, R.

(2006) Cytoplasmic mRNA polyadenylation

and translation assays. Methods Mol Biol 322,

183–198.

10. Belloc, E., Méndez, R. (2008) A deadeny-

lation negative feedback mechanism gov-

erns meiotic metaphase arrest. Nature 452,

1017–1022.

Chapter 10

Analysis of Mutations that Inﬂuence Pre-mRNA Splicing

Zhaiyi Zhang and Stefan Stamm

Abstract

A rapidly increasing number of human diseases are now recognized as being caused by the selection

of wrong splice sites. In most cases, these changes in alternative splice site selection are due to single

nucleotide exchanges in splicing regulatory elements. This chapter describes the use of bioinformatics

tools to predict the inﬂuence of a mutation on alternative pre-mRNA splicing and the experimental

testing of these predictions. The bioinformatic analysis determines the inﬂuence of a mutation on splicing

enhancers and silencers, splice sites and RNA secondary structures. This approach generates hypotheses

that are tested using splicing reporter constructs, which are then analyzed in transfection assays. We

describe a recombination-based system that allows for the generation of splicing reporter constructs in

the ﬁrst week and their subsequent analysis in the second week.

Key words: Alternative splicing, mutation, splicing enhancer, splicing silencer, minigene analysis,

single nucleotide polymorphisms.

1. Introduction

In the ﬂow of genetic information, pre-messenger RNAs (pre-

mRNAs) transcribed from DNA templates carry the information

from genomic sequences to protein synthesis. The pre-mRNA is

processed, and sequences known as exons are incorporated into

the mRNA and exported into the cytosol. The remaining inter-

vening sequences, known as introns, stay in the nucleus where

they are eventually degraded. A pre-mRNA sequence can be rec-

ognized as an intr on or an exon, depending on the cellular envi-

ronment. This process is called alternative splicing. Almost all

(95%) of human multi-exon genes undergo alternative splicing

(1, 2). Unlike promoter activity that predominantly regulates the

H. Nielsen (ed.), RNA, Methods in Molecular Biology 703,

DOI 10.1007/978-1-59745-248-9_10, © Springer Science+Business Media, LLC 2011

137

138 Zhang and Stamm

abundance of transcripts, alternative splicing inﬂuences the struc-

ture of the mRNAs and their encoded pr oteins. As a result, it

inﬂuences binding properties, intracellular localization, enzymatic

activity, protein stability, and post-translational modiﬁcation of

numerous gene products (reviewed in (3 )).

1.1. Patterns of

Alternative Splicing

Alternative splicing events can be subdivided into ﬁve basic pat-

terns, as shown in Fig. 10.1. Exons can be skipped or included,

extended or shortened, or included in a mutually exclusive man-

ner; introns can be either removed or retained. Cassette exons

(or exon skipping) account for the majority of alternative splicing

events conserved between human and mouse genomes. Less fre-

quent are alternatively used 3



and 5



splice sites. Intron retention

is the least frequently used pattern and is responsible for less than

3% of the alternative splice events conserved between human and

mouse genomes. There are more complex events, such as mutu-

ally exclusive events, alternative transcription start sites, and mul-

tiple polyadenylation sites. In addition, these basic patterns can

be combined resulting in highly complex transcripts (4). An esti-

mated 75% of all alternative splicing patterns change the coding

sequence (5), indicating that alternative splicing is a major mech-

anism for enhancing protein diversity (reviewed by (3)).

Cassette exon

Intron retention

Alternative 3’ splice sites

Alternative 5’ splice sites

Mutually exclusive exons

Fig. 10.1. Types of alternative splicing. Flanking constitutive exons are indicated as

white boxes

, and alternative spliced regions are shown in

grey gradient

; introns are

shown by

solid lines

. The splicing patterns are indicated.

1.2. Mechanism of

Splice Site Selection

The introns that are removed from the pre-mRNA are deﬁned by

the 5



and 3



splice sites located at their ends and by the branch

point upstream of the 3



splice site (see Fig. 10.2). The molec-

ular mechanism of the splicing reaction that connects these sites

has been determined in great detail (6, 7). In contrast, it is not

Analysis of Mutations that Inﬂuence Pre-mRNA Splicing 139

U1 U1U2

RGguragu

ynyurAy

U2AF65

10-20

yagG

U2AF35

RGguragu

protein

hnRNP

ESE ESSISE ISS

Fig. 10.2. Splicing elements and splicing factors. Exons are indicated as

boxes

and introns as

thick lines

. Splicing reg-

ulator elements (enhancers or silencers) are shown as boxes labeled as ESE/ESS in exons or as ISE/ISS in introns. The



splice site (RGguragu), 3



splice site (y)

ncagG, and the branch point (ynyurAy) are indicated (r= aorg,y=coru,

n=a, t, c, or g). Two major groups of proteins, hnRNPs and SR or SR-related proteins bind to splicing regulator ele-

ments. ISE: intronic splicing enhancer, ISS: intronic splicing silencer, ESE: exonic splicing enhancer, ESS: exonic splicing

silencer.

clear how splice sites are recognized in the large background of

the pre-mRNA sequences. One major difﬁculty is the degener-

acy of 5



and 3



splice sites and branch point. To precisely iden-

tify the relatively small exons and excise large introns, additional

regulatory elements play an important role in splice site recog-

nition. They are classiﬁed according to their location and their

functional effect on splicing as exonic splicing enhancer (ESE),

exonic splicing silencer (ESS), intronic splicing enhancer (ISE),

or intronic splicing silencer (ISS). These elements are again char-

acterized by the loose consensus sequences (8). This sequence

degeneracy prevents splicing regulatory elements from interfer-

ing with the coding capacity of the exons (9). As a result, the

accurate splice site selection in vivo is achieved through a com-

binatorial regulatory mechanism by which the exonic or intronic

auxiliary elements aid exon recognition by binding to regulatory

proteins (10). Proteins binding to regulatory sequence e lements

can be classiﬁed into two groups: serine/arginine-rich (SR) pro-

teins and heterogeneous nuclear ribonucleoproteins (hnRNPs).

Generally, these proteins not only bind to RNA, but also to other

regulatory proteins. The interaction between individual splicing

factors and the regulatory sequence is weak, which allows easy

dislodging of the pr oteins from processed RNA after the splic-

ing reaction. As the protein:RNA interaction is weak, different

SR and SR-like proteins can act through the same regulatory

elements and inﬂuence the same splice sites. Higher speciﬁcity

is achieved by protein–protein interactions that allow simultane-

ous binding of multiple proteins to RNA. Several SR and SR-

like proteins bind to the catalytic component of the spliceosome,

e.g., to the U1 and U2 snRNP. Therefore, the transient forma-

tion of these protein complexes facilitates splicing complex assem-

bly (11). In addition, SR and SR-like proteins can bridge the

introns by interacting with themselves and the classical spliceo-

somal components (9), (see Fig. 10.2). In summary, numerous

factors binding to RNA elements inﬂuence splice site selection.

This degeneracy makes it difﬁcult to accurately predict splice site

usage.

140 Zhang and Stamm

1.3. Single

Nucleotide Changes

Can Inﬂuence

Splicing Pattern

Single nucleotide changes in the pre-mRNA can disturb the frag-

ile balance of multiple weak interactions governing exon recog-

nition and alter pre-mRNA splicing pattern. Mutations of cis-

elements can be classiﬁed into four categories according to their

location and effect. Type I and type II mutations occur in the

splice sites. They either destroy known splice sites or create novel

ones, which leads to exon skipping or inclusion. Type III and

type IV mutations take place in exons or introns, respectively,

and alter exon usage. From all the mutations that are anno-

tated in the human genome, about 10% of the 80,000 reported

affect canonical splice site sequences (12). This number is most

likely an underestimation since most mutations that affect the

intronic and exonic splicing elements are not included in the

statistic. Exonic nucleotide exchanges that inﬂuence splice site

selection are often synonymous (13) and polymorphisms located

in introns can inﬂuence splice site selection (14). Because these

single nucleotide polymorphisms (SNPs) do not change the pre-

dicted reading frame they were considered ‘noise’ without func-

tional effects. However, detailed analyses of synonymous exonic

and intronic mutations revealed a strong effect on splicing that

leads to frameshifts, subsequent loss of protein function and

human disease (15). Recent array analysis suggests that a large

number of SNPs associate with changes in splicing (16). An

increased awareness concer ning the role of alternative splicing in

the etiology of human diseases has led to a strong increase in

the number of diseases reported to be associated with changes in

alterative splicing (reviewed in (17–21)). It is estimated that up

to 50% of the mutations that cause human disease alter the efﬁ-

ciency and pattern of splicing (16). Analysis of splicing mutations

causing cystic ﬁbrosis revealed that the splicing pattern caused by

a SNP can differ between individuals. This most likely reﬂects that

splice site selection is regulated by multiple factors that work in

combination and that a mutated allele responds only to a cer-

tain combination. These ﬁndings suggest that alternative splic-

ing is a genetic modiﬁer (18, 22) and imply that a large fraction

of mutations affect exon usage. A list of single nucleotide muta-

tions in splicing regulatory elements is given in Table 10.1.The

widespread inﬂuence of SNPs on alternative splicing is the reason

for their further b ioinformatics and experimental analysis.

1.4. Bioinformatics

Resources for

Alternative Splicing

The completion of numerous genomic sequencing projects has

provided a wealth of information revealing the abundant usage of

alternative splicing in metazoan organisms. A number of groups

have created resources by collecting splice variants and alternative

transcript structures. These resources can be classiﬁed into two

categories: computer and manually generated databases on alter-

native splicing events and computational tools to decipher the

Analysis of Mutations that Inﬂuence Pre-mRNA Splicing 141

Table 10.1

Examples of single nucleotide mutations change splicing pattern. The table lists

examples of mutations in the intronic or exonic sequences that cause aberrant

splicing

Gene Mutation Effect References

ADA CTGTCCACGCC→CTGTCCACACC Exon 7 skipping (31)

ATM ATTCGAGTG→ATTTGAGTG

ACTCAACAT→ACTTAACAT

AGgtaa→Agttaa

tttagGT→tttaaGT

AAGGTTTTA→AAGATTTTA

CTCGAAACA→CTCAAAACA

Exon 9 skipping

Exon 9 skippig

Intron 12 retention

Exon 18 skipping

Exon 26 skipping

Exon 44 skipping

(32)

ATP7A GATGGAATC→GATC/AGAATC Exon 4 skipping (33)

BRCA1 ATCTTAGAG→ATCGTAGAG Exon 18 skipping (34)

FAH ATGAACGAC→ATCAATGAC

AAGCAGGAC→AAGCGGGAC

Exon 8 skipping

Exon 9 skipping

(35, 36)

HEXB GCGCCGGGC→GCGCTGGGC Exon 11 skipping (37)

HPRT1 CATGGACTA→CATAGACTA

GAACGTCTT→GAACATCTT

ATTGTGGAA→ATTATGGAA

Exon 8 skipping (38)

IKBKAP gtaagtgc→gtaagcgc Exon 20 skipping (39)

MAPT

(tau)

ATTAATAAG→ATTAAGAAG

GGCAGTgtg→GGCAATgtg

GATCTTAGC→GATCTCAGC

ATAATATCA→ATAACATCA

Exon 10 inclusion ( 40, 41)

MLH1 GAGAAGAGA→GAGTAGAGA Exon 12 skipping (42)

NF1 CTTAAGAAC→CTTAAAAAC Exon 7 skipping (43)

SMN2 GGTTTTAGAC→GGTTTCAGAC Exon 7 skipping ( 44)

Large letters indicate exonic sequences; small letters indicate intronic sequences. The sequence on the left side of the

arrow is wild type, and the right side is mutant. The bold letter indicates the single nucleotide mutation.

splicing signals. Most of the databases are based on the contin-

uously increasing amount of expressed sequence tag (EST) data.

These EST data provide the major information source for com-

putational detection of alternative splicing patterns.

In order to predict alternative splicing events with accuracy,

several algorithms were specially devised. The ﬁrst computational

approach is based on EST and mRNA comparison (23). However,

EST-mRNA comparison has limited power because the intronic

information is not included (24). To address the problems caused

by EST-mRNA comparison, algorithms based on genome-EST

pair-wise alignment are used in computational prediction pro-

grams. Several popular programs, such as BLAT, are designed

using alignment of cDNA and genomic segments. These pro-

grams perform both genomic mapping and alignment (25). How-

ever, genome-EST comparison algorithms do not provide direct

142 Zhang and Stamm

exon–intron gene structures and may not be reliable. Hence, an

algorithm based on EST-genome multiple alignment comparison

has been devised in order to overcome this limitation. The algo-

rithm minimizes the false splice site prediction due to incorrect

EST-gene alignment that is not supported by the majority of EST

data (26). Table 10.2 lists database resources for alternative splic-

ing.

Splicing regulatory RNA sequences and their trans-acting fac-

tors have been individually studied in great detail, both by exper-

imental and bioinformatics appr oaches. The result of these stud-

ies let to the development of programs that predict splice sites,

splicing regulatory sequences, their binding partners, as well as

possible RNA secondary structure. Table 10.3 lists these compu-

tational tools. It should be emphasized that due to the complexity

of splice site selection the programs are currently fairly inaccurate.

However, the usage of several programs allows the generation of

hypotheses that can be experimentally tested.

1.5. Reporter Gene

Analysis of Splicing

Events

The most common technique to analyze exon usage and especially

the effect of a mutation on splice site selection is reporter mini-

gene analysis. In this method, an exon of interest, as well as its

ﬂanking exons are cloned into an expression vector and analyzed

after transfecting this construct into eukaryotic cells (reviewed

in (27, 28)). Currently about 200 such constructs have been

reported in the literature. The comparison of two minigenes that

were mutated to reﬂect naturally occurring alleles allows one to

determine how a SNP inﬂuences alternative splicing.

The system can be expanded for the analysis of trans-

acting factors by cotransfecting an incre asing amount of factor-

expressing cDNA constructs with the reporter minigene. To facil-

itate cloning of splicing reporter constructs, a recombination-

based system that allows rapid generation of minigenes from

PCR products containing the alternative exon has been developed

(29). The system allows generating reporter minigenes within 1

week (see Fig. 10.3). Reporter minigenes then permit experimen-

tal tests concerning the inﬂuence of a mutation on splicing.

2. Materials

The computational analysis requires only internet access, as all

programs are freely available.

2.1. Cloning of the

Minigenes

1. Bacterial strain DB3.1 (Invitrogen, E. coli F

–

gyrA462

endA1 (sr1-recA) mcrB mr r hsdS20(r

-, m

) supE44 ara14

Analysis of Mutations that Inﬂuence Pre-mRNA Splicing 143

Table 10.2

Overview of existing databases on alternative splicing events

Database Description

Reference

sequence

Species

covered

Additional

analysis tool

Integration

with other

resource URL References

ASAP Database of human tissue-

speciﬁc regulation of

alternative splicing

information through a

genome-wide analysis of

expressed sequence tags

(ESTs)

ESTs Human Microarray

analysis

tutorial

download

Unigene,

genbank

database

http://bioinfo.mbi.

ucla.edu/ASAP/

(45)

ASD ( Alterna-

tive Splicing

Database)

Database of manually

annotated and compu-

tational generated data

on alternative splicing

events and the resultant

isoform splice patterns

of genes from model

species. Database Alt-

Splice and AEdb are

included

Genomic

sequence

Human and

mouse

Intron analy-

sis, scoring

ATG-

context

sequence,

MZEF-

SPC exon

ﬁnder,

regulatory

sequences

Ensemble

genome

annotation

project

http://www.ebi.

ac.uk/asd/

(46, 47)

ASDB (Alterna-

tive Splicing

Database)

Database of alternatively

spliced gene, their prod-

ucts and expression pat-

terns

Genomic

sequence

Human Genbank

database,

Swiss-Prot

protein

knowledge-

base

http://hazelton.

lbl.gov/~teplitski/

alt/

(48, 49)