AluScan: a method for genome-wide scanning of sequence and structure variations in the human genome

Forward-reverse mutation cycles in cancer cell lines under chemical treatments

Spontaneous forward-reverse mutations were reported by us earlier in clinical samples from various types of cancers and in HeLa cells under normal culture conditions. To investigate the effects of chemical stimulations on such mutation cycles, the present study examined single nucleotide variations (SNVs) and copy number variations (CNVs) in HeLa and A549 cells exposed to wogonin-containing or acidic medium. In wogonin, both cell lines showed a mutation cycle during days 16-18. In acidic medium, both cell lines displayed multiple mutation cycles of different magnitudes. Genomic feature colocalization analysis suggests that CNVs tend to occur in expanded and unstable regions, and near promoters, histones, and non-coding transcription sites. Moreover, phenotypic variations in cell morphology occurred during the forward-reverse mutation cycles under both types of chemical treatments. In conclusion, chemical stresses imposed by wogonin or acidity promoted cyclic forward-reverse mutations in both HeLa and A549 cells to different extents.

Generation of somatic de novo structural variation as a hallmark of cellular senescence in human lung fibroblasts

Cellular senescence is characterized by replication arrest in response to stress stimuli. Senescent cells accumulate in aging tissues and can trigger organ-specific and possibly systemic dysfunction. Although senescent cell populations are heterogeneous, a key feature is that they exhibit epigenetic changes. Epigenetic changes such as loss of repressive constitutive heterochromatin could lead to subsequent LINE-1 derepression, a phenomenon often described in the context of senescence or somatic evolution. LINE-1 elements decode the retroposition machinery and reverse transcription generates cDNA from autonomous and non-autonomous TEs that can potentially reintegrate into genomes and cause structural variants. Another feature of cellular senescence is mitochondrial dysfunction caused by mitochondrial damage. In combination with impaired mitophagy, which is characteristic of senescent cells, this could lead to cytosolic mtDNA accumulation and, as a genomic consequence, integrations of mtDNA into nuclear DNA (nDNA), resulting in mitochondrial pseudogenes called numts. Thus, both phenomena could cause structural variants in aging genomes that go beyond epigenetic changes. We therefore compared proliferating and senescent IMR-90 cells in terms of somatic de novo numts and integrations of a non-autonomous composite retrotransposons - the so-called SVA elements-that hijack the retropositional machinery of LINE-1. We applied a subtractive and kinetic enrichment technique using proliferating cell DNA as a driver and senescent genomes as a tester for the detection of nuclear flanks of de novo SVA integrations. Coupled with deep sequencing we obtained a genomic readout for SVA retrotransposition possibly linked to cellular senescence in the IMR-90 model. Furthermore, we compared the genomes of proliferative and senescent IMR-90 cells by deep sequencing or after enrichment of nuclear DNA using AluScan technology. A total of 1,695 de novo SVA integrations were detected in senescent IMR-90 cells, of which 333 were unique. Moreover, we identified a total of 81 de novo numts with perfect identity to both mtDNA and nuclear hg38 flanks. In summary, we present evidence for possible age-dependent structural genomic changes by paralogization that go beyond epigenetic modifications. We hypothesize, that the structural variants we observe potentially impact processes associated with replicative aging of IMR-90 cells.

Copy number variation profile-based genomic typing of premenstrual dysphoric disorder in Chinese

Premenstrual dysphoric disorder (PMDD) affects nearly 5% women of reproductive age. Symptomatic heterogeneity, together with largely unknown genetics, have greatly hindered its effective treatment. In the present study, analysis of genomic sequencing-based copy-number-variations (CNVs) called from 100-kb white blood cell DNA sequence windows by means of semi-supervised clustering led to the segregation of patient genomes into the D and V groups, which correlated with the depression and invasion clinical types respectively with 89.0% consistency. Application of diagnostic CNV features selected using the correlation-based machine-learning method enabled the classification of the CNVs obtained into the D group, V group, total-patient group and control group with an average accuracy of 83.0%. The power of the diagnostic CNV features was 0.98 on average, suggesting that these CNV features could be employed for the molecular diagnosis of the major clinical types of PMDD. This demonstrated concordnce between the CNV profiles and clinical types of PMDD supported the validity of symptom-based diagnosis of PMDD for differentiating between its two major clinical types, as well as the predominanly genetic nature of PMDD with a host of overlaps between multiple susceptibility genes/pathways and the diagnostic CNV features as indicators of involvement in PMDD etiology.

NGS-based identification and tracing of microsatellite instability from minute amounts DNA using inter-Alu-PCR

Sensitive detection of microsatellite instability (MSI) in tissue or liquid biopsies using next generation sequencing (NGS) has growing prognostic and predictive applications in cancer. However, the complexities of NGS make it cumbersome as compared to established multiplex-PCR detection of MSI. We present a new approach to detect MSI using inter-Alu-PCR followed by targeted NGS, that combines the practical advantages of multiplexed-PCR with the breadth of information provided by NGS. Inter-Alu-PCR employs poly-adenine repeats of variable length present in every Alu element and provides a massively-parallel, rapid approach to capture poly-A-rich genomic fractions within short 80–150bp amplicons generated from adjacent Alu-sequences. A custom-made software analysis tool, MSI-tracer, enables Alu-associated MSI detection from tissue biopsies or MSI-tracing at low-levels in circulating-DNA. MSI-associated indels at somatic-indel frequencies of 0.05–1.5% can be detected depending on the availability of matching normal tissue and the extent of instability. Due to the high Alu copy-number in human genomes, a single inter-Alu-PCR retrieves enough information for identification of MSI-associated-indels from ∼100 pg circulating-DNA, reducing current limits by ∼2-orders of magnitude and equivalent to circulating-DNA obtained from finger-sticks. The combined practical and informational advantages of inter-Alu-PCR make it a powerful tool for identifying tissue-MSI-status or tracing MSI-associated-indels in liquid biopsies.

Genomic subtyping of liver cancers with prognostic application

BACKGROUND

Cancer subtyping has mainly relied on pathological and molecular means. Massively parallel sequencing-enabled subtyping requires genomic markers to be developed based on global features rather than individual mutations for effective implementation.

METHODS

In the present study, the whole genome sequences (WGS) of 110 liver cancers of Japanese patients published with different pathologies were analyzed with respect to their single nucleotide variations (SNVs) comprising both gain-of-heterozygosity (GOH) and loss-of-heterozygosity (LOH) mutations, the signatures of combined GOH and LOH mutations, along with recurrent copy number variations (CNVs).

RESULTS

The results, obtained based on the WGS sequences as well as the Exome subset within the WGSs that covered ~ 2.0% of the WGS and the AluScan-subset within the WGSs that were amplifiable by Alu element-consensus primers and covered ~ 2.1% of the WGS, indicated that the WGS samples could be employed with the mutational parameters of SNV load, LOH%, the Signature α%, and survival-associated recurrent CNVs (srCNVs) as genomic markers for subtyping to stratify liver cancer patients prognostically into the long and short survival subgroups. The usage of the AluScan-subset data, which could be implemented with sub-micrograms of DNA samples and vastly reduced sequencing analysis task, outperformed the usage of WGS data when LOH% was employed as stratifying criterion.

CONCLUSIONS

Thus genomic subtyping performed with novel genomic markers identified in this study was effective in predicting patient-survival duration, with cohorts of hepatocellular carcinomas alone and those including intrahepatic cholangiocarcinomas. Such relatively heterogeneity-insensitive genomic subtyping merits further studies with a broader spectrum of cancers.

AluScanCNV2: An R package for copy number variation calling and cancer risk prediction with next-generation sequencing data

The usage of next-generation sequencing (NGS) to detect copy number variation (CNV) is widely accepted in cancer research. Based on an AluScanCNV software developed by us previously, an AluScanCNV2 software has been developed in the present study as an R package that performs CNV detection from NGS data obtained through AluScan, whole-genome sequencing or other targeted NGS platforms. Its applications would include the expedited usage of somatic CNVs for cancer subtyping, and usage of recurrent germline CNVs to perform machine learning-assisted prediction of a test subject's susceptibility to cancer.

Forward and reverse mutations in stages of cancer development

Background

Massive occurrences of interstitial loss of heterozygosity (LOH) likely resulting from gene conversions were found by us in different cancers as a type of single-nucleotide variations (SNVs), comparable in abundance to the commonly investigated gain of heterozygosity (GOH) type of SNVs, raising the question of the relationships between these two opposing types of cancer mutations.

Methods

In the present study, SNVs in 12 tetra sample and 17 trio sample sets from four cancer types along with copy number variations (CNVs) were analyzed by AluScan sequencing, comparing tumor with white blood cells as well as tissues vicinal to the tumor. Four published “nontumor”-tumor metastasis trios and 246 pan-cancer pairs analyzed by whole-genome sequencing (WGS) and 67 trios by whole-exome sequencing (WES) were also examined.

Results

Widespread GOHs enriched with CG-to-TG changes and associated with nearby CNVs and LOHs enriched with TG-to-CG changes were observed. Occurrences of GOH were 1.9-fold higher than LOH in “nontumor” tissues more than 2 cm away from the tumors, and a majority of these GOHs and LOHs were reversed in “paratumor” tissues within 2 cm of the tumors, forming forward-reverse mutation cycles where the revertant LOHs displayed strong lineage effects that pointed to a sequential instead of parallel development from “nontumor” to “paratumor” and onto tumor cells, which was also supported by the relative frequencies of 26 distinct classes of CNVs between these three types of cell populations.

Conclusions

These findings suggest that developing cancer cells undergo sequential changes that enable the “nontumor” cells to acquire a wide range of forward mutations including ones that are essential for oncogenicity, followed by revertant mutations in the “paratumor” cells to avoid growth retardation by excessive mutation load. Such utilization of forward-reverse mutation cycles as an adaptive mechanism was also observed in cultured HeLa cells upon successive replatings. An understanding of forward-reverse mutation cycles in cancer development could provide a genomic basis for improved early diagnosis, staging, and treatment of cancers.

Electronic supplementary material

The online version of this article (10.1186/s40246-018-0170-6) contains supplementary material, which is available to authorized users.

Feature co-localization landscape of the human genome

Although feature co-localizations could serve as useful guide-posts to genome architecture, a comprehensive and quantitative feature co-localization map of the human genome has been lacking. Herein we show that, in contrast to the conventional bipartite division of genomic sequences into genic and inter-genic regions, pairwise co-localizations of forty-two genomic features in the twenty-two autosomes based on 50-kb to 2,000-kb sequence windows indicate a tripartite zonal architecture comprising Genic zones enriched with gene-related features and Alu-elements; Proximal zones enriched with MIR- and L2-elements, transcription-factor-binding-sites (TFBSs), and conserved-indels (CIDs); and Distal zones enriched with L1-elements. Co-localizations between single-nucleotide-polymorphisms (SNPs) and copy-number-variations (CNVs) reveal a fraction of sequence windows displaying steeply enhanced levels of SNPs, CNVs and recombination rates that point to active adaptive evolution in such pathways as immune response, sensory perceptions, and cognition. The strongest positive co-localization observed between TFBSs and CIDs suggests a regulatory role of CIDs in cooperation with TFBSs. The positive co-localizations of cancer somatic CNVs (CNVT) with all Proximal zone and most Genic zone features, in contrast to the distinctly more restricted co-localizations exhibited by germline CNVs (CNVG), reveal disparate distributions of CNVTs and CNVGs indicative of dissimilarity in their underlying mechanisms.

SAMSVM: A tool for misalignment filtration of SAM-format sequences with support vector machine

Sequence alignment/map (SAM) formatted sequences [Li H, Handsaker B, Wysoker A et al., Bioinformatics 25(16):2078-2079, 2009.] have taken on a main role in bioinformatics since the development of massive parallel sequencing. However, because misalignment of sequences poses a significant problem in analysis of sequencing data that could lead to false positives in variant calling, the exclusion of misaligned reads is a necessity in analysis. In this regard, the multiple features of SAM-formatted sequences can be treated as vectors in a multi-dimension space to allow the application of a support vector machine (SVM). Applying the LIBSVM tools developed by Chang and Lin [Chang C-C, Lin C-J, ACM Trans Intell Syst Technol 2:1-27, 2011.] as a simple interface for support vector classification, the SAMSVM package has been developed in this study to enable misalignment filtration of SAM-formatted sequences. Cross-validation between two simulated datasets processed with SAMSVM yielded accuracies that ranged from 0.89 to 0.97 with F-scores ranging from 0.77 to 0.94 in 14 groups characterized by different mutation rates from 0.001 to 0.1, indicating that the model built using SAMSVM was accurate in misalignment detection. Application of SAMSVM to actual sequencing data resulted in filtration of misaligned reads and correction of variant calling.

Massive interstitial copy-neutral loss-of-heterozygosity as evidence for cancer being a disease of the DNA-damage response

Background

The presence of loss-of-heterozygosity (LOH) mutations in cancer cell genomes is commonly encountered. Moreover, the occurrences of LOHs in tumor suppressor genes play important roles in oncogenesis. However, because the causative mechanisms underlying LOH mutations in cancer cells yet remain to be elucidated, enquiry into the nature of these mechanisms based on a comprehensive examination of the characteristics of LOHs in multiple types of cancers has become a necessity.

Methods

We performed next-generation sequencing on inter-Alu sequences of five different types of solid tumors and acute myeloid leukemias, employing the AluScan platform which entailed amplification of such sequences using multiple PCR primers based on the consensus sequences of Alu elements; as well as the whole genome sequences of a lung-to-liver metastatic cancer and a primary liver cancer. Paired-end sequencing reads were aligned to the reference human genome to identify major and minor alleles so that the partition of LOH products between homozygous-major vs. homozygous-minor alleles could be determined at single-base resolution. Strict filtering conditions were employed to avoid false positives. Measurements of LOH occurrences in copy number variation (CNV)-neutral regions were obtained through removal of CNV-associated LOHs.

Results

We found: (a) average occurrence of copy-neutral LOHs amounting to 6.9 % of heterologous loci in the various cancers; (b) the mainly interstitial nature of the LOHs; and (c) preference for formation of homozygous-major over homozygous-minor, and transitional over transversional, LOHs.

Conclusions

The characteristics of the cancer LOHs, observed in both AluScan and whole genome sequencings, point to the formation of LOHs through repair of double-strand breaks by interhomolog recombination, or gene conversion, as the consequence of a defective DNA-damage response, leading to a unified mechanism for generating the mutations required for oncogenesis as well as the progression of cancer cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s12920-015-0104-2) contains supplementary material, which is available to authorized users.

Glioma Association and Balancing Selection of ZFPM2

ZFPM2, encoding a zinc finger protein and abundantly expressed in the brain, uterus and smooth muscles, plays important roles in cardiac and gonadal development. Abnormal expression of ZFPM2 in ovarian tumors and neuroblastoma has been reported but hitherto its genetic association with cancer and effects on gliomas have not been studied. In the present study, the hexamer insertion-deletion polymorphism rs71305152, located within a large haplotype block spanning intron 1 to intron 3 of ZFPM2, was genotyped in Chinese cohorts of glioma (n = 350), non-glioma cancer (n = 354) and healthy control (n = 463) by direct sequencing and length polymorphism in gel electrophoresis, and ZFPM2 expression in glioma tissues (n = 69) of different grades was quantified by real-time RT-PCR. Moreover, potential natural selection pressure acting on the gene was investigated. Disease-association analysis showed that the overall genotype of rs71305152 was significantly associated with gliomas (P = 0.016), and the heterozygous genotype compared to the combined homozygous genotypes was less frequent in gliomas than in controls (P = 0.005) or non-glioma cancers (P = 0.020). ZFPM2 mRNA expression was negatively correlated with the grades of gliomas (P = 0.002), with higher expression levels in the low-grade gliomas. In the astrocytoma subtype, higher ZFPM2 expression was also correlated with the rs71305152 heterozygous genotype (P = 0.028). In addition, summary statistics tests gave highly positive values, demonstrating that the gene is under the influence of balancing selection. These findings suggest that ZFPM2 is a glioma susceptibility gene, its genotype and expression showing associations with incidence and severity, respectively. Moreover, the balancing selection acting on ZFPM2 may be related to the important roles it has to play in multiple organ development or associated disease etiology.

Copy number variation analysis based on AluScan sequences

BACKGROUND

AluScan combines inter-Alu PCR using multiple Alu-based primers with opposite orientations and next-generation sequencing to capture a huge number of Alu-proximal genomic sequences for investigation. Its requirement of only sub-microgram quantities of DNA facilitates the examination of large numbers of samples. However, the special features of AluScan data rendered difficult the calling of copy number variation (CNV) directly using the calling algorithms designed for whole genome sequencing (WGS) or exome sequencing.

RESULTS

In this study, an AluScanCNV package has been assembled for efficient CNV calling from AluScan sequencing data employing a Geary-Hinkley transformation (GHT) of read-depth ratios between either paired test-control samples, or between test samples and a reference template constructed from reference samples, to call the localized CNVs, followed by use of a GISTIC-like algorithm to identify recurrent CNVs and circular binary segmentation (CBS) to reveal large extended CNVs. To evaluate the utility of CNVs called from AluScan data, the AluScans from 23 non-cancer and 38 cancer genomes were analyzed in this study. The glioma samples analyzed yielded the familiar extended copy-number losses on chromosomes 1p and 9. Also, the recurrent somatic CNVs identified from liver cancer samples were similar to those reported for liver cancer WGS with respect to a striking enrichment of copy-number gains in chromosomes 1q and 8q. When localized or recurrent CNV-features capable of distinguishing between liver and non-liver cancer samples were selected by correlation-based machine learning, a highly accurate separation of the liver and non-liver cancer classes was attained.

CONCLUSIONS

The results obtained from non-cancer and cancerous tissues indicated that the AluScanCNV package can be employed to call localized, recurrent and extended CNVs from AluScan sequences. Moreover, both the localized and recurrent CNVs identified by this method could be subjected to machine-learning selection to yield distinguishing CNV-features that were capable of separating between liver cancers and other types of cancers. Since the method is applicable to any human DNA sample with or without the availability of a paired control, it can also be employed to analyze the constitutional CNVs of individuals.

A proposal for the reference-based annotation of de novo transposable element insertions

Understanding the causes and consequences of transposable element (TE) activity in the genomic era requires sophisticated bioinformatics approaches to accurately identify individual insertion sites. Next-generation sequencing technology now makes it possible to rapidly identify new TE insertions using resequencing data, opening up new possibilities to study the nature of TE-induced mutation and the target site preferences of different TE families. While the identification of new TE insertion sites is seemingly a simple task, the mechanisms of transposition present unique challenges for the annotation of de novo transposable element insertions mapped to a reference genome. Here I discuss these challenges and propose a framework for the annotation of de novo TE insertions that accommodates known mechanisms of TE insertion and established coordinate systems for genome annotation.

Application of Machine Learning to Development of Copy Number Variation-based Prediction of Cancer Risk

In the present study, recurrent copy number variations (CNVs) from non-tumor blood cell DNAs of Caucasian non-cancer subjects and glioma, myeloma, and colorectal cancer-patients, and Korean non-cancer subjects and hepatocellular carcinoma, gastric cancer, and colorectal cancer patients, were found to reveal for each of the two ethnic cohorts highly significant differences between cancer patients and controls with respect to the number of CN-losses and size-distribution of CN-gains, suggesting the existence of recurrent constitutional CNV-features useful for prediction of predisposition to cancer. Upon identification by machine learning, such CNV-features could extensively discriminate between cancer-patient and control DNAs. When the CNV-features selected from a learning-group of Caucasian or Korean mixed DNAs consisting of both cancer-patient and control DNAs were employed to make predictions on the cancer predisposition of an unseen test group of mixed DNAs, the average prediction accuracy was 93.6% for the Caucasian cohort and 86.5% for the Korean cohort.

The dynamic proliferation of CanSINEs mirrors the complex evolution of Feliforms

BACKGROUND

Repetitive short interspersed elements (SINEs) are retrotransposons ubiquitous in mammalian genomes and are highly informative markers to identify species and phylogenetic associations. Of these, SINEs unique to the order Carnivora (CanSINEs) yield novel insights on genome evolution in domestic dogs and cats, but less is known about their role in related carnivores. In particular, genome-wide assessment of CanSINE evolution has yet to be completed across the Feliformia (cat-like) suborder of Carnivora. Within Feliformia, the cat family Felidae is composed of 37 species and numerous subspecies organized into eight monophyletic lineages that likely arose 10 million years ago. Using the Felidae family as a reference phylogeny, along with representative taxa from other families of Feliformia, the origin, proliferation and evolution of CanSINEs within the suborder were assessed.

RESULTS

We identified 93 novel intergenic CanSINE loci in Feliformia. Sequence analyses separated Feliform CanSINEs into two subfamilies, each characterized by distinct RNA polymerase binding motifs and phylogenetic associations. Subfamily I CanSINEs arose early within Feliformia but are no longer under active proliferation. Subfamily II loci are more recent, exclusive to Felidae and show evidence for adaptation to extant RNA polymerase activity. Further, presence/absence distributions of CanSINE loci are largely congruent with taxonomic expectations within Feliformia and the less resolved nodes in the Felidae reference phylogeny present equally ambiguous CanSINE data. SINEs are thought to be nearly impervious to excision from the genome. However, we observed a nearly complete excision of a CanSINEs locus in puma (Puma concolor). In addition, we found that CanSINE proliferation in Felidae frequently targeted existing CanSINE loci for insertion sites, resulting in tandem arrays.

CONCLUSIONS

We demonstrate the existence of at least two SINE families within the Feliformia suborder, one of which is actively involved in insertional mutagenesis. We find SINEs are powerful markers of speciation and conclude that the few inconsistencies with expected patterns of speciation likely represent incomplete lineage sorting, species hybridization and SINE-mediated genome rearrangement.