Publications

Transposable elements (TEs) significantly contribute to shaping the diversity of the human genome, and lines of evidence suggest TEs as one of driving forces of human brain evolution. Existing computational approaches, including cross-species comparative genomics and population genetic modeling, can be adapted for the study of the role of TEs in evolution. In particular, diverse ancient and archaic human genome sequences are increasingly available, allowing reconstruction of past human migration events and holding the promise of identifying and tracking TEs among other evolutionarily important genetic variants at an unprecedented spatiotemporal resolution. However, highly degraded short DNA templates and other unique challenges presented by ancient human DNA call for major changes in current experimental and computational procedures to enable the identification of evolutionarily important TEs. Ancient human genomes are valuable resources for investigating TEs in the evolutionary context, and efforts to explore ancient human genomes will potentially provide a novel perspective on the genetic mechanism of human brain evolution and inspire a variety of technological and methodological advances. In this review, we summarize computational and experimental approaches that can be adapted to identify and validate evolutionarily important TEs, especially for human brain evolution. We also highlight strategies that leverage ancient genomic data and discuss unique challenges in ancient transposon genomics.

Transposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea .

Thyroid cancer incidences have been steadily increasing worldwide and are projected to become the fourth leading cancer diagnosis by 2030. Improved diagnosis and prognosis predictions for this type of cancer depend on understanding its genetic bases and disease biology. RAS mutations have been found in a wide range of thyroid tumors, from benign to aggressive thyroid carcinomas. Based on that and in vivo studies, it has been suggested that RAS cooperates with other driver mutations to induce tumorigenesis. This study aims to identify genetic alterations or pathways that cooperate with the RAS mutation in the pathogenesis of thyroid cancer. From a cohort of 120 thyroid carcinomas, 11 RAS-mutated samples were identified. The samples were subjected to RNA-Sequencing analyses. The mutation analysis in our eleven RAS-positive cases uncovered that four genes that belong to the Hippo pathway were mutated. The gene expression analysis revealed that this pathway was dysregulated in the RAS-positive samples. We additionally explored the mutational status and expression profiling of 60 RAS-positive papillary thyroid carcinomas (PTC) from The Cancer Genome Atlas (TCGA) cohort. Altogether, the mutational landscape and pathway enrichment analysis (gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genome (KEGG)) detected the Hippo pathway as dysregulated in RAS-positive thyroid carcinomas. Finally, we suggest a crosstalk between the Hippo and other signaling pathways, such as Wnt and BMP.

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with a complex genetic etiology. Besides the apolipoprotein E ε4 (APOE ε4) allele, a few dozen other genetic loci associated with AD have been identified through genome-wide association studies (GWAS) conducted mainly in individuals of European ancestry. Recently, several GWAS performed in other ethnic groups have shown the importance of replicating studies that identify previously established risk loci and searching for novel risk loci. APOE-stratified GWAS have yielded novel AD risk loci that might be masked by, or be dependent on, APOE alleles. We performed whole-genome sequencing (WGS) on DNA from blood samples of 331 AD patients and 169 elderly controls of Korean ethnicity who were APOE ε4 carriers. Based on WGS data, we designed a customized AD chip (cAD chip) for further analysis on an independent set of 543 AD patients and 894 elderly controls of the same ethnicity, regardless of their APOE ε4 allele status. Combined analysis of WGS and cAD chip data revealed that SNPs rs1890078 (P = 6.64E-07) and rs12594991 (P = 2.03E-07) in SORCS1 and CHD2 genes, respectively, are novel genetic variants among APOE ε4 carriers in the Korean population. In addition, nine possible novel variants that were rare in individuals of European ancestry but common in East Asia were identified. This study demonstrates that APOE-stratified analysis is important for understanding the genetic background of AD in different populations.

UNLABELLED: Hi-C is a common technique for assessing 3D chromatin conformation. Recent studies have shown that long-range interaction information in Hi-C data can be used to generate chromosome-length genome assemblies and identify large-scale structural variations. Here, we demonstrate the use of Hi-C data in detecting mobile transposable element (TE) insertions genome-wide. Our pipeline Hi-C-based TE analyzer (HiTea) capitalizes on clipped Hi-C reads and is aided by a high proportion of discordant read pairs in Hi-C data to detect insertions of three major families of active human TEs. Despite the uneven genome coverage in Hi-C data, HiTea is competitive with the existing callers based on whole-genome sequencing (WGS) data and can supplement the WGS-based characterization of the TE-insertion landscape. We employ the pipeline to identify TE-insertions from human cell-line Hi-C samples.

AVAILABILITY AND IMPLEMENTATION: HiTea is available at https://github.com/parklab/HiTea and as a Docker image.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Transposable element (TE) mobilization is a significant source of genomic variation and has been associated with various human diseases. The exponential growth of population-scale whole-genome sequencing and rapid innovations in long-read sequencing technologies provide unprecedented opportunities to study TE insertions and their functional impact in human health and disease. Identifying TE insertions, however, is challenging due to the repetitive nature of the TE sequences. Here, we review computational approaches to detecting and genotyping TE insertions using short- and long-read sequencing and discuss the strengths and weaknesses of different approaches. © 2020 Wiley Periodicals LLC.

Elucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed parallel RNA and DNA analysis after deep sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single-cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation ("birthdate") in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an "inside-out" layer formation of excitatory neurons as seen in other species. In addition our analysis allows an estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition.

BACKGROUND: Genomic rearrangements exert a heavy influence on the molecular landscape of cancer. New analytical approaches integrating somatic structural variants (SSVs) with altered gene features represent a framework by which we can assign global significance to a core set of genes, analogous to established methods that identify genes non-randomly targeted by somatic mutation or copy number alteration. While recent studies have defined broad patterns of association involving gene transcription and nearby SSV breakpoints, global alterations in DNA methylation in the context of SSVs remain largely unexplored.

RESULTS: By data integration of whole genome sequencing, RNA sequencing, and DNA methylation arrays from more than 1400 human cancers, we identify hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of a somatic structural variant (SSV) breakpoint is recurrently associated with altered expression or DNA methylation, respectively, independently of copy number alterations. CGIs with SSV-associated increased methylation are predominantly promoter-associated, while CGIs with SSV-associated decreased methylation are enriched for gene body CGIs. Rearrangement of genomic regions normally having higher or lower methylation is often involved in SSV-associated CGI methylation alterations. Across cancers, the overall structural variation burden is associated with a global decrease in methylation, increased expression in methyltransferase genes and DNA damage response genes, and decreased immune cell infiltration.

CONCLUSION: Genomic rearrangement appears to have a major role in shaping the cancer DNA methylome, to be considered alongside commonly accepted mechanisms including histone modifications and disruption of DNA methyltransferases.

Genome sequencing is often pivotal in the diagnosis of rare diseases, but many of these conditions lack specific treatments. We describe how molecular diagnosis of a rare, fatal neurodegenerative condition led to the rational design, testing, and manufacture of milasen, a splice-modulating antisense oligonucleotide drug tailored to a particular patient. Proof-of-concept experiments in cell lines from the patient served as the basis for launching an "N-of-1" study of milasen within 1 year after first contact with the patient. There were no serious adverse events, and treatment was associated with objective reduction in seizures (determined by electroencephalography and parental reporting). This study offers a possible template for the rapid development of patient-customized treatments. (Funded by Mila's Miracle Foundation and others.).