 \227\206 16. Aylward EH, Codori AM, Barta PE, et al. Basal ganglia volume and prox- imity to onset i n presymptomatic Huntington disease. Arch Neurol 1996; 53 : 1293 \200\2236 . FDG PET can demonstrate striatal hypometabolism in suspected atypical PD variants, so discr iminating them from PD. \227\206 17. Aylward EH, Codori AM, Rosenblatt A, et al. Rate of caudate atrophy in presymptomatic a nd symptomatic stages of Huntington \200\231s disease. Mov Disord 2000; 15 : 552 \200\2236 0 . PET and SPECT can detect subclinical dopamine terminal dys- function in subjects at risk fo r PD if present and detect reduced striatal D2 binding in pre-manifest HD gene carriers. Th is could help identify cases for neuroprotective approaches if a successful therapy is ide ntifi ed. \227\206 18. Brooks DJ . Imaging approaches to Parkinson disease. J Nucl Med 2010; 51 : 596 \200\22360 9 . 19. Morrish PK, Rakshi JS, Sawle GV, Brooks DJ . Measuring the rate of pro- gression and es timating the preclinical period of Parkinson \200\231s disease with [ 18 F]dopa PET. J Neur ol Neurosurg Psychiatry 1998; 64 : 314 \200\2231 9 . CHAPTER 6 Movement Disorders: Structural and Functional Imaging 51 40 . Parkinson Study Group. Mixed lineage kinase inhibitor CEP-134 7 fails to delay disabil ity in early Parkinson disease. Neurology 2007; 69 : 1480 \200\2239 0 . 41. Freed CR, Green e PE, Breeze RE, et al . Transplantation of embryonic dopamine neurons for severe Parkinson \200\231s disease. N Engl J Med 2001; 344 : 710 \200\2231 9 . 20. Vingerhoets FJG, Schulzer M, Calne DB, Snow BJ. Which clinical sign of Parkinson \200 \231s disease best refl ects the nigrostriatal lesion? Ann Neurol 1997; 41 : 58 \200\2236 4 . 21. Benamer TS, Patterson J, Grosset DG, et al. Accurate diff erentiation of parkinsonism a nd essential tremor using visual assessment of [123I]- FP-CI T imaging: the [123I]-FP-CI T Study Group. 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Bohnen NI, Kaufer DI, Hendrickson R, et al . Cognitive correlates of cor- tical choline rgic denervation in Parkinson \200\231s disease and parkinsonian dementia. J Neurol 2006; 2 53 : 242 \200\2237 . 28. Laruelle M. Imaging synaptic neurotransmission with in vivo binding competition techniq ues: a critical review. J Cereb Blood Flow Metab 2000; 20 : 423 \200\2235 1 . 50. Eidelberg D . Metabolic brain networks in neurodegenerative disorders: a 29. Pavese N, Evans AH, Tai YF, et al. Clinical correlates of levodopa-induce d dopamine re lease in Parkinson disease: a PET study. Neurology 2006; 67 : 1612 \200\2231 7 . functional imaging approach. Trends Neurosci 2009; 32 : 548 \200\2235 7 . 51. Kuhl DE, Metter EJ, Benson DF . Similarities of cerebral glucose metabo- lism in Alzhei mer \200\231s and Parkinsonian dementia. J Cereb Blood Flow Metab 1985; 5 : S169 \200\2237 0 . 30. Evans AH, Pavese N, Lawrence AD, et al. Compulsive drug use linked to sensitized ventra l striatal dopamine transmission. Ann Neurol 2006; 59 : 852 \200\2238 . 52. Vander-Borght T, Minoshima S, Giordani B, et al . Cerebral metabolic diff erences in Pa rkinson \200\231s and Alzheimer \200\231s disease matched for dementia severity. J Nucl Med 1997; 38 : 797 \200\22380 2 . 31. Steeves TD, Miyasaki J, Zurowski M, et al. Increased striatal dopamine release in Parki nsonian patients with pathological gambling: a [ 11 C] raclopride PET study. Brain 2009; 13 2 : 1376 \200\2238 5 . 53. Edison P, Rowe CC, Rinne JO, et al . Amyloid load in Parkinson \200\231s dis- ease deme ntia and Lewy body dementia measured with [ 11 C]PIB posi- tron emission tomography. J Neur ol Neurosurg Psychiatry 2008; 79 : 1331 \200\2238. 32. Ponsen MM, Stoff ers D, Booij J, et al. Idiopathic hyposmia as a preclini- cal sign of Parkinson \200\231s disease. Ann Neurol 2004; 56 : 173 \200\2238 1 . 33. Eisensehr I, Linke R, Noachtar S, et al. Reduced striatal dopamine trans- porters in id iopathic rapid eye movement sleep behavior disorder \200\224 comparison with Parkinson \200 \231s disease and controls. Brain 2000; 123 : 1155 \200\2236 0 . 54. Nagayama H, Hamamoto M, Ueda M, Nagashima J, Katayama Y . Reliability of MIBG myocardia l scintigraphy in the diagnosis of Parkinson \200\231s disease. J Neurol Neurosurg Psychiat ry 2005; 76 : 249 \200\2235 1 . 55. Antonini A, Kazumata K, Feigin A, et al . Diff erential diagnosis of par- kinsonism with [ 18 F]fl uorodeoxyglucose and PET. Mov Disord 1998; 13 : 268 \200\2237 4 . 34. de la Fuente-Fernandez R, Lu JQ, Sossi V, et al. Biochemical variations in the synaptic level of dopamine precede motor fl uctuations in Parkinson \200\231s disease: PET evidence of increased dopamine turnover. Ann Neurol 2001; 49: 298 \200\22330 3 . 56. Spetsieris PG, Ma Y, Dhawan V, Eidelberg D . Diff erential diagnosis of parkinsonian sy ndromes using PCA-base d functional imaging features. NeuroImage 2009; 45 : 1241 \200\2235 2 . 35. Troiano AR, de la Fuente-Fernandez R, Sossi V, et al. PET demonstrates reduced dopamine transporter expression in PD with dyskinesias. Neurology 2009; 72 : 1211 \200\2231 6 . 57. Schwarz J, Tatsch K, Gasser T, et al. 123I-IBZ M binding compared with long-ter m clini cal follow up in patients with de novo parkinsonism. Mov Disord 1998; 13 : 16 \200\2231 9 . 36. Ramlackhansingh AF, Bose SK, Ahmed I, et al. Adenosine A2A recep- tor availability in P arkinson \200\231s disease patients with and without levodopa induced dyskinesias studied w ith C-1 1 SCH442416 PET. Neurology 2010; 74 : A588 58. Druschky A, Hilz MJ, Platsch G, et al . Diff erentiation of Parkinson \200\231s disease and multiple system atrophy in early disease stages by means of I-123-MIBG-SPEC T. J Neuro l Sci 2000; 175 : 3 \200\2231 2 . 37. Ahmed I, Bose SK, Pavese N, et al. Glutamate NMDA receptor dys- regulation in Parkinson \200\231s disease with dyskinesias. Brain 2011; 134 : 979 \200\2238 6 . 59. Eckert T, Barnes A, Dhawan V, et al . FDG PET in the diff erential diagno- sis of parkinsonian disorders. NeuroImage 2005; 26 : 912 \200\2232 1 . 60. Burn DJ, Sawle GV, Brooks DJ . Th e diff erential diagnosis of Parkinson \200\231s dise ase, multiple system atrophy, and Steele \200\223Richardson \200\223Olszewsk i syndrome: di scriminant analysis of striatal 18 F-dop a PET data. J Neurol Neurosurg Psychiatry 1994; 57 : 278 \200\2238 4 . 38. Whone AL, Watts RL, Stoessl J, et al . Slower progression of PD with ropinirole versus l -dop a: the REAL-PE T study. Ann Neurol 2003; 54 : 93 \200\22310 1 . 39 . Parkinson Study Group. Dopamine transporter brain imaging to assess the eff ects of pr amipexole vs levodopa on Parkinson disease progression. JAMA 2002; 287 : 1653 \200\2236 1 . 61. Kuwert T, Lange HW, Langen KJ, et al . Cortical and subcortical glucose consumption mea sured by PET in patients with Huntington \200\231s disease. Brain 1990; 113 : 1405 \200\223 2 3 . Oxford Textbook of Movement Disorders 52 69. Naumann M, Pirker W, Reiners K, et al . Imaging the pre- and postsynap- tic side of str iatal dopaminergic synapses in idiopathic cervical dystonia: a SPECT study using [ 123 I]ep idepride and [ 123 I] -CIT. Mov Disord 1998; 13 : 319 \200\2232 3 . 62. Dubinsky RM, Hallett M, Levey R, Di Chiro G . Regional brain glucose metabolism in neuroacanthocytosis. Neurology 1989; 39 : 1253 \200\2235 . 63. Hosokawa S, Ichiya Y, Kuwabara Y, et al . Positron emission tomography in cases of chor ea with diff erent underlying diseases. J Neurol Neurosurg Psychiatry 1987; 50: 1284 \200 \2237 . 70. Perlmutter JS, Stambuk MK, Markham J, et al . Decreased [F-1 8] spiper- one binding in putamen in idiopathic focal dystonia. J Neurosci 1997; 17 : 843 \200\2235 0 . 64. Turjanski N, Weeks R, Dolan R, et al . Striatal D 1 and D 2 receptor binding in patient s with Huntington \200\231s disease and other choreas: a PET study. Brain 1995; 118 : 689 \200\2239 6 . 71. Garibotto V, Romito LM, Elia AE, et al. In vivo evidence for GABAA receptor changes in the sensorimotor system in primary dystonia. Mov Disord 2011; 26 : 852 \200\2237 . 65. Antonini A, Leenders KL, Eidelberg D . [C-1 1]Raclopride-PE T studies of the Huntington \200\231s disease rate of progression: relevance of the trinucle- otide repeat length. Ann Neurol 1998; 43 : 253 \200\2235 . 72. Snow BJ, Nygaard TG, Takahashi H, Calne DB . Positron emission tom- ography studies of dopa-responsiv e dystonia and early-onse t idiopathic parkinsonism. Ann Neurol 1993; 34: 73 3 \200\2238 . 66. Andersson U, Eckernas SA, Hartvig P, et al . Striatal binding of 11C-NMS P studied with positron emission tomography in patients with persistent tardive dyskinesia: no evidence f or altered dopamine receptor binding. J Neural Transm 1990; 79: 215 \200\2232 6 . 73. Turjanski N, Bhatia K, Burn DJ, et al . Comparison of striatal 18 F-dop a uptake in adu lt-onse t dystonia-parkinsonis m, Parkinson \200\231s disease, and dopa-responsiv e dystoni a. Neurology 1993; 43 : 1563 \200\2238 . 67. Andrews TC, Weeks RA, Turjanski N, et al . Huntington \200\231s disease pro- gression: PET and clinical observations. Brain 1999; 122: 2353 \200\2236 3 . 68. Tai YF, Pavese N, Ge rhard A, et al. Microglial activation in presympto- matic Huntington \200\231s disease gene carriers. Brain 2007; 130 : 1759 \200\2236 6 . CHAPTER 7 Genetic Techniques, Impact and Diagnostic Issues in Movement Disorders Jos Br s and John Hardy Advances in the diagnosis of movement disorders Th e last decade has seen remarkable progre ss in molecular genet- ics, which has allowed us to gain greater insight into the molecular events underlying inherited neurological diseases. For those dis- eases where a clear Mend elian pattern of inheritance is present, a majority of the common genes harboring pathogeni c mutations has been identifi ed, allowing, in some cases, the correct reclassifi ca- tion of heterogeneous clinical syndromes, in addition to enabling novel diagnostic possibilities . It is expected that ultimately these fi ndings will form the basis of new therapeutic and preventive approaches. are heterozygous deletions of complete exons, which are undetect- able by routine sequencin g (8). Notwithstanding the fact that only a small percentage of move- ment disorders can be eff ec tively treated, molecular diagnosis remains a very important tool because it provides valua ble infor- mation for the aff ected individual, allowing them to make informed life choices , including family planning. Genetic knowledge of the etiology of neurological diseases has been expanded based on recen t advances in genomic technologies. Th ese have allowed us to look at genetic variability l inked to disease from a completely diff erent perspective than was possible fi ve to ten ye ars ago. Th ese advances have allowed us to move from studying one individual exon at a tim e, to being able to interrogate the entire genome of an individual in a single experiment. Th is clearly has the potential to impact on the diagnosis of these diseases and, in a way, revolutionize molecular diagnosis. A major part of this revolution in the genetics of neurological disorders, and movement dis orders in particular, comes from the understanding that, in many cases, a single gene, cont aining a single mutation and acting in a purely dominant or recessive mode, does not explai n the genetic component of that particular disease. In these cases, common genetic variabil ity may act as a risk for the development of the disease, but is not the single underlying cause. In this chapter we will discuss the applicability of these new tech- nologies to diagnosis, consider their limitations and pitfalls, and look at the next wave of genomic technologies that are likely to turn the promise of personalized medicine into a reality. Sanger sequencing: the cornerstone of diagnostic tests Th e gold standard for genetic diagn osis is Sanger sequencing. Here, one is able to interrogate small fragments of DNA \200\224 typically <800 base pairs (bp) \200\224for sequence changes. Th is method is based on a met hodological approach taken by Fred Sanger and Alan Coulson in the late 1970s (9, 10), but g reatly improved in speed and ease of use by the employment of automated DNA sequencing inst ru- ments. Th e principle of capillary sequencing is based on the incor- poration of the fo ur nucleotides, each carrying its own specifi c dye, enabling identifi cation of the base p resent at any given position of the DNA sequence being analyzed. Following PCR amplifi cati on of the locus of interest from genomic DNA using appropriate prim- ers, the automated seq uencing machine performs the sequence Huntington \200\231s disease is the classic example of a purely genetic movement disorder ( 1). Here, the presence of an expanded ver- sion of the huntingtin gene invariably means the development of the disease, while its absence precludes it, simultaneously helping our und erstanding of the pathobiology of the disease and implying that routine molecular diagnosti c tests can be provided by simple assays, usually based on the polymerase chain reaction (P CR). At the opposite end of the spectrum are diseases such as Parkinson \200\231s disease, where clear Mendelian inheritance represents a minority of cases, and several genes are kno wn to contain pathogenic mutations (2 \200\2237). Depending on the size of these genes, thi s may render molec- ular diagnosis too costly or time-consuming; in addition, if some of th ese mutations are not simple sequence changes, and therefore sequencing the genes fails to detect them. Again, Parkinson \200\231s dis- ease provides such an example: some mutations in the PRKN gene Oxford Textbook of Movement Disorders 54 detection. Although not without its fl aws, capillary sequencing is a robust method with a low error rate, and was the method chosen for the Human Genome Project (11). copy number changes, this severely limits the accuracy of Sanger sequencing as a diagnostic tool for that particular disease. A third limitation relates to sequencing more complex genomic regions. Two examples are the GBA and CR1 genes. Th e former is known to harbor mutations which, when homozygous, cause Gaucher \200\231s disease and, when heterozygous, confer risk for Parkinson \200\231s disea se (12), while the latter was one of the hits from a genome-wide association study in Alzhe imer \200\231s disease (13). GBA , which is located on chromosome 1, is very close to a pse udo-gene, with which it shares approximately 96% homology (14, 15). Furthermore, a large nu mber of known pathogenic mutations in GBA are present in the normal sequence of the pseudo- gene (16). In such a gene, exon sequencing is very complicated because of the similarity be tween sequences. Unless the primers are able to distin- guish completely between the two re gions, it is diffi cult to be abso- lutely certain which fragment is being sequenced. Th e second gene, CR1 , is even more complex; it contains repetitions of entire exons that can h arbor diff erent mutations in the same individual. Repeat detection, such as those in the HTT gene that causes Huntington \200\231s disease, e mploys the same principles, although siz- ing of the DNA fragment is ultimately performed b y simultanous comparison with a known standard run. Sanger sequencing as a diagnostic technique is usually used in two scenarios: (i) when the genes causing the disease are known; (ii) when the disease genes are not yet described but several indi- viduals, both aff ected and unaff ected, from the same kindred are available for testing. In the fi rst scenario the genes are initially amplifi ed by PCR fol- lowed by sequencing, determining their DNA sequence for the individual. Even in these cases, where genes have be en described and the phenotype is suggestive of their involvement, one must bear in mind so me of the limitations of this approach: large het- erozygous deletions encompassing the reg ion being sequenced are likely to go unnoticed, and the same holds true for duplications. A lso, complete screening of genes with a large number of exons is typically too costly, and in these cases it is common for only a subset of exons to be tested. While this is common p ractice, it is worth noting that rare mutations may go unnoticed. LRRK2, one of the most co mmon genetic causes of Parkinson \200\231s disease, contains 42 exons and screening is usua lly performed only for the two or three exons where mutations are most common; very few stu dies have screened the entire coding region of the gene, and it certainly is not practicabl e to do this on a routine basis. Th us it is clear that while Sanger sequencing is a robust and widely used technology for g enetic diagnosis, some limitations have become apparent as we have improved our understandi ng of the genetic basis of neurological diseases and should be taken into account when inte rpreting these results. Whole-genome genotyping Assaying about two million single nucleotide polymorphisms (SNPs) p resent in the human genome is currently a trivial and fairly inexpensive approach for many laboratories. Th e growth of this fi eld in the past four years has been remarkable and we have now moved from assaying tens of markers to assaying millions which cover all the known common variability in the genome. In the second scenario a clear genetic component to the disease is present (e.g. family his tory), but the causative genes are either unknown or screening for the known gene(s) has be en unsuccess- ful. In such cases it is possible to map the position of the gene by comparin g fragments of DNA between aff ected and unaff ected individuals in the family (a method kn own as family-based link- age). Aft er this initial mapping has been performed, sequencing of the region is undertaken to identify the causal gene and mutation. While Sanger sequenci ng is still widely used, there are limi- tations to the types of mutations it can detect th at should be noted. In some recessive diseases it is possible that instead of one homozygou s mutation underlying the disease, the subject presents with compound heterozygous mutation s. Here, one allele presents one mutation while the other allele presents a diff erent muta tion. If these two mutations are positioned very close together, one can usually determine the phase. However, if they are located in diff er- ent exons, and there are several thousa nd bases separating them, Sanger sequencing of the proband alone will not reveal the phase of these mutations. In these cases one typically needs to sequence additional family member s, if they are available. Th is is oft en the case for PRKN, the most common recessive gene for Parkinson \200\231s disease. PRKN contains 12 exons and spans over 1.3 million bases, and mutations have been described in the majority of these exons, implying that two mutatio ns may be separated by as many as a mil- lion base pairs. Th ere are currently several platforms that allow high-throughput genotyping, but the Illum ina Infi nium Beadchips (Illumina Inc.) are arguably the ones with the largest user base. V ery briefl y, the Infi nium protocol is based on genotyping chips (glass slides) con- taini ng probes that are complementary to the sequence adjacent to the SNP of interest. When hybr idized to the test DNA, the probes are polymerase-extended to the SNP base using labeled nu cle- otides, which provide a way of detecting the nucleotide incorpo- rated at that positio n. When coupled with image analysis hardware, it is possible to assay several million of th ese probes in a very short time span. Genotyping chips were initially based on the HapMap project fi ndings which depicted over 3 .1 million SNP locations on the genome, compiled using 269 samples from four human popula- tions (17). Probes were then selected that \200\230tagged \200\231 (i.e. were in close lin kage disequilibrium) with the majority of these markers, allowing a genome-wide analysis wh ile assaying only a subset of well-defi ned surrogate markers. Th is powerful technology no t only allows genotyping of SNPs, but also facilitates the determina- tion of copy number v ariation in an extraordinarily easy manner (Fig. 7.1). Additionally, capillary sequencing is unable to detect some copy number variations. For exa mple, a heterozygous deletion of an entire exon and fl anking regions would be missed using com- mon sequencing primers, since it would appear as if the individual simply had no hete rozygous variants in that particular exon. If a disease can be caused by a combination of p oint mutations and Th e initial application of this technology was for genome-wide association studies (GWAS). Until that point, research into the genetic associations of disease was typically limited to the study of a handful of markers in a gene of interest. Th is obviously meant that with out a correct assumption of a candidate gene, the study could prove to be meaningless. GWAS has enabled the evaluation CHAPTER 7 Genetic Techniques, Impact and Diagnostic Issues in Movement Disorders 55 GT Samples 5359856120_R01C01 [9] (1px1-6KB) 1.00 0.75 0.50 0.25 q e r F e l e l l A B 0.00 2.00 1.00 GT Samples 5359858120_R01C01 [9] (1px1=8KB) o i t a R R g o L 0.00 \200\2231.00 \200\2232.00 1.00 0.75 0.50 0.25 GT Samples 5359856120_R04C01 [12] (1px1-6KB) q e r F e l e l l A B 0.00 2.00 1.00 GT Samples 5359858120_R04C01 [12] (1px1=8KB) o i t a R R g o L 0.00 \200\2231.00 \200\2232.00 Base Position Cytogenetic Band Sequence (+) 86,382,205 87,204,415 88,026,625 88,848,835 89,671,045 90,493,256 91,315,466 92,137,675 92,959,885 No sequence data \201le found for this chromosome. Fig. 7.1 GenomeStudio plot showing the two common metrics analyzed (LogR ratio and B allele frequency). Th e \201 rst metric indicates the normalized intensity for each probe/SNP d epicted by a single blue dot. In case of an increase in copy number (duplication, triplicat ion, etc.) LogR ratio for that SNP becomes higher than the average value and this can easil y be seen in these plots. Th e second metric depicts heterozygosity by outputting the B all ele frequency. Th is allows rapid examination of regions of homozygosity. (GenomeStudio is a registered trademark of Illumina Inc.) 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 ) p ( 0 1 g o \200\223 l 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Chromosome Fig. 7.2 Manhattan plot showing genome-wide association values. Th ese plots have quickly b ecome the standard for illustrating GWAS results. Th ey allow genomic regions that appear t o be associated with a particular phenotype to be detected in a quick and easy manner. Here , individual SNPs are plotted by position and association p -value. Th e higher the peak fo r a locus, the stronger is the association with disease. of associations in a global manner without the need for a prior hypothesis, relying simply on the tenet that common sequence vari- ants are responsible for common diseases (CV \200 \223CD). Th is approach has proved to be extremely successful, with new loci and genes now being identifi ed for a variety of diseases on an almost monthly basis (Fig. 7.2). a particular disease and assay all those variants in a single three-day run. Furthermore, since the cost of such experiments is rapidly falling below the $100 barrier, one can envisage this technology being used as an initial screen for all samples coming to a diagnostic labora- tory. For example, a neurogenetics laboratory would assay all the gene s known to be involved in neurological diseases for all sam- ples received, providing infor mation for all the known causes of neurological diseases in a single experiment that would cost $100. Th is approach will very likely revolutionize diagnostic laboratories and great ly improve the speed and accuracy with which results are reported back to the clinician. Although this approach was purely directed at research goals, the implications for genetic diagnosis are also very signifi cant. With the improvement in array design and decrease in costs, it is now possible to create custom assays that target relevant variation in a very cost-eff ective manner, such that one can create an array that targets all the known sequen ce variation in all the genes involved in Oxford Textbook of Movement Disorders 56 In addition to assaying sequence variants of interest, the array simultaneously assays for copy number changes. Th is has been shown to be a signifi cant determinant of common neurol ogical dis- orders; for example, the alpha-synuclein gene ( SNCA ) is not only known to con tain pathogenic point mutations, but also duplication and triplication of the entire gene h ave been described (18, 19). In the same manner, the amyloid precursor protein gene ( APP ) asso- ciated with Alzheimer \200\231s disease has been shown to contain not only sequence variants, but also an increased number of copies (20). Th e ability to assay both types of variation in a single experiment will contribute greatly to improvement in genetic diagnost ics. enabled us to answer questions that range from interrogating a single base to large copy nu mber variation on a genome-wide scale. Th is will ultimately change our understanding of th e human genome in a radical manner. Th e fi eld of \200\230next-generation \200\231 sequencing started with three major player s: Illumina (Genome Analyzer), Life Technologies (SOLiD), and Roche (454). All fi rst-gener ation instruments have since seen major improvements and, in the case of Illumina, the majo rity of sequencing centers quickly updated to a successor of the Genome Analyzer, the HiSeq 2000. All three instruments are based on diff erent chemistries, but they all share fundamental s imilarities that set them apart from capillary sequencing. Instead of processing up to 96 D NA fragments at a time (the maximum for Sanger sequencing machines), these instruments are able to process several millions of sequence reads in parallel. Th is throughput usually me ans that a single machine can success- fully fi nish a mid-size project in just a few runs. Additionally, the DNA preparation for sequencing is straightforward and does not require c omplex cloning or amplifi cation stages as used in capil- lary sequencing. Th us it is poss ible to avoid some of the bias issues that have plagued genome representation in several se quencing projects. Nevertheless, each of these technologies has its own set of biases. Th e typical workfl ow for sample preparation for any of these three technologies starts with b reaking up genomic DNA into small fragments, to which specifi c adaptor \200\230oligos \200\231 are ligated at both ends; at this point, the sample is ready to be sequenced. A re latively small amount of starting DNA (typically up to a cou- ple of micrograms) is needed to perform a complete experiment that can potentially sequence the entire genome of that sa mple. All three platforms also allow for sequencing both ends of each DNA fragment (paired ends), which is helpful for read mapping and de novo genome sequencing. Additionally, the d ata produced by these platforms is typically comprised of shorter reads (36 \200\223500 bp) com- pared with capillary sequencing (650 \200\223900 bp), which has an impact on several applications. Nonetheless, every technology has its limitations and genotyp- ing arrays are not immune to this. While the fact that markers can be chosen to be included in the array off ers great fl exibility, it also means that any unknown variant will be missed by this method. Th is i s particularly relevant for complex diseases where it is still believed that a signifi cant proportion of genes causing the disease are yet to be found. Likewise, although the genes may be identi- fi ed and a number of mutations discovered, novel mutations in the same gene would still be missed using this approach. Another limitation of genotyping arrays relates to the probe set that is used. For each mar ker, the array contains a 50 bp probe complementary to the genomic sequence. If an unknown SNP is present within the length of this probe, the genotype result may not be accurate sin ce the hybridization will not be completely effi cient. Th is is a diffi cult issue to addr ess since diff erent samples will carry diff erent benign rare variants which have no impac t on pathobiol- ogy of disease. Before an array is designed, all markers go through a very thorough process of screening to ensure that they will be suc- cessful. However, if SNPs ha ve not been described previously, there is no screening procedure that would detect this is sue. Similarly to Sanger sequencing, genomic regions that have homologous loci are also diffi cu lt to assay. Even though this is usually screened for before designing the array, if the va riant to be assessed is within one of these high-homology regions, a probe with suffi cient specifi city will be diffi cult to design. Th e Roche (454) GS FLX sequencer was fi rst introduced com- mercially in 2004. Th is seque ncer works on the principle of \200\230pyro- sequencing \200\231, which uses the pyrophosp hate molecule released on nucleotide incorporation by DNA polymerase to fuel a downstream s et of reactions that ultimately produce light from the cleavage of oxyluciferin by lucifera se (21). Th e current 454 instrument pro- duces an average read length of approximately 400 bp per sample, with a throughput of about a billion bases per day. It is also worth noting that since this technology assays individ- ual SNPs, chromosomal tr anslocations are virtually impossible to detect, given that the only output obtained is sig nal intensity per individual marker, regardless of its position on the genome. Although high-throughput genome-wide genotyping studies have yielded very exciting results, and the technology is now stable, robust, and very reproducible, the use of this approach has always been perceived as transitory and not as the ultimate analytical meth- odology. A s we advance rapidly towards ever more cost-eff ective sequencing technology, it is expecte d that high-throughput geno- typing will be replaced by whole-genome sequencing. Applied Biosystem \200\231s SOLiD sequencer was initially released in 2007 and relies on an innovative ligation-based chemistry (21). One of the main advantages of this approach is t hat it has one of the lowest error rates of all three technologies. Th e current SOLiD inst rument, the 5500xl, has a throughput of 30 billion bases per day with read lengths of up to 75 bp. Massively parallel sequencing In the past fi ve years new chemistries and instruments have been developed to perform sequencing (so-called \200\230next-generation \200\231 or \200 \230massively parallel \200\231 instruments), and such technology has already transformed t he fi eld. Th eir impact on genomics has been so dra- matic that the very nature of genetic experimentation has shift ed towards more comprehensive and complete analysis. Th e requir e- ments for handling these data are also fundamentally diff erent from those associated wi th Sanger sequencing, particularly the compu- tational algorithms used, and their continuou s improvement has In 2006 Illumina introduced their fi rst instrument, the Genome Analyzer, which has since s een several improvements, increasing throughput and reducing the times per run (22). In 201 0 a new instrument was released commercially which, although utilizing the same chemistry, improved throughput dramatically and quickly became the sequencer of choice for the vast ma jority of genome centers. Illumina \200\231s approach is based on the concept of \200\230s equencing by synthesis \200\231 (SBS) to produce sequence reads of 35 \200\223150 bp from t ens of millions of surface-amplifi ed DNA fragments simultane- ously. Th e major features o f this technology are the low turnaround CHAPTER 7 Genetic Techniques, Impact and Diagnostic Issues in Movement Disorders 57 time and the amount of data produced. At the time of writing, Illumina \200\231s HiSeq is c apable of producing over 600 billion bases per eight-day run, with read lengths of up to 15 0 bp. In parallel with whole-exome and whole-genome sequencing, it is now also possible to sequen ce the entire transcriptome (the collection of RNA molecules, including mRNA, rRNA, tRNA, a nd non-coding RNA, usually called RNA-seq) of an individual (30). Th is is potentially a ve ry powerful approach that is still in its early days, partly because the data analysis is m ore complex than that required for DNA sequencing. For example, a single gene will have sev eral transcripts, created by alternative splicing, which may or may not have been previousl y described. Th is has implications for primary data analysis, particularly the mapping of reads to the genome, which means that if a read is uniquely aligned to the wrong gene, such as a paralog, this may result in false-positive vari- ants being called. One of the added benefi ts of RNA-seq is that it detects both sequence variability and expression levels sim ultane- ously. Th is means that tissue-specifi c genes will only be detected (for both expr ession and sequence variability) when using RNA extracted from that same tissue. While the improvements in sequencing have been astonishing, clearly defying Moore \200\231s Law (23), the cost is still high enough to preclude whole-genome sequencing en masse at th e present time. To this end, strategies need to be developed to leverage this tech- nology and simultaneously provide cost-eff ectiveness. Th e fi rst approach was derived from commo n sense: given that the por- tion of the genome that we can most easily understand is the c oding region, sequencing should start by targeting this small portion \200\224the so-called exome (24). Much like genotyping arrays, exome sequencing is a transitory approach that re fl ects the most cost-eff ective approach to \200\230next-generation \200\231 sequencing t hat is cur- rently available. Exome sequencing follows the same principle as described for the technologies above, but in cludes an additional step where the genomic DNA library is hybridized with a pool of short biotin-labeled oligonucleotides that were designed to be comple- mentary to the entire coll ection of exons in the genome. Th ese are then magnetically captured and the non-coding DNA is washed away. Th is creates a library that contains only DNA fragments rep- resentative of the coding region. Th ese high-throughput approaches may play a very signifi cant role in the diagnostics labo ratory in the next three to fi ve years. One can certainly envisage a screening approach th at relies on the geno- typing of disease-specifi c markers using microarrays, while simul- taneously whole-genome and transcriptome are being sequenced to detect novel variability. T h is approach is likely to be very suc- cessful in determining the genetic causes of a high proportion of diseases at a fraction of the total cost that novel/complex diseases face in their diagnostic work-up. Th is approach has already permitted the identifi cation of the genetic causes underlying a signifi cant number of Mendelian dis- eases (24 \200\22329). While this is a powerful appr oach, there are some caveats. Th e fi rst of these is that by sequencing the exome, a sig- nifi cant proportion of variation in regulatory regions that may play a role in the disease is missed. Additionally, no method has yet allowed for the sequencing of the entire collec tion of known exons. Typically, 15 \200\22320% of known coding exons are not captured as th ey are located in complex genomic regions, for which capture probes are diffi cult to desig n. Added to this percentage are all the exons that are not properly described or annotated in the current genome reference build. Moreover, since these technologies all use short-rea ds, determining phase is still a poorly addressed issue, unless relevant family members are available for testing, which increases costs linearly. Th e combination of short-reads wit h the fact that only small dispersed fragments of the genome are being sequenced also means that mid-size insertions or deletions are dif- fi cult to assess, particularly if they are heterozygous. Th e identifi - cation of 1 \200\2235 bp deletions is quite accurate, but a heterozygous deletion of 60 \200\223100 bp is less so.