Next Generation Sequencing methods
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Next-generation DNA sequencing technologies have significantly impacted genetics research. Three major platforms - Roche/454, Illumina Genome Analyzer, and Applied Biosystems SOLiD - utilize massively parallel sequencing to generate large amounts of sequence data. Roche/454 uses emulsion PCR to amplify DNA fragments on beads and pyrosequencing to determine sequences. Illumina performs bridge amplification on a flow cell to generate DNA clusters then sequences by synthesis. Applied Biosystems SOLiD uses ligation-based sequencing. These new methods have enabled genome-wide studies and applications such as ancient DNA sequencing and metagenomics that were previously difficult or impossible.
Next Generation Sequencing methods
- 1. Next-Generation DNA Sequencing Methods Elaine R. Mardis Departments of Genetics and Molecular Microbiology and Genome Sequencing Center, Washington University School of Medicine, St. Louis MO 63108; email: emardis@wustl.edu Annu. Rev. Genomics Hum. Genet. 2008. 9:387–402 First published online as a Review in Advance on June 24, 2008 The Annual Review of Genomics and Human Genetics is online at genom.annualreviews.org This article’s doi: 10.1146/annurev.genom.9.081307.164359 Copyright c 2008 by Annual Reviews. All rights reserved 1527-8204/08/0922-0387$20.00 Key Words massively parallel sequencing, sequencing-by-synthesis, resequencing Abstract Recent scientific discoveries that resulted from the application of next- generation DNA sequencing technologies highlight the striking impact of these massively parallel platforms on genetics. These new meth- ods have expanded previously focused readouts from a variety of DNA preparation protocols to a genome-wide scale and have fine-tuned their resolution to single base precision. The sequencing of RNA also has transitioned and now includes full-length cDNA analyses, serial analysis of gene expression (SAGE)-based methods, and noncoding RNA dis- covery. Next-generation sequencing has also enabled novel applications such as the sequencing of ancient DNA samples, and has substantially widened the scope of metagenomic analysis of environmentally derived samples. Taken together, an astounding potential exists for these tech- nologies to bring enormous change in genetic and biological research and to enhance our fundamental biological knowledge. 387 Click here for quick links to Annual Reviews content online, including: • Other articles in this volume • Top cited articles • Top downloaded articles • Our comprehensive search FurtherANNUAL REVIEWS Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 2. INTRODUCTION The sequencing of the reference human genome was the capstone for many years of hard work spent developing high-throughput, high- capacity production DNA sequencing and as- sociated sequence finishing pipelines. The ap- proach used >20,000 large bacterial artificial chromosome (BAC) clones that each contained an approximately 100-kb fragment of the hu- man genome, which together provided an over- lapping set or tiling path through each human chromosome as determined by physical map- ping (31). In BAC-based sequencing, each BAC clone is amplified in bacterial culture, isolated in large quantities, and sheared to produce size- selected pieces of approximately 2−3 kb. These pieces are subcloned into plasmid vectors, am- plified in bacterial culture, and the DNA is selectively isolated prior to sequencing. By generating approximately eightfold oversam- pling (coverage) of each BAC clone in plasmid subclone equivalents, computer-aided assembly can largely recreate the BAC insert sequence in contigs (contiguous stretches of assembled sequence reads). Subsequent refinement, in- cluding gap closure and sequence quality improvement (finishing), produces a single con- tiguous stretch of high-quality sequence (typi- cally with less than 1 error per 40,000 bases). Since the completion of the human genome project (HGP) (26, 51), substantive changes have occurred in the approach to genome se- quencing that have moved away from BAC- based approaches and toward whole-genome sequencing (WGS), with changes in the ac- companying assembly algorithms. In the WGS approach, the genomic DNA is sheared di- rectlyintoseveraldistinctsizeclassesandplaced into plasmid and fosmid subclones. Oversam- pling the ends of these subclones to gener- ate paired-end sequencing reads provides the necessary linking information to fuel whole- genome assembly algorithms. The net result is that genomes can be sequenced more rapidly and more readily, but highly polymorphic or highly repetitive genomes remain quite frag- mented after assembly. Despite these dramatic changes in sequenc- ing and assembly approaches, the primary data production for most genome sequencing since the HGP has relied on the same type of capillary sequencing instruments as for the HGP. How- ever, that scenario is rapidly changing owing to the invention and commercial introduction of several revolutionary approaches to DNA sequencing, the so-called next-generation se- quencing technologies. Although these instru- ments only began to become commercially available in 2004, they already are having a ma- jor impact on our ability to explore and an- swer genome-wide biological questions; more than 100 next-generation sequencing–related manuscripts have appeared to date in the peer- reviewed literature. These technologies are not only changing our genome sequencing ap- proaches and the associated timelines and costs, but also accelerating and altering a wide va- riety of types of biological inquiry that have historically used a sequencing-based readout, or effecting a transition to this type of read- out, as detailed in this review. Furthermore, next-generation platforms are helping to open entirely new areas of biological inquiry, includ- ing the investigation of ancient genomes, the characterization of ecological diversity, and the identification of unknown etiologic agents. NEXT-GENERATION DNA SEQUENCING Three platforms for massively parallel DNA sequencing read production are in reasonably widespread use at present: the Roche/454 FLX (30) (http://www.454.com/enabling- technology/the-system.asp), the Illumina/ Solexa Genome Analyzer (7) (http://www. illumina.com/pages.ilmn?ID=203), and the Applied Biosystems SOLiDTM System (http:// marketing.appliedbiosystems.com/images/ Product/Solid Knowledge/flash/102207/ solid.html). Recently, another two massively parallel systems were announced: the Helicos HeliscopeTM (www.helicosbio.com) and Pacific Biosciences SMRT (www. pacificbiosciences.com) instruments. The 388 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 3. Helicos system only recently became com- mercially available, and the Pacific Biosciences instrument will likely launch commercially in early 2010. Each platform embodies a complex interplay of enzymology, chemistry, high-resolution optics, hardware, and software engineering. These instruments allow highly streamlined sample preparation steps prior to DNA sequencing, which provides a significant time savings and a minimal requirement for associated equipment in comparison to the highly automated, multistep pipelines necessary for clone-based high-throughput sequencing. By different approaches outlined below, each technology seeks to amplify single strands of a fragment library and perform sequencing reactions on the amplified strands. The fragment libraries are obtained by anneal- ing platform-specific linkers to blunt-ended fragments generated directly from a genome or DNA source of interest. Because the presence of adapter sequences means that the molecules then can be selectively amplified by PCR, no bacterial cloning step is required to amplify the genomic fragment in a bacterial intermediate as is done in traditional sequencing approaches. Importantly, both the Helicos and Pacific Biosystems instruments mentioned above are so-called “single molecule” sequencers and do not require any amplification of DNA fragments prior to sequencing. Another contrast between these instruments and capillary platforms is the run time required to generate data. Next-generation sequencers require longer run times of between 8 h and 10 days, depending upon the platform and read type (single end or paired ends). The longer run times result mainly from the need to im- age sequencing reactions that are occurring in a massively parallel fashion, rather than a peri- odic charge-coupled device (CCD) snapshot of 96 fixed capillaries. The yield of sequence reads and total bases per instrument run is signifi- cantly higher than the 96 reads of up to 750 bp each produced by a capillary sequencer run, and can vary from several hundred thousand reads (Roche/454) to tens of millions of reads (Il- lumina and Applied Biosystems SOLiD). The Charge-coupled device (CCD): a capacitor array used in optical scanners to capture images Emulsion PCR (ePCR): method for DNA amplification that uses a water in oil emulsion to isolate single DNA molecules in aqueous microreactors combination of streamlined sample preparation and long run times means that a single oper- ator can readily keep several next-generation sequencing instruments at full capacity. The following sections aim to introduce the reader to the primary features of each of the three most widely used next-generation platforms and to discuss strengths and weaknesses. Roche/454 FLX Pyrosequencer This next-generation sequencer was the first to achieve commercial introduction (in 2004) and uses an alternative sequencing technology known as pyrosequencing. In pyrosequencing, each incorporation of a nucleotide by DNA polymerase results in the release of pyrophos- phate, which initiates a series of downstream reactions that ultimately produce light by the firefly enzyme luciferase. The amount of light produced is proportional to the number of nu- cleotides incorporated (up to the point of de- tector saturation). In the Roche/454 approach (Figure 1), the library fragments are mixed with a population of agarose beads whose sur- faces carry oligonucleotides complementary to the 454-specific adapter sequences on the frag- ment library, so each bead is associated with a single fragment. Each of these fragment:bead complexes is isolated into individual oil:water micelles that also contain PCR reactants, and thermal cycling (emulsion PCR) of the micelles produces approximately one million copies of each DNA fragment on the surface of each bead. These amplified single molecules are then sequenced en masse. First the beads are ar- rayed into a picotiter plate (PTP; a fused silica capillary structure) that holds a single bead in each of several hundred thousand single wells, which provides a fixed location at which each se- quencing reaction can be monitored. Enzyme- containing beads that catalyze the downstream pyrosequencing reaction steps are then added to the PTP and the mixture is centrifuged to surround the agarose beads. On instrument, the PTP acts as a flow cell into which each pure nucleotide solution is introduced in a step- wise fashion, with an imaging step after each www.annualreviews.org • Next-Generation DNA Sequencing Methods 389 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 4. Anneal sstDNA to an excess of DNA capture beads Emulsify beads and PCR reagents in water-in-oil microreactors Clonal amplification occurs inside microreactors Break microreactors and enrich for DNA-positive beads Amplified sstDNA library beads Quality filtered bases a b c DNA library preparation Emulsion PCR Sequencing A A A B B B 4.5 hours 8 hours 7.5 hours Ligation Selection (isolate AB fragments only) •Genome fragmented by nebulization •No cloning; no colony picking •sstDNA library created with adaptors •A/B fragments selected using avidin-biotin purification gDNA sstDNA library sstDNA library Bead-amplified sstDNA library •Well diameter: average of 44 μm •400,000 reads obtained in parallel •A single cloned amplified sstDNA bead is deposited per well 390 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 5. nucleotide incorporation step. The PTP is seated opposite a CCD camera that records the light emitted at each bead. The first four nu- cleotides (TCGA) on the adapter fragment ad- jacent to the sequencing primer added in library construction correspond to the sequential flow of nucleotides into the flow cell. This strategy allows the 454 base-calling software to calibrate the light emitted by a single nucleotide incor- poration. However, the calibrated base calling cannot properly interpret long stretches (>6) of the same nucleotide (homopolymer run), so these areas are prone to base insertion and dele- tion errors during base calling. By contrast, because each incorporation step is nucleotide specific, substitution errors are rarely encoun- tered in Roche/454 sequence reads. The FLX instrument currently provides 100 flows of each nucleotide during an 8-h run, which produces an average read length of 250 nucleotides (an average of 2.5 bases per flow are incorporated). These raw reads are processed by the 454 analysis software and then screened by various quality filters to remove poor-quality sequences, mixed sequences (more than one ini- tial DNA fragment per bead), and sequences without the initiating TCGA sequence. The resulting reads yield 100 Mb of quality data on average. Downstream of read processing, an as- sembly algorithm (Newbler) can assemble FLX reads.Althoughshorterthanreadsderivedfrom capillary sequencers, FLX reads are of sufficient length to assemble small genomes such as bacte- rial and viral genomes to high quality and con- tiguity. As mentioned, the lack of a bacterial cloning step in the Roche/454 process means that sequences not typically sampled in a WGS approach owing to cloning bias will be more likely represented in a FLX data set, which con- Bridge amplification: allows the generation of in situ copies of a specific DNA molecule on an oligo-decorated solid support tributes to more comprehensive genome cover- age. Illumina Genome Analyzer The single molecule amplification step for the Illumina Genome Analyzer starts with an Illumina-specific adapter library, takes place on the oligo-derivatized surface of a flow cell, and is performed by an automated device called a Cluster Station. The flow cell is an 8-channel sealed glass microfabricated device that allows bridge amplification of fragments on its surface, and uses DNA polymerase to produce multiple DNA copies, or clusters, that each represent the single molecule that initiated the cluster ampli- fication. A separate library can be added to each of the eight channels, or the same library can be used in all eight, or combinations thereof. Each cluster contains approximately one mil- lion copies of the original fragment, which is sufficient for reporting incorporated bases at the required signal intensity for detection dur- ing sequencing. The Illumina system utilizes a sequencing- by-synthesis approach in which all four nu- cleotides are added simultaneously to the flow cell channels, along with DNA polymerase, for incorporation into the oligo-primed clus- ter fragments (see Figure 2 for details). Specif- ically, the nucleotides carry a base-unique flu- orescent label and the 3 -OH group is chem- ically blocked such that each incorporation is a unique event. An imaging step follows each base incorporation step, during which each flow cell lane is imaged in three 100-tile segments by the instrument optics at a cluster density per tile of 30,000. After each imaging step, the 3 blocking group is chemically removed ←−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−−− Figure 1 The method used by the Roche/454 sequencer to amplify single-stranded DNA copies from a fragment library on agarose beads. A mixture of DNA fragments with agarose beads containing complementary oligonucleotides to the adapters at the fragment ends are mixed in an approximately 1:1 ratio. The mixture is encapsulated by vigorous vortexing into aqueous micelles that contain PCR reactants surrounded by oil, and pipetted into a 96-well microtiter plate for PCR amplification. The resulting beads are decorated with approximately 1 million copies of the original single-stranded fragment, which provides sufficient signal strength during the pyrosequencing reaction that follows to detect and record nucleotide incorporation events. sstDNA, single-stranded template DNA. www.annualreviews.org • Next-Generation DNA Sequencing Methods 391 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 6. to prepare each strand for the next incorpora- tion by DNA polymerase. This series of steps continues for a specific number of cycles, as de- termined by user-defined instrument settings, which permits discrete read lengths of 25–35 bases. A base-calling algorithm assigns se- quences and associated quality values to each read and a quality checking pipeline evaluates the Illumina data from each run, removing poor-quality sequences. Adapter DNA fragment Dense lawn of primers Adapter Attached DNA Adapters Prepare genomic DNA sample Randomly fragment genomic DNA and ligate adapters to both ends of the fragments. Attach DNA to surface Bind single-stranded fragments randomly to the inside surface of the flow cell channels. Bridge amplification Add unlabeled nucleotides and enzyme to initiate solid- phase bridge amplification. Denature the double stranded molecules Nucleotides a Figure 2 The Illumina sequencing-by-synthesis approach. Cluster strands created by bridge amplification are primed and all four fluorescently labeled, 3 -OH blocked nucleotides are added to the flow cell with DNA polymerase. The cluster strands are extended by one nucleotide. Following the incorporation step, the unused nucleotides and DNA polymerase molecules are washed away, a scan buffer is added to the flow cell, and the optics system scans each lane of the flow cell by imaging units called tiles. Once imaging is completed, chemicals that effect cleavage of the fluorescent labels and the 3 -OH blocking groups are added to the flow cell, which prepares the cluster strands for another round of fluorescent nucleotide incorporation. 392 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 7. Applied Biosystems SOLiDTM Sequencer The SOLiD platform uses an adapter-ligated fragment library similar to those of the other next-generation platforms, and uses an emul- sion PCR approach with small magnetic beads to amplify the fragments for sequencing. Un- like the other platforms, SOLiD uses DNA lig- ase and a unique approach to sequence the am- plified fragments, as illustrated in Figure 3a. Two flow cells are processed per instrument run, each of which can be divided to contain different libraries in up to four quadrants. Read lengths for SOLiD are user defined between 25–35 bp, and each sequencing run yields be- tween 2–4 Gb of DNA sequence data. Once the reads are base called, have quality values, and low-quality sequences have been removed, the reads are aligned to a reference genome to enable a second tier of quality evaluation called two-base encoding. The principle of two-base encoding is shown in Figure 3b, which illus- trates how this approach works to differenti- ate true single base variants from base-calling errors. Two key differences that speak to the utility of next-generation sequence reads are (a) the length of a sequence read from all current next- generation platforms is much shorter than that from a capillary sequencer and (b) each next- generation read type has a unique error model different from that already established for b Laser First chemistry cycle: determine first base To initiate the first sequencing cycle, add all four labeled reversible terminators, primers, and DNA polymerase enzyme to the flow cell. Image of first chemistry cycle After laser excitation, capture the image of emitted fluorescence from each cluster on the flow cell. Record the identity of the first base for each cluster. Sequence read over multiple chemistry cycles Repeat cycles of sequencing to determine the sequence of bases in a given fragment a single base at a time. Before initiating the next chemistry cycle The blocked 3' terminus and the fluorophore from each incorporated base are removed. GCTGA... Figure 2 (Continued ) www.annualreviews.org • Next-Generation DNA Sequencing Methods 393 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 8. A C G T 1stbase 2nd base A C G T 3'TAnnnzzz5' 3'TCnnnzzz5' 3'TGnnnzzz5' 3'TTnnnzzz5' Cleavage site Di base probesSOLiD™ substrate 3' TA AT Universal seq primer (n) 3' P1 adapter Template sequence POH Universal seq primer (n–1) Ligase Phosphatase + 1. Prime and ligate 2. Image 4. Cleave off fluor 5. Repeat steps 1–4 to extend sequence 3' Universal seq primer (n–1) 1. Melt off extended sequence 2. Primer reset3' AA AC G G GG C C C T AA A GG CC T TTT 6. Primer reset 7. Repeat steps 1–5 with new primer 8. Repeat Reset with , n–2, n–3, n–4 primers TA AT AT 3' TA AT 3' Excite Fluorescence Cleavage agent P HO TA AA AG AC AAAT TT TC TG TT AC TG CG GC 3' 3. Cap unextended strands 3' PO4 1 2 3 4 5 6 7 ... (n cycles)Ligation cycle 3' 3'1 μm bead 1 μm bead 1 μm bead –1 Universal seq primer (n–1) Universal seq primer (n) Universal seq primer (n–2) Universal seq primer (n–3) Universal seq primer (n–4) 3' 3' 3' 3' 3' 1 2 3 4 5 Primer round 1 Template Primer round 2 1 base shift Glass slide 3'5' Template sequence 1 μm bead P1 adapter Bridge probe Bridge probe Bridge probe Read position Indicates positions of interrogation 35343332313029282726252423222120191817161514131211109876543210 Ligation cycle Primerround 1 2 3 4 5 6 7 a 394 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 9. Color space sequence Possible dinucleotides Decoded sequence Base space sequence TA GC CG AC CA GT TG AA CC GG TT AT TG GG A T G G AT GA TC AG CT GA A Possible dinucleotides encoded by each color Decoding A A C C G G T T 1stbase 2nd base AT CG GC TA AC CA GT TG AA CC GG T T GA TC AG CT Data collection and image analysis Collect color image Collect color image Identify beads Identify beads Identify bead color Identify bead color Primer round 1, ligation cycle 1 Primer round 2, ligation cycle 1 Primer round 3, ligation cycle 1 Color space for this sequence Glass slide R R G BG R G B BY RR G B Y Primer round 4, ligation cycle 1G R B B Y A AT G G With 2 base encoding each base is defined twice Double interrogation Template sequence Base zero b Figure 3 (a) The ligase-mediated sequencing approach of the Applied Biosystems SOLiD sequencer. In a manner similar to Roche/454 emulsion PCR amplification, DNA fragments for SOLiD sequencing are amplified on the surfaces of 1-μm magnetic beads to provide sufficient signal during the sequencing reactions, and are then deposited onto a flow cell slide. Ligase-mediated sequencing begins by annealing a primer to the shared adapter sequences on each amplified fragment, and then DNA ligase is provided along with specific fluorescent- labeled 8mers, whose 4th and 5th bases are encoded by the attached fluorescent group. Each ligation step is followed by fluorescence detection, after which a regeneration step removes bases from the ligated 8mer (including the fluorescent group) and concomitantly prepares the extended primer for another round of ligation. (b) Principles of two-base encoding. Because each fluorescent group on a ligated 8mer identifies a two-base combination, the resulting sequence reads can be screened for base-calling errors versus true polymorphisms versus single base deletions by aligning the individual reads to a known high-quality reference sequence. www.annualreviews.org • Next-Generation DNA Sequencing Methods 395 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 10. Chromatin immunoprecipitation (ChIP): chemical crosslinking of DNA and proteins, and immunoprecipitation using a specific antibody to determine DNA:protein associations in vivo Quantitative polymerase chain reaction (qPCR): rapidly measures the quantity of DNA, cDNA, or RNA present in a sample through cycle-by-cycle measurement of incorporated fluorescent dyes capillary sequence reads. Both differences affect how the reads are utilized in bioinformatic anal- yses, depending upon the application. For ex- ample, in strain-to-reference comparisons (re- sequencing), the typical definition of repeat content must be revised in the context of the shorter read length. In addition, a much higher read coverage or sampling depth is required for comprehensive resequencing with short reads to adequately cover the reference sequence at the depth and low gap size needed. Some applications are more suitable for cer- tain platforms than others, as detailed below. Furthermore, read length and error profile issues entail platform- and application-specific bioinformatics-based considerations. More- over, it is important to recognize the signifi- cant impacts that implementation of these plat- forms in a production sequencing environment has on informatics and bioinformatics infras- tructures. The massively parallel scale of se- quencing implies a similarly massive scale of computational analyses that include image anal- ysis, signal processing, background subtraction, base calling, and quality assessment to produce the final sequence reads for each run. In every case, these analyses place significant demands on the information technology (IT), computa- tional, data storage, and laboratory information management system (LIMS) infrastructures ex- tant in a sequencing center, thereby adding to the overhead required for high-throughput data production. This aspect of next-generation sequencing is at present complicated by the dearth of current sequence analysis tools suited to shorter sequence read data; existing data analysis pipelines and algorithms must be mod- ified to accommodate these shorter reads. In many cases, and certainly for new applica- tions of next-generation sequencing, entirely new algorithms and data visualization inter- faces are being devised and tested to meet this new demand. Therefore, the next-generation platforms are effecting a complete paradigm shift, not only in the organization of large-scale data production, but also in the downstream bioinformatics, IT, and LIMS support required for high data utility and correct interpretation. This paradigm shift promises to radically alter the path of biological inquiry, as the following review of recent endeavors to implement next- generation sequencing platforms and accompa- nying bioinformatics-based analyses serves to substantiate. ELUCIDATING DNA-PROTEIN INTERACTIONS THROUGH CHROMATIN IMMUNOPRECIPITATION SEQUENCING The association between DNA and proteins is a fundamental biological interaction that plays a key part in regulating gene expression and con- trolling the availability of DNA for transcrip- tion, replication, and other processes. These interactions can be studied in a focused manner using a technique called chromatin immuno- precipitation (ChIP) (43). ChIP entails a series of steps: (a) DNA and associated proteins are chemically cross-linked; (b) nuclei are isolated, lysed, and the DNA is fragmented; (c) an an- tibody specific for the DNA binding protein (transcription factor, histone, etc.) of interest is used to selectively immunoprecipitate the as- sociated protein:DNA complexes; and (d ) the chemical crosslinks between DNA and protein are reversed and the DNA is claimed for down- stream analysis. In early applications, typical analyses examined the specific gene of interest by qPCR (quantitative PCR) or Southern blot- ting to determine if corresponding sequences were contained in the captured fragment pop- ulation. Recently, genome-wide ChIP-based studies of DNA-protein interactions became possible in sequenced genomes by using ge- nomic DNA microarrays to assay the released fragments. This so-called ChIP-chip approach was first reported by Ren and coworkers (38). Although utilized for a number of important studies, it has several drawbacks, including a low signal-to-noise ratio and a need for replicates to build statistical power to support putative bind- ing sites. 396 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 11. Many of these drawbacks were addressed by shifting the readout of ChIP-derived DNA se- quences onto next-generation sequencing plat- forms. The precedent-setting paper for this paradigm was published by Johnson and col- leagues (21), who used the model organism Caenorhabditis elegans and the Roche platform to elucidate nucleosome positioning on ge- nomic DNA. This study established that se- quencing the micrococcal nuclease–derived di- gestion products of genomic DNA carefully isolated from mixed stage hermaphrodite pop- ulations of C. elegans was sufficient to gener- ate a genome-wide, highly precise positional profile of chromatin. This capability enables studies of specific physiological conditions and their genome-wide impact on nucleosome posi- tioning, among other applications. Subsequent studies have utilized a ChIP-based approach and the Illumina platform to provide insights into transcription factor binding sites in the hu- man genome such as neuron-restrictive silencer factor (NRSF) (20) and signal transducer and activator of transcription 1 (STAT1) (39). In a landmark study, Mikkelsen and coworkers (32) explored the connection between chromatin packaging of DNA and differential gene ex- pression using mouse embryonic stem cells and lineage-committed mouse cells (neural progen- itor cells and embryonic fibroblasts), provid- ing a next-generation sequencing-based frame- work for using genome-wide chromatin profil- ing to characterize cell populations. This group demonstrated that trimethylation of lysine 4 and lysine 27 determines genes that are ei- ther expressed, poised for expression, or sta- bly repressed, effectively reflecting cell state and lineage potential. Also, lysine 4 and lysine 9 trimethylation mark imprinting control re- gions, whereas lysine 9 and lysine 20 trimethy- lation identifies satellite, telomeric, and ac- tive long-terminal repeats. These early studies demonstrated that the ability to map genome- wide changes in transcription factor binding or chromatin packaging under different environ- mental conditions offers a profound opportu- nity to couple evidence of altered DNA:protein interactions to expression level changes of Serial analysis of gene expression (SAGE): measures the quantitative expression of genes in an mRNA population sample by generating SAGE tags that are then sequenced specific genes in the context of specific envi- ronmental stimuli, thereby enhancing our un- derstanding of gene expression–based cellular responses. GENE EXPRESSION: SEQUENCING THE TRANSCRIPTOME Historically, mRNA expression has been gauged by microarray or qPCR-based ap- proaches; the latter is most efficient and cost- effective for a genome-wide survey of gene ex- pression levels. Even the exquisite sensitivity of qPCR, however, is not absolute, nor is it straightforward or reliable to evaluate novel al- ternative splicing isoforms using either technol- ogy. In the past, serial analysis of gene expres- sion (SAGE) (50) and variants have provided a digital readout of gene expression levels using DNA sequencing. These approaches are pow- erful in their ability to report the expression of genes at levels below the sensitivity of microar- rays, but have been limited in their application by the cost of DNA sequencing. By contrast, the rapid and inexpensive se- quencing capacity offered by next-generation sequencing instruments meshes perfectly with SAGE tagging or conventional cDNA sequenc- ing approaches, as evidenced by several studies that used Roche/454 technology (6, 11, 46, 53). Undoubtedly, the shorter read lengths offered by the Illumina and Applied Biosystems instru- ments will be utilized with these approaches in the future, offering the advantage of sequenc- ing individual SAGE tags rather than requir- ing concatenation of the tags prior to sequenc- ing. Indeed, one might imagine combining the data obtained from isolating and sequencing ChIP-derived DNA bound by a transcription factor of interest to the corresponding coiso- lated and sequenced mRNA population from the same cells. Such experiments will be en- tirely feasible with next-generation technolo- gies, especially given the low input amount of each type of biomolecule required for a suitable library and the high sensitivity afforded by the sequencing method. www.annualreviews.org • Next-Generation DNA Sequencing Methods 397 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 12. Noncoding RNA (ncRNA): any native RNA that is transcribed but not translated into a protein microRNA (miRNA): 21–23-base RNA molecules that participate in RNA- induced silencing of gene expression DISCOVERING NONCODING RNAs One of the most exciting areas of biological research in recent years has been the discov- ery and functional analysis of noncoding RNA (ncRNA) systems in different organisms. First described in plants, ncRNAs are providing new insights into gene regulation in animal systems as well, as recognized by the awarding of the Nobel Prize in Medicine and Physiology to An- drew Fire and Craig Mello in 2006. Perhaps the most profound impact of next-generation se- quencing technology has been on the discovery of novel ncRNAs belonging to distinct classes in an extraordinarily diverse set of species (3, 8, 9, 18, 22, 29, 41, 55). In fact, this approach has been responsible for the discovery of ncRNA classes in organisms not previously known to possess them (41). These discoveries are being coupled with an ever-expanding comprehen- sion of the functions embodied by these unique RNA species, including gene regulation by a variety of mechanisms. In this regard, studying the roles of specific microRNAs (miRNAs) in cancer is helping to uncover certain aspects of the disease (10, 44). Noncoding RNA discovery is best accom- plished by sequencing because the evolution- ary diversity of ncRNA gene sequences makes it difficult to predict their presence in a genome with high certainty by computational methods alone. The unique structures of the processed ncRNAs pose difficulties for converting them into next-generation sequencing libraries (29), but remarkable progress has already been made in characterizing these molecules. With these barriers dissolving, the high capacity and low cost of next-generation platforms ensure that discovery of ncRNAs will continue at a rapid pace and that sequence variants with impor- tant functional impacts will also be determined. Because the readout from next-generation se- quencers is quantitative, ncRNA characteri- zation will include detecting expression level changes that correlate with changes in envi- ronmental factors, with disease onset and pro- gression, and perhaps with complex disease on- set or severity, for example. Importantly, the discovery and characterization of ncRNAs will enhance the annotation of sequenced genomes such that, especially in model organisms and humans, the impact of mutations will become more broadly interpretable across the genome. ANCIENT GENOMES RESURRECTED Attempts to characterize fossil-derived DNAs have been limited by the degraded state of the sample, which in the past permitted only mi- tochondrial DNA sequencing and typically in- volved PCR amplification of specific mitochon- drial genome regions (1, 15, 23, 24, 35, 40). The advent of next-generation sequencing has for the first time made it possible to directly sample the nuclear genomes of ancient remains from the cave bear (34), mammoth (37), and the Neanderthal (17, 33). Several non-trivial technical complications arise in these inquiries, most notably the need to identify contaminat- ing DNA from modern humans in the case of Neanderthal remains. Although even next- generation sequencing of these sample remains is quite inefficient, owing largely to bacterial DNA that is coisolated with the genomic prepa- ration and the degraded nature of the ancient genome, important characterizations are being made. So far, one million bases of the Nean- derthal genome have been sequenced, starting from DNA obtained from a single fossil bone (17). METAGENOMICS EMERGES Characterizing the biodiversity found on Earth is of particular interest as climate changes reshape our planet. DNA- or RNA-based ap- proaches for this purpose are becoming in- creasingly powerful as the growing number of sequenced genomes enables us to interpret partial sequences obtained by direct sampling of specific environmental niches. Such investi- gations are referred to as metagenomics, and are typically aimed at answering the question: who’s there? Conventionally, this question is 398 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 13. addressed by isolating DNA from an environ- mental sample, amplifying the collective of 16S ribosomal RNA (rRNA) genes with degenerate PCR primer sets, subcloning the PCR prod- ucts that result, and classifying the taxa present according to a database of assigned 16S rRNA sequences. As an alternative, DNA (or RNA) is isolated, subcloned, and then sequenced to pro- duce a fragment pool representative of the ex- isting population. These sequences can then be translated in silico into protein fragments and compared with the existing database of anno- tated genome sequences to identify community members. In both approaches, deep sequencing of the population of subclones is necessary to obtain the full spectrum of taxa present, and is limited by potential cloning bias that can result from the use of bacterial cloning. By sampling RNA sequences from a metagenomic isolate, one can attempt to reconstruct metabolic path- ways that are active in a given environment (45, 47). Several early metagenomic studies utilized DNA sequence sampling by capillary sequenc- ing to investigate an acidophilic biofilm (49), an acid mine site (12) and the Sargasso Sea (52). Although these studies defined metagenomics as a scientific pursuit, they were limited in the breadth of diversity that could be sampled ow- ing to the expense of the conventional sequenc- ing process. By contrast, the rapid, inexpensive, and massive data production enabled by next- generation platforms has caused a recent ex- plosion in metagenomic studies. These studies include previously sampled environments such as the ocean (2, 19, 42) and an acid mine site (13), but soil (14, 27) and coral reefs (54) also were studied by Roche/454 pyrosequencing. Another metagenomic environment that is being characterized by next-generation se- quencing is the human microbiome; the human body contains several highly specific environ- ments that are inhabited by various microbial, fungal, viral, and eukaryotic symbiont com- munities, the inhabitants of which may vary according to the health status of the individual. These environments include the skin, the oral and nasal cavities, the gastrointestinal tract, and the vagina, among others. Particularly well- Metagenomics: the genomics-based study of genetic material recovered directly from environmentally derived samples without laboratory culture Epigenomics: seeks to define the influence of changes to gene expression that are independent of gene sequence studied is the lower intestine of humans, first characterized by 16S rRNA classification (4, 5, 28) and more recently by 454 pyrosequencing in adult humans (16, 36, 48) and in infants (25, 36). Supporting these characterization efforts will be a large-scale project to sequence hundreds of isolated microbial genomes that are known symbionts of humans as references (http://www.genome.gov/25521743). The early successes in human microbiome charac- terization and the apparent interplay between the human host and its microbial census have resulted in the inclusion of a Human Micro- biome Initative in the NIH Roadmap (http:// nihroadmap.nih.gov/hmp/). The associated funding opportunities, with the advantages offered by next-generation sequencing instru- mentation, should initiate a revolution in our understanding of how the human microbiome influences our health status. FUTURE POSSIBILITIES As this review has described, the advent and widespread availability of next-generation se- quencing instruments has ushered in an era in which DNA sequencing will become a more universal readout for an increasingly wide variety of front-end assays. However, more applications of next-generation sequencing, beyond those covered here, are yet to come. For example, genome resequencing will likely be used to characterize strains or isolates rela- tive to high-quality reference genomes such as C. elegans, Drosophila, and human. Studies of this type will identify and catalog genomic variation on a wide scale, from single nucleotide poly- morphisms (SNPs) to copy number variations in large sequence blocks (>1000 bases). Ulti- mately, resequencing studies will help to better characterize, for example, the range of normal variation in complex genomes such as the hu- man genome, and aid in our ability to compre- hensively view the range of genome variation in clinical isolates of pathogenic microbes, viruses, etc. Epigenomic variation, as an extension of genome resequencing applications, also will be www.annualreviews.org • Next-Generation DNA Sequencing Methods 399 Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 14. investigated using next-generation sequencing approaches that enable the ascertainment of genome-wide patterns of methylation and how these patterns change through the course of an organism’s development, in the context of dis- ease, and under various other influences. Perhaps the most exciting possibility en- gendered by the ability to use DNA sequenc- ing to rapidly read out experimental results is the enhanced potential to combine the results of different experiments—correlative analyses of genome-wide methylation, histone binding patterns, and gene expression, for example— owing to the similar data type produced. The power in these correlative analyses is the power to begin unlocking the secrets of the cell. DISCLOSURE STATEMENT The author serves as a Director of the Applera Corporation. LITERATURE CITED 1. Adcock GJ, Dennis ES, Easteal S, Huttley GA, Jermiin LS, et al. 2001. Mitochondrial DNA sequences in ancient Australians: implications for modern human origins. Proc. Natl. Acad. Sci. USA 98:537–42 2. Angly FE, Felts B, Breitbart M, Salamon P, Edwards RA, et al. 2006. The marine viromes of four oceanic regions. PLoS Biol. 4:e368 3. Axtell MJ, Snyder JA, Bartel DP. 2007. Common functions for diverse small RNAs of land plants. Plant Cell 19:1750–69 4. B¨ackhed F, Ding H, Wang T, Hooper LV, Koh GY, et al. 2004. The gut microbiota as an environmental factor that regulates fat storage. Proc. Natl. Acad. Sci. USA 101:15718–23 5. B¨ackhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI. 2005. Host-bacterial mutualism in the human intestine. Science 307:1915–20 6. Bainbridge MN, Warren RL, Hirst M, Romanuik T, Zeng T, et al. 2006. Analysis of the prostate cancer cell line LNCaP transcriptome using a sequencing-by-synthesis approach. BMC Genomics 7:246 7. Bentley DR. 2006. Whole-genome resequencing. Curr. Opin. Genet. Dev. 16:545–52 8. Berezikov E, Thuemmler F, van Laake LW, Kondova I, Bontrop R, et al. 2006. Diversity of microRNAs in human and chimpanzee brain. Nat. Genet. 38:1375–77 9. Brennecke J, Aravin AA, Stark A, Dus M, Kellis M, et al. 2007. Discrete small RNA-generating loci as master regulators of transposon activity in Drosophila. Cell 128:1089–103 10. Calin GA, Liu CG, Ferracin M, Hyslop T, Spizzo R, et al. 2007. Ultraconserved regions encoding ncRNAs are altered in human leukemias and carcinomas. Cancer Cell 12:215–29 11. Cheung F, Haas BJ, Goldberg SM, May GD, Xiao Y, Town CD. 2006. Sequencing Medicago truncatula expressed sequenced tags using 454 Life Sciences technology. BMC Genomics 7:272 12. Edwards KJ, Bond PL, Gihring TM, Banfield JF. 2000. An archaeal iron-oxidizing extreme acidophile important in acid mine drainage. Science 287:1796–99 13. Edwards RA, Rodriguez-Brito B, Wegley L, Haynes M, Breitbart M, et al. 2006. Using pyrosequencing to shed light on deep mine microbial ecology. BMC Genomics 7:57 14. Fierer N, Breitbart M, Nulton J, Salamon P, Lozupone C, et al. 2007. Metagenomic and small-subunit rRNA analyses of the genetic diversity of bacteria, archaea, fungi, and viruses in soil. Appl. Environ. Microbiol. 73:7059–66 15. Gilbert MT, Tomsho LP, Rendulic S, Packard M, Drautz DI, et al. 2007. Whole-genome shotgun sequencing of mitochondria from ancient hair shafts. Science 317:1927–30 16. Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, et al. 2006. Metagenomic analysis of the human distal gut microbiome. Science 312:1355–59 17. Green RE, Krause J, Ptak SE, Briggs AW, Ronan MT, et al. 2006. Analysis of one million base pairs of Neanderthal DNA. Nature 444:330–36 18. Houwing S, Kamminga LM, Berezikov E, Cronembold D, Girard A, et al. 2007. A role for Piwi and piRNAs in germ cell maintenance and transposon silencing in zebrafish. Cell 129:69–82 400 Mardis Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
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- 17. AR353-GG09-FM ARI 25 July 2008 5:19 Annual Review of Genomics and Human Genetics Volume 9, 2008 Contents Human Telomere Structure and Biology Harold Riethman p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 1 Infectious Disease in the Genomic Era Xiaonan Yang, Hongliang Yang, Gangqiao Zhou, and Guo-Ping Zhao p p p p p p p p p p p p p p p p p p p21 ENU Mutagenesis, a Way Forward to Understand Gene Function Abraham Acevedo-Arozena, Sara Wells, Paul Potter, Michelle Kelly, Roger D. Cox, and Steve D.M. Brown p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p49 Clinical Utility of Contemporary Molecular Cytogenetics Bassem A. Bejjani and Lisa G. Shaffer p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p71 The Role of Aminoacyl-tRNA Synthetases in Genetic Diseases Anthony Antonellis and Eric D. Green p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p87 A Bird’s-Eye View of Sex Chromosome Dosage Compensation Arthur P. Arnold, Yuichiro Itoh, and Esther Melamed p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 109 Linkage Disequilibrium and Association Mapping B. S. Weir p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 129 Positive Selection in the Human Genome: From Genome Scans to Biological Significance Joanna L. Kelley and Willie J. Swanson p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 143 The Current Landscape for Direct-to-Consumer Genetic Testing: Legal, Ethical, and Policy Issues Stuart Hogarth, Gail Javitt, and David Melzer p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 161 Transcriptional Control of Skeletogenesis Gerard Karsenty p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 183 A Mechanistic View of Genomic Imprinting Ky Sha p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 197 Phylogenetic Inference Using Whole Genomes Bruce Rannala and Ziheng Yang p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 217 v Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 18. AR353-GG09-FM ARI 25 July 2008 5:19 Transgenerational Epigenetic Effects Neil A. Youngson and Emma Whitelaw p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 233 Evolution of Dim-Light and Color Vision Pigments Shozo Yokoyama p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 259 Genetic Basis of Thoracic Aortic Aneurysms and Dissections: Focus on Smooth Muscle Cell Contractile Dysfunction Dianna M. Milewicz, Dong-Chuan Guo, Van Tran-Fadulu, Andrea L. Lafont, Christina L. Papke, Sakiko Inamoto, and Hariyadarshi Pannu p p p p p p p p p p p p p p p p p p p p p p p p p p p 283 Cohesin and Human Disease Jinglan Liu and Ian D. Krantz p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 303 Genetic Predisposition to Breast Cancer: Past, Present, and Future Clare Turnbull and Nazneen Rahman p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 321 From Linkage Maps to Quantitative Trait Loci: The History and Science of the Utah Genetic Reference Project Stephen M. Prescott, Jean Marc Lalouel, and Mark Leppert p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 347 Disorders of Lysosome-Related Organelle Biogenesis: Clinical and Molecular Genetics Marjan Huizing, Amanda Helip-Wooley, Wendy Westbroek, Meral Gunay-Aygun, and William A. Gahl p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 359 Next-Generation DNA Sequencing Methods Elaine R. Mardis p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 387 African Genetic Diversity: Implications for Human Demographic History, Modern Human Origins, and Complex Disease Mapping Michael C. Campbell and Sarah A. Tishkoff p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 403 Indexes Cumulative Index of Contributing Authors, Volumes 1–9 p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 435 Cumulative Index of Chapter Titles, Volumes 1–9 p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p p 438 Errata An online log of corrections to Annual Review of Genomics and Human Genetics articles may be found at http://genom.annualreviews.org/ vi Contents Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.
- 19. Annual Reviews It’s about time. Your time. It’s time well spent. Annual Reviews | Connect With Our Experts Tel: 800.523.8635 (us/can) | Tel: 650.493.4400 | Fax: 650.424.0910 | Email: service@annualreviews.org New From Annual Reviews: Annual Review of Statistics and Its Application Volume 1 • Online January 2014 • http://statistics.annualreviews.org Editor: Stephen E. Fienberg, Carnegie Mellon University Associate Editors: Nancy Reid, University of Toronto Stephen M. Stigler, University of Chicago The Annual Review of Statistics and Its Application aims to inform statisticians and quantitative methodologists, as well as all scientists and users of statistics about major methodological advances and the computational tools that allow for their implementation. It will include developments in the field of statistics, including theoretical statistical underpinnings of new methodology, as well as developments in specific application domains such as biostatistics and bioinformatics, economics, machine learning, psychology, sociology, and aspects of the physical sciences. Complimentary online access to the first volume will be available until January 2015. table of contents: • What Is Statistics? Stephen E. Fienberg • A Systematic Statistical Approach to Evaluating Evidence from Observational Studies, David Madigan, Paul E. Stang, Jesse A. Berlin, Martijn Schuemie, J. Marc Overhage, Marc A. Suchard, Bill Dumouchel, Abraham G. Hartzema, Patrick B. Ryan • The Role of Statistics in the Discovery of a Higgs Boson, David A. van Dyk • Brain Imaging Analysis, F. DuBois Bowman • Statistics and Climate, Peter Guttorp • Climate Simulators and Climate Projections, Jonathan Rougier, Michael Goldstein • Probabilistic Forecasting, Tilmann Gneiting, Matthias Katzfuss • Bayesian Computational Tools, Christian P. Robert • Bayesian Computation Via Markov Chain Monte Carlo, Radu V. Craiu, Jeffrey S. Rosenthal • Build, Compute, Critique, Repeat: Data Analysis with Latent Variable Models, David M. Blei • Structured Regularizers for High-Dimensional Problems: Statistical and Computational Issues, Martin J. Wainwright • High-Dimensional Statistics with a View Toward Applications in Biology, Peter Bühlmann, Markus Kalisch, Lukas Meier • Next-Generation Statistical Genetics: Modeling, Penalization, and Optimization in High-Dimensional Data, Kenneth Lange, Jeanette C. Papp, Janet S. Sinsheimer, Eric M. Sobel • Breaking Bad: Two Decades of Life-Course Data Analysis in Criminology, Developmental Psychology, and Beyond, Elena A. Erosheva, Ross L. Matsueda, Donatello Telesca • Event History Analysis, Niels Keiding • Statistical Evaluation of Forensic DNA Profile Evidence, Christopher D. Steele, David J. Balding • Using League Table Rankings in Public Policy Formation: Statistical Issues, Harvey Goldstein • Statistical Ecology, Ruth King • Estimating the Number of Species in Microbial Diversity Studies, John Bunge, Amy Willis, Fiona Walsh • Dynamic Treatment Regimes, Bibhas Chakraborty, Susan A. Murphy • Statistics and Related Topics in Single-Molecule Biophysics, Hong Qian, S.C. Kou • Statistics and Quantitative Risk Management for Banking and Insurance, Paul Embrechts, Marius Hofert Access this and all other Annual Reviews journals via your institution at www.annualreviews.org. Annu.Rev.Genom.HumanGenet.2008.9:387-402.Downloadedfromwww.annualreviews.org Accessprovidedby39.54.106.120on04/04/15.Forpersonaluseonly.