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1.  Characterization of X Chromosome Inactivation Using Integrated Analysis of Whole-Exome and mRNA Sequencing 
PLoS ONE  2014;9(12):e113036.
In females, X chromosome inactivation (XCI) is an epigenetic, gene dosage compensatory mechanism by inactivation of one copy of X in cells. Random XCI of one of the parental chromosomes results in an approximately equal proportion of cells expressing alleles from either the maternally or paternally inherited active X, and is defined by the XCI ratio. Skewed XCI ratio is suggestive of non-random inactivation, which can play an important role in X-linked genetic conditions. Current methods rely on indirect, semi-quantitative DNA methylation-based assay to estimate XCI ratio. Here we report a direct approach to estimate XCI ratio by integrated, family-trio based whole-exome and mRNA sequencing using phase-by-transmission of alleles coupled with allele-specific expression analysis. We applied this method to in silico data and to a clinical patient with mild cognitive impairment but no clear diagnosis or understanding molecular mechanism underlying the phenotype. Simulation showed that phased and unphased heterozygous allele expression can be used to estimate XCI ratio. Segregation analysis of the patient's exome uncovered a de novo, interstitial, 1.7 Mb deletion on Xp22.31 that originated on the paternally inherited X and previously been associated with heterogeneous, neurological phenotype. Phased, allelic expression data suggested an 83∶20 moderately skewed XCI that favored the expression of the maternally inherited, cytogenetically normal X and suggested that the deleterious affect of the de novo event on the paternal copy may be offset by skewed XCI that favors expression of the wild-type X. This study shows the utility of integrated sequencing approach in XCI ratio estimation.
doi:10.1371/journal.pone.0113036
PMCID: PMC4264736  PMID: 25503791
2.  In vitro-differentiated neural cell cultures progress towards donor-identical brain tissue 
Human Molecular Genetics  2013;22(17):3534-3546.
Multiple research groups have observed neuropathological phenotypes and molecular symptoms in vitro using induced pluripotent stem cell (iPSC)-derived neural cell cultures (i.e. patient-specific neurons and glia). However, the global differences/similarities that may exist between in vitro neural cells and their tissue-derived counterparts remain largely unknown. In this study, we compared temporal series of iPSC-derived in vitro neural cell cultures to endogenous brain tissue from the same autopsy donor. Specifically, we utilized RNA sequencing (RNA-Seq) to evaluate the transcriptional progression of in vitro-differentiated neural cells (over a timecourse of 0, 35, 70, 105 and 140 days), and compared this with donor-identical temporal lobe tissue. We observed in vitro progression towards the reference brain tissue, and the following three results support this conclusion: (i) there was a significant increasing monotonic correlation between the days of our timecourse and the number of actively transcribed protein-coding genes and long intergenic non-coding RNAs (lincRNAs) (P < 0.05), consistent with the transcriptional complexity of the brain; (ii) there was an increase in CpG methylation after neural differentiation that resembled the epigenomic signature of the endogenous tissue; and (iii) there was a significant decreasing monotonic correlation between the days of our timecourse and the percent of in vitro to brain-tissue differences (P < 0.05) for tissue-specific protein-coding genes and all putative lincRNAs. Taken together, these results are consistent with in vitro neural development and physiological progression occurring predominantly by transcriptional activation of downregulated genes rather than deactivation of upregulated genes.
doi:10.1093/hmg/ddt208
PMCID: PMC3736871  PMID: 23666530
3.  Plasma cytokine profiling in sibling pairs discordant for autism spectrum disorder 
Objective
Converging lines of evidence point to the existence of immune dysfunction in autism spectrum disorder (ASD), which could directly affect several key neurodevelopmental processes. Previous studies have shown higher cytokine levels in patients with autism compared with matched controls or subjects with other developmental disorders. In the current study, we used plasma-cytokine profiling for 25 discordant sibling pairs to evaluate whether these alterations occur within families with ASD.
Methods
Plasma-cytokine profiling was conducted using an array-based multiplex sandwich ELISA for simultaneous quantitative measurement of 40 unique targets. We also analyzed the correlations between cytokine levels and clinically relevant quantitative traits (Vineland Adaptive Behavior Scale in Autism (VABS) composite score, Social Responsiveness Scale (SRS) total T score, head circumference, and full intelligence quotient (IQ)). In addition, because of the high phenotypic heterogeneity of ASD, we defined four subgroups of subjects (those who were non-verbal, those with gastrointestinal issues, those with regressive autism, and those with a history of allergies), which encompass common and/or recurrent endophenotypes in ASD, and tested the cytokine levels in each group.
Results
None of the measured parameters showed significant differences between children with ASD and their related typically developing siblings. However, specific target levels did correlate with quantitative clinical traits, and these were significantly different when the ASD subgroups were analyzed. It is notable that these differences seem to be attributable to a predisposing immunogenetic background, as no other significant differences were noticed between discordant sibling pairs. Interleukin-1β appears to be the cytokine most involved in quantitative traits and clinical subgroups of ASD.
Conclusions
In the present study, we found a lack of significant differences in plasma-cytokine levels between children with ASD and in their related non-autistic siblings. Thus, our results support the evidence that the immune profiles of children with autism do not differ from their typically developing siblings. However, the significant association of cytokine levels with the quantitative traits and the clinical subgroups analyzed suggests that altered immune responses may affect core feature of ASD.
doi:10.1186/1742-2094-10-38
PMCID: PMC3616926  PMID: 23497090
4.  Induction of Pluripotent Stem Cells from Autopsy Donor-Derived Somatic Cells 
Neuroscience letters  2011;502(3):219-224.
Human induced pluripotent stem cells (iPSCs) have become an intriguing approach for neurological disease modeling, because neural lineage-specific cell types that retain the donors' complex genetics can be established in vitro. The statistical power of these iPSC-based models, however, is dependent on accurate diagnoses of the somatic cell donors; unfortunately, many neurodegenerative diseases are commonly misdiagnosed in live human subjects. Postmortem histopathological examination of a donor's brain, combined with premortem clinical criteria, is often the most robust approach to correctly classify an individual as a disease-specific case or unaffected control. In this study, we describe iPSCs generated from a skin biopsy collected postmortem during the rapid autopsy of a 75-year-old male, whole body donor, defined as an unaffected neurological control by both clinical and histopathological criteria. These iPSCs were established in a feeder-free system by lentiviral transduction of the Yamanaka factors, Oct3/4, Sox2, Klf4, and c-Myc. Selected iPSC clones expressed both nuclear and surface antigens recognized as pluripotency markers of human embryonic stem cells (hESCs) and were able to differentiate in vitro into neurons and glia. Statistical analysis also demonstrated that fibroblast proliferation was significantly affected by biopsy site, but not donor age (within an elderly cohort). These results provide evidence that autopsy donor-derived fibroblasts can be successfully reprogrammed into iPSCs, and may provide an advantageous approach for generating iPSC-based neurological disease models.
doi:10.1016/j.neulet.2011.07.048
PMCID: PMC3195418  PMID: 21839145
induced pluripotent stem cells; genetic disease models; diagnostics; neurodegenerative diseases; postmortem; autopsy; neural differentiation
5.  IDENTIFICATION OF GENETIC VARIANTS USING BARCODED MULTIPLEXED SEQUENCING 
Nature methods  2008;5(10):887-893.
We developed a generalized framework for multiplexed resequencing of targeted regions of the human genome on the Illumina Genome Analyzer using degenerate indexed DNA sequence barcodes ligated to fragmented DNA prior to sequencing. Using this method, the DNA of multiple HapMap individuals was simultaneously sequenced at several ENCODE (ENCyclopedia of DNA Elements) regions. We then evaluated the use of Bayes factors for discovering and genotyping polymorphisms from aligned sequenced reads. If we required that predicted polymorphisms be either previously identified by dbSNP or be visually evident upon reinspection of archived ENCODE traces, we observed a false-positive rate of 11.3% using strict thresholds (Ks>1,000) for predicting variants and 69.6% for lax thresholds (Ks>10). Conversely, false-negative rates ranged from 10.8% to 90.8%, with those at stricter cut-offs occurring at lower coverage (< 10 aligned reads). These results suggest that >90% of genetic variants are discoverable using multiplexed sequencing provided sufficient coverage at the polymorphic base.
doi:10.1038/nmeth.1251
PMCID: PMC3171277  PMID: 18794863
6.  Genome-Wide Association of Bipolar Disorder Suggests an Enrichment of Replicable Associations in Regions near Genes 
PLoS Genetics  2011;7(6):e1002134.
Although a highly heritable and disabling disease, bipolar disorder's (BD) genetic variants have been challenging to identify. We present new genotype data for 1,190 cases and 401 controls and perform a genome-wide association study including additional samples for a total of 2,191 cases and 1,434 controls. We do not detect genome-wide significant associations for individual loci; however, across all SNPs, we show an association between the power to detect effects calculated from a previous genome-wide association study and evidence for replication (P = 1.5×10−7). To demonstrate that this result is not likely to be a false positive, we analyze replication rates in a large meta-analysis of height and show that, in a large enough study, associations replicate as a function of power, approaching a linear relationship. Within BD, SNPs near exons exhibit a greater probability of replication, supporting an enrichment of reproducible associations near functional regions of genes. These results indicate that there is likely common genetic variation associated with BD near exons (±10 kb) that could be identified in larger studies and, further, provide a framework for assessing the potential for replication when combining results from multiple studies.
Author Summary
Bipolar disorder (BD) is a highly heritable disease that has been difficult to characterize genetically. We have genotyped 1,190 BD cases and 401 controls to find regions of the genome associated with BD. After combining these data with previously existing genotyped samples, we did not find any genome-wide significant associations. However, when we used an additional study to prioritize loci for replication and meta-analysis purposes, we found that we were more likely to see an association in our sample with variants for which we had the highest power. We quantified this effect using logistic regression and saw a strong association between power to detect an effect based on an initial study's results and replication P-value in a second study (P = 1.5×10−7), supporting the presence of shared genetic risk factors across the studies. Moreover, this association was stronger when we restricted analysis to SNPs near coding regions, and it was further enriched when SNPs had the same direction of effect in both studies. This result supports the presence of genetic factors underlying BD near exons whose collective effect results in a detectable signal and provides a framework for assessing the potential for replication when combining results from multiple studies.
doi:10.1371/journal.pgen.1002134
PMCID: PMC3128104  PMID: 21738484
7.  Multimarker analysis and imputation of multiple platform pooling-based genome-wide association studies 
Bioinformatics  2008;24(17):1896-1902.
Summary: For many genome-wide association (GWA) studies individually genotyping one million or more SNPs provides a marginal increase in coverage at a substantial cost. Much of the information gained is redundant due to the correlation structure inherent in the human genome. Pooling-based GWA studies could benefit significantly by utilizing this redundancy to reduce noise, improve the accuracy of the observations and increase genomic coverage. We introduce a measure of correlation between individual genotyping and pooling, under the same framework that r2 provides a measure of linkage disequilibrium (LD) between pairs of SNPs. We then report a new non-haplotype multimarker multi-loci method that leverages the correlation structure between SNPs in the human genome to increase the efficacy of pooling-based GWA studies. We first give a theoretical framework and derivation of our multimarker method. Next, we evaluate simulations using this multimarker approach in comparison to single marker analysis. Finally, we experimentally evaluate our method using different pools of HapMap individuals on the Illumina 450S Duo, Illumina 550K and Affymetrix 5.0 platforms for a combined total of 1 333 631 SNPs. Our results show that use of multimarker analysis reduces noise specific to pooling-based studies, allows for efficient integration of multiple microarray platforms and provides more accurate measures of significance than single marker analysis. Additionally, this approach can be extended to allow for imputing the association significance for SNPs not directly observed using neighboring SNPs in LD. This multimarker method can now be used to cost-effectively complete pooling-based GWA studies with multiple platforms across over one million SNPs and to impute neighboring SNPs weighted for the loss of information due to pooling.
Contact: dcraig@tgen.org
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btn333
PMCID: PMC2732219  PMID: 18617537
8.  Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays 
PLoS Genetics  2008;4(8):e1000167.
We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed.
Author Summary
In this report we describe a framework for accurately and robustly resolving whether individuals are in a complex genomic DNA mixture using high-density single nucleotide polymorphism (SNP) genotyping microarrays. We develop a theoretical framework for detecting an individual's presence within a mixture, show its limits through simulation, and finally demonstrate experimentally the identification of the presence of genomic DNA of individuals within a series of highly complex genomic mixtures. Our approaches demonstrate straightforward identification of trace amounts (<1%) of DNA from an individual contributor within a complex mixture. We show how probe-intensity analysis of high-density SNP data can be used, even given the experimental noise of a microarray. We discuss the implications of these findings in two fields: forensics and genome-wide association (GWA) genetic studies. Within forensics, resolving whether an individual is contributing trace amounts of genomic DNA to a complex mixture is a tremendous challenge. Within GWA studies, there is a considerable push to make experimental data publicly available so that the data can be combined with other studies. Our findings show that such an approach does not completely conceal identity, since it is straightforward to assess the probability that a person or relative participated in a GWA study.
doi:10.1371/journal.pgen.1000167
PMCID: PMC2516199  PMID: 18769715

Results 1-8 (8)