Analysis Of Structural Variants Research Articles

High density LD-based structural variations analysis in cattle genome.

Genomic structural variations represent an important source of genetic variation in mammal genomes, thus, they are commonly related to phenotypic expressions. In this work, ∼770,000 single nucleotide polymorphism genotypes from 506 animals from 19 cattle breeds were analyzed. A simple LD-based structural variation was defined, and a genome-wide analysis was performed. After applying some quality control filters, for each breed and each chromosome we calculated the linkage disequilibrium (r 2) of short range (≤100 Kb). We sorted SNP pairs by distance and obtained a set of LD means (called the expected means) using bins of 5 Kb. We identified 15,246 segments of at least 1 Kb, among the 19 breeds, consisting of sets of at least 3 adjacent SNPs so that, for each SNP, r 2 within its neighbors in a 100 Kb range, to the right side of that SNP, were all bigger than, or all smaller than, the corresponding expected mean, and their P-value were significant after a Benjamini-Hochberg multiple testing correction. In addition, to account just for homogeneously distributed regions we considered only SNPs having at least 15 SNP neighbors within 100 Kb. We defined such segments as structural variations. By grouping all variations across all animals in the sample we defined 9,146 regions, involving a total of 53,137 SNPs; representing the 6.40% (160.98 Mb) from the bovine genome. The identified structural variations covered 3,109 genes. Clustering analysis showed the relatedness of breeds given the geographic region in which they are evolving. In summary, we present an analysis of structural variations based on the deviation of the expected short range LD between SNPs in the bovine genome. With an intuitive and simple definition based only on SNPs data it was possible to discern closeness of breeds due to grouping by geographic region in which they are evolving.

Comparative genomic analysis of Klebsiella pneumonia (LCT-KP214) and a mutant strain (LCT-KP289) obtained after spaceflight.

BackgroundWith the development of space science, it is important to analyze the relationship between the space environment and genome variations that might cause phenotypic changes in microbes. Klebsiella pneumoniae is commonly found on the human body and is resistant to multiple drugs. To study space-environment-induced genome variations and drug resistance changes, K. pneumoniae was carried into outer space by the Shenzhou VIII spacecraft.ResultsThe K. pneumoniae strain LCT-KP289 was selected after spaceflight based on its phenotypic differences compared to the ground-control strain. Analysis of genomic structural variations revealed one inversion, 25 deletions, fifty-nine insertions, two translocations and six translocations with inversions. In addition, 155 and 400 unique genes were observed in LCT-KP214 and LCT-KP289, respectively, including the gene encoding dihydroxyacetone kinase, which generates the ATP and NADH required for microbial growth. Furthermore, a large number of mutant genes were related to transport and metabolism. Phylogenetic analysis revealed that most genes in these two strains had a dN/dS value greater than 1, indicating that the strain diversity increased after spaceflight. Analysis of drug-resistance phenotypes revealed that the K. pneumoniae strain LCT-KP289 was resistant to sulfamethoxazole, whereas the control strain, LCT-KP214, was not; both strains were resistant to benzylpenicillin, ampicillin, lincomycin, vancomycin, chloramphenicol and streptomycin. The sulfamethoxazole resistance may be associated with sequences in Scaffold7 in LCT-KP289, which were not observed in LCT-K214; this scaffold contained the gene sul1. In the strain LCT-KP289, we also observed a drug-resistance integron containing emrE (confers multidrug resistance) and ant (confers resistance to spectinomycin, streptomycin, tobramycin, kanamycin, sisomicin, dibekacin, and gentamicin). The gene ampC (confers resistance to penicillin, cephalosporin-ii and cephalosporin-i) was present near the integron. In addition, 30 and 26 drug-resistance genes were observed in LCT-KP289 and LCT-KP214, respectively.ConclusionsComparison of a K. pneumoniae strain obtained after spaceflight with the ground-control strain revealed genome variations and phenotypic changes and elucidated the genomic basis of the acquired drug resistance. These data pave the way for future studies on the effects of spaceflight.

STRUCTURAL VARIANTS SHUFFLE CHROMATIN TO ACTIVATE GFI1 FAMILY ONCOGENES IN MEDULLOBLASTOMA

BACKGROUND: Genomics has illuminated the extensive intertumoural heterogeneity of medulloblastoma and identified at least four distinct molecular subgroups of the disease. Group 3 and Group 4 subgroup medulloblastomas account for the majority of pediatric cases, yet, oncogenic drivers for these subtypes remain poorly understood. Exome and genome sequencing studies have confirmed a paucity of recurrent gene-level mutations in Group 3 and Group 4, suggesting that alternative oncogenic mechanisms must account for the large fraction of cases that cannot currently be explained by single-nucleotide variants or insertions/deletions alone. METHODS: Analysis of whole-genome sequencing data consisting of 128 primary Group 3 and Group 4 medulloblastoma samples facilitated a systematic, high-resolution screen for chromosomal breakpoints recurrently targeting novel medulloblastoma drivers by structural variation. A non-overlapping set of 22 medulloblastomas was sequenced by long-range paired-end mapping in order to validate structural variants observed in our discovery cohort. Select cases of interest were also investigated at the epigenome-level using a combination of whole-genome bisulphite sequencing and enhancer histone mark ChIP-sequencing. RESULTS: Our systematic analysis of structural variants identified highly disparate genomic structural rearrangements, restricted to Groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 & GFI1B. Diverse mechanisms of structural variation, including duplications, deletions, inversions, translocations, and other complex genomic variants were observed in nearly all GFI1/1B-activated cases. Comprehensive characterization of these structural variants established that GFI1/GFI1B expression becomes activated through relocation of their coding sequences to genomic regions of transcriptionally active chromatin. Functional analyses performed in mice confirmed the oncogenicity of Gfi1/Gfi1b in the context of medulloblastoma and demonstrated apparent synergy between both of these candidates and the c-Myc oncogene. CONCLUSIONS: These studies establish GFI1 and GFI1B as novel, highly prevalent medulloblastoma oncogenes specifically active in Group 3 and Group 4. Given their high frequencies of activation, GFI1 and GFI1B represent excellent candidates for prioritization of molecularly targeted therapy aimed at treatment of a significant proportion of Group 3 and Group 4 medulloblastoma patients. SECONDARY CATEGORY: Pediatrics.

CIRCUS: a package for Circos display of structural genome variations from paired-end and mate-pair sequencing data.

BackgroundDetection of large genomic rearrangements, such as large indels, duplications or translocations is now commonly achieved by next generation sequencing (NGS) approaches. Recently, several tools have been developed to analyze NGS data but the resulting files are difficult to interpret without an additional visualization step. Circos (Genome Res, 19:1639–1645, 2009), a Perl script, is a powerful visualization software that requires setting up numerous configuration files with a large number of parameters to handle. R packages like RCircos (BMC Bioinformatics, 14:244, 2013) or ggbio (Genome Biol, 13:R77, 2012) provide functions to display genomic data as circular Circos-like plots. However, these tools are very general and lack the functions needed to filter, format and adjust specific input genomic data.ResultsWe implemented an R package called CIRCUS to analyze genomic structural variations. It generates both data and configuration files necessary for Circos, to produce graphs. Only few R pre-requisites are necessary. Options are available to deal with heterogeneous data, various chromosome numbers and multi-scale analysis.ConclusionCIRCUS allows fast and versatile analysis of genomic structural variants with Circos plots for users with limited coding skills.

Gene copy number alterations in the azoospermia-associated AZFc region and their effect on spermatogenic impairment.

The azoospermia factor c (AZFc) region in the long arm of human Y chromosome is characterized by massive palindromes. It harbors eight multi-copy gene families that are expressed exclusively or predominantly in testis. To assess systematically the role of the AZFc region and these eight gene families in spermatogenesis, we conducted a comprehensive molecular analysis (including Y chromosome haplogrouping, AZFc deletion typing and gene copy quantification) in 654 idiopathic infertile men and 781 healthy controls in a Han Chinese population. The b2/b3 partial deletion (including both deletion-only and deletion-duplication) was consistently associated with spermatogenic impairment. In the subjects without partial AZFc deletions, a notable finding was that the frequency of DAZ and/or BPY2 copy number alterations in the infertile group was significantly higher than in the controls. Combined patterns of DAZ and/or BPY2 copy number abnormality were associated with spermatogenic impairment when compared with the pattern of all AZFc genes with common level copies. In addition, in Y chromosome haplogroup O1 (Y-hg O1), the frequency of copy number alterations of all eight gene families was significantly higher in the case group than that in the control group. Our findings indicate that the DAZ, BPY2 genes may be prominent players in spermatogenesis, and genomic rearrangements may be enriched in individuals belonging to Y-hg O1. Our findings emphasize the necessity of routine molecular analysis of AZFc structural variation during the workup of azoospermia and/or oligozoospermia, which may diminish the genetic risk of assisted reproduction.

Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm.

BackgroundPopulation genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data. However, the genotypes at known variable sites can only be inferred with uncertainty from low coverage data. Thus, statistical approaches that infer genotype likelihoods, test hypotheses, and estimate population parameters without requiring accurate genotypes are becoming popular. Unfortunately, the current implementations of these methods are intended to analyse only single nucleotide and short indel variation, and they usually assume that the two alleles in a heterozygous individual are sampled with equal probability. This is generally false for structural variants detected with paired ends or split reads. Therefore, the population genetics of structural variants cannot be studied, unless a painstaking and potentially biased genotyping is performed first.ResultsWe present svgem, an expectation-maximization implementation to estimate allele and genotype frequencies, calculate genotype posterior probabilities, and test for Hardy-Weinberg equilibrium and for population differences, from the numbers of times the alleles are observed in each individual. Although applicable to single nucleotide variation, it aims at bi-allelic structural variation of any type, observed by either split reads or paired ends, with arbitrarily high allele sampling bias. We test svgem with simulated and real data from the 1000 Genomes Project.Conclusionssvgem makes it possible to use low-coverage sequencing data to study the population distribution of structural variants without having to know their genotypes. Furthermore, this advance allows the combined analysis of structural and nucleotide variation within the same genotype-free statistical framework, thus preventing biases introduced by genotype imputation.

Spatio-temporal variability of copepod abundance along the 20 °S monitoring transect in the Northern Benguela upwelling system from 2005 to 2011.

Long-term data sets are essential to understand climate-induced variability in marine ecosystems. This study provides the first comprehensive analysis of longer-term temporal and spatial variations in zooplankton abundance and copepod community structure in the northern Benguela upwelling system from 2005 to 2011. Samples were collected from the upper 200 m along a transect at 20°S perpendicular to the coast of Namibia to 70 nm offshore. Based on seasonal and interannual trends in surface temperature and salinity, three distinct time periods were discernible with stronger upwelling in spring and extensive warm-water intrusions in late summer, thus, high temperature amplitudes, in the years 2005/06 and 2010/11, and less intensive upwelling followed by weaker warm-water intrusions from 2008/09 to 2009/10. Zooplankton abundance reflected these changes with higher numbers in 2005/06 and 2010/11. In contrast, zooplankton density was lower in 2008/09 and 2009/10, when temperature gradients from spring to late summer were less pronounced. Spatially, copepod abundance tended to be highest between 30 and 60 nautical miles off the coast, coinciding with the shelf break and continental slope. The dominant larger calanoid copepods were Calanoides carinatus, Metridia lucens and Nannocalanus minor. On all three scales studied, i.e. spatially from the coast to offshore waters as well as temporally, both seasonally and interannually, maximum zooplankton abundance was not coupled to the coldest temperature regime, and hence strongest upwelling intensity. Pronounced temperature amplitudes, and therefore strong gradients within a year, were apparently important and resulted in higher zooplankton abundance.

Biological relevance of CNV calling methods using familial relatedness including monozygotic twins.

BackgroundStudies involving the analysis of structural variation including Copy Number Variation (CNV) have recently exploded in the literature. Furthermore, CNVs have been associated with a number of complex diseases and neurodevelopmental disorders. Common methods for CNV detection use SNP, CNV, or CGH arrays, where the signal intensities of consecutive probes are used to define the number of copies associated with a given genomic region. These practices pose a number of challenges that interfere with the ability of available methods to accurately call CNVs. It has, therefore, become necessary to develop experimental protocols to test the reliability of CNV calling methods from microarray data so that researchers can properly discriminate biologically relevant data from noise.ResultsWe have developed a workflow for the integration of data from multiple CNV calling algorithms using the same array results. It uses four CNV calling programs: PennCNV (PC), Affymetrix® Genotyping Console™ (AGC), Partek® Genomics Suite™ (PGS) and Golden Helix SVS™ (GH) to analyze CEL files from the Affymetrix® Human SNP 6.0 Array™. To assess the relative suitability of each program, we used individuals of known genetic relationships. We found significant differences in CNV calls obtained by different CNV calling programs.ConclusionsAlthough the programs showed variable patterns of CNVs in the same individuals, their distribution in individuals of different degrees of genetic relatedness has allowed us to offer two suggestions. The first involves the use of multiple algorithms for the detection of the largest possible number of CNVs, and the second suggests the use of PennCNV over all other methods when the use of only one software program is desirable.

Identification and mapping of a novel dominant resistance gene, TuRB07 to Turnip mosaic virus in Brassica rapa

A novel dominant resistance gene, TuRB07, was found to confer resistance to an isolate of TuMV strain C4 in B. rapa line VC1 and mapped on the top of chromosome A06. The inheritance of resistance to Turnip mosaic virus in Brassica rapa was investigated by crossing the resistant line, VC1 with the susceptible line, SR5, and genotyping and phenotyping diverse progenies derived from this cross. Both a doubled haploid population, VCS3M-DH, an F2 and two BC1 (F1×VC1 and F1×SR5) populations were created. Population tests revealed that the resistance to the TuMV C4 isolate in B. rapa is controlled by a single dominant gene. This resistance gene, TuRB07 was positioned on the top of linkage group A06 of the B. rapa genome through bulk segregation analysis and fine mapping recombinants in three doubled haploid- and one backcross population using microsatellite markers developed from BAC end sequences. Within the region between the two closely linked markers flanking TuRB07, H132A24-s1, and KS10960, in the Chiifu reference genome, two genes encoding nucleotide-binding site and leucine-rich repeat proteins with a coiled-coil motif (CC-NBS-LRR), Bra018862 and Bra018863 were identified as candidate resistance genes. The gene Bra018862 is truncated, but the gene Bra018863 has all the domains to function. Furthermore, the analysis of structural variation using resequencing data of VC1 and SR5 revealed that Bra018863 might be a functional gene because the gene has no structural variation in the resistant line VC1 when compared with Chiifu, whereas at the other NBS-LRR genes large deletions were identified in the resistant line. Allelic differences of Bra018863 were found between VC1 and SR5, supporting the notion that this gene is a putative candidate gene for the virus resistance.

RAG-Mediated Recombination Is The Predominant Driver Of Oncogenic Rearrangement In ETV6-RUNX1 Acute Lymphoblastic Leukemia

▪Approximately 25% of pediatric B-cell precursor ALL are characterized by the ETV6-RUNX1 fusion and are associated with a favorable prognosis. Monozygotic twin studies with concordant ALL and ‘backtracking' studies using archived neonatal blood spots established that ETV6-RUNX1 is an initiating event arising prenatally in a committed B-cell progenitor. However, the fusion gene is not sufficient on its own to cause overt leukemia and a number of subsequent studies have now provided strong evidence that additional mutations are essential for the clinical development of ALL.To obtain a detailed understanding of genetic events that drive this subtype of ALL, we carried out extensive genomic analysis in patients with ETV6-RUNX1 ALL. A total of 57 cases with diagnostic (leukemic) cell DNA paired with matched, remission samples as a source of constitutive DNA were used for exome sequencing (n=56) and low-depth wholegenome sequencing for structural variation (SV) analysis (n=51). Integrative analysis of exome and wholegenome data was performed and data were evaluated for recurrent gene mutations, copy number alterations and genomic rearrangements. Signatures of somatic mutation and structural variation were studied for insights into operative mutational processes and exposures that may drive ETV6-RUNX1pathogenesis.Wholegenome profiling identified 524 somatic SVs (average:11, range 0-49) including 34 tandem duplications, 66 inversions, 106 intrachromosomal translocations and 317 deletions. Resolution of the breakpoint junction to the base-pair level was possible for 354 SVs and in 40% of these breakpoints, we identified a significant enrichment of V(D)J recombination signal sequences or motifs that closely approximate these (E-value=3.8x10-116). Correlation with chromatin marks reveals a ten-fold genomewide enrichment of SVs (p<2.2x10-16) at promoters and enhancers of genes actively transcribed in early B-lineage development. Overall, 83% of resolved rearrangements mapping to promoters and 76% of rearrangements mapping to enhancer regions were in close proximity to a V(D)J recombination sequence motif as opposed to an average of 29% of the rearrangements in other chromatin states. These findings suggest that RAG-mediated genomic rearrangement is the dominant mutational process driving SV in ETV6-RUNX1 ALL. Single-cell tracking of genomic rearrangements bearing the hallmarks of aberrant V(D)J targeting in two patients, shows that these can occur multiple times and in distinct clones. This suggests that this mechanism is not restricted to one founder cell but is rather continuous during leukemic evolution and likely to contribute to the branching clonal phylogenies observed in ETV6-RUNX1ALL at presentation.Exome sequencing analysis confirmed 775 somatic substitutions and 16 indels across 715 protein coding genes. Oncogenic mutations in KRAS, NRAS, CTCF, DAXX, EZH2, and KDM6A are described as well as components of the cohesion complex including STAG2, SMC5 and SMC1A. Integrative analysis of whole-genome and exome sequencing data identified ATF7IP, MGA and STAG2 to be recurrently affected by both deletions or inactivating mutations and highlights their role as novel tumor suppressors in ETV6-RUNX1 ALL.Sequence context analyses on the acquired point mutations identifies two distinct mutational signatures that are operative in ETV6-RUNX1 ALL, signature A characterized by C>T transitions at CpGs and signature B characterized by C>G and C>T at TpCs, contributing 56% and 32% of all substitutions respectively. Signature B is consistent with the reported preference of the APOBEC family of enzymes and is often observed in patients presenting with a hypermutator phenotype and dense clustering of mutations.We report the identification of a novel spectrum of somatic mutations in ETV6-RUNX1 ALL and present the first detailed characterization of the genomic landscape of this ALL subtype. Our analysis shows that the critical secondary events to the ETV6-RUNX1 fusion gene formation are genomic rearrangements mostly driven by aberrant V(D)J recombination events targeting of actively transcribed genes during early B-Cell development. This represents a unique mechanism of genomic instability in cancer, that specifically targets the very genes required for normal B-Cell development and survival, which may in part explain the positive therapeutic response in this subtype of ALL. Disclosures:No relevant conflicts of interest to declare.

Analysis of structural variations of the precipitate based on monitoring the industrial electrolysis of copper powders of various brands

This study is associated with the solution to the blending problem of the charge for the output of ready articles. The main requirements are claimed to the specific surface and the packed density of the pow� ders of basic brands PML0, PMS�1, and GG. The dynamics of the development of the dendrite depositions for powders of mentioned brands with the simultaneous registration of the cathodic overvoltage is investigated under industrial experimental conditions. The procedure is developed and the results of the continuous mon� itoring of the deposition growth with the direct immersion of a video camera into the electrolyte are pre� sented. The reproducibility of the results is evaluated statistically. Based on the galvanostatic crystallization model of the dendrite deposition on the rod electrode, the dynamics of varying the density ( N) and radius (r t ) of growing tips on the growth front is calculated. It is established by variance analysis that structural param� eters N and rt are individual for depositions of every brand, so that the preparation conditions of the deposi� tion during the electrolysis should be strictly fulfilled as the charge forms.

Rebelling for a reason: protein structural "outliers".

Analysis of structural variation in domain superfamilies can reveal constraints in protein evolution which aids protein structure prediction and classification. Structure-based sequence alignment of distantly related proteins, organized in PASS2 database, provides clues about structurally conserved regions among different functional families. Some superfamily members show large structural differences which are functionally relevant. This paper analyses the impact of structural divergence on function for multi-member superfamilies, selected from the PASS2 superfamily alignment database. Functional annotations within superfamilies, with structural outliers or ‘rebels’, are discussed in the context of structural variations. Overall, these data reinforce the idea that functional similarities cannot be extrapolated from mere structural conservation. The implication for fold-function prediction is that the functional annotations can only be inherited with very careful consideration, especially at low sequence identities.

Unraveling genomic variation from next generation sequencing data

Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have been generated in various biological areas. Few of these areas, which get shaped by the new technological advances, involve evolution of species, microbial mapping, population genetics, genome-wide association studies (GWAs), comparative genomics, variant analysis, gene expression, gene regulation, epigenetics and personalized medicine. While NGS techniques stand as key players in modern biological research, the analysis and the interpretation of the vast amount of data that gets produced is a not an easy or a trivial task and still remains a great challenge in the field of bioinformatics. Therefore, efficient tools to cope with information overload, tackle the high complexity and provide meaningful visualizations to make the knowledge extraction easier are essential. In this article, we briefly refer to the sequencing methodologies and the available equipment to serve these analyses and we describe the data formats of the files which get produced by them. We conclude with a thorough review of tools developed to efficiently store, analyze and visualize such data with emphasis in structural variation analysis and comparative genomics. We finally comment on their functionality, strengths and weaknesses and we discuss how future applications could further develop in this field.

Structural Dynamic Analysis and Optimization of High-Speed Precision Machining Center Column

The theory of structural dynamic analysis is put forward firstly. Then the dynamic performance of HMC80 high-speed precision machining center column is analyzed by means of finite element method. The dynamic performance of the column is analyzed using structural dynamic optimization theory and variation analysis with the thickness of wall plate and the inner rib plates as the parameters thirdly. Based on the analysis results, the structure optimization scheme of the column is obtained. The structure optimization scheme is analyzed and the analysis results show that the dynamic performance of the column optimization scheme is improved obviously.

Phenotypic impact of genomic structural variation: insights from and for human disease

Genomic structural variants have long been implicated in phenotypic diversity and human disease, but dissecting the mechanisms by which they exert their functional impact has proven elusive. Recently however, developments in high-throughput DNA sequencing and chromosomal engineering technology have facilitated the analysis of structural variants in human populations and model systems in unprecedented detail. In this Review, we describe how structural variants can affect molecular and cellular processes, leading to complex organismal phenotypes, including human disease. We further present advances in delineating disease-causing elements that are affected by structural variants, and we discuss future directions for research on the functional consequences of structural variants.

Strong signatures of selection in the domestic pig genome

Domestication of wild boar ( Sus scrofa ) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig—the elongation of the back and an increased number of vertebrae. The three loci were associated with the NR6A1, PLAG1 , and LCORL genes. The latter two have repeatedly been associated with loci controlling stature in other domestic animals and in humans. Most European domestic pigs are homozygous for the same haplotype at these three loci. We found an excess of derived nonsynonymous substitutions in domestic pigs, most likely reflecting both positive selection and relaxed purifying selection after domestication. Our analysis of structural variation revealed four duplications at the KIT locus that were exclusively present in white or white-spotted pigs, carrying the Dominant white , Patch , or Belt alleles. This discovery illustrates how structural changes have contributed to rapid phenotypic evolution in domestic animals and how alleles in domestic animals may evolve by the accumulation of multiple causative mutations as a response to strong directional selection.

Fastbreak: a tool for analysis and visualization of structural variations in genomic data

Genomic studies are now being undertaken on thousands of samples requiring new computational tools that can rapidly analyze data to identify clinically important features. Inferring structural variations in cancer genomes from mate-paired reads is a combinatorially difficult problem. We introduce Fastbreak, a fast and scalable toolkit that enables the analysis and visualization of large amounts of data from projects such as The Cancer Genome Atlas.

Genome mapping on nanochannel arrays for structural variation analysis and sequence assembly

We describe genome mapping on nanochannel arrays. In this approach, specific sequence motifs in single DNA molecules are fluorescently labeled, and the DNA molecules are uniformly stretched in thousands of silicon channels on a nanofluidic device. Fluorescence imaging allows the construction of maps of the physical distances between occurrences of the sequence motifs. We demonstrate the analysis, individually and as mixtures, of 95 bacterial artificial chromosome (BAC) clones that cover the 4.7-Mb human major histocompatibility complex region. We obtain accurate, haplotype-resolved, sequence motif maps hundreds of kilobases in length, resulting in a median coverage of 114× for the BACs. The final sequence motif map assembly contains three contigs. With an average distance of 9 kb between labels, we detect 22 haplotype differences. We also use the sequence motif maps to provide scaffolds for de novo assembly of sequencing data. Nanochannel genome mapping should facilitate de novo assembly of sequencing reads from complex regions in diploid organisms, haplotype and structural variation analysis and comparative genomics.

Functional Genomics Approach for Identification of Molecular Processes Underlying Neurodegenerative Disorders in Prion Diseases

Prion diseases or transmissible spongiform encephalopathies (TSEs) are infectious neurodegenerative disorders leading to death. These include Cresutzfeldt-Jakob disease (CJD), familial, sporadic and variant CJD and kuru in humans; and animal TSEs include scrapie in sheep, bovine spongiform encephalopathy (BSE) in cattle, chronic wasting disease (CWD) of mule deer and elk, and transmissible mink encephalopathy. All these TSEs share common pathological features such as accumulation of mis-folded prion proteins in the central nervous system leading to cellular dysfunction and cell death. It is important to characterize the molecular pathways and events leading to prion induced neurodegeneration. Here we discuss the impact of the functional genomics approaches including microarrays, subtractive hybridization and microRNA profiling in elucidating transcriptional cascades at different stages of disease. Many of these transcriptional changes have been observed in multiple neurodegenerative diseases which may aid in identification of biomarkers for disease. A comprehensive characterization of expression profiles implicated in neurodegenerative disorders will undoubtedly advance our understanding on neuropathology and dysfunction during prion disease and other neurodegenerative disorders. We also present an outlook on the future work which may focus on analysis of structural genetic variation, genome and transcriptome sequencing using next generation sequencing with an integrated approach on animal and human TSE related studies.

Genome-wide Transcriptome Profiling Reveals the Functional Impact of Rare De Novo and Recurrent CNVs in Autism Spectrum Disorders

Copy-number variants (CNVs) are a major contributor to the pathophysiology of autism spectrum disorders (ASDs), but the functional impact of CNVs remains largely unexplored. Because brain tissue is not available from most samples, we interrogated gene expression in lymphoblasts from 244 families with discordant siblings in the Simons Simplex Collection in order to identify potentially pathogenic variation. Our results reveal that the overall frequency of significantly misexpressed genes (which we refer to here as outliers) identified in probands and unaffected siblings does not differ. However, in probands, but not their unaffected siblings, the group of outlier genes is significantly enriched in neural-related pathways, including neuropeptide signaling, synaptogenesis, and cell adhesion. We demonstrate that outlier genes cluster within the most pathogenic CNVs (rare de novo CNVs) and can be used for the prioritization of rare CNVs of potentially unknown significance. Several nonrecurrent CNVs with significant gene-expression alterations are identified (these include deletions in chromosomal regions 3q27, 3p13, and 3p26 and duplications at 2p15), suggesting that these are potential candidate ASD loci. In addition, we identify distinct expression changes in 16p11.2 microdeletions, 16p11.2 microduplications, and 7q11.23 duplications, and we show that specific genes within the 16p CNV interval correlate with differences in head circumference, an ASD-relevant phenotype. This study provides evidence that pathogenic structural variants have a functional impact via transcriptome alterations in ASDs at a genome-wide level and demonstrates the utility of integrating gene expression with mutation data for the prioritization of genes disrupted by potentially pathogenic mutations.