TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements.

The Long interspersed nuclear element 1 (LINE-1) is a primary source of genetic variation in humans and other mammals. Despite its importance, LINE-1 activity remains difficult to study because of its highly repetitive nature. Here, we developed and validated a method called TeXP to gauge LINE-1 activity accurately. TeXP builds mappability signatures from LINE-1 subfamilies to deconvolve the effect of pervasive transcription from autonomous LINE-1 activity. In particular, it apportions the multiple reads aligned to the many LINE-1 instances in the genome into these two categories. Using our method, we evaluated well-established cell lines, cell-line compartments and healthy tissues and found that the vast majority (91.7%) of transcriptome reads overlapping LINE-1 derive from pervasive transcription. We validated TeXP by independently estimating the levels of LINE-1 autonomous transcription using ddPCR, finding high concordance. Next, we applied our method to comprehensively measure LINE-1 activity across healthy somatic cells, while backing out the effect of pervasive transcription. Unexpectedly, we found that LINE-1 activity is present in many normal somatic cells. This finding contrasts with earlier studies showing that LINE-1 has limited activity in healthy somatic tissues, except for neuroprogenitor cells. Interestingly, we found that the amount of LINE-1 activity was associated with the with the amount of cell turnover, with tissues with low cell turnover rates (e.g. the adult central nervous system) showing lower LINE-1 activity. Altogether, our results show how accounting for pervasive transcription is critical to accurately quantify the activity of highly repetitive regions of the human genome

FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods.

Comprehensive and accurate identification of structural variations (SVs) from next generation sequencing data remains a major challenge. We develop FusorSV, which uses a data mining approach to assess performance and merge callsets from an ensemble of SV-calling algorithms. It includes a fusion model built using analysis of 27 deep-coverage human genomes from the 1000 Genomes Project. We identify 843 novel SV calls that were not reported by the 1000 Genomes Project for these 27 samples. Experimental validation of a subset of these calls yields a validation rate of 86.7%. FusorSV is available at https://github.com/TheJacksonLaboratory/SVE . Genome Biol 2018 Mar 20; 19(1):38

High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts.

The processes by which tumors evolve are essential to the efficacy of treatment, but quantitative understanding of intratumoral dynamics has been limited. Although intratumoral heterogeneity is common, quantification of evolution is difficult from clinical samples because treatment replicates cannot be performed and because matched serial samples are infrequently available. To circumvent these problems we derived and assayed large sets of human triple-negative breast cancer xenografts and cell cultures from two patients, including 86 xenografts from cyclophosphamide, doxorubicin, cisplatin, docetaxel, or vehicle treatment cohorts as well as 45 related cell cultures. We assayed these samples via exome-seq and/or high-resolution droplet digital PCR, allowing us to distinguish complex therapy-induced selection and drift processes among endogenous cancer subclones with cellularity uncertaint

An integrated map of structural variation in 2,504 human genomes

© 2015 Macmillan Publishers Limited. All rights reserved. Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association

De novo single-nucleotide and copy number variation in discordant monozygotic twins reveals disease-related genes

Recent studies have demonstrated genetic differences between monozygotic (MZ) twins. To test the hypothesis that early post-twinning mutational events associate with phenotypic discordance, we investigated a cohort of 13 twin pairs (n = 26) discordant for various clinical phenotypes using whole-exome sequencing and screened for copy number variation (CNV). We identified a de novo variant in PLCB1, a gene involved in the hydrolysis of lipid phosphorus in milk from dairy cows, associated with lactase non-persistence, and a variant in the mitochondrial complex I gene MT-ND5 associated with amyotrophic lateral sclerosis (ALS). We also found somatic variants in multiple genes (TMEM225B, KBTBD3, TUBGCP4, TFIP11) in another MZ twin pair discordant for ALS. Based on the assumption that discordance between twins could be explained by a common variant with variable penetrance or expressivity, we screened the twin samples for known pathogenic variants that are shared and identified a rare deletion overlapping ARHGAP11B, in the twin pair manifesting with either schizotypal personality disorder or schizophrenia. Parent-offspring trio analysis was implemented for two twin pairs to assess potential association of variants of parental origin with susceptibility to disease. We identified a de novo variant in RASD2 shared by 8-year-old male twins with a suspected diagnosis of autism spectrum disorder (ASD) manifesting as different traits. A de novo CNV duplication was also identified in these twins overlapping CD38, a gene previously implicated in ASD. In twins discordant for Tourette's syndrome, a paternally inherited stop loss variant was detected in AADAC, a known candidate gene for the disorder

Array-Based Comparative Genomic Hybridization (aCGH).

Copy number variations (CNVs) in the genomes have been suggested to play important roles in human evolution, genetic diversity, and disease susceptibility. A number of assays have been developed for the detection of CNVs, including fluorescent in situ hybridization (FISH), array-based comparative genomic hybridization (aCGH), PCR-based assays, and next-generation sequencing (NGS). In this chapter, we describe a microarray method that has been used for the detection of genome-wide CNVs, loss of heterozygosity (LOH), and uniparental disomy (UPD) associated with constitutional and neoplastic disorders. Methods Mol Biol. 2017;1541:167-179

Multicolor Fluorescence In Situ Hybridization (FISH) Approaches for Simultaneous Analysis of the Entire Human Genome.

Analysis of the organization of the human genome is vital for understanding genetic diversity, human evolution, and disease pathogenesis. A number of approaches, such as multicolor fluorescence in situ hybridization (FISH) assays, cytogenomic microarray (CMA), and next-generation sequencing (NGS) technologies, are available for simultaneous analysis of the entire human genome. Multicolor FISH-based spectral karyotyping (SKY), multiplex FISH (M-FISH), and Rx-FISH may provide rapid identification of interchromosomal and intrachromosomal rearrangements as well as the origin of unidentified extrachromosomal elements. Recent advances in molecular cytogenetics have made it possible to efficiently examine the entire human genome in a single experiment at much higher resolution and specificity using CMA and NGS technologies. Here, we present an overview of the approaches available for genome-wide analyses. © 2018 by John Wiley & Sons, Inc

TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements.

The Long interspersed nuclear element 1 (LINE-1) is a primary source of genetic variation in humans and other mammals. Despite its importance, LINE-1 activity remains difficult to study because of its highly repetitive nature. Here, we developed and validated a method called TeXP to gauge LINE-1 activity accurately. TeXP builds mappability signatures from LINE-1 subfamilies to deconvolve the effect of pervasive transcription from autonomous LINE-1 activity. In particular, it apportions the multiple reads aligned to the many LINE-1 instances in the genome into these two categories. Using our method, we evaluated well-established cell lines, cell-line compartments and healthy tissues and found that the vast majority (91.7%) of transcriptome reads overlapping LINE-1 derive from pervasive transcription. We validated TeXP by independently estimating the levels of LINE-1 autonomous transcription using ddPCR, finding high concordance. Next, we applied our method to comprehensively measure LINE-1 activity across healthy somatic cells, while backing out the effect of pervasive transcription. Unexpectedly, we found that LINE-1 activity is present in many normal somatic cells. This finding contrasts with earlier studies showing that LINE-1 has limited activity in healthy somatic tissues, except for neuroprogenitor cells. Interestingly, we found that the amount of LINE-1 activity was associated with the with the amount of cell turnover, with tissues with low cell turnover rates (e.g. the adult central nervous system) showing lower LINE-1 activity. Altogether, our results show how accounting for pervasive transcription is critical to accurately quantify the activity of highly repetitive regions of the human genome