Molecular and Genetic Characterization of Spinocerebellar Ataxia Type 5 (SCA5)

A DISSERTATION SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY

Katherine Andrea Dick Krueger

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

ADVISOR: Laura P. W. Ranum, Ph.D.

September, 2008

© KATHERINE ANDREA DICK KRUEGER, 2008

AKNOWLEDGEMENTS

Portions of this thesis are previously published and involve the work of others. I

would like to thank Yoshio Ikeda and Marcy Weatherspoon for their contributions towards

mapping and identifying the SCA5 mutations; and our collaborators from France and

Germany, specifically, Alexis Brice, Giovanni Stevanin, Alexandra Dürr, Christine Zühlke,

and Katrin Bürk for access to their DNA samples (Chapter 2). I would also like to thank

Karen Armbrust for the initial wildtype SPTBN2 constructs; Dr. Vann Bennett and members of his lab, particularly, Jonathan Davis and Khadar Abdi, for their assistance with the protein purification and circular dichroism; and Dr. James Ervasti for helpful discussions and reagents (Chapter 3). The research presented in Appendix A also involves the contributions of others and I would like to thank Dr. Shoji Tsuji and members of his lab for performing the SNP analysis; Dr. Michael Miller for his assistance with the VITESSE analysis; and the NHLBI Mammalian Genotyping Service (Contract Number NO1-HV-

48141). Additionally, I would like to thank Dr. John Day for his clinical expertise and work with both the SCA5 and ALS patients. I would also like to express my gratitude for the funding support I received from the Doctoral Dissertation Fellowship (2007-08).

I would like to thank past and present members of the Ranum lab for their

assistance, advice and friendships over these many years. I would particularly like to

express my gratitude to Laura P. W. Ranum, who has not only been an advisor but a true

mentor.

Lastly, I would not have accomplished this goal without the love and support of

my family and would especially like to thank both of my parents and my husband,

Benjamin.

i ABSTRACT

Spinocerebellar ataxia type 5 (SCA5) is a progressive neurodegenerative disorder,

which primarily affects the cerebellum. The disease is inherited in an autosomal

dominant pattern, with onset typically occurring in the 3rd or 4th decade of life. In 1994,

SCA5 was mapped to the centromeric region of chromosome 11 using an 11-generation

American kindred, and was later refined to 11q13. Using a multifaceted mapping approach, which involved screening for expansion mutations, searching for haplotype conservation and sequencing, we discovered β-III spectrin (SPTBN2) mutations cause

SCA5 in the American family and two additional ataxia families from France and

Germany. In-frame microdeletions were identified in the American (39 bp) and French

(15 bp) families within the third of 17 homologous, triple-helical, spectrin repeat motifs.

In the German SCA5 family, a point mutation (Leu253Pro) was found within the C-

terminal calponin homology (CH) domain, which is known to bind F-actin.

Through expression studies in tissue culture and circular dichroism analyses, I

characterized the effects of the German SCA5 mutation on protein folding, stability and

function. These experiments demonstrate that the leucine to proline substitution causes a

temperature sensitive misfolding of the protein, rendering it insoluble and subject to

degradation. Additionally, the mutation likely disrupts the tightly controlled binding

between spectrin and actin, resulting in an enhanced interaction of the mutant protein

with both G- and F-actin.

Spectrin mutations are a novel cause of ataxia and the continued characterization

of these mutations will lead to a better understanding of the pathogenic mechanisms

underlying SCA5 and neurodegenerative disease in general.

ii

TABLE OF CONTENTS

Acknowledgements

Abstract______i

Table of Contents ______iii

List of Figures and Tables______vi

Abbreviations ______viii

Chapter 1: Introduction to SCA5

I. Introduction______1

II. Genetic and Physical Mapping of SCA5 ______3

III. Anticipation______4

IV. CAG Repeat Expansion Investigation ______6

V. Clinical Features ______8

VI. Neuroimaging and Neuropathology ______10

VII. Conclusions______11

VIII. Overall Aims and Hypotheses ______11

Chapter 2: Genetic Mapping of SCA5

Abstract______20

I. Introduction______21

II. Results______22

iii III. Discussion______25

Chapter 3: Molecular Characterization of the L253P SCA5 Mutation in a Tissue Culture

Model

Abstract______39

I. Introduction______40

II. Results______42

III. Discussion______47

IV. Conclusion ______50

Chapter 4: Conclusions and Future Directions

I. Summary and Conclusions ______60

II. Future Directions ______62

Chapter 5: Materials and Methods

I. Genetic Mapping of SCA5 ______65

II. Molecular Characterization of the L253P Mutation ______69

Appendix A: Mapping Mendelian disorders in small families: validation of SNP haplotype mapping

Abstract______80

I. Introduction______82

II. Materials and Methods ______84

iv III. Results______87

IV. Discussion______94

References______111

v LIST OF TABLES AND FIGURES

Chapter 1

Figure 1- Pedigree of American SCA5 family ______13-4

Figure 2- Genetic map of SCA5 critical region ______15

Figure 3- Sagittal MRI scan from an affected individual ______16

Table 1- Classification of the SCAs ______17

Table 2- Pairwise LOD scores ______18

Table 3- SCA5 clinical features in the American family ______19

Chapter 2

Figure 4- Critical regions for the three SCA5 families______31

Figure 5- BAC map spanning the SCA5 region ______32

Figure 6- Illustration of SPTBN2 gene and β-III spectrin protein structure ______33

Figure 7- The three SCA5 mutations ______35

Figure 8- RNA and protein expression cerebellar tissues______36

Table 4- Marker and genotype data for the haplotype conservation region ______37

Table 5- Summary of DNA sequence variations in the three BAC regions ______38

Chapter 3

Figure 9- Ribbon illustration of the C-terminal CH domain of β-III spectrin ______51

Figure 10- Circular dichroism of the N-terminal of β-III spectrin ______53

Figure 11- Tissue culture expression of wildtype and mutant β-III spectrin ______55

Figure 12- Promotion of protein folding at 25°C ______56

Figure 13- Promotion of protein folding by HSP-70 ______57

vi Figure 14- Aberrant binding to actin ______58

Figure 15- G- versus F-Actin ______59

Chapter 5

Table 6- Primer sequences for SPTBN2 sequencing______77

Table 7- PCR conditions for SPTBN2 sequencing ______78

Table 8- Primer sequences and PCR conditions for mutation screening ______79

Appendix A

Figure 16- ALS-A pedigree ______100

Figure 17- Examples of the haplotype analysis ______102

Figure 18- Haploid and multipoint analysis comparison ______103

Figure 19- Comparison of recombination points identified by haploid mapping and SNPs ______104

Figure 20- Physical location of the shared regions. ______106

Figure 21- Non-parametric LOD score analysis of the SNP genotypes ______107

Figure 22- Parametric LOD score analysis of the SNP genotypes ______108

Table 9- Data for the haploid and SNP shared regions and the SNP ambiguous regions ______109

Table 10- Genetic status of unaffected individuals II:3 & II:9 for the seventeen shared and ambiguous regions ______110

vii ABREVIATIONS

Å ______angstrom

ADCA ______autosomal dominant cerebellar ataxia

ARP1______actin related protein 1

ATP______adenosine triphosphate

BAC ______bacterial artificial chromosome

bp, kb, Mb______basepairs, kilobases, megabases

°C ______temperature in degrees Celsius

CEPH ______Centre d'Etude du Polymorphisme Humain

CH domain ______calponin homology domain

CD______circular dichroism

CMV ______cytomegalovirus

Co-IP______co-immunoprecipitation

Da, kDa ______daltons, kilodaltons

DMEM ______dulbecco’s modified eagle’s medium

DNA ______deoxyribonucleic acid

E2 ______embryonic day 2

EAAT4 ______excitatory amino acid transporter 4

ECL______enhanced chemiluminescence

eGFP ______enhanced green fluorescent protein

°F______temperature in degrees Fahrenheit

F-actin ______filamentous actin fALS ______familial amyotrophic lateral sclerosis

viii FBS ______fetal bovine serum

FITC ______fluorescein isothiocyanate

FTD______frontotemporal dementia

G-actin______globular actin

HAT ______sodium hypoxanthine aminopterin and thymidine

HEK 293T______human embryonic kidney cell line

IgG ______immunoglobulin G

IRES ______internal ribosome entry site

LOD ______logarithm of the odds

MRI______magnetic resonance imaging

µg, mg, g ______micrograms milligrams, grams

µl, mL, L ______microliters, milliliters, liters

µM, mM, M______micromolar, millimolar, molar

N2A______mouse neuroblastoma-2A cell line

NPL______nonparametric linkage

OD______optical density

PBLs ______peripheral blood lymphocytes

PBS ______phosphate buffered saline

PCR______polymerase chain reaction

RAPID______repeat analysis pooled isolation and detection

RED______repeat expansion detection

RIPA ______radioimmunoprecipitation buffer

RNA ______ribonucleic acid

ix RT-PCR______reverse transcriptase polymerase chain reaction sALS ______sporadic amyotrophic lateral sclerosis

SCA______spinocerebellar ataxia

SPTBN2______spectrin, beta, nonerythrocytic, 2

SNP ______single nucleotide polymorphism

STRP______short tandem repeat polymorphism

U ______units

UTR______untranslated region

x CHAPTER 1

INTRODUCTION TO SCA5

I. Introduction

The spinocerebellar ataxias (SCAs) are a heterogeneous group of

neurodegenerative disorders characterized by incoordination, slurred speech and

swallowing difficulties. These disorders can lead to death within a period of years, as in

SCA1, or in other cases, such as SCA5, not significantly shorten life span. In 1982,

Harding proposed that these autosomal dominant cerebellar ataxias (ADCA) be divided into three classes based on clinical symptoms (Harding 1982). The ADCA type I category encompasses the cerebellar ataxias that are also associated with ophthalmoplegia, pyramidal or extrapyramidal signs, cognitive impairment or peripheral neuropathy (Duenas et al. 2006). The degeneration is not restricted to the cerebellum and can affect other regions of the brain, including the basal ganglia, cerebral cortex, optic nerve, pontomedullary systems, peripheral nerves or spinal tracts. ADCA type II is distinguished from the first category by retinal and macular degeneration while the third

ADCA category is defined by relatively pure cerebellar degeneration and symptoms.

There are at least two genetic loci within the ADCA type II category (Giunti et al. 1999), while the first and second classes are clearly genetically heterogeneous and contain the remaining 26 SCA loci (Table 1) (Duenas et al. 2006).

In addition to being categorized by clinical features, the SCAs are also classified genetically and currently can be organized into three groups (Soong and Paulson 2007).

1 The first and foremost category, which accounts for over 50% of affected families,

includes SCAs that are caused by CAG repeat expansions encoding polyglutamine tracts

(Duenas et al. 2006; Soong and Paulson 2007). SCA1, 2, 3, 6, 7, 17 and dentatorubral

pallidoluysian atrophy (DRPLA) fall within this mechanistic classification. The second category includes SCA8, 10 and 12, which are caused by repeat expansions located in non-coding regions of their respective genes (Holmes et al. 1999; Koob et al. 1999;

Matsuura et al. 2000; Duenas et al. 2006; Soong and Paulson 2007). While the SCA8

expansion was initially recognized as a non-coding expansion, it was recently reported

that bi-directional expression of the SCA8 repeat expansion results in the expression of

two potentially pathogenic molecules: CUG expansion transcripts expressed in the CTG

direction and a nearly pure polyglutamine expansion protein in the CAG direction

(Moseley et al. 2006). Finally, a third category of SCA mutations are caused by

traditional mutations, such as point mutations, deletions and insertions that affect the

protein coding regions of genes. SCA13, SCA14 and SCA27 have been shown to be

caused by point mutations in the voltage-gated potassium channel (KCNC3) (Waters et al.

2006), protein kinase C gamma (PCKγ) (Chen et al. 2003) and fibroblast growth factor 14

(FGF14) genes (van Swieten et al. 2003), respectively. Additionally, mutations in tau tubulin kinase-2 (TTBK2), inositol 1,4,5-triphosphate receptor, type 1 (ITPR1) and puratrophin-1 (PLEKHG4) have been reported to cause of SCA11 (Houlden et al. 2007),

SCA15 and 16 (van de Leemput et al. 2007; Iwaki et al. 2008), and chromosome 16q22 linked SCA, respectively (Ishikawa et al. 2005). The mutations responsible for 11 additional SCAs have been mapped but are not yet identified (Gardner et al. 1994; Worth et al. 1999; Miyoshi et al. 2001; Brkanac et al. 2002; Burmeister 2002; Swartz et al.

2 2002; Verbeek et al. 2002; Vuillaume et al. 2002; Chung et al. 2003; Knight et al. 2003;

Dudding et al. 2004; Knight et al. 2004; Stevanin et al. 2004; Verbeek et al. 2004; Yu et al. 2005; Cagnoli et al. 2006). The number of different dominant ataxia genes is not yet clear, but may substantially exceed the 27 genetic loci that are currently defined.

II. Genetic and Physical Mapping of SCA5

A. The Identification and Characterization of an American

Family with a Novel Form of SCA

In 1994, Ranum et al. reported a ten-generation American kindred with a

relatively mild autosomal dominant form of spinocerebellar ataxia (Figure 1). The family

has two major branches, which can be traced back to the paternal grandparents of

President Abraham Lincoln. DNA was collected from 248 family members, including 77

affected individuals, and a genome-wide screen was performed after excluding known

loci. The mutation was mapped to the centromeric region of chromosome 11 and the

disorder was designated SCA5 (Ranum et al. 1994). Table 2 shows pairwise LOD scores

for selected markers spanning this region. A maximal LOD score of 14.66 was generated

at marker D11S913 (Θ=0.0). After mapping the SCA5 locus to chromosome 11 (Ranum

et al. 1994), a positional cloning approach was implemented and a high-resolution genetic

map was developed. Analyses of recombinant chromosomes placed the SCA5 locus on

11q13, between PYGM and INT2 (Figure 2) (Koob et al. 1995). Consistent with reduced

male recombination rates near centromeric regions (Fain et al. 1996), all affected

recombinants used to narrow the SCA5 critical region were maternally transmitted. The

absence of paternally transmitted recombinant chromosomes limited the number of

3 recombinant chromosomes available for analysis and slowed efforts to genetically refine the region.

B. The Identification of Two Additional SCA5 Families

In 1999, a second family with a similar disease presentation was mapped to the

SCA5 locus (Stevanin et al. 1999). This sixteen member family of French descent included six affected individuals. Pairwise LOD score analysis was performed between the disease locus and five markers spanning a ~20cM centromeric region of chromosome

11, and a maximal LOD score of 3.97 was generated for marker PYGM (Θ=0.0). No recombination events between these five markers were identified in the affected individuals, indicating the critical region for this family spanned at least 28Mb

(D11S905-INT2) (Figure 2).

In 2004, Bürk et al. reported a third, unrelated SCA5 family of German descent, whose affected haplotype spanned the region between D11S1883 and D11S4136

(6.19Mb). Two-point LOD score analysis generated a maximum score of 4.21 at marker

D11S1889 (Θ=0.0), while multipoint linkage analysis produced a LOD score of 5.76 between the markers flanking the affected haplotype (Burk et al. 2004). The identification of this family slightly refined the telomeric end of the critical region, which had previously been defined by the American family (INT2), to D11S4136 (Figure 2).

III. Anticipation—a Phenotypic Marker of Unstable Repeat Expansions

Because anticipation is hallmark of neurodegenerative diseases caused by unstable repeat expansions (Klockgether and Evert 1998), the three SCA5 families were

4 examined to determine if succeeding generations had earlier ages of onset (Ranum et al.

1994; Stevanin et al. 1999; Ikeda et al. 2006). In the American family, examination of parent offspring pairs showed that the mean ages of onset for the older (43.3 years) versus younger (29.9 years) generations were significantly different (p<0.001) (Ranum et al. 1994). Additionally, several three-generation examples of anticipation were observed in which grandparents had onsets 10-40 years later in life than their children and grandchildren. However, unlike many forms of SCA, the largest decreases in age of onset were preferentially associated with maternal transmissions: the average decrease in age of onset for maternal v. paternal transmissions was -15.7 and -9.3 years. Furthermore, five of the six juvenile onset cases in the American family were maternally inherited

(Ranum et al. 1994). In the French family, there was a trend towards earlier onset, although it was not significant (Stevanin et al. 1999). Onset of the disease was found to occur at 32 ± 7 years in generation IV and 21 ± 11 years in generation V. However, five parent-child pairs were analyzed and mean anticipation was only -0.6 ± 8 years (Stevanin et al. 1999). In the German family, there was also a non-significant trend toward earlier onset in consecutive generations, with disease symptoms beginning at 38.6 ± 11.5 years in the third generation and 28 ± 10.2 years in the fourth (p=0.09) (Burk et al. 2004).

Additionally, mean anticipation from eight parent-child pairs was found to be 15.8 ± 8 years (Burk et al. 2004). Although the mean age of onset did not significantly decrease in the youngest generation of either the French and German SCA5 families, anticipation may have not been apparent given the small size of these families (Stevanin et al. 1999;

Burk et al. 2004). Conversely, the anticipation observed in the American family could also be explained by an ascertainment bias. For example, the age of onset difference for

5 the older versus the younger generations will be lessened when the currently unaffected

offspring develop signs of the disease later in life and are included in the calculation

(Ranum et al. 1994).

IV. CAG Repeat Expansion Investigation

To investigate the possibility that the variable ages of onset and disease severity

in the American family were caused by the expansion of an unstable CAG/CTG trinucleotide expansion, the Repeat Expansion Detection (RED) assay was performed.

Additionally, the 1C2 antibody, which recognizes expanded polyglutamine tracts, was also used in the analysis of SCA5 autopsy tissue.

A. RED and RAPID Cloning

The Repeat Expansion Detection (RED) assay is an elegant technique for

detecting potentially pathological trinucleotide repeat expansions without requiring

knowledge of chromosomal location (Schalling et al. 1993). Human genomic DNA is

used as a template for a two-step ligation cycling process, which results in the formation

of ligated primers that correspond in length to the longest repeat in the genome (Schalling

et al. 1993). RED was performed on DNA from a juvenile onset American SCA5 patient

and subsequently performed on DNA from the French family (Stevanin et al. 1999; Schut

et al. 2000). A candidate CAG/CTG expansion was detected in the American SCA5

patient, however, analysis of French family DNA did not provide evidence of a

expansion mutation (Stevanin et al. 1999).

To determine if the putative American CAG/CTG repeat expansion was the

6 pathogenic cause of SCA5, a method to clone and identify unique sequences surrounding

expanded repeat tracts was developed. This method, called Repeat Analysis Pooled

Isolation and Detection (RAPID) cloning, uses an optimized RED protocol to follow an expanded repeat tract through a series of enrichment steps until a clone containing the expanded repeat is isolated (Koob et al. 1998). Nucleotide sequence flanking the repeat is then obtained and used to design a PCR assay that can be used to determine if an expanded repeat co-segregates with the disease. RAPID cloning was successfully used to identify the SCA7 (Koob et al. 1998), SCA8 (Koob et al. 1999), SCA12 (Holmes et al.

1999) and Huntington’s disease-like 2 (Holmes et al. 2001) repeat expansions. Although

RED analysis suggested the possibility that a CAG/CTG expansion causes SCA5, RAPID cloning and subsequent PCR analysis demonstrated the expansion was a non-pathogenic background expansion that did not co-segregate with the disease. Additional RED and

RAPID analyses performed on genomic DNA from other family members with juvenile- onset SCA5, who would be expected to have the largest repeat expansions, also indicated that SCA5 was not caused by a CAG/CTG expansion greater than 40 repeats (Schut et al.

2000; Liquori et al. 2002).

B. The 1C2 Antibody and Evidence of a CAG Expansion Mutation

The monoclonal 1C2 antibody has been shown to recognize expanded polyglutamine tracts in a set of diseases caused by CAG repeat expansions, including

SCA1, SCA2, SCA3 and Huntington’s disease (HD) (Trottier et al. 1995; Stevanin et al.

1996). To determine if a protein containing an expanded polyglutamine was present in the French family, western blot analysis with the 1C2 antibody was performed, however, evidence of an expanded CAG repeat was not detected (Stevanin et al. 1999).

7 Additionally, immunohistochemistry was performed with the 1C2 antibody using autopsy

tissue from an American SCA5 patient, but reactive inclusions were not detected (Dr.

Laura Ranum, personal communication). While an expanded polyglutamine was not

detected in either of the two SCA5 families tested, it was plausible that a pathogenic

polyQ repeat was present but below the threshold of detection of the 1C2 antibody.

However, taken together, these results suggested that if SCA5 was caused by a

microsatellite expansion, the mutation was most likely a trinucleotide motif other than

CAG/CTG, or a variant repeat motif such as those that cause SCA10 (ATTCT) (Matsuura et al. 2000) or myotonic dystrophy type 2 (CCTG) (Liquori et al. 2001).

V. Clinical Features

The clinical symptoms of SCA5 progress over time and include incoordination of the extremities, slurred speech, and gait ataxia. Disease onset generally occurs in the

third or fourth decade of life, but has been reported to occur as young as 10 and as old as

68 years of age (Ranum et al. 1994; Stevanin et al. 1999; Schut et al. 2000; Burk et al.

2004). SCA5 is a relatively pure cerebellar disorder, with little brainstem or spinocerebellar tract involvement (Ranum et al. 1994; Stevanin et al. 1999; Schut et al.

2000; Burk et al. 2004). Similar to SCA6 (Zhuchenko et al. 1997), SCA11 (Worth et al.

1999) and SCA15 (Knight et al. 2003), SCA5 generally does not shorten life span and has a relatively mild disease course, likely due to the absence of bulbar paralysis in adult- onset patients (Ranum et al. 1994; Stevanin et al. 1999; Burk et al. 2004). In contrast, several juvenile onset SCA5 patients have been shown to have some bulbar and pyramidal tract dysfunction, in conjunction with a weakened ability to cough and

8 swallow—an indication that some individuals may develop a predisposition for

pneumonia that may shorten lifespan (Ranum et al. 1994).

Table 3 provides a summary of the clinical features for 77 affected members of

the American family. Onset, often marked by stumbling or imbalance during routine

activities, generally occurs in the third or fourth decade of life, with a mean age of 33.0 ±

13 yrs (range 10-68 yrs) (Schut et al. 2000). The primary feature observed in affected patients is a progressive gait ataxia with truncal instability, however, 90% of affected individuals also present with the less disabling upper limb ataxia. As symptoms progress

over time, many patients require the use of mobility aids, though rarely and only after

several decades does this entail the use of a wheelchair. While most patients eventually

experience difficulties with activities that require fine finger dexterity, such as

handwriting, only four individuals suffered from severely debilitating upper extremity

ataxia (70-90 yrs.) (Schut et al. 2000).

Cerebellar dysarthria, which lacks significant bulbar or spastic elements, was also

a common finding. Approximately 75% of patients presented with moderately affected

articulation, which typically did not interfere with communication. One third of the

patients examined experienced mild sensory deficits and half of the patients showed

definite extraocular movement incoordination, with gaze-evoked nystagmus, square wave

jerks, or saccadic intrusions during smooth pursuit. While extensor plantar reflexes were

present in only one person, brisk reflexes were observed in one-third of the patients,

suggesting mild pyramidal tract involvement (Schut et al. 2000; Liquori et al. 2002).

9 VI. Neuroimaging and Neuropathology

Magnetic resonance imaging (MRI) showed dramatic cerebellar cortical atrophy,

with extensive deterioration in the superior hemispheres and anterior vermis, in twelve

affected members of the American family (Schut et al. 2000). The cerebral hemispheres,

basal ganglia, inferior vermis, tonsils, and brainstem also appear spared by MRI

(Stevanin et al. 1999; Liquori et al. 2002; Burk et al. 2004). A representative sagittal

MRI section from an SCA5 patient is shown in Figure 3.

Neuropathological analysis was performed on an autopsy brain from an affected

American family member who had slight upper extremity ataxia and dysarthria, but

normal sensory and strength testing in a clinical examination five years prior to death.

The patient was immobile for the last decade of her life due to the combination of ataxia

and severe arthritis. Atypical of SCA5, this patient also suffered from dementia due to

superimposed and pathologically confirmed Alzheimer’s disease (Schut et al. 2000;

Liquori et al. 2002).

The cerebellum from this individual was found to be exceptionally small (88g), showing marked folial atrophy in the anterior vermis and the anterior-superior portions of the hemispheres, with relative sparing of the tonsillar cortex (Schut et al. 2000; Liquori et al. 2002). Analysis further revealed cerebellar cortical degeneration with predominant

Purkinje cell loss and thinning of the molecular layer, along with granular cell loss and frequent empty basket fibers. Afferent loss from the Purkinje cells was suggested by gliotic but intact deep cerebellar nuclei. With the exception of the inferior olivary nuclei, brainstem and spinal cord nuclei were spared (Schut et al. 2000; Liquori et al. 2002).

10 VII. Conclusions

In contrast to many of the ataxias, SCA5 is a slowly progressive disease that usually does not shorten lifespan. Clinical, neuroimaging and pathological data indicate that SCA5 primarily affects the cerebellum with little or no brainstem involvement, at least for adult-onset cases. Although onset typically occurs in mid-life, a broad range in the age of onset has been observed (10-68 yrs). Decreases in ages of onset with consecutive generations suggested that an unstable microsatellite expansion could be responsible for the disease; however RED and RAPID analysis indicated that the presence of a CAG/CTG expansion was unlikely. The SCA5 locus was mapped to 11q13 and a positional cloning strategy was used to identify the mutation. Ultimately, through the identification and characterization of the SCA5 mutation a more comprehensive understanding of the genetic causes of ataxia and the interdependence of the neuronal systems affected during SCA pathogenesis will be obtained.

VIII. Overall Aims and Hypotheses

The overall aim of my thesis is to identify the mutation that causes SCA5 and subsequently characterize the mutation in a tissue culture model. To address this aim, I implemented a multifaceted mapping approach that included screening for expansion mutations, examining the affected haplotype from the three SCA5 families for conservation and both targeted and brute force sequencing (Chapter 2). Using this approach, I identified and characterized three distinct mutations in the American, French and German families. In a tissue culture model, I subsequently examined the effects of the German SCA5 mutation (L253P) on protein folding, stability and interactions with

11 known binding partners (Chapter 3).

Copyright Notice

Portions of this chapter are reproduced with permission from the articles published in:

Subramony SH, Dürr A (Eds.), Ataxic Disorders 1, A volume to the Handbook of Clinical Neurology series, 3rd Edition, Dick KA, Ikeda Y, Day JW, Ranum LPW, Spinocerebellar Ataxia Type 5, ©Elsevier, (in press).

Pulst SM (Ed.), The Genetics of Movement Disorders, The Handbook of Clinical Neurology 3rd Series, Ranum LPW, Dick KA, Day JW, Spinocerebellar Ataxia 5, ©Elsevier, Amsterdam, pp. 75-80, (2003).

12 13

Figure 1. Pedigree of the American SCA5 family. (A) An 11-generation SCA5 kindred descended from paternal grandparents of President Abraham Lincoln. SCA5, referred to as “Lincoln’s Disease” by family members, is found among the descendents of President Lincoln’s paternal uncle Josiah and aunt Mary, indicating that one of President American’s paternal grandparents carried the SCA5 mutation. These two branches of the family are shown. Squares and circles represent males and females, respectively, shaded symbols represent affected individuals, symbols with a dot indicate obligate mutation carriers, and diagonal lines denote individuals who are deceased. The asterisks beneath the symbols indicate individuals whose blood samples were obtained for analysis. (B) Enlargement of a portion of the pedigree showing the common ancestry of the two branches and their relationship to President Lincoln. Because the disease in some individuals is relatively mild and the clinical status of the President, his father Thomas, and Thomas’s descendants (all deceased since 1984) are unknown, the prior probability that the President inherited the SCA5 mutation is 25%. The pedigrees of the two branches are abbreviated, and the genders of Josiah and Mary and individuals in generations III, IV, V are masked in (A) to preserve confidentiality. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

14

Figure 2. Genetic map of the SCA5 critical region. Recombinant information from affected individuals from the three SCA5 families is summarized. The region of chromosome 11 common to all of the affected individuals is indicated in red. Regions in white indicate portions of chromosome 11 that do not contain the SCA5 mutation and striped red regions indicate the portions of the chromosome within which key recombination events defining the critical region have occurred. Members of the German family define the telomeric border, while all other boundaries are defined by recombinant individuals from the American family.

15

Figure 3. Sagittal MRI scan from an affected individual at age 64. There is marked cerebellar atrophy, minimal brainstem atrophy, and no evidence of cerebral involvement. The relative preservation of the posterior hemisphere, and tonsillar cortex is evident. Modified and reprinted with permission from Liquori et al., (2002). Spinocerebellar ataxia type 5. In: M. Manto and M. Pandolfo (Eds.), The Cerebellum and its Disorders. Cambridge University Press©, Cambridge, U.K, pp. 445-450.

16 SCA ADCA Location Mutation SCA1 I 6p23 Coding CAG expansion in ATXN1 SCA2 I 12q24 Coding CAG expansion in ATXN2 SCA3 I 14q32 Coding CAG expansion in ATXN3 SCA4 I 16q22 SCA5 III 11q13 Mutations in SPTBN2 Coding CAG expansion in SCA6 III 19p13 CACNA1A SCA7 II 3p14 Coding CAG expansion in ATXN7 Coding CAG expansion in ATXN8 SCA8 I 13q21 & non-coding CTG expansion in ATXN8OS Non-coding ATTCT expansion in SCA10 I 22q13 ATXN10 SCA11 III 15q15.2 Mutations in TTBK2 Non-coding CAG expansion in SCA12 I 5q32 PPP2R2B SCA13 I 19q13.3-q14.4 Mutations in KCNC3 SCA14 III 19q13.4 Mutations in PRKCG SCA15/16 III 3p26.2 Mutations in ITPR1 SCA17 I 6q27 Coding CAG expansion in TBP SCA18 I 7q22-q32 SCA19 I 1p21-q21 SCA20 I 11p11.2-q13 SCA21 I 7p21-p15 SCA22 I 1p21-q23 SCA23 I 20p13-12.3 SCA25 I 2p21-p13 SCA26 III 19p13.3 SCA27 I 13q34 Mutations in FGF14 SCA28 I 18p11.22-q11.2 SCA29 III 3p26 16q22 III 16q22.1 Mutations in PLEKHG4 SCA Table 1. Classification of the SCAs. Gene names are listed in italics.

17

LOD Scores at Θ= 0.0 0.01 0.05 0.10 0.20 0.30 0.40 GATA2A01 -∞ 8.76 10.25 14.40 8.30 5.68 2.69 D11S913 14.66 14.39 13.28 11.85 8.83 5.64 2.48 INT2 -∞ 12.6 14.40 14.07 11.66 8.18 4.05

Table 2. Pairwise LOD scores. Reprinted with permission of Marcel Dekker, from Schut et al., Spinocerebellar ataxia type 5. In: T. Klockgether (Ed.), Handbook of Ataxia Disorders. Marcel Dekker © 2000, New York, pp. 435-445; permission conveyed through Copyright Clearance Center, Inc.

18

SCA5 Clinical Features Limb Ataxia ++++ Gait Ataxia ++++ Truncal Ataxia +++ Muscle Weakness - Muscle Atrophy - Deep Tendon Reflexes Hypoactive + Hyperactive ++

Bulbar Abnormalities +/- Abnormal Eye Movements +++ Sensory ++ Dysarthria +++ Abnormal 3-Cough Sequence +/- Babinski Sign - Table Legend: “++++” > 90%; “+++” 50 to 89%; “++” 25 to 49%; “+” 10% to 24%; “+/-” 2 to 9%, “-“ < 2%

Table 3. SCA5 clinical features in the American family. Reprinted with permission of Marcel Dekker, from Schut et al., Spinocerebellar ataxia type 5. In: T. Klockgether (Ed.), Handbook of Ataxia Disorders. Marcel Dekker © 2000, New York, pp. 435-445; permission conveyed through Copyright Clearance Center, Inc.

19 CHAPTER 2

GENETIC MAPPING OF SCA5

Abstract

Spinocerebellar ataxia type 5 (SCA5) was previously mapped to 11q13 using an

11-generation American kindred descended from the paternal grandparents of President

Abraham Lincoln. The first major goal of my thesis was to identify the genetic mutation causing this dominant form of ataxia. I am pleased to report that I have accomplished this goal and have discovered β-III spectrin (SPTBN2) mutations cause SCA5 in the

American family and two additional ataxia families from France and Germany. The

American and French families have separate in-frame deletions of 39 and 15 bp,

respectively. Both of these deletions are within the third of 17 homologous, triple-helical,

spectrin repeat motifs. In the German SCA5 family, a point mutation (Leu253Pro) was

found within the N-terminal region of the protein, which has previously been reported to

bind to actin/ARP1. β-III spectrin is highly expressed in Purkinje cells, a primary site of

degeneration in SCA5, has been shown to stabilize membrane proteins and has been

implicated in vesicle transport. Spectrin mutations are a novel cause of ataxia and the

future characterization of these mutations will likely lead to a better understanding of the

pathogenic mechanisms underlying SCA5 and neurodegenerative disease in general.

20

I. Introduction

The large number of genetic loci that cause ataxia provides an opportunity to use

human genetics to define the fundamental causes and common molecular pathways

underlying this group of neurodegenerative diseases. Specifically, the SCAs are a

heterogeneous group of neurodegenerative disorders characterized by incoordination of

gait, limb, and eye movements, slurred speech and swallowing difficulties. Over half of

the known SCA mutations are microsatellite repeat expansions (Schols et al. 2004). In

1994, a ten-generation American kindred of European ancestry, with a generally mild

autosomal dominant form of SCA was described (Ranum et al. 1994). The family has

two major branches, which can be traced back to the paternal grandparents of President

Abraham Lincoln (Figure 1). After excluding linkage to the known ataxia loci, a genome-wide screen was performed and the mutation was mapped to the long arm of chromosome 11, which was later refined to 11q13 (Ranum et al. 1994; Koob et al. 1995).

Two additional SCA5 families from France and Germany were subsequently reported with similar clinical and neuroradiological findings (Stevanin et al. 1999; Burk et al.

2004).

SCA5 disease onset most often occurs in the 3rd or 4th decade of life, but ranges from 10 to 68 years of age (Ranum et al. 1994; Stevanin et al. 1999). Symptoms, which progress over time, include incoordination of the upper extremities, slurred speech, and gait ataxia. SCA5 predominantly affects the cerebellum, while largely sparing the brainstem and spinocerebellar tracts (Ranum et al. 1994; Schut et al. 2000; Liquori et al.

2002). MRI and autopsy findings show cerebellar cortical atrophy, Purkinje cell loss and

21 thinning of the molecular layer (Liquori et al. 2002). The predominant cerebellar

involvement and mild disease course of SCA5 are similar to SCA6 (Zhuchenko et al.

1997), SCA11 (Worth et al. 1999), and SCA15 (Storey et al. 2001). Unlike many of the

other SCAs (Harding 1983; Brice 1998; Klockgether and Evert 1998; Herman-Bert et al.

2000; Nakamura et al. 2001; O'Hearn et al. 2001; Rasmussen et al. 2001), SCA5 typically

does not shorten life span in adult-onset patients, (Ranum et al. 1994) probably due to the

lack of bulbar paralysis. However, several patients with juvenile onset SCA5 have been

found to have some bulbar atrophy and demonstrate a weakened ability to cough and

swallow, suggesting that they may develop a predisposition for pneumonia that may

shorten lifespan (Ranum et al. 1994).

To determine the pathogenic mutation responsible for SCA5, I used a

multifaceted mapping approach, including screening repeat expansions, searching for

haplotype conservation between the three SCA5 families, refinement of the critical region

and both targeted and brute force sequencing.

II. Results

Over the past decade we have collected DNA samples from and have performed clinical evaluations on 299 members of a large American family, including 90 affected individuals (Figure 1) (Ranum et al. 1994; Ikeda et al. 2006). These samples were used in the identification of recombinants and the refinement of the critical region. While

DNA was collected from an extensive number of family members, the suppressed recombination typical of centromeric regions limited the number of recombinant chromosomes available for analysis and significantly slowed the genetic refinement of

22 the locus. Therefore, a multifaceted mapping approach was implemented. First, a panel of 445 novel di-, tri-, tetra-, and penta-nucleotide repeat markers was developed and used to refine the SCA5 region, to screen for expansion mutations and to search for haplotype conservation between the families. These efforts refined the SCA5 critical region to a

2.99 Mb interval on 11q13, containing more than 100 genes (Figure 4) (Ikeda et al. 2006).

The critical regions for the German and French families were significantly larger and fully encompassed the American critical region, at 6 Mb and >28 Mb, respectively

(Figure 4) (Stevanin et al. 1999; Burk et al. 2004). A second and parallel approach involved the generation of chromosome-separated cell lines haploid for the affected or the normal chromosome 11. These cell lines, generated from an affected American family member, were used to directly and unambiguously define the affected haplotype.

Additionally, DNA from the affected chromosome-separated cell line known to contain the American SCA5 mutation was used to construct a BAC genomic DNA library and clone contig spanning nearly the entire 2.99 Mb critical region, which was then used to sequence candidate genes and regions of haplotype conservation.

Haplotype comparisons between the three families identified a 255 kb region of possible conservation between the American and French families (Table 4). This region included 11 novel polymorphic STR markers and 8 single nucleotide polymorphisms

(SNPs). Although this haplotype was also found in 3/84 (3.5%) control chromosomes, this region was prioritized because of the possibility that this conservation resulted from a common ancestral mutation. Shotgun sequencing of three BACs (VI-C2, VI-C11 and IV-

H4) from the clone contig, which spanned the region of haplotype conservation, was performed (Figure 5). 23 A 39-base pair deletion was found in exon 12 of the β-III spectrin gene (SPTBN2), which causes an in-frame 13 amino-acid deletion (p.E532_M544del) within the third of

17 spectrin repeats (Figure 6, 7A). The mutation, which is detectable by PCR (Figure

7A), was found in all 90 affected individuals (age of exam 7-80 yrs, mean 45 yrs) and 35 presymptomatic carriers (age of exam 13-67 yrs, mean 34 yrs). While previously reported polymorphisms were also identified, this mutation was the only unreported difference predicted to alter the protein coding region of the gene (Table 5).

Although the American and French families share a common haplotype, the 39-bp

American deletion was not found in the French family. Sequencing of the SPTBN2 gene revealed the French family has a short in-frame deletion in the same spectrin repeat as the

American family, which consists of a 15-base pair deletion in exon 14 (c.1886_1900del; p.L629_R634delinsW) (Figure 6, 7B). With the exception of the insertion of a tryptophan, this deletion does not disrupt the remainder of the open-reading frame (Figure 7B). The

French mutation was found in all six available affected individuals and one apparently presymptomatic carrier (age 24).

In the German family a T to C transition mutation (c.758T>C) in exon 7 that causes a leucine to proline change (p.L253P) (Figure 6, 7C) was found in the calponin- homology domain containing the actin/ARP1 binding site. This region is highly conserved with the leucine 253 residue found in all five human β-spectrin proteins as well as chimp, mouse, rat, dog and fly (Figure 7C). The German mutation co-segregated with the disease in 12 available affected individuals. None of the three SCA5 mutations were found on 1,000 control chromosomes.

β-III spectrin, a 2,390 amino-acid protein highly expressed in Purkinje cells

24 (Ohara et al. 1998; Stankewich et al. 1998), is homologous to four other human β- spectrin proteins. The functional unit of spectrin is typically a noncovalently joined tetrameric complex consisting of two α and β spectrin subunits. β-III spectrin has been reported to be associated with Golgi and vesicle membranes (Stankewich et al. 1998) and to bind to the dynactin subunit ARP1, suggesting a possible role in transport (Holleran et al. 2001). Another function of β-spectrin is the stabilization of membrane proteins

(Parkinson et al. 2001); notably β-III spectrin stabilizes the Purkinje cell specific glutamate transporter EAAT4 (Jackson et al. 2001). RT-PCR analysis shows both normal and deleted β-III spectrin transcripts are expressed in affected cerebellar autopsy tissue (Figure 8A). Additionally, immunohistochemistry shows staining of Purkinje cell bodies, dendrites and axons in both SCA5 and control cerebella, with marked Purkinje cell loss in SCA5 (Figure 8B).

III. Discussion

We report a novel mutational mechanism for spinocerebellar ataxia with the identification of three separate mutations in the β-III spectrin gene (SPTBN2) responsible for SCA5. The American and French families have similar but separate in-frame deletions within the third spectrin repeat, and are likely to disrupt the highly ordered triple-alpha-helical structure of the repeat and thus changing the overall shape of the tetrameric alpha-beta-spectrin complex. Although it is possible that some feature of the shared haplotype between the American and French families led to similar microdeletions, it appears more likely that the shared haplotypes are coincidence as this haplotype is found on 3.5% of control chromosomes. The German family has a missense

25 mutation in the calponin-homology domain, which may affect the binding of spectrin to

the actin cytoskeleton and similarly alter the stabilization of membrane proteins or cause

changes in transport by disrupting binding to ARP1 and the dynein motor complex

(Holleran et al. 2001).

It has been reported that one of the functions of the β-III spectrin protein is to bind and stabilize membrane proteins, including the glutamate transport protein EAAT4 and the glutamate receptor protein GluRδ2 (Hirai and Matsuda 1999; Pinder and Baines

2000; Jackson et al. 2001). Additionally, altered expression of EAAT4 has been reported to increase the susceptibility of Purkinje cells to injury and degeneration (Welsh et al.

2002). Protein blot analysis using cerebellar autopsy tissue from an affected American family member, showed EAAT4 was dramatically reduced relative to calbindin, a

Purkinje cell specific control, when extraction was performed with RIPA buffer, but was present in comparable levels when using a harsher buffer (8M urea and 4% SDS) (Ikeda et al. 2006). These results suggested the mutation affects protein distribution or stabilization, but not overall protein levels. Subsequent subcellular fractionations of cerebellar autopsy tissue showed that the synaptic membrane proteins EAAT4 and

GluRδ2 were not enriched in the synaptosomal fractions from SCA5 tissue, in contrast to fractions from control tissues (Ikeda et al. 2006).

Additional experiments using total internal reflection fluorescence (TIRF) microscopy in cell culture demonstrates that, in contrast to control spectrin, mutant β-III spectrin does not properly stabilize EAAT4 at the plasma membrane (Ikeda et al. 2006).

The lateral movement of EAAT4 at the cell’s membrane was observed in HEK293 cells co-transfected with EAAT4-eGFP and either empty vector, control β-III spectrin, or

26 mutant β-III spectrin (39 bp deletion). Approximately 40% of eGFP-EAAT4 was observed to be laterally moving across the membrane in cells that had been co-transfected with empty vector, while in contrast only 5% of eGFP-EAAT4 was moving in cells co- transfected with normal β-III spectrin. The stabilization of EAAT4 at the plasma membrane was not observed when the mutant β-III spectrin was examined, indicating that mutant β-III spectrin is no longer able to perform this function (Ikeda et al. 2006).

Interestingly, EAAT4 and GluRδ2, two proteins shown to be altered in SCA5, have previously been implicated in ataxia. Impairment of EAAT4 synthesis causes progressive ataxia in mice (Lin et al. 2000; Raiteri et al. 2002; Serra et al. 2004) and down-regulation of both β-III spectrin and EAAT4 transcripts have been found by micro- array analysis in SCA1 transgenic (Lin et al. 2000; Serra et al. 2004) and staggerer mice

(Gold et al. 2003). These findings suggest the convergence pathogenic mechanisms triggered by distinct mutations. Additionally, mutations in GluRδ2 have been shown to cause ataxia in lurcher and hotfoot mice (Zuo et al. 1997; Lalouette et al. 1998).

β-III spectrin was initially described as a protein associated with Golgi and vesicle membranes (Stankewich et al. 1998). Indirect immunofluorescence using Madin-Darby

Canine Kidney (MDCK) and normal rat kidney (NRK) cells shows β-III spectrin has a punctate cytoplasmic distribution that overlaps with the subcellular distribution of Golgi markers, and β-III spectrin cosediments with Golgi and vesicle membrane proteins in a sucrose gradient. Additionally biochemical studies show β-III spectrin binds ARP1, a subunit of dynactin (Holleran et al. 2001). Because dynactin associates with cytoplasmic dynein to participate in transport of many types of intracellular vesicles, it has been postulated that β-III spectrin may play a role in vesicle transport. The location of the

27 German SCA5 point mutation in the calponin homology domain and the substitution of a

leucine to a proline, suggests the actin/ARP1 binding site is likely altered and

intracellular protein and vesicle trafficking may be disrupted, as in other

neurodegenerative diseases. These disorders include a dominantly inherited motor

neuron disease caused by mutations in p150Glued, a subunit of dynactin (DCTN1) (Puls et

al. 2003) and a motor neuronopathy caused by missense mutations in the mouse dynein

heavy chain gene (Dnchc1) (Hafezparast et al. 2003). In Huntington disease, alterations

of the huntingtin/HAP1/p150Glued complex induce transport deficits and loss of neurotrophic support contributing to neuronal toxicity (Gauthier et al. 2004), and axonal

transport defects are found in Alzheimer’s patients and murine models (Stokin et al.

2005).

The distribution differences in Purkinje cell proteins from SCA5 autopsy tissue

(American) and the cell culture data demonstrating the failure of the mutant spectrin

(39bp deletion) to stabilize EAAT4, indicate that destabilization of membrane proteins may be a downstream consequence of the SCA5 mutations, while the location of the

German mutation suggests that protein trafficking may also be affected in SCA5.

Because the three SCA5 families all have distinct mutations in SPTBN2, it will be

particularly interesting to determine whether there are additional mutations within this

gene that cause ataxia. This information would be likely to provide further insight into

the normal functions of β-III spectrin and the molecular pathways involved in neurodegeneration. Towards this effort, we also sequenced DNA from an affected individual in the SCA20 family, whose critical region includes SPTBN2 (Knight et al.

2004). No unreported changes were identified in the upstream region, intron/exon

28 boundaries or coding sequence, except for two synonymous alterations that would not be

predicted to affect splicing (Lorenzo et al. 2006). In addition to screening other families

with unknown forms of ataxia, it will be important to determine if mutations in SPTBN5

or SPTBN1, which also encode non-erythrocytic forms of β-spectrin and are expressed in

the brain, cause ataxia. Interestingly, SPTBN5 lies within the SCA25 critical region

(Stevanin et al. 2004). Consistent with the possibility that the β-spectrins may play

additional roles in disease, dominantly inherited mutations in a beta spectrin homologue cause an uncoordinated phenotype (unc-70) in C. elegans (Park and Horvitz 1986) and recessive mutations in the mouse spectrin beta 4 gene (Spnb4), an orthologue of human beta-IV spectrin (SPTBN4), cause a progressive ataxia with hind limb paralysis, deafness and tremor in quivering mice (qv) (Parkinson et al. 2001). The identification of SCA5 mutations in a gene encoding a well known cytoskeletal protein will allow testing of specific hypotheses of disease pathogenesis involving destabilization of membrane

proteins, glutamate dysregulation and vesicle trafficking deficits which will provide

insight into the downstream molecular mechanisms common to SCA5 and other

neurodegenerative diseases.

Copyright Notice

Portions of this chapter have been reproduced with permission from the following articles:

Ikeda Y*, Dick KA*, Weatherspoon MR, Gincel D, Armbrust KR, Dalton JC, Stevanin

G, Dürr A, Zühlke C, Bürk K, Clark HB, Brice A, Rothstein JD, Schut LJ, Day

JW, Ranum LP. Spectrin mutations cause spinocerebellar ataxia type 5. Nat

29 Genet. 38(2):184-90 (2006) (* co-first authors).

Subramony SH, Dürr A (Eds.), Ataxic Disorders 1, A volume to the Handbook of

Clinical Neurology series, 3rd Edition, Dick KA, Ikeda Y, Day JW, Ranum LPW,

Spinocerebellar Ataxia Type 5, ©Elsevier, (in press).

Pulst SM (Ed.), The Genetics of Movement Disorders, The Handbook of Clinical

Neurology 3rd Series, Ranum LPW, Dick KA, Day JW, Spinocerebellar Ataxia 5,

©Elsevier, Amsterdam, pp. 75-80, (2003).

30

Figure 4. Critical regions for the three SCA5 families. Critical regions defined by recombination events in the three SCA5 families are indicated by black arrows. The boundaries of the French critical region are not defined because no recombination events were found among affected family members. Markers defining recombination events, along with other published markers are shown. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

31

Figure 5. BAC map spanning the SCA5 region. The enlarged BACs, highlighted in gray, span a 255 kb region of haplotype conservation between the American and French families, containing 11 novel polymorphic STR markers and 8 SNPs (size and NCBI accession number noted). The three BACs generated from the affected SCA5 haploid cell line are depicted in black along with their relative position and size. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

32

Figure 6. Illustration of SPTBN2 gene (top) and β-III spectrin protein structure (bottom). The relative size and location of the 3’/ 5’-UTR and exons are represented by clear and solid squares, respectively. Locations of the three mutations are indicated by arrows on the gene and protein diagrams. β-III spectrin is a 2,390 amino acid protein that is highly homologous to the four other human β-spectrin proteins. Known domains in the protein are specified along with the seventeen spectrin repeats. The calponin-homology (CH)/actin binding domain (ABD), ankyrin binding domain (ANK), and pleckstrin- homology domain (PH) are shaded in gray. The functional unit of spectrin is typically a non-covalently-joined tetrameric complex consisting of two alpha and two beta spectrin subunits. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

33

Figure 7. The three SCA5 mutations. PCR analysis and the corresponding genotype for the three SCA5 families are illustrated for each mutation. Sequence electropherograms and the corresponding amino acid sequence are also shown. (A) American SCA5 mutation. The PCR analysis generated a 222 bp normal allele and a 183 bp deleted allele. The sequence of SCA5 BAC DNA is shown with the deletion mutation relative to control. The black and red arrows indicate the two possible deletion sites, and the corresponding 39-base deletion including one of the two flanking TGGA tetranucleotides is underlined with the respective color. The two TGGA tetranucleotides flanking the American deletion are reminiscent of the deletions caused by slipped- mispairing (Krawczak and Cooper 1991). (B) French SCA5 mutation. The [γ-33P] ATP- labeled PCR generated a 105 bp normal allele and a 90 bp deleted allele. Sequence of the heterozygous and deletion specific PCR product is shown. Arrows indicate the site of the mutation and the 15-base deletion is underlined. (C) German SCA5 mutation. The T to C base change, which converts a leucine to a proline, is depicted. The allele-specific PCR produced a 177 bp normal allele and a 158 bp mutation allele. Amino acid sequence comparisons, of a region containing the German SCA5 mutation (L253P), of five human beta spectrins and beta spectrins from other species are shown. The leucine residue which is mutated in the German family (highlighted in green) is conserved in all five of human beta spectrin proteins and evolutionarily conserved in multiple species. Amino acid alignments were performed with Clustal W. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

34

35

Figure 8. RNA and protein expression in American SCA5 and control cerebellar tissues. (A) RT-PCR of control and American SCA5 cerebellar tissues. The normal SPTBN2 amplified product is 227 bp and the product containing the deletion is 188 bp. There was no amplification in the RT- or no RNA control lanes. (B) Immunohistochemistry of control and American SCA5 cerebellar tissues. Sections were stained with an antibody raised against the N-terminal portion of the β-III spectrin, and visualized at 200X magnification. Enlarged images of the Purkinje cells are also shown (630X). Purkinje cell loss, dendritic atrophy and significant thinning of the molecular layer are seen in SCA5 compared to control. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

36 t c haplotype conservation. This is haplotypes are shared between the tw number. SNPs are referred to by the “rs” nom markers, which were developed for the mapping, Table 4. Marker and genotype data for the region of haplotype conservation. h o e n

s l o e c r v a a t i t o i o n n o . f

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37 Number Number of Exon NCBI SNP Gene Status of Sequence Number ID Exons Variations MRPL11 Reviewed 5 0 - - MGC35521 Predicted 8 2 Exon 6 rs2277302 Exon 8 rs3179961 DPP3 Reviewed 18 3 Exon 4 rs11550299 Exon 17 rs1671063 Exon 17 rs2305535 BBS1 Reviewed 17 4 Exon 4 rs2298806 Exon 14 rs3816492 Exon 17 rs8432 Exon 17 rs3741360 AK126268 Predicted 1 2 Exon 1 rs7116921 Exon 1 rs7116940 LOC254359 Predicted 3 1 Exon 1 rs2305534 ACTN3 Reviewed 21 7 Exon 14 rs1671064 Exon 15 rs2305537 Exon 15 rs1815739 Exon 16 rs618838 Exon 16 rs7924602 Exon 18 Unregistereda Exon 19 rs540874 CTSF Reviewed 13 4 Exon 2 rs2075791 Exon 6 rs545009 Exon 13 rs572846 Exon 13 rs4576 FLJ10786 Predicted 1 0 - - CCS Reviewed 8 1 Exon 8 rs1127145 RBM14b Validated 3 0 - - MGC15912b Predicted 1 0 - - RBM4b Provisional 5 0 - - RBM30 Predicted 4 0 - - SPTBN2 Provisional 37 1c Exon 14 rs4930388 FLJ22531 Predicted 6d 0 - -

Table 5. Summary of DNA sequence variations of exons found in 3 BAC regions. While previously reported polymorphisms were also found in each family, the SCA5 mutations were the only unreported differences that would alter the corresponding protein. The letters indicate: “a”=synonymous SNP (AGG→AGA: Arg774); “b”= sequence gap between the contigs; “c”=except for the pathogenic SCA5 mutations; and “d”=exons 7-17 were not included in the IV-H4 BAC. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190. 38

CHAPTER 3

MOLECULAR CHARACTERIZATION OF THE SCA5 L253P MUTATION: A TEMPERATURE SENSITIVE ALTERATION RESULTING IN AN UNSTABLE PROTEIN

Abstract

Spectrin is a key component of the cytoskeleton and in addition to providing

membrane stability, has also been shown to organize integral membrane proteins into

specialized domains, regulate vesicle membrane interactions, and has been implicated in

vesicle transport. I have shown that a leucine to proline substitution in the C-terminal CH

domain of β-III spectrin, which is highly expressed in Purkinje cells, causes SCA5 in a

family of German descent. As part of an initial characterization of the SCA5 German

mutation, I investigated the impact of this amino acid substitution on protein stability,

folding and function. Through expression studies in human embryonic kidney (HEK

293T) and mouse neuroblastoma (N2A) cells and circular dichroism (CD) analyses, I

show that the mutation causes misfolding of the protein, which renders it insoluble and

subject to degradation. Additionally, the mutation dysregulates the tightly controlled

binding between spectrin and actin, resulting in an enhanced interaction with both globular (G)- and filamentous (F)- actin. Interestingly, the effects of the mutation are reversible under some conditions. For example, when the mutant protein is expressed at a lower temperature or in the presence of HSP-70, which encourages protein folding, these downstream effects on stability, solubility and actin binding are largely ameliorated.

Further characterization of the German mutation and its impact on β-III spectrin will lead to a better understanding of SCA5 pathogenesis and the molecular pathways involved in 39

neurodegenerative disease.

I. Introduction

Spectrin, a 0.2 micron flexible rod that binds filamentous-actin (F-actin), was initially characterized in red blood cells and shown to provide mechanical stability to the

erythrocyte plasma membrane (Bennett and Gilligan 1993; Bennett and Baines 2001).

The functional unit of spectrin is typically a non-covalently-joined tetrameric complex

comprised of two alpha and two beta spectrin subunits, in which the N-terminus of each

alpha subunit interacts with the C-terminus of beta spectrin (Bennett and Healy 2008). In

the human erythrocyte cell, five to six tetramers combine and interact with F-actin to

form a geodesic dome-like structure directly under the plasma membrane (Byers and

Branton 1985). Within the spectrin family in humans, there are now known to be five

beta and two alpha spectrin proteins and their recognized roles have greatly expanded

(Bennett and Healy 2008). Spectrin is expressed in most metazoan cells and in addition

to providing membrane stability, also organizes integral membrane proteins into

specialized domains, regulates vesicle membrane interactions, and has been implicated in vesicle transport (Holleran et al. 2001; Bennett and Healy 2008).

β-III spectrin, which is highly homologous to the other four β-spectrins, is a 2,390

amino acid protein encoded by the SPTBN2 gene (Ohara et al. 1998; Stankewich et al.

1998). Human β-III spectrin contains a tandem calponin-homology (CH) domain at the

N-terminus, followed by 17 spectrin repeat motifs and a pleckstrin homology domain at the C-terminus (Figure 6). Transcript analysis indicates β-III spectrin is widely expressed in a pattern similar to β-II spectrin; transcripts are concentrated in the brain, with moderate levels observed in the kidneys, liver, testes, prostate, pituitary, adrenal, and

40

salivary glands (Stankewich et al. 1998). Initially described as a protein associated with

Golgi and vesicle membranes, β-III spectrin has been shown to bind ARP1, a subunit of dynactin, and the glutamate transporter EAAT4—implicating the protein in both vesicle transport and stabilization of membrane proteins (Stankewich et al. 1998; Holleran et al.

2001; Jackson et al. 2001).

As previously described, β-III spectrin (SPTBN2) mutations cause SCA5 in the three families that were previously mapped to the SCA5 locus on chromosome 11q13

(Ranum et al. 1994; Stevanin et al. 1999; Burk et al. 2004; Ikeda et al. 2006). In an

SCA5 family of German descent, a point mutation (Leu253Pro) was found in the second of two CH domains (Ikeda et al. 2006). The CH domain consists of ~110 amino acids and is found in both cytoskeletal and signal-transduction proteins (Banuelos et al. 1998).

Spectrin, α-actinin, dystrophin, utrophin and fimbrin all belong to a family of proteins

with tandem CH domains; these regions comprise the actin-binding domain (ABD) and

cross-link F-actin (Djinovic Carugo et al. 1997; Banuelos et al. 1998). In addition to

binding actin, CH domains have also been reported to bind to protein 4.1 and ARP1

(Bennett and Healy 2008), suggesting the German family mutation may cause a general

dysfunction of the membrane-cytoskeletal complex or deficits in dynein-dynactin

mediated transport.

Spectrin mutations are a novel cause of ataxia and future characterization of the mutations will likely lead to a better understanding of both the pathogenic mechanisms underlying SCA5 and normal protein function. I have used a tissue culture model to investigate the effects of the German SCA5 point mutation (L253P) and show that this mutation results in a misfolded, insoluble protein that is targeted for degradation.

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Furthermore, the mutation disrupts the highly regulated binding to F-actin; unlike

wildtype β-III spectrin the mutant protein strongly interacts with both actin monomers

and polymers. Additionally, I demonstrate the mutation is temperature sensitive, and the

protein partially regains normal properties at a lower temperature.

II. Results

In 1997, Djinovic Carugo et. al determined the crystal structure of the C-terminal

CH domain from human β-spectrin at a 2.0Å resolution, which was later refined to the

atomic resolution of 1.1 Å (Djinovic Carugo et al. 1997; Banuelos et al. 1998). The CH

domain is highly α-helical, with four major α-helices (A, C, E, G) and three minor α- helices (B, D, F) that are shorter and less regular (Figure 9) (Djinovic Carugo et al. 1997).

A ribbon presentation of the predicted three dimensional structure of the human β-III spectrin C-terminal CH domain, based on comparisons with the β-spectrin analysis, is shown in Figure 9. The folding analysis indicates the CH domains from the two proteins are highly similar, however, an additional minor helix (D') is predicted for β-III spectrin.

Based on this modeling, the German mutation falls within the long loop connecting the major E helix with the minor F helix. To determine the impact of the leucine to proline substitution on the folding of the β-III spectrin N-terminus, circular dichroism (CD) was performed and wildtype and mutant profiles were compared. For the analysis, wildtype and mutant constructs containing the first 281 amino acids of β-III spectrin (pGEX-

SPTBN2-CH) were expressed in E. coli and the protein was purified using a C-terminal

HIS tag (Figure 10A). As predicted, the CD profiles indicated that both the wildtype and mutant proteins were alpha helical in nature (Figure 10B). Specifically, two minimums

42

were observed at 208 nn and 223 nm and a maximum at 193 nm, all characteristics of α- helical spectrums (Holzwarth and Doty 1965). However, the lower peak and flatter valleys of the mutant spectrum indicates a loss of α-helical content, with wildtype and mutant α-helical content calculated at 31.52% and 23.96%, respectively. Confirming the accuracy of the assay, the helical content for the wildtype protein is just slightly lower than the NMR predicted value for the C-terminal CH domain of β-III spectrin (40%)

(Berman et al. 2000; Berman et al. 2003; PDB ID: 1wyq_A 2005) and the x-ray structures of CH domains from other proteins (Banuelos et al. 1998; Keep et al. 1999;

Norwood et al. 2000). This deviation is likely because the CD analysis I performed used purified protein containing the full N-terminal portion of the protein and not just the C- terminal CH domain. Protein stability of the wildtype and mutant proteins was also examined using a temperature gradient that ranged from 20-90°C (Figure 10C). The wildtype protein is highly stable and dramatically unfolds in a single step starting at 56°C.

In contrast, the mutant protein is highly unstable and unfolding gradually occurs in two phases separated by a plateau. The first unfolding phase begins and 34°C, indicating the mutant protein is in a partially unfolded state at the physiological relevant temperature of

37°C (98.6°F). The loss of α-helical content is also apparent across temperatures, with a significantly flatter mutant profile (Figure 10C).

To further characterize the German mutation and its impact on protein dynamics, wildtype and mutant proteins were also expressed in tissue culture. A variety of constructs were created, including full-length untagged, 5’myc tagged and IRES eGFP constructs and a 5’ myc tagged shortened construct, which only encodes the N-terminus of β-III spectrin (CH2) (Figure 11A). When these constructs are expressed in either HEK

43

293T or Neuro-2A (N2A) cells, there is consistently a reduced amount of full length mutant protein, along with the presence of two degradation products (~22 and ~26 kDa)

(Figure 11B, C). These smaller products are recognized by both the N-terminal β-III spectrin and myc antibodies, indicating the fragments contain the N-terminus of the protein. These products are generally only observed with the mutant protein, however, under lysis conditions that lack protease inhibitors these fragments eventually appear from the wildtype protein as well (data not shown). Additionally, while these fragments are characteristic of the mutant protein, these specific products are no longer detectable when the amount of protein that is expressed is reduced significantly (data not shown).

To examine expression over time, the constructs containing the IRES eGFP were expressed in HEK 293T cells and lysates were collected over a 48 hour time course

(Figure 11D). The eGFP protein was used as a marker for the translation of wildtype and mutant β-III spectrin. While the wildtype and eGFP proteins increased over time, the mutant β-III spectrin protein remained fairly constant with the fragments increasing

(Figure 11D). This observation likely results from degradation of the increasing amounts

of mutant protein being expressed. In addition to degradation, the proline substitution

also results in the decreased solubility of the mutant protein (Figure 11E, F). Specifically,

the mutant protein is present at much higher levels than wildtype protein in the insoluble pellets from cell lysates. Both degradation and insolubility of the mutant protein are consistent with the results from the CD; the CD analysis determined that the mutation resulted in an unstable and unfolded protein at 37°C (Figure 10).

To further characterize the misfolding of mutant β-III spectrin, wildtype and mutant proteins were expressed under conditions that promote folding (lower temperature

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and in the presence of a heat shock protein). First, wildtype and mutant eGFP β-III spectrin constructs were expressed in HEK 293T cells, and at 24 hours post-transfection the cells were cultured for an additional 24 hours at 25°C. At the lower temperature, the amount of full length mutant β-III spectrin increased relative to eGFP expression and wildtype β-III spectrin controls, while the degradation products decreased (Figure 12A).

While expression levels of the mutant protein were still lower than the wildtype protein at the lower temperature, this was not unexpected given the results of the CD, which indicated the mutant protein had lost α-helical content and not fully folded properly at

25°C (Figure 10). In a second experiment, transfected N2A cells were cultured at only

37°C or 25°C for 48 hours prior to lysate collection. Consistent with the HEK 293T results, the amount of full length mutant protein was increased and the degradation products were reduced at 25°C compared to the mutant protein at 37°C (Figure 12B). A similar trend was also observed when the mutant eGFP β-III spectrin was co-expressed with the protein folding chaperone, heat shock protein 70 (HSP-70) (Bross et al. 1999)

(Figure 13). Taken together, these results support the conclusion that the German

(L253P) mutation, located in the second CH domain, causes the β-III spectrin protein to misfold.

To investigate the impact of this leucine to proline substitution on the function of

the CH domain, binding of wildtype and mutant β-III spectrin to actin was examined.

The short CH2 constructs or 5’myc full-length constructs were expressed in HEK 293T cells and co-immunoprecipitations were performed. In general, substantially less mutant

β-III spectrin than wildtype is pulled down with the myc antibody, however, a robust interaction between actin and the mutant, but not the wildtype protein, is observed

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(Figure 14A, B). While there is no visible interaction between the wildtype protein and actin, this is not surprising given the weak binding affinity between β-spectrin and F- actin (Kd=26 µM) (Li and Bennett 1996). These results indicate the German mutation results in the dysregulation of the β-III spectrin/actin interaction and an enhanced binding affinity between the two proteins. Importantly, the temperature sensitive nature of the mutation appears to correlate with CH domain function; the aberrant actin interaction is almost eliminated if lysates are used from cells that were cultured for an additional 24 hours at 25°C (Figure 14C).

To further characterize the aberrant interaction between actin and mutant β-III spectrin, and to determine whether the mutant protein was binding actin monomers or polymers, high speed centrifugation was performed to separate the two types of actin.

Initially, lysates from untransfected HEK 293T cells were separated to determine whether the lysis conditions used for the co-IP experiments were preserving action polymers.

Specifically, lysates were centrifuged at 18,000 x g, which had previously been used for the co-IPs, and the supernatant from this spin was further separated at 100,000 x g

(Figure 15A). While the 18,000 x g supernatant should contain G-actin and potentially F- actin, the actin monomer should remain in the supernatant of the 100,000 x g fraction and if present, F-actin should pellet at this speed. This analysis indicated there was potentially a small amount of F-actin present in the lysates used for the actin binding assays (Figure 15A). To determine whether mutant β-III spectrin was binding to actin monomer or polymer, high speed centrifugation of HEK 293T lysates, which express mutant CH2, was performed. Protein from the 18K x g supernatant, 100K x g supernatant and 100K x g pellet were subsequently used in co-immunoprecipitations.

46

This experiment suggests actin is robustly pulled down in all three fractions and mutant spectrin likely interacts with both G- and F-actin (Figure 15B). A potential caveat to this analysis is the possibility that the misfolded mutant β-III spectrin protein is simply sticking to actin, rather than actually binding, and further experimentation to characterize this interaction will be important.

III. Discussion

Through the characterization of the SCA5 German point mutation, I have demonstrated the leucine to proline alteration dramatically affects protein stability, folding and function of β-III spectrin. Both CD and western analyses indicate the mutant protein is unstable and misfolded at the physiologically relevant temperature of 37°.

Consistent with misfolding, the protein appears to be subject to degradation and is highly insoluble, with increased levels of mutant protein present in the insoluble pellets and prone to precipitation upon purification. Additionally, the mutation results in an aberrantly strong interaction between β-III spectrin and both G- and F-actin. Finally, these consequences of the leucine to proline substitution appear to be temperature sensitive.

Protein misfolding commonly results from point mutations and short-in-frame deletions/insertions, which in turn causes genetic diseases. Typically, the alterations reduce the propensity of the proteins to reach a functional conformation, and as a result, are subject to degradation and aggregation (Bross et al. 1999). While our results indicate that the German SCA5 point mutation causes β-III spectrin to misfold, it will be important to further characterize the folding and degradation pathways the mutant protein

47

participates—by more fully understanding these pathways, we will be able to more accurately design experiments and potential therapies. Additionally, examining protein localization by immunoflorescence will be valuable in determining whether mutant β-III spectrin is able to reach the plasma membrane or is aggregated, particularly given the insolubility of the protein.

The actin cytoskeleton is highly dynamic, and as a result, binding with actin is tightly regulated (Myers and Casanova 2008). The leucine to proline alteration appears to dysregulate this interaction, where in the mutant protein more strongly binds to both actin monomers and polymers. This finding is consistent with a dominant disease—the enhanced binding to F-actin is likely to impair the dynamic nature of the cytoskeleton, whereas binding to G-actin could inappropriately fill the ABD and prevent the appropriate stabilization of bound membrane proteins or the trafficking of vesicle cargo.

Future studies that further characterize this aberrant interaction will be important to

understand the molecular consequences of the actin binding dynamics. Specifically, it will be valuable to perform co-sedimentation assays with F-actin and purified protein to confirm the ability of mutant β-III spectrin to interact with not only G-actin but actin

polymers.

Mutation screening in families with unknown forms of ataxia has uncovered two

additional putative mutations in the N-terminus of β-III spectrin (Dr. Laura Ranum, personal communication). Importantly, one of these potential mutations is also located within the C-terminal CH domain and nearby the German mutation. If control individuals are screened and these alterations are not found in the general population, it will be important to examine the functional impact of these substitutions. It would be

48

expected that if aberrant actin binding plays an important role in the molecular pathology

of the disease, these putative mutations would have a similar impact on the interaction

between β-III spectrin and actin.

The tandem CH domains in the β-spectrins have been reported to bind other molecules in addition to F-actin, including the dynactin component, ARP1, and the 4.1 protein, which holds the tetramers together at the junctional complex and promotes interactions with actin (Holleran et al. 2001; Delaunay 2007; Bennett and Healy 2008). It will be important to examine the binding between these proteins and mutant β-III spectrin to more fully assess the impact of the proline substitution. In particular, it will be of interest to determine whether the enhanced binding to actin competes with these proteins for the binding to β-III spectrin or if the mutant domain is promiscuous and binds all of these proteins with increased affinity.

SCA5 is currently known to be caused by three mutations in β-III spectrin: a point mutation in the C-terminal CH domain and two micro-deletions in the third spectrin repeat (Ikeda et al. 2006). It will be imperative to determine the molecular downstream effects from these mutations and to ascertain whether the identified consequences converge into similar pathways. It would not necessarily be expected that the American or French deletions would dysregulate spectrin-actin binding, however, binding to another protein may be affected by these two mutations, which could ultimately lead to the same molecular consequence. For example, a specific membrane protein would not be properly stabilized at the membrane. Through the identification of specific pathways that are affected, we can begin to understand how these different mutations cause the same disorder, and by filtering through primary and secondary effects, ultimately gain a

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better understanding of the disease process.

IV. Conclusions

The German SCA5 point mutation, located in the C-terminal CH domain of β-III spectrin, causes misfolding of the protein and consequently affects its stability and function. The mutant protein appears to be temperature sensitive, insoluble and subject to degradation. Additionally, the proline substitution causes the dysregulation of the tightly controlled binding of spectrin and actin, resulting in an enhanced interaction between the mutant protein and actin monomers and polymers. Future characterization of these effects will likely lead to a better understanding of SCA5 pathogenesis and the molecular pathways involved in neurodegenerative disease.

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Figure 9. Ribbon illustration of the C-terminal CH domain of β-III spectrin. Folding of the amino acids 176-281 was predicted by 3D-JIGSAW comparative modeling (Bates et al. 2001; Contreras-Moreira and Bates 2002) using the PDB model 1bkr_A, which was developed from X-ray crystallography results of the C-terminal CH domain from β-spectrin (Banuelos et al. 1998; Berman et al. 2000; Berman et al. 2003). The predicted folding was visualized using RasMol version 2.6 (Sayle and Milner-White 1995). The helices are labeled A-G. The arrow indicates the location of the SCA5 German mutation (L253P). Alternatively, in solution NMR analysis of β-III spectrin (PDB model 1wyq_A) identifies the four major helices A, C, E & G (Berman et al. 2000; Berman et al.; PDB ID: 1wyq_A 2005).

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Figure 10. Circular dichroism of the N-terminal of β-III spectrin. (A) Expression constructs. Protein was expressed using wildtype and mutant pGEX-SPTBN2-CH constructs, which encoded the first 281 amino acids and a 7x HIS tag, and purified protein was subsequently used in the analysis. (B) Molar ellipicity of wildtype and mutant proteins at 25°. The wildtype spectrum is shown in black and mutant is depicted in red. Wildtype α-helical content is 31.52% while the mutant α-helical content is 23.96%. The percent helical content was calculated by dividing the molar ellipticity at 222 nm by 40,000 molar elliptical units (Abdi et al. 2006). (C) Melting curves for wildtype and mutant proteins. At a wavelength of 222 nm, the protein stability of wildtype and mutant proteins were examined across a temperature gradient, which ranged from 20-90°C.

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Figure 11. Expression of wildtype and mutant β-III spectrin in HEK 293T and N2A cells. (A) The four constructs used for the tissue culture analysis. Tagged or untagged versions of either wildtype or mutant SPTBN2 cDNA were inserted into the pcDNA3.1 vector for expression. The CH2 constructs encoded the first 281 amino acids of β-III spectrin. (B-F) The asterisk indicates the two apparent degradation products, running between 20 and 30kDa. Tubulin is shown as a loading control. The eGFP protein is shown as a control for translation of wildtype and mutant β-III spectrin. (B) Western blot of wildtype and mutant β-III spectrin CH2 expression, detected by the myc antibody, in HEK 293T cells. The estimated molecular weight of the truncated protein is 33 kDa. The mutant protein also appears to be degraded, with two fragments running between 20 and 30 kDa. (C) Western blots of wildtype and mutant full length β-III spectrin expression in HEK 293T and N2A cells. The 271 kDa full length protein and degradation products are detected by an N-terminal β-III spectrin antibody. The protein fragments vary in size depending on presence or absence of the 5’myc tag, indicating they contain the N-terminal portion of the protein. (D) Western blot of the β-III spectrin- eGFP expression in HEK 293T cells, over a 48 hour timecourse. Time points were taken at 24, 31 and 48 hours post-transfection and lysates were collected. Using an IRES, eGFP was used as a control for translation. The β-III spectrin protein is detected by the N-terminal antibody (E) Western blot showing the solubility of wildtype and mutant β-III spectrin CH2, expressed in HEK 293T cells. The β-III spectrin protein is detected by the myc antibody. S indicates the supernatant and P represents the insoluble pellet. (F) Western blot showing the solubility of myc-tagged wildtype and mutant β-III spectrin, which were expressed in HEK 293T (left) and N2A (right) cells. The β-III spectrin protein is detected by the myc antibody. S indicates the supernatant and P represents the insoluble pellet.

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Figure 12. Promotion of protein folding at 25°C. β-III spectrin protein is detected by an N-terminal antibody. Tubulin is shown as a loading control and eGFP as a marker for translation. The asterisk indicates the protein fragments. (A) Western blots of wildtype and mutant β-III spectrin eGFP expression in HEK 293T. 37°C indicates the cells were cultured at this temperature for 48 hours post-transfection. 25°C indicates the cells were cultured at 37°C for 24 hours post-transfection and then moved to 25°C for an additional 24 hours. (B) Western blot of wildtype and mutant β-III spectrin eGFP expression in N2A cells. Protein was expressed at either 37°C or 25°C for the entire 48 hour period post-transfection.

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Figure 13. Promotion of protein folding by HSP-70. Western blots of wildtype or mutant β-III spectrin eGFP co-expression with HSP-70. Expression in HEK 293T cells is detected by the N-terminal β-III spectrin antibody. Tubulin is shown as a loading control and eGFP was used as a translation control. The asterisk indicates the β-III spectrin degradation fragments.

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Figure 14. Aberrant binding to actin. Co-immunoprecipitations (co-IP) using lysates from HEK 293T cells that express either wildtype or mutant β-III spectrin. β-III spectrin was pulled down using the 5’myc tag, and the proteins were visualized by western blot. Cell lysate, mock co-IP with no antibody (no Ab), and co-IP using the myc antibody (myc Ab) are shown for untransfected, wildtype and mutant expressing cells. Actin is detected by the actin (C11) goat polyclonal antibody. (A) Co-IP using cell lysates expressing β-III spectrin CH2 constructs. (B) Co-IP using cell lysates expressing full-length wildtype and mutant β-III spectrin myc-tagged constructs. (C) Co-IP using cell lysates expressing full- length mutant β-III spectrin myc-tagged constructs. The cells were either cultured at 37°C for 48 hours post-transfection or at 37°C for 24 hours and then for an additional 24 hours at 25°C.

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Figure 15. G- versus F-Actin. (A) Western blot of untransfected HEK 293T lysates, subjected to two rounds of centrifugation and probed for actin. Lysates were centrifuged at 18,000g and the supernatant (Sup.) and pellet were collected. The 18K x g supernatant, containing G-actin and potentially F-actin, was subsequently centrifuged at 100,000 x g, which resulted in the 100K sup. and 100K pellet. At 100K x g spins, actin monomers and polymers separate, with the G-actin remaining in the supernatant while the F-actin pellets. (B) Western blot of co-IPs using protein from lysates expressing mutant β-III spectrin CH2. Prior to the co-IP, the lysates were centrifuged and the 18K and 100K supernatants and 100K pellet were used in the experiment. The 18K x g supernatant was previously used in the co-immunoprecipitations and was included as a positive control. Strong interactions between the truncated β-III spectrin and actin are observed for both the 100K supernatant and 100K pellet, indicating the mutant protein is binding to both G- and F- actin. Actin was detected using the actin (C4) mouse monoclonal antibody.

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CHAPTER 4

CONCLUSIONS AND FUTURE DIRECTIONS

I. Summary and Conclusions

SCA5 is a slowly progressive neurodegenerative disorder, which causes incoordination of gait, limb and eye movements and slurred speech (Ikeda et al. 2006).

While symptoms of this autosomal dominant disease generally begin in the 3rd or 4th decade of life, onset can range from 10 to 68 years of age (Ranum et al. 1994; Stevanin et al. 1999). In 1994, the American SCA5 family that I later worked with was formally described and mapped to 11q13, the centromeric region the chromosome (Ranum et al.

1994). Subsequently, two additional families from France and Germany with similar clinical and neuroradiological findings, were also mapped to this region (Stevanin et al.

1999; Burk et al. 2004). Because there is reduced recombination near centromeric regions, including the SCA5 region, mapping efforts were hindered by the relatively few recombinant individuals available to narrow the region. Therefore, a multifaceted mapping approach was implemented to determine the pathogenic mutation responsible for SCA5. These efforts included screening repeat expansions, searching for haplotype conservation between the three SCA5 families, refinement of the critical region and both targeted and brute force sequencing.

In 2006, we discovered β-III spectrin (SPTBN2) mutations cause SCA5 in the three reported families from the United States, France and Germany (Ikeda et al. 2006).

Separate in-frame deletions were identified in the American (39 bp) and French (15 bp) families, which are located within the third of 17 homologous, triple-helical, spectrin

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repeat motifs. In the German SCA5 family, a point mutation (Leu253Pro) was found within the second of two calponin homology domains, a region reported to bind to actin and the subunit of dynactin, ARP1. Consistent with its role in SCA5, β-III spectrin is highly expressed in Purkinje cells, the primary site of neurodegeneration in this disease.

Additionally, β-III spectrin has been shown to stabilize membrane proteins through interactions with the actin-cytoskeleton (Jackson et al. 2001; Ikeda et al. 2006) and has been suggested to play a role in vesicle transport (Holleran et al. 2001).

Spectrin mutations are a novel cause of ataxia and the identification of these pathogenic alterations provides an opportunity to not only gain insight into the molecular

mechanisms underlying SCA5 but also to understand neurodegenerative disease in

general. When novel mutations are discovered, particularly when located in well characterized proteins like β-III spectrin, researchers are able to further to piece together the puzzle that defines the fundamental causes and common molecular pathways involved in the disease process. Towards this effort, I have performed an initial characterization of the SCA5 German mutation by investigating the impact of the leucine to proline substitution on protein stability, folding and function. Through expression studies in human embryonic kidney (HEK 293T) and mouse neuroblastoma (N2A) cell lines and circular dichroism (CD) analyses, I have shown the single amino acid substitution dramatically affects the protein’s ability to properly fold, rendering it insoluble and subject to degradation. Additionally, the mutation likely causes the dysregulation of the tightly controlled binding between spectrin and actin, resulting in an enhanced interaction with both actin monomers and polymers. Importantly, the mutation appears to be temperature sensitive, with the downstream effects of the substitution

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largely ameliorated when the protein is expressed at a lower temperature. This attribute of the mutation may prove to be a valuable tool for researchers investigating the mechanisms underlying the disease, as was found for cystic fibrosis. The most common cystic fibrosis mutation, the delta F508 mutation in the CF transmembrane conductance regulator (CFTR) gene, was discovered to be temperature sensitive; through proper

folding increased amounts of the functional mutant protein is able to reach the plasma

membrane (Dalemans et al. 1991; Denning et al. 1992; Egan et al. 1995; French et al.

1996). These discoveries have led researchers to target the various folding and

degradation pathways in the development of treatments and this may prove to be a

valuable template for SCA5.

II. Future Directions

As additional putative mutations are identified through patient screening at

Athena Diagnostics and sequencing samples from our DNA bank (Dr. Laura Ranum,

personal communication) and other collections (Zuhlke et al. 2007), a bioassay, which

can quickly ascertain the impact of the mutations on protein function, will become

increasingly important. This will not only provide invaluable information to patients,

who are currently receiving reports detailing changes of unknown significance, but will

also aid researchers in the identification of key residues and their roles in specific protein

functions. Theoretically, one could test the pathogenic properties of the putative

mutations by creating animal models; however these experiments would not only be

laborious and expensive for an initial characterization but would not necessarily provide

mechanistic information. An alternative strategy, which would be more economical, is to

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develop a panel of assays for yeast or cell culture that would target specific domains and functions. The specific assay performed would then be dependant on the location of the mutation. Specifically, the aberrant actin binding observed from the German mutant β-

III spectrin may be an appropriate assay for studying the putative mutations located within the CH domains at the N-terminus of the protein. Through the further characterization of the known mutations and their impact on both established and newly identified functions and interactions, these assays can be developed.

In addition to identifying and characterizing putative mutations in β-III spectrin, it will also be important to investigate the binding partners of this protein for potential alterations that also cause ataxia. The rationale for these experiments stems from the heredity red blood cell disorders, in which mutations in spectrin and interacting proteins cause erthrocytosis (Delaunay 2007). Specifically, hereditary spherocytosis or elliptocytosis can be caused by mutations in genes encoding ankyrin-1 (ANKI), alpha spectrin (SPTA1) and beta spectrin (SPTB), the anion exchanger 1 (SLC4A 1), protein 4.1

(EPB41), protein 4.2 (EPB42), and beta-adducin (ADD2) (Delaunay 2007). Similar to erythrocytic spectrin, β-III spectrin is likely an integral member of the actin-cytoskeleton, providing important structural support of the Purkinje cell while anchoring proteins

important for synaptic transmission. Therefore, interacting proteins of this complex

could also be involved in ataxia. Importantly, like spectrin, the complex of proteins

involved in the red blood cell disorders are members of families, with homologues and

isoforms expressed in specific spatial patterns; many of these proteins have counterparts

expressed within Purkinje cells. While all of these proteins are potential candidates, the

ankyrin-G (ANKG) gene is particularly attractive; targeted knockout of ankryin-G in the

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mouse cerebellum results in severe ataxia, Purkinje cell degeneration, reduced generation of Purkinje cell action potential and loss of the voltage-gated Na+ channel (Nav1.6) from the initial segment (Zhou et al. 1998; Jenkins and Bennett 2001). Beyond the proteins known to be involved in erythrocytosis, other β-III spectrin binding partners are also potential ataxia candidate genes, specifically EAAT4. EAAT4 is a glutamate transporter expressed in Purkinje cells and has been shown to be stabilized at the cell surface by

wildtype but not mutant β-III spectrin (Ikeda et al. 2006). Additionally, intracisternal

antisense knockdown of EAAT4 in rats results in a progressive ataxia (Raiteri et al. 2002)

and transcript levels have been shown to be downregulated in SCA1 transgenic mice (Lin

et al. 2000; Serra et al. 2004). The characterization of both known mutations and the

identification of additional alternations in β-III spectrin and its binding partners will

allow us to delve deeper in the molecular mechanisms and pathways that result in SCA5

and ataxia.

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CHAPTER 5

MATERIALS AND METHODS

I. Genetic Mapping of SCA5

A. Human Subjects

All participating subjects and control individuals referred to in this study signed

an informed consent form as approved by the Human Subjects Committee at the

University of Minnesota or by the participating institutions. Unrelated control DNA

samples were obtained from the CEPH panel and from healthy North Americans (n=500).

DNA was extracted from peripheral venous blood using the Puregene kit (Gentra

Systems, Plymouth, MN).

B. Generation of Chromosome-Separated Cell Lines

Mouse/human hybrid cell lines haploid for the affected or normal copy of

chromosome 11 were generated at GMP Genetics (Waltham, MA) by fusing mouse E2

cells with human lymphoblastoid cells from an affected American family member, as

previously described (Papadopoulos et al. 1995). In brief, lymphoblast cells from an affected individual were electrofused to mouse E2 cells and HAT plus geneticin was used to select against unfused E2 and lymphoblast cells, respectively. The surviving colonies were expanded and clones containing only a single copy of the affected or normal chromosome 11 were selected by typing microsatellite markers that span the SCA5 region.

C. Screening of Microsatellite Repeat Markers in the SCA5 Region

A panel of 445 novel di-, tri-, tetra-, and penta-nucleotide repeats, spanning the 65

SCA5 critical region, were identified. Primers were designed for approximately 380 repeats using Primer 3 (Rozen and Skaletsky 2000). These microsatellite repeat markers were amplified by PCR using a [γ-33P] ATP tagged primer. Products were separated on

4% denaturing polyacrylamide gels and visualized by autoradiography. Genotyping of

the single affected chromosome allowed for the exclusion of repeat-expansion mutations

in non-polymorphic markers. The E2 mouse DNA was used as a negative control to

confirm the amplified product was specific to human but not mouse DNA. All

polymorphic markers were subsequently used to determine the affected haplotypes for

each of the SCA5 families.

D. Construction of a BAC Library from an Affected SCA5 Haploid Cell

Line and Shotgun DNA Sequencing

Lark Technologies, Inc. created the BAC Library. Specifically, an incomplete

Hind III digestion was performed on DNA from the haploid cell line containing the affected chromosome 11 and introduced into the plndigoBAC-5 vector (Epicentre,

Madison, WI), which was then used to prepare a BAC library of approximately 352,000 recombinant clones. Yoshio Ikeda and Marcy Weatherspoon screened the BAC libraries by PCR using microsatellite markers that we developed and positive BAC clones were subsequently isolated by hybridization. Lark Technologies Inc. (Houston, TX) performed the shotgun sequencing and assembly. In brief, shotgun libraries were constructed for three BACs (VI-C2, VI-C11, IV-H4), which spanned the region of haplotype conservation between the American and French SCA5 families, by subcloning the fragmented DNA into the pUC57 vector. Sequencing reactions of the three shotgun libraries were performed and subsequently analyzed on ABI3730xl DNA sequencers.

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The sequence data was assembled using the Phred-Phrap-Consed software (Gordon et al.

1998) . This sequence was subsequently BLASTED against specific genes using data available through UCSC Genome Bioinformatics and National Center for Biotechnology

Information, by Yoshio Ikeda, Marcy Weatherspoon and me.

E. SPTBN2 Gene Sequencing in SCA5 Families and Mutation Screening

in Controls

Genomic DNA of affected French and German SCA5 patients was used to amplify SPTBN2 exons by PCR and the resulting products were sequenced. After the

American and French mutations were identified, family members and 1,000 control

chromosomes were screened for these deletion mutations by PCR. PCR was performed

by labeling the 5’ end of each forward primer with [γ-33P] ATP. The resulting products were separated on 4% denaturing polyacrylamide gels and visualized by autoradiography.

After the German mutation was identified, allele-specific PCR was used to screen for the

German missense mutation. Two forward primers, one containing an altered nucleotide

(C) at its 3’-end and the other containing a 19bp-tail at its 5’-end, were used in a single reaction to amplify both the mutant (shorter product) and normal (longer product) alleles, respectively. The resulting products were separated on 4% agarose gels and visualized by ethidium bromide. PCR was subsequently performed on 1,000 unrelated control chromosomes to screen for the German mutation. The PCR primer sequences and conditions used for SPTBN2 sequencing and mutation screening are shown in Tables 6, 7 and 8.

F. RT-PCR Analysis

RNA was harvested from ~100 mg of cerebellar autopsy tissue from an American

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SCA5 patient and a control individual using TRIzol (Invitrogen, Carlsbad, CA). First- strand synthesis was performed using the Invitrogen SuperScript™ First-Strand Synthesis

System for RT-PCR kit (Invitrogen) and a SPTBN2 gene specific primer from exon 14

(5’-CCT CAG CTT CAC CCA CCT C-3’). PCR was performed at 54 ˚C with 1 mM

MgCl2. PCR primers flanking the Lincoln SCA5 deletion region were located in exon 12

and 13 (5’-AGC GCT ACC ACG ACA TCA AG-3’; 5’-CAG GTC CTC CAC TCC TGC

TA-3’), respectively. The products were separated on a 2% agarose gel and visualized

with ethidium bromide.

G. Immunohistochemistry

The immunohistochemistry was performed by Yoshio Ikeda. The autopsy tissue

from an American SCA5 family member and a control individual, without neurological

disease, were embedded in paraffin and 5 µm sections were prepared. These sections

were incubated in 0.3% H2O2 for 30 min to bleach endogenous peroxidase activity, and

then heated by a steamer in 10 mM citrate buffer at pH 6.0. Sections were blocked in 5%

normal serum, derived from animals in which the secondary antibodies had been made.

Slides were incubated at 4˚C overnight with β-III spectrin (Santa Cruz Biotechnology,

Santa Cruz, CA) diluted at 1:500. Positive staining was visualized by the avidin-biotin-

peroxidase complex method (Vector, Burlingame, CA) with diaminobenzidine as the

chromogen and counterstained with hemotoxylin.

H. URLs

The website for UCSC Genome Bioinformatics is available at

http://genome.ucsc.edu/. The National Center for Biotechnology Information database is

available at http://www.ncbi.nlm.nih.gov/. The multiple sequence alignment program

68

Clustal W is available at http://clustalw.genome.jp/. Primer 3 is available at

http://frodo.wi.mit.edu/cgi-bin/primer3/primer3_www.cgi.

I. Accession Numbers

GenBank: Homo sapiens SPTBN2 mRNA, AB008567 and NM_006946.

II. Molecular Characterization of the L253P Mutation

A. Creation of β-III Spectrin Constructs

Standard techniques were used in the construction of the β-III spectrin wildtype and L253P mutant constructs. Untagged and 5' myc-tagged wildtype β-III spectrin

constructs were provided by Karen Armbrust, a member of the Ranum lab. Specifically,

a full-length SPTBN2 pBluescript cDNA clone (KIAA0302, Kazusa DNA Research

Institute) was re-cloned into the mammalian expression vector pcDNA3.1 (Invitrogen)

and a myc-tag was introduced immediately downstream of the ATG start codon by PCR

and subcloning (Ikeda et al. 2006). The L253P mutation was introduced into the wildtype

and wildtype myc-tagged β-III spectrin constructs using the QuikChange II XL Site-

Directed Mutagenesis Kit (Stratagene, La Jolla, CA), using the primers German Mut F

(5'-GGG ACT TAC CAA GCC GCT GGA TCC CGA AGA C-3') and German Mut R

(5'-GTC TTC GGG ATC CAG CGG CTT GGT AAG TCC C-3').

The wildtype and mutant β-III spectrin eGFP constructs, containing an IRES

eGFP, were created by PCR and subcloning into the wildtype and mutant β-III spectrin constructs. A portion of the 3'UTR was deleted, leaving 122 bp of sequence between the

TAG stop codon and the beginning of the IRES. This modification was made by PCR using overlapping primer sets (Set 1: 3'UTR Del Set 1F (5'-CGC AAG CAG GAG ATG

69

GAG-3') and 3'UTR Del Set 1R (5'-GAG CGG GCG CCA GAC CCT AGC AGC AGG

CAG-3'); Set 2: 3'UTR Del Set 2F (5'-CTA GGG TCT GGC GGC CGC TCG AGT CTA

GAG GG-3') and 3'UTR Del Set 2R (5'-AGG GAA GAA AGC GAA AGG AG-3')).

Separate PCR products were generated (3'UTR Del primer sets 1 and 2), followed by a third PCR reaction, which used PCR product from the initial reactions as template

(3'UTR Del set 1F and set 2R primers). The three PCR reactions were performed using a

MgCl2 concentration of 1.5 mM and an annealing temperature of 54°C. The final PCR

product was subcloned using XbaI and PciI digestion. The IRES eGFP was excised from

the pCSII CMV IRES2-GFP vector, developed in the McIvor lab (Dr. Scott McIvor)

using NotI and subcloned into the wildtype and mutant β-III spectrin constructs

containing the 3'UTR deletion (NotI).

Wildtype and mutant β-III spectrin CH2 constructs were created by PCR and subcloning, using the wildtype and mutant 5' myc-tagged constructs. The 5' end of the

constructs was amplified by PCR using the primer set CH Domain (F primer: 5'-CCA

AGC TGG CTA GCG TTT A-3' and R primer: 5'-GAA TCT AGC GGC CGC CTA

GGA GAA GTA ATG GTA GTA AG-3'). PCR conditions were 1.5 mM MgCl2 and an annealing temperature of 54°C. The wildtype and mutant 5' myc-tagged constructs were

digested with NotI and KpnI to remove the SPTBN2 cDNA and the PCR product was

digested and subcloned into these vectors (NotI and KpnI).

The pGEX-SPTBN2-CH constructs were created by amplification of wildtype and mutant β-III spectrin constructs and subcloning into the pGEX6p1 vector (GE Healthcare,

Piscataway, NJ), modified to contain a 3' 6X HIS tag (Dr. Vann Bennett). First, untagged wildtype and mutant β-III spectrin CH2 constructs were created by using PCR to amplify

70

the 5' end of the original β-III spectrin constructs using the primer set CH Domain (F primer: 5'-CCA AGC TGG CTA GCG TTT A-3' and R primer: 5'-GAA TCT AGC GGC

CGC CTA GGA GAA GTA ATG GTA GTA AG-3'). PCR reactions were performed using an MgCl2 concentration of 1.5 mM and an annealing temperature of 54°C. The

wildtype and mutant β-III spectrin constructs were sequentially digested with NotI and

KpnI to remove the SPTBN2 cDNA and the PCR product was digested and subcloned into these vectors (NotI and KpnI), creating untagged β-III spectrin CH2 constructs.

These untagged constructs were subcloned into the pGEX6p1HIS vector using SalI and

NotI digestion. A series of deletions were performed using PCR and overlapping primer

sets (Set 1: pGEXCHset1F (5'-CGG TGT TTC GAG AAT TGC AT-3') and

pGEXCHset1R (5'-GCG TGC TGC TGG GCC CCT GGA ACA GAA CTT -3'); Set 2:

pGEXCHset2F (5'-CCA GGG GCC CAG CAG CAC GCT GTCACCCAC-3') and

pGEXCHset2R (5'-GAT GAT GAT GGG AGA AGT AAT GGT AGT AAG-3'); Set 3:

pGEXCHset3F (5'-TTA CTT CTC CCA TCA TCA TCA TCA TCA TCA TGC GTG

ACT G-3') and pGEXCHset3R (5'-GAT GAT GAT GGG AGA AGT AAT GGT AGT

AAG-3')). Separate PCR products were generated using the primers from pGEXCH sets

1, 2 & 3. A second round of PCR (pGEXCH set 1F/2R primers) was performed using

product from pGEXCH set 1 and 2. A subsequent third round of PCR, using product

from the second round, was performed using primers pGEXCH set 1F/3R. The PCR

reactions were performed using an MgCl2 concentration of 1.5 mM and an annealing temperature of 54°C. The final PCR product and the pGEX-STPBN2-CH construct were digested with AatII and BstBI and ligated together.

The HSP-70 construct was provided by Dr. Harry Orr (Jorgensen et al. 2007).

71

Sequencing of all of the constructs was performed to verify the integrity of the entire cDNA.

B. Protein Expression and Purification

Wildtype and mutant pGEX-SPTBN2-CH constructs were transformed into the

BL21(DE3)pLysS strain of E. coli (Invitrogen) and grown overnight at 37°C in 2XYT media/amp/chloramphenicol. The starter culture was diluted for large scale expression, grown to an optical density (OD600) of ~.4 and expression was induced with 0.1 M isopropyl 1-thio-β-D-galactophyranoside (IPTG). After induction, the wildtype

transformation was grown at 37°C for 3 hours, while the mutant transformation was

grown overnight at 25°C to maintain solubility of the protein. Cells were harvested by

centrifugation at 6,000 x g for 15 min, washed with 1X phosphate buffered saline (PBS)

and frozen at -80°C.

For the purification, the pellets were thawed on ice, and lysed in buffer (50 mM

phosphate buffer, pH 8.0, 0.3 M sodium bromide, 0.2 mM beta-mercaptoethanol, 1 mM

sodium azide, 20 mM imidazole and a cocktail of protease inhibitors (0.4 mM 4-(2-

aminoethyl)benzenesulfonylfluoride hydrochloride, 10 mM benzamidine, 30 µg/ml

leupeptin and 10µg/ml pepstatin)). The extract was repeatedly syringed through a 20

gauge needle, to shear the bacterial DNA, and was centrifuged at 110,000 x g (35,000 rpm) for 1 hour. The supernatants were incubated with a 2 ml slurry of equilibrated high performance nickel Sepharose beads (GE Healthcare) batchwise and rotated at 4°C for 2 hours. The beads were washed and proteins were eluted with buffer containing 0.3 M imidizole. The GST tag was cleaved using 80 units of Precision Protease (GE

Healthcare) and digests were dialyzed in buffer overnight at 4°C. An additional 20 units

72

of the protease was added the next day, incubating 1 hour at 4°C in dialysis buffer. To remove the GST contamination, the protein was re-coupled to Ni-Sepharose, washed, eluted with buffer containing 0.3 M imidizole and dialyzed overnight at 4°C in buffer containing 50mM salt. Protein precipitation from the mutant was removed by ultra- centrifugation. High-pressure liquid chromatography (HPLC) was performed on a Mono

Q 5/5 HR column for additional purification. Protein was dialyzed overnight in buffer containing 10 mM Na phosphate, pH 7.4, and 150 mM NaF. Protein concentrations were determined using a Bradford assay and protein purification steps were analyzed by running SDS-PAGE gradient gels, which were stained with Coomassie Brilliant Blue.

C. Circular Dichroism

Purified wildtype and mutant proteins were brought to the same concentration of

0.13 mg/ml and 200 µl were loaded into a 1-mm path-length quartz cuvette. CD analysis was performed on an Aviv 62 DS model CD spectrometer and measurements were taken at 25°C, between 190 nm and 260 nm. Spectra are an average of five runs and buffer was used to determine background signal, which was subtracted from protein spectra prior to conversion to mean molar ellipticity. Melting curves for wildtype and mutant proteins were performed across a temperature gradient (20-90°C) at 222 nm. The spectra for the melting curve analysis represent a single scan.

D. Cell Culture and Transfection

HEK 293T and N2A cells were cultured in DMEM (Invitrogen) and 10% fetal bovine serum (FBS) (Invitrogen) at 37°C (or 25°C where specified) and 10% CO2. Cells were transfected using Lipofectimine 2000 and Lipofectimine LTX (Invitrogen) following protocols from manufacture. Lysates were collected 48 hours post-transfection.

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E. Immunoblot Analysis

Cells were lysed in radioimmunoprecipitation (RIPA) buffer (1X PBS, 1%

Nonidet P-40, 0.5% sodium deoxycholate, 0.1% sodium dodecyl sulfate (SDS), 1X protease inhibitors (Complete Mini, Roche Applied Science, Indianapolis, IN)), syringed

through a 27 gauge needle and centrifuged at 18,000 x g for 10 min at 4°C. The pellet

was solubilized by incubating at 60°C for 1 hour in 1% SDS. Ten volumes of RIPA

buffer with 10 mM MgCl2 and ~500 units of DNase1 (Invitrogen) were added, and incubated at 37°C for 10 min. The solubilized pellet was centrifuged at 16,000 x g for 15 min and the supernatants were collected. Total protein concentration was determined with a Bio-Rad protein assay. Two-4 µg of supernatant/pellet were boiled at 80°C for 10 min, separated by SDS-PAGE on NuPage 4-12% Bis-Tris gels (Invitrogen) and transferred to a nitrocellulose membrane (GE Healthcare). Blots were incubated in 5% non-fat milk in PBS-T (1 X PBS, 0.1% Triton X-100), to block non-specific binding, for

1 hour and washed with PBS-T. The membranes were incubated at 4˚C overnight with the primary antibody in 1% non-fat milk/PBS-T. Primary antibodies used in these analyses included: 1) β-III spectrin (N-19) goat polyclonal (Santa Cruz Biotechnology,

Inc., Santa Cruz, CA) (1:200 dilution); 2) C-myc mouse monoclonal (Sigma-Aldrich,

Saint Louis, MO) (1:5,000 dilution); 3) α-tubulin mouse monoclonal (Sigma-Aldrich)

(1:5,000 dilution); 4) GFP-HRP conjugated (GeneTex, Inc., San Antonio, TX) (1:3,000 dilution); 5) HSP-70 FITC conjugated mouse monoclonal (StressGen/Assay Designs, Inc.,

Ann Arbor, MI) (1:1,000 dilution); 6) Actin (C11) goat polyclonal (Santa Cruz

Biotechnology, Inc.) (1:200 dilution); 7) Actin (C4) mouse monoclonal (Dr. James

Ervasti) (1:10,000 dilution). Blots were washed 3 times with PBS-T. Membranes were

74

incubated with horseradish peroxidase-conjugated secondary antibodies in 1% non-fat milk in PBS-T for 1 hr at room temperature, followed by 5 PBS-T washes. Secondary antibodies used in these analyses included: 1) Sheep-anti-mouse IgG-HRP (Sigma

Aldrich) (1:5,000 dilution); 2) Donkey-anti-goat IgG-HRP (Santa Cruz Biotechnology,

Inc.) (1:20,000 dilution). The immunoblots were visualized with enhanced chemiluminescence (GE Healthcare).

F. Co-Immunoprecipitation

100 µg of total protein in 500 µl of RIPA buffer were used in each IP (100K x g

pellet used 70 µg). Lysates were precleared using 35 µl of equilibrated nProtein A

Sepharose 4 Fast Flow beads (1:1 slurry) (GE Healthcare), which were incubated

together by rotating for 3 hours at 4°C. Beads were removed by centrifugation at

18,000 x g for 2 min at 4°C. Except for the no antibody controls, 5 µl of the c-myc

antibody (Sigma Aldrich) were added to each IP and incubated at 4°C for 1 hr on a

rotator. 35 µl of equilibrated nProtein A Sepharose 4 Fast Flow beads (1:1 slurry) (GE

Healthcare) were incubated with the lysates for 1hr at 4°C on a rotator. Lysates were

centrifuged at 18,000 x g for 2 min at 4°C and the supernatants discarded. The beads

were washed 5X with RIPA buffer and resuspended in 1.5X loading buffer (4.5 µl

NuPage reducing agent (Invitrogen), 11.3 µl NuPage sample dye (Invitrogen), 14.2 µl

RIPA buffer). Prior to western analyses, samples were boiled at 80°C for 10 min.

G. Ultra-Centrifugation and Separation of G- and F-actin

18,000 x g supernatants were centrifuged at 100,000 x g (50,000 rpm) for 30 min in a Beckman TLX Optima Ultracentrifuge (Beckman Coulter, Fullerton, CA). The supernatants were removed and the pellets were washed in RIPA buffer, re-centrifuged

75

for an additional 15 min and resuspended in RIPA buffer

H. URLs

The website for 3D-JIGSAW is available at:

http://bmm.cancerresearchuk.org/~3djigsaw/. The Protein Data Bank is available at:

http://www.pdb.org/.

Copyright Notice

Portions of this chapter have been reproduced with permission from the following article:

Ikeda Y*, Dick KA*, Weatherspoon MR, Gincel D, Armbrust KR, Dalton JC, Stevanin

G, Dürr A, Zühlke C, Bürk K, Clark HB, Brice A, Rothstein JD, Schut LJ, Day

JW, Ranum LP. Spectrin mutations cause spinocerebellar ataxia type 5. Nat

Genet. 38(2):184-90 (2006) (* co-first authors).

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Exon(s) Forward Primer (5'-3') Reverse Primer (5'-3')

Exons 1-2 CTGCCTTCCTGCTTCACTTT TCATGACGAGCTGACAAAGC Exon 3 CCCTGCCAACTGGTGTTTAG GGTCCCCTTGGACACTTTTC Exon 4 TGCCTGTCTGTGTTCCTGAG TCCTCCATCTTTGTGTTTGTTG Exons 5-6 ACACCAGGAGTTCCTGTCCA TGCTCCGAGTGCTATTCCTT Exon 7 TTGGTGTGGGTTTCCTCTTC CACTGGTCCACCTCCTGTCT Exons 8-9 GAACTTCTGGGAGGCCTGA TCCCTGAAGGCTGTGCTAAT Exon 10 CCTCGTGGGCTTTAATTCTG ATGTGTGCAAGGCATCTGG Exon 11 CCACCCTGTCCCTTCCACTA CCCAGTTCTGACCAGCCTAA Exon 12 AGAGGCACTGTCCCTTGGT GCTGGTTCACACTCCACAGA Exon 13 GAAAAACGCAGCCAGGTTAG GCTCTTGATGTGCTCCTTCC Exon 14 GGCTGGGTTAAGGCTCTGAC AGGGACTCACCACCCACAT Exon 15 GCTGCCTCCCACAATTCAC TCCCCATTGCTTCATTTTTC Exon 16 GGAAGAAGCTTCCAAACAGG CCATCCTGCTCCTTCACATT Exon 17 TGCTTGTTGGTCCCTACCTC GGTTTCCTGTGCCACGTTTA Exon 18-19 GGTTAGCCAAAGGGTCACAA ACAAAAACCACGTCCTGGAG Exon 20 GGCTAATTTGGGCACTTTGA CCCCTTTCTTCTGCTGTTCA Exon 21 GCGGAAATGCAGAGCTAACA GGAGATGGTCAATGCCAAAG Exon 22 TGTCCCCACTCCCACTAATC AAAAACACGTCCAAGTCTGG Exons 23-24 CTGACGGGTGTTACCATCG AGCACTGAAGGCTCCACATT Exon 25 GAACAGACCGGAGGTCAGAG CTGTGGGTCCTCCACTCTTC Exon 26 TAACATCACGGCATGGTCTG CCCTAGCTCCTGGGAACTCT Exons 27-28 CTTGGAGTCCCCCGCTCT AAGCAGAAAGCCACCAAGAA Exon 29 TCACATCCTGGTGCTAACTCA CCTACTCTGGAACCCACAGG Exon 30 CCACTCTGACCCACCATCTT AAGCCAGCACAGGTCAGG Exons 31-33 CCCTCTTACACGCAACCTTC GACCCTTCGCCTCACAGTTA Exon 34 GGTTAGGGATCTCCCGTCTC CCCTTTGCCCAGAAGATGTA Exon 35 AGATGGGAGCAGAACTGGAA CTGGCCTGGTTACTCCACTC Exon 36 TACGCTCTCACCAGCAGCTA CGCACACATCCAGTCTTACC Exon 37 CAGCTCACTTTCTGCCTCCT AGAGAGGCTGTGGTCAGGAA

Table 6. Primer sequences for SPTBN2 sequencing. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

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MgCl Product Exon(s) Ta (°C) 2 (mM) Size (bp) Exons 1-2 54 1 468

Exon 3 54 1 282

Exon 4 54 1 395 Exons 5-6 54 1 495

Exon 7 54 1 248

Exons 8-9 54 1 568 Exon 10 54 1 228

Exon 11 54 1 244

Exon 12 54 1 464 Exon 13 54 1 279

Exon 14 57 1 990

Exon 15 54 1 234 Exon 16 54 1 895

Exon 17 54 1 395

Exon 18-19 54 1 593 Exon 20 54 1 354

Exon 21 54 1 395 Exon 22 54 1 233 Exon 23-24 54 1 712

Exon 25 61 2 328 Exon 26 54 1 498 Exons 27-28 54 1 599

Exon 29 61 3 201 Exon 30 54 1 300 Exons 31-33 54 1 541

Exon 34 54 1 374 Exon 35 54 1 392 Exon 36 59 2 243

Exon 37 57 1 998 Table 7. PCR conditions for SPTBN2 sequencing. Ta indicates annealing temperature. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184- 190.

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Mutation Forward Primer Reverse Primer

E532_M544del AGCGCTACCACGACATCAAG CCCTCGACTCTTGATCACTCTT (Lincoln)

L629_R634del- GTGGCCAAGCTAGAGCAGAG CACCTCCCAGAGGAAACG insW (French)

758T>C Normal: CACGACGTTGTAAAACG CCAAAGAAGCCCCTGTATCA (German) ACGAACTGGGACTTACCAAGCT

Mutant: GAACTGGGACTTACCAAGCC

Mutation Ta (°C) MgCl2 (mM) Product Size (bp)

E532_M544del Normal = 222 54 1 (Lincoln) Mutant = 183

L629_R634delinsW Normal = 105 61 2 (French) Mutant = 90

758T>C Normal = 177 55 1.5 (German) Mutant = 158

Table 8. Primer sequences and PCR conditions for SPTBN2 mutation screening. Ta indicates annealing temperature. Reproduced with permission from Ikeda et al., (2006), Nature Genetics, Vol. 38, pp. 184-190.

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APPENDIX A

MAPPING MENDELIAN DISORDERS IN SMALL FAMILIES: VALIDATION

OF SNP HAPLOTYPE MAPPING

ABSTRACT

The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans.

Nevertheless, while thousands of Mendelian disorders have not yet been mapped there has been a trend away from studying single-gene disorders. In part, this is due to the fact that many of the remaining single-gene families are not large enough to map the disease locus to a single site in the genome. New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine. Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density SNP arrays to define genome-wide haplotypes and candidate regions, using a small ALS family as a prototype. Specifically, we used haploid-cell lines to determine if high-density SNP

arrays accurately predict haplotypes across entire chromosomes and show that haplotype

information significantly enhances the genetic information in small families. Panels of

haploid-cell lines were generated and a 5-cM STRP genome scan was performed.

Experimentally derived haplotypes for entire chromosomes were used to directly identify

regions of the genome identical-by-descent in 5 affected individuals. Comparisons

between experimentally determined and in silico haplotypes predicted from SNP arrays

demonstrate that SNP analysis of diploid DNA accurately predicted chromosomal

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haplotypes. These methods precisely identified 12 candidate intervals, which are shared by all 5 affected individuals. Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders

in small families.

.

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I. Introduction

The identification of genes for Mendelian disorders has been a highly effective approach for understanding disease mechanisms and normal gene function (Antonarakis and Beckmann 2006; Ropers 2007). One of many examples is the identification of dystrophin gene as the cause of Duchenne muscular dystrophy. This initial discovery led investigators to uncover additional disease genes that cause various forms of muscular dystrophy by affecting the structure and function of distinct proteins within the dystrophin-dystroglycan complex (Ervasti 2007). Additionally, single-gene discoveries have also been instrumental in shedding light on multigenic and sporadic disorders. For example, adenomatous polyposis coli (APC) mutations in hereditary colon cancer directly led to the identification of other genes involved in the more common sporadic and polygenic forms of colon cancer (Rustgi 2007). It is currently estimated that genes for approximately 3,705 Mendelian and suspected Mendelian disorders have not yet been mapped (Online Mendelian Inheritance in Man, 2008) and because many familial disorders have not yet been formally described in the literature, the number of unidentified single-gene disorders is likely to be grossly underestimated. Although the identification of the causes of these disorders will almost certainly have broad and significant impact on our understanding of the pathophysiology underlying major disease classes (e.g. neurodegenerative, cancer and heart disease), there has been a trend away from studying single gene disorders, in favor of the more common complex diseases.

This is in part due to the fact that many of the remaining single-gene families are difficult to study because they have rare mutations and/or are not large enough to map the disease locus to a single site in the genome. New tools and approaches are needed to allow 82

researchers to effectively utilize these important families. Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density SNP arrays to define genome wide haplotypes and candidate regions, using a small ALS family.

Clinically, typical ALS is a neurodegenerative disease selectively involving upper

and lower motor neurons that progresses from initial symptoms to death in three to five

years. The etiology of most cases of ALS remains obscure, with proposed mechanisms

including viral, autoimmune, excitotoxic, metabolic/mitochondrial, toxic or apoptotic

processes, protein misfolding or altered axonal transport (Cleveland 1999; Berger et al.

2000; Julien 2001; Pasinelli and Brown 2006). There is, however, no conclusive evidence

that any of these pathways are responsible for even a small fraction of ALS cases.

Although ALS usually occurs sporadically, without family history (sALS), ~10%

of cases are familial (fALS), generally with an autosomal-dominant pattern of inheritance

(Ton et al. 1991; Pasinelli and Brown 2006). While fALS is uncommon, investigation of

families with this disease have provided significant insight into the causes of ALS. The

first example was the discovery that mutations in the Cu/Zn superoxide dismutase

(SOD1) gene cause ALS1 (Rosen et al. 1993), which is thought to account for 20-25% of

fALS and 1-3% of sALS cases (Jackson et al. 1997; Shaw et al. 1998; Battistini et al.

2005; Pasinelli and Brown 2006). A mutation in the vesicle associated membrane protein

(VAMP)-associated protein B (VAPB) gene has been shown to cause a clinically typical

form of ALS (ALS8) (Nishimura et al. 2004; Nishimura et al. 2004), and rare mutations

in the TAR DNA binding protein (TARDBP) have recently been shown to cause both

fALS and sALS (Sreedharan et al. 2008).

83

While these discoveries have been important for increasing our understanding of the causes ALS and for developing and testing various treatment strategies, our understanding of the molecular underpinnings of ALS is still in its infancy and identifying additional mutations with forms of ALS that are clinically similar to sALS is likely to clarify the molecular pathways involved in these diseases. However, large families with dominantly inherited ALS are difficult to study because the lethality of the disease limits the ability to obtain DNA from affected individuals. Furthermore, family members can be reluctant to participate in research studies because they do not want to

consider the possibility that they or their children might be at risk. For these reasons, the

novel ALS family (ALS-A) we have been studying for the past 19 years is of significant

scientific importance (Figure 16). We have collected blood from 14 members of this

family, including 5 affected individuals, and as a first step in positional cloning have used

haploid and high-density SNPs analysis to precisely define all of the regions of the

genome that are shared among affected individuals. Because the disorder in the ALS-A

family is indistinguishable from sALS, the identification of the genetic cause of this

disorder is likely to provide insight into the pathogenic mechanisms of the more common

sporadic disease which may ultimately lead to more effective treatments.

II. Materials & Methods

A. Human Subjects

All subjects participating in this study signed an informed consent form approved

by the Human Subjects Committee at the University of Minnesota. DNA was extracted

from peripheral venous blood using the Gentra Puregene blood kit (Qiagen, Valencia,

CA).

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B. Generation of Haploid Cells Lines

Panels of haploid mouse/human hybrid cell lines were generated at GMP Genetics

for eight ALS-A family members (Figure 16) by electrofusing lymphoblast cells from

each individual with E2 mouse cells, using HAT and geneticin to select against unfused

E2 and lymphoblast cells, respectively (Papadopoulos et al. 1995; Yan et al. 2000).

Eighteen to thirty seven cell lines were selected for each individual. In general, each

hybrid cell line should contain 8-14 random human chromosomes, some of which are in

the haploid state while others are diploid. On average, an entire single set of monosomic

chromosomes is represented in ~23 independent cell lines (Yan et al. 2000; Douglas et al.

2001).

C. 800 Marker Genome Screen

A 777 STRP marker high-density genome screen was performed on both diploid and haploid DNA from members of the ALS-A family by the Center of Medical Genetics,

Marshfield, WI (Figure 16). All markers were taken from Marshfield screening sets 13 and 52 and all of the cell lines generated by GMP Genetics were included in the genome screen.

D. Haplotype Ascertainment

Haplotypes for each individual were directly determined along entire chromosomes by analyzing the genotypes of cell lines haploid for each chromosome, including the 22 autosomes and the X chromosome. The diploid DNA was used as an internal control for each patient and cell lines monosomic for each chromosome were selected for further analysis so that each homologue was represented. For the eight patients in which haploid cell lines were established, phase was determined for each

85

chromosome using the two independently represented homologues. However, rarely both homologues were not present in the monosomic state, in which case haplotypes were defined by comparing genotypes of the available haploid cell line with the diploid DNA.

E. Multipoint LOD Score Analysis

Linkage analysis of the 22 autosomes and the X chromosome were performed using the computer program VITESSE version 2.0 (O'Connell and Weeks 1995). Five age-dependent penetrance classes were established for at-risk unaffected individuals based on the age-at-onset profile for the family (<20 years, 5%; 20-30 years, 10%; 31-60 years, 50%; 61-70 years, 80%; 71+ years, 90%). Affected individuals and unaffected spouses were classified separately. The lifetime risk of developing a phenotypically similar disease, sALS, was estimated to be 1/1000. Allele frequencies and the order of the microsatellite markers used in the genome screen were established by Marshfield

Genetics.

F. 100K SNP Screen and Analysis

The 100K SNP screen and analysis was performed by Dr. Shoji Tsuji and members of his lab. High-density SNP based linkage analysis was conducted using the

GeneChip™ Human Mapping 100K Set (Affymetrix, Santa Clara, CA). SNP genotype data were extracted with the following “cut-off values”: call rate of control samples >

0.95, p value of HWE (Hardy-Weinberg equilibrium test) in control samples > 0.05,

MAF (minor allele frequencies) of control samples > 0, and confidence scores of all family members < 0.1. Control samples were collected from 24 healthy Japanese individuals. SNPs were selected to keep the inter-marker distance at approximately 100 kb. Parametric and non-parametric multipoint linkage analyses were performed using the

86

Allegro version 2.0 program (Gudbjartsson et al. 2005). Penetrance classes were set as

described above, and disease gene frequencies were set at 0.001. In the non-parametric

analysis the following allele sharing model was used: multipoint, linear model, robdom

and power=0.5. Because the size of inheritance vectors of this family exceeded the

limitation, we calculated LOD scores in which two unaffected individuals (III:1 and III:2)

were removed. Haplotype prediction was performed using the ‘haplotype’ option in the

multipoint linkage analysis of the Allegro version 2.0 package.

III. Results

A. The ALS-A Family

A pedigree of the ALS-A family is shown in Figure 16. The disease in this family

is phenotypically indistinguishable from sALS, and characterized by progressive upper

and lower motor neuron degeneration without the involvement of sensory nerves or other

complex neurological features, such as FTD or Parkinson’s features. Age of onset varies,

ranging from 35 to 73 years. Lifespan after initial diagnosis ranged from 6 months to 5

years; the individual who lived for five years had a tracheotomy and mechanical

ventilation for approximately one year. The dominant inheritance pattern and number of

meioses predict that ~3% of the diploid genome is likely to be shared among affected

family members and hence, contain the mutation causing this single-gene disorder.

Conversely, if completely informative, unambiguously defined haplotypes should allow

~97% of the genome which is not shared by the affected individuals to be excluded. A

limitation of traditional linkage analysis, which is illustrated by the results of an 777

STRP marker screen and conventional multipoint analysis on the ALS-A family, is that

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there is a significant disparity between the theoretical portion of the genome that should be excluded from containing the ALS-A locus (>97%), and the portion of the genome actually excluded (67%).

B. Haplotype Analysis: STRP Markers and Haploid DNA

Although haplotype analysis is often used to precisely follow the segregation of small chromosomal regions, recombination and uninformative markers have historically made establishing unequivocal haplotypes for large chromosomal regions impossible. To test if obtaining accurate chromosomal haplotypes can be achieved using high-density

SNP arrays and if this would provide more complete segregation information, we directly compared high-density SNP genotype analysis with experimentally determined haplotypes ascertained using a panel of haploid mouse-human hybrid cell lines generated from ALS-A family members (Papadopoulos et al. 1995).

Experimental haplotypes were established by generating panels of 18-37 haploid cell lines for eight family members including five affecteds. A 777 STRP marker genome scan was performed on DNA from the haploid cell lines, as well as diploid lymphocyte DNA. Genotyping results from chromosome separated cell lines were used to directly define haplotypes for entire chromosomes. Figure 17 illustrates how haplotype comparisons were used to identify shared, excluded and ambiguous regions using chromosome 17 as an example. Because DNA was not available for individuals I:1 or I:2, transmitted haplotypes were arbitrarily assigned to the parental generation by genotyping chromosome separated cell lines from a single affected individual in generation II. Specifically, one of the parental chromosomal haplotypes from generation

I was designated by a RED bar and the haplotype transmitted from the other parent was

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assigned a YELLOW bar. Recombinant haplotypes defined by the haploid cell lines of other members of generation II were used to predict the other two founder haplotypes

(BLUE and GREEN). Haplotypes from spouses who married into the family and do not contain the ALS-A mutation are indicated by grey bars. STRP markers were spaced at

~5cM intervals and double recombinations were expected to be infrequent. Genomic intervals that are found among all five affected individuals are indicated by a shared chromosomal region of the same color (RED or YELLOW). Because any of the regions of the genome that are shared (i.e. identical by descent) among the affected individuals could contain the mutation, all shared regions are considered candidates. Areas not shared among all five affected individuals are excluded, while regions are considered ambiguous if the probability of the double recombination was greater than 1/100 (the threshold for exclusion by LOD score analysis) (Figure 17). Diploid genotypes from 777 STRP markers were also analyzed using the parametric multipoint linkage program VITESSE

(O'Connell and Weeks 1995).

C. Comparison of STRP Haplotype and LOD Score Analyses

Figure 18 shows a comparison of the effectiveness of multipoint linkage using

STRP markers and haploid mapping to define shared or excluded regions for

chromosome 1 and across the entire genome. Specifically, three positive LOD scores were generated for chromosome 1, which correspond to a shared region (LOD=0.785)

and two regions known to be excluded by haplotype analysis (LOD=0.557 & 0.76)

(Figure 18). This comparison illustrates the problems investigators face when using

small families for linkage analysis —shared and excluded regions are not accurately

defined and candidate regions are not always easily distinguished. Genome-wide,

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haploid mapping identified 10 regions (7.4% of the genome) identical by descent or shared among the 5 affected individuals and definitively excluded 83.1% of the genome as unshared. In contrast, traditional multipoint LOD score analysis using STRP markers on diploid DNA excluded only 67.1% (LOD<-2), failed to identify any shared regions

(LOD>3), and generated suggestive scores (most between 0.5-1.2) for regions that were both shared and definitively excluded by haploid analysis. In addition to the shared regions, haploid mapping identified 24 ambiguous regions (indicated in grey), which most likely result from an uninformative marker. The use of haploid cell lines increased the amount of the genome that could be excluded (83%) in comparison to the traditional multipoint linkage analysis (67%) and more closely approximated defining the theoretical portion of the genome that should be shared or identical by descent among the affected individuals (7.4% by haploid analysis vs. 3.0% theoretical).

D. SNP Markers

As a second and parallel approach to maximize the genetic information from this small ALS family, we investigated the utility of high density SNP arrays to predict shared haplotypes. While SNP arrays have typically been used to examine heterogeneous DNA samples in association studies, we sought to determine whether this technology would be successful in large scale haplotype reconstruction in a small family with ethnically similar individuals. By comparing the haplotypes that were experimentally derived using haploid cells lines, we were able to test the accuracy of in silico SNP haplotypes predicted by Allegro (Gudbjartsson et al. 2005). Additionally, the SNP haplotypes were subsequently used to validate the power of nonparametric linkage analysis (NPL) of the

SNP data to identify shared regions in small kindreds.

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1. Haplotype Analysis Using SNP Genotypes

a. Comparison of Experimental and In Silico Defined

Recombinations

Diploid DNA samples from fourteen members of the ALS-A family were analyzed using the GeneChip™ Human Mapping 100K Set (Affymetrix) and the resultant data were analyzed using the linkage program Allegro (Gudbjartsson et al.

2005). Specifically, haplotypes were determined in silico and were compared with the experimentally defined haplotypes from the haploid cell lines. Evaluation and comparison of recombination points revealed that the SNP arrays were able to precisely and accurately reconstruct haplotypes over large chromosomal regions. Figure 19 shows the comparison of the experimentally and predicted recombinations over the entire length of chromosome 22. While the recombination points are essentially the same, arrows point to deviations between the haploid and SNP methods. Arrows (1) and (5) specify sites where STRP markers were not informative but SNPs accurately defined the haplotype and excluded the regions. Arrows (2) and (4) show regions where a block of

SNPs were not informative and the haplotypes could not be unambiguously defined.

Arrow (3) represents a region where a double recombination over a small area occurred and was not detected by the STRPs due to marker spacing.

b. Comparison of Experimental and In Silico Haplotypes:

Defining Shared Regions

Haplotypes determined from the SNP analysis were examined and regions shared between all five affected individuals were then defined across the entire genome. The

SNP method identified a total of 10 shared regions (red), eight of which were detected

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using the haploid mapping approach and an additional 2 regions that were not previously identified (Figure 20, Table 9). The haploid method was unable to detect the shared region on chromosome 15 because this small interval is located between two STRP markers and on chromosome 16 because two corresponding STRP markers were not informative. Conversely, the SNP method did not detect the shared region on chromosome 13 or the telomeric shared region on chromosome 16 that were identified by the haploid STRP method. A significant advantage of the SNP approach was that each of the shared regions identified were significantly refined and the maximal regions were much smaller than those defined by the haploid STRP approach. Furthermore, the SNP method eliminated nearly all of the ambiguous regions detected by the STRP markers and only detected an additional four new ambiguous regions; the high density of SNP markers significantly cleaned up the data and removed nearly all ambiguity. Nearing the theoretical value of 3%, these methods show that approximately 4.7% (142 Mb) of the genome is shared among the five affected individuals. Table 9 lists the shared regions identified by the two methods and the ambiguous regions detected by the SNPs, along with the markers and physical positions of the boundaries for each region.

2. Parametric and Non-parametric Linkage Analysis

In addition to examining the utility and accuracy of predicted SNP haplotypes, we also investigated the power of nonparametric or model free linkage analysis to detect shared chromosomal regions. The non-parametric linkage analyses (NPL and allele sharing LOD scores), which perform statistical analysis of an increase in the number of alleles shared among the affected individuals with respect to identity by descent (IBD), weigh the genotypes of affected individuals rather than those of unaffected individuals;

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therefore all shared regions have equally high allele sharing LOD and NPL scores and can be easily identified. Using the linkage program Allegro (Gudbjartsson et al. 2005) we generated both NPL and allele sharing LODs for all of the autosomal chromosomes, which are depicted in Figure 21. This method clearly distinguished all ten regions identified by the SNP haplotypes, confirming the power of model free analysis in the identification of candidate regions within small families. Parametric analysis was also performed; because the genotypes from unaffected, but at-risk individuals were factored into the calculations not all of the shared candidate regions were clearly identifiable

(Figure 22).

E. Prioritization of the Shared Regions

As a final step, additional pedigree analysis was done to prioritize the candidate gene regions to those shared among affected individuals but absent from older unaffected family members. Although the range in disease onset is broad in the ALS-A family (35-

73 years), two unaffected elderly individuals, II:3 and II:9, had no evidence of the disease; neither had signs or symptoms of ALS when examined (ages 68 and 82, respectively). Additionally, individual II:3 had no signs of ALS when interviewed at age

76, and prior to dying from Alzheimer’s disease at age 90y, individual II:9 did not demonstrate ALS symptoms according to relatives or medical records. There was no evidence of frontotemporal dementia in the family, including II:9, who had onset of dementia in the late 80s, no unusual behavior while dementing, and responded to anticholinesterase medication. Although neither II:3 and II:9 showed signs of ALS, the possibility that they carry/carried the disease gene can not be excluded. However, the age of these individuals make the risk that they carry the ALS-A gene quite low, and hence

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make the regions of the genome that they do not share with the affected individuals more

likely to contain the gene. Similarly, regions shared by all five affected individuals and

II:3 or II:9 have a lower probability of containing the ALS-A gene. Using this approach

we have prioritized the candidate regions into three categories (RI-1-3), with RI-1 being

the most likely (Table 10). Three of these regions/subregions, which span ~23 Mb, are

higher priority regions for future studies because they are not shared in older unaffected

members of the ALS-A family: the 6p25.3-23 region, ~50% of the 4p15.2-p14 region

and ~7% of the 4q32.2-34.3 (Table 10). The remaining unaffected individuals within the

ALS-A family were not useful in the prioritization because they are still within the

disease onset range.

IV. Discussion

In linkage studies of large families with Mendelian disorders LOD score analysis

is an effective method to define the disease locus i.e. the single region of the genome that

is shared among affected individuals. However, in small families with limited numbers

of meioses, traditional LOD score analysis using STRP markers is less informative, often

showing suggestive LOD scores for regions of the genome that should be excluded and

missing other regions that may contain the gene. We have explored methods to maximize

the amount of genetic information that can be derived from a small family with an

autosomal dominant form of ALS and show that analysis of high density SNP haplotypes

are able to precisely define nearly all regions of the genome that are shared among the

affected individuals. Specifically, we used haploid cell lines to experimentally

demonstrate that high density SNP arrays can be used to accurately define chromosomal

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haplotypes, precisely identify shared candidate regions among affecteds and exclude the remaining regions of genome that are not shared. Additionally, we show that SNP genotypes can be accurately analyzed by nonparametric linkage programs and validate the power of model free analysis to detect shared regions in small families.

Over the past 20 years, genetic investigations using families with monogenic disorders have provided unparalleled information into gene function, normal and pathogenic pathways and disease mechanisms (Antonarakis and Beckmann 2006).

Because most of the remaining single-gene families have rare mutations and/or few affected members, new strategies are needed to effectively use this valuable resource for genetic studies. Shifting our expectations from the idea that mapping single-gene disorders necessarily requires sufficient meioses to localize the gene to a single site in the genome, to the idea that small families can also be included in genetic studies if as a first step all shared regions of the genome can be accurately defined. Because novel disease genes in small families are likely to hold key lessons for understanding the molecular pathophysiology of devastating disorders, it is imperative that these families are investigated and that candidate loci are reported—informed collaborative efforts will lead to the eventual identification of these genes.

Towards this effort, we have mapped a rare familial form of ALS that is clinically similar to sALS. Candidate regions for the ALS-A gene span 142 Mb of DNA located in twelve intervals. Three of these regions/subregions, which span ~23 Mb, are higher priority regions for future studies because they are not shared in older unaffected members of the ALS-A family. While the following paragraphs describe the next steps in identifying the ALS-A gene, similar strategies would be generally applicable to

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mapping efforts of any single gene disorder in any similarly small family. First, newly identified candidate regions can be refined and prioritized, additional families with similar diseases can be screened for linkage to separate candidate loci and genes of interest can be sequenced.

Comparisons of known ALS loci with our newly defined candidate region show several regions of overlap or possible overlap. For example, an ambiguous region defined by the haploid cell lines at 1p36.21 contains the recently identified TARDBP gene.

Mutations in this gene cause a phenocopy of sALS (Sreedharan et al. 2008), however, this gene has been ruled out by the SNP haplotype analysis and sequencing of an affected member of the ALS-A family. Additionally, two of the 12 candidate regions potentially overlap known ALS loci, ALS-FTD on 9p21.3-13.2 (Morita et al. 2006; Vance et al.

2006; Yan 2006) and ALS6 on 16q12 (Abalkhail et al. 2003; Ruddy et al. 2003; Sapp et al. 2003).

The disease spectrum for both ALS and FTD are still evolving, and families linked to the ALS-FTD locus on chromosome 9 have members that present with pure

ALS, pure FTD or both (Morita et al. 2006; Vance et al. 2006; Yan 2006). Therefore, while members of the ALS-A family have not displayed symptoms of FTD, this shared region remains a viable candidate. However, because this region is shared by one of the two unaffected individuals in generation II (Table 10), the likelihood that this region

contains the mutation is low.

ALS6, which maps to chromosome 16, is clinically indistinguishable from sALS and hence clinically similar to the ALS-A disorder. The shared region we detected on chromosome 16 (located between rs10492807 (31.7 Mb) and rs7500906 (48.4 Mb))

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overlaps or partially overlaps critical regions defined by two previously reported ALS6 families (Table 9) (Abalkhail et al. 2003; Sapp et al. 2003). However, this shared region does not overlap with the critical region defined by Ruddy et al. (2003) (~49.7-54.2 Mb).

While combining the critical regions of all three ALS6 families would rule out this locus for the ALS-A family, combining mapping information for this genetically heterogeneous disorder should be done with caution and this locus should not necessarily be disregarded.

Additional information that further lowers the likelihood that the ALS-A mutation is located in this region, is that almost the entire region is shared by both of the unaffected individuals in the second generation (II:3 and II:9) (Table 10).

To further refine the ALS-A locus we propose additional independent linkage studies using other small ALS families with clinically similar forms of ALS. While many of these additional families will be even smaller than the ALS-A family, our mapping study will enable other groups to determine if ALS families they have collected share any of the candidate ALS-A regions we describe here. Multiple families with linkage to one of these regions would provide additional support for prioritizing specific regions for detailed gene cloning efforts. Additionally, haplotype conservation could indicate the presence of an ancestral mutation and potentially pinpoint regions of special interest for sequencing.

As a complementary approach, we have begun examining candidate genes within shared regions, initially focusing on genes encoding proteins expressed within the CNS or that act in pathways implicated in ALS. For example, we sequenced superoxide dismutase 3 (SOD3) located within the 4p15.2-p14 region, due to the similarity with

SOD1, although no mutations were detected in the exons, exon/intron boundaries or

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upstream sequence. While careful examination of known genes will not be as complicated in small gene poor areas (chr.4p), this process will be more difficult in large gene rich regions, such as the shared interval on chromosome 6p. Therefore, in addition to targeted gene sequencing, brute force sequencing of entire shared regions may be appropriate.

In summary, we have demonstrated through experimentally derived haplotypes using haploid DNA that dense genomic SNP arrays can accurately define chromosomal haplotypes in small families. Additionally, we experimentally validate the power and effectiveness of model free linkage analysis of SNP genotypes in the detection of the shared candidate regions. Application of this rapidly improving technology will enable genetic investigations of a whole class of families with Mendelian disorders that have typically been ignored by the scientific community due to their size. By changing the mapping paradigm from the idea that families with Mendelian disorders need to be large enough to map the gene to a single site in the genome, to include the concept that small families can be useful if all regions that could contain the gene are identified, we can begin to use a valuable and virtually untapped resource. Improving the power of mapping single-gene disorders will uncover new disease pathways and mechanisms and clarify the pathogenesis of devastating disorders like ALS.

Acknowledgements: We thank Jeff O’Connell, Jamie Margolis, Karen Armbrust and

Andrew Kale for their help with this study. Additionally, we gratefully acknowledge grants from the ALS Association (JWD), the NHLBI Mammalian Genotyping Service

(Contract Number NO1-HV-48141) (LPWR) and the Academic Health Center at the

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University of Minnesota (LPWR).

Copyright Notice:

This chapter is currently submitted in its entirety for publication:

Katherine A. Dick Krueger, Shoji Tsuji, Yoko Fukuda, Yuji Takahashi, Jun Goto, Joline

C. Dalton, Michael B. Miller, John W. Day, Laura P.W. Ranum. Mapping

Mendelian disorders in small families: validation of SNP haplotype mapping.

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Figure 16. ALS-A pedigree. Affected individuals are indicated with solid symbols and symbols with a line show the individual is deceased. The asterisk indicates individuals from whom DNA was collected and the H denotes individuals from whom haploid cell lines were generated. For confidentiality purposes gender is not indicated.

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Figure 17. Examples of the haplotype analysis. Haplotypes from the founder generation (I) were reconstructed using haplotypes defined by haploid analysis of generation II (colored either red or blue and yellow or green). In subsequent generations the chromosomal regions inherited from unrelated members were identified and eliminated from the analysis (variations of grey). Regions that are shared among the affecteds, excluded, or ambiguous were then directly determined. Where a marker was not fully informative, the founder haplotype was not designated and the region was subsequently denoted by a question mark. Data presented is from chromosome 17.

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Figure 18. Haploid and multipoint analysis comparison. Comparison of information obtained from haploid mapping (A) and multipoint linkage analysis of diploid DNA (B) for chromosome 1. Comparison of the information obtained from haploid mapping (C) and multipoint linkage analysis (D) for the entire genome. Regions excluded by haploid mapping or multipoint linkage analysis (LOD < -2.0) are white and ambiguous regions are grey (LOD scores between -2 and +3). Shared regions defined as identical by descent through haploid mapping or with a LOD score > 3.0 are shown in red.

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Figure 19. Comparison of recombination points identified by haploid mapping and SNPs. Recombinations are depicted for the four founder chromosomes for chromosome 22. The four founder haplotypes are shown in blue, red, green and yellow and the unaffected chromosomes are shown in grey. Arrows point to deviations between the haploid and SNP methods. Regions that are designated by a hatched mixture of two colors result from markers that were not fully informative. The (1) and (5) arrows specify regions where the STRPs were not informative but the SNPs were able to accurately determine the correct haplotype. The (2) and (4) arrows show regions where a block of SNPs were not informative and the haplotypes could not be accurately designated. The (3) arrow represents a region where a double recombination over a small area occurred and was not detected by the STRPs due to marker spacing. 104

Figure 20. Physical location of the shared regions. The regions that are shared between the five affected individuals are depicted in red. All regions that were identified as ambiguous by the SNP method are shown in grey, along with the any corresponding ambiguous regions identified by the STRP markers. The physical locations of the regions’ boundaries were determined by UCSC Genome Browser and approximate positions are shown by each region in Mb. The * indicates the chromosome 13 STRP marker gata73A05, which defines the haploid shared region, is at 62.5 Mb and is not shared by the SNPs at this location. The ‡ symbol denotes an inconsistency between the two methods for the shared region on chromosome 15. While the SNP method identified a shared region, the haploid method identified an ambiguous region with a probability of 1/1000 and was therefore ruled out.

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Figure 21. Non-parametric LOD score analysis of the SNP genotypes. The SNP genotype data were analyzed by Allegro and non-parametric LOD scores were generated for each autosomal chromosome. The NPL scores are shown by a black line and the red line represents the allele-sharing LOD. Chromosomal location is shown along the X-axis.

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Figure 22. Parametric LOD score analysis of the SNP genotypes. The SNP genotype data were analyzed by Allegro and parametric LOD scores were generated for each autosomal chromosome. Chromosomal location is shown along the X-axis.

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Beginning Ending Method Chromosomal Physical Physical Boundary Boundary Identified Region Location Location Marker Marker Haploid 1q24.1-25.3 ATA38A05 164,115,369 AAT200 179,292,171 SNP 1q24.2-25.2 rs952963 165,669,836 rs10489882 176,171,118 Haploid 2p25.1-22.1 GAAT1A5 9,858,029 GATA194B06 41,077,763 SNP 2p25.1-23.3 rs1405948 10,500,611 rs1822300 24,578,289 Haploid 3p26.2-25.3 GATA131D09 4,288,250 ATCT053 10,338,466 SNP 3p26.1-25.3 rs2196302 5,780,096 rs3868891 9,674,059 Haploid 4p15.31-14 GATA70E01 20,722,813 ATCT018 39,814,243 SNP 4p15.2-p14 rs4697055 23,876,434 rs7695130 35,959,708 Haploid 4q32.1-35.1 GATA8A05 158,556,255 AATA045 183,213,532 SNP 4q32.2-34.3 rs6811083 162,010,831 rs4234867 178,742,190 Shared Haploid 6p25.3-p22.3 NA 1 GATA29A01 20,020,074 SNP 6p25.3-23 NA 1 rs2327869 15,096,746 Haploid 9p24.1-q21.13 GATA175H06 7,918,932 AGAT140 78,454,471 SNP 9p23-21.1 rs10491744 12,710,106 rs621277 32,506,864 Haploid 13q21.1-22.1 GATA11C08P 54,003,967 GATA64F08 72,772,650 SNP 15q12 rs1553890 23,688,680 rs4073083 24,737,820 SNP 16p11.2-q12.1 rs10492807 31,687,619 rs7500906 48,354,332 Haploid 16q24.1-24.3 GATA11C06 84,943,535 NA 88,827,254 Haploid 17q21.32-24.3 ATC6A06N 44,028,054 GATA31B11 66,012,504 SNP 17q22-24.1 rs716392 50,944,412 rs10514869 60,531,720

Haploid 1p36.22-p36.13 AAT238 10,910,244 TTTA063 16,412,894 SNP 1p36.21 rs848578 12,760,221 rs10492987 15,865,925 SNP 10p13 rs963336 12,964,446 rs552437 13,087,512

guous SNP 13q21.1 rs7335975 53,714,107 rs9316943 57,196,412 SNP 15q25.2-25.3 rs10520582 82,143,780 rs10520601 84,159,205

Ambi SNP 15q25.3 rs2120650 84,419,700 rs4887244 85,147,853 Haploid 16p12.1-q12.1 CATA002Z 23,656,985 GATA143D05 49,152,042 Table 9. Data for the haploid and SNP shared regions and the SNP ambiguous regions. Physical locations were determined using the UCSC Genome Browser (www.genome.ucsc.edu) and the NCBI SNP database (http://www.ncbi.nlm.nih.gov/sites/entrez?db=snp) was used to convert the SNP ID into the RS nomenclature recognized by the UCSC Browser.

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Region of Maximum Unaffected Unaffected Region Interest Rank Size (Mb) Individual Individual RI-1 6p25.3-23 15.1 Mb

RI-1/2 4p15.2-p14 12.1 Mb P (49.2%) P (6.3%) RI-1/2 4q32.2-34.3 16.7 Mb P (92.4%)

RI-2 2p25.1-23.3 14.1 Mb X RI-2 3p26.1-25.3 3.9 Mb X RI-2 13q21.1-22.1 18.8 Mb X Shared RI-2 15q12 1.0 Mb X RI-2 16q24.1-24.3 3.9 Mb X RI-2 17q22-24.1 9.6 Mb X

RI-2/3 9p23-21.1 19.8 Mb A (12.4%) X RI-2/3 16p11.2-q12.1 16.7 Mb X P (94.2%)

RI-3 1q24.2-25.2 10.5 Mb X X

RI-3 1p36.21 3.1 Mb X X RI-3 10p13 0.1 Mb X X RI-3 13q21.1 3.5 Mb X X RI-3 15q25.2-25.3 2.0 Mb X X Ambiguous Ambiguous RI-3 15q25.3 0.7 Mb X X

Table 10. Genetic status of unaffected individuals II:3 & II:9 for the seventeen shared and ambiguous regions. The letter “X” specifies the region is also shared by the unaffected individual, the letter “P” indicates the region is partially shared and the letter “A” designates the region is ambiguous. The maximum physical size is shown for each region. The shared regions of interest are classified into three categories based on the genomic content of the two unaffected individuals (II:3 and II:9). The RI-1 category contains regions that are the most likely to containthe ALS-A gene while the RI-3 category includes regions that are the least likely to hold the gene. 110

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