Prevalence and Spectrum of Pathogenic Germline Variants in Japanese Patients With Early-Onset Colorectal, Breast, and Prostate Cancer

Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing

We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.

Detection of trait-associated structural variations using short-read sequencing

Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.

Genomic analysis of familial pancreatic cancers and intraductal papillary mucinous neoplasms: A cross-sectional study

Environmental and genetic factors play a critical role in the pathogenesis of pancreatic cancer, which is likely to follow a multistep process that includes intraductal papillary mucinous neoplasm. The pathogenesis of familial pancreatic cancer has been reported; however, epidemiological characteristics and causative genes remain unclear. This study aimed to determine the relationship between the family history of pancreatic cancer and tumor malignancy and identify novel susceptible germline variants of pancreatic cancer. We performed an epidemiologic study at our institute on a cohort of 668 patients with intraductal papillary mucinous neoplasm and 242 with pancreatic cancer but without associated intraductal papillary mucinous neoplasm stratified by family history of pancreatic cancer. Whole-exome sequencing was conducted for 10 patients from seven families with familial pancreatic cancer and intraductal papillary mucinous neoplasm. We found that patients who had intraductal papillary mucinous neoplasm with positive family history of pancreatic cancer within first-degree relatives were more likely to develop malignancy in a shorter period than those without family history. Duplicate frameshift variants in TET2 c.3180dupG (p.Pro1061fs) and ASXL1 c.1934dupG (p.Gly646fs) in one family and POLN c.1194dupT (p.Glu399fs) in another were identified as pathogenic truncating germline variants which were previously recognised susceptibility genes. Moreover, PDIA2 c.1403C>T (p.Pro468Leu) and DPYSL4 c.926C>A (p.Pro309Gln) were shared in four and two patients, respectively. In particular, PDIA2 was identified as a novel candidate for one of the deleterious variants of familial pancreatic cancer.

Bioinformatics Method Was Used to Analyze the Highly Expressed Gene FAM83A of Breast Cancer in Young Women

Objectives

Preliminary analysis of breast cancer related to unknown functional gene FAM83A through bioinformatics knowledge to inform further experimental studies. Select high expression genes for breast cancer and use bioinformatics methods to predict the biological function of FAM83A.

Methods

Genes with significant differences in expression between breast tumors and normal breast tissue libraries were selected from CGAP's SAGE Digital Gene Expression Displayer (DGED) database. An unknown functional gene, FAM83A, which is highly expressed in breast cancer, was screened. We performed an analysis of the gene structure, subcellular localization, physicochemical properties of the encoding products, functional sites, protein structure, and functional domains.

Results

Through SAGE DGED, a total of 185 genes with expression differences were found. The structure and function of FAM83A have ideal predictions, and it is generally determined that this gene encodes a nuclear protein with a nucleoprotein. The active site of PLDc and the functional domain of DUF1669 can be involved in signal transduction and gene expression regulation in tumorigenesis and metastasis. Digital gene representation of the Tumor Genome Project Data Library was used to select differentially expressed genes in breast cancer tissue and breast benign tumor tissue.

Conclusion

Studies show that FAM83A is a potential research target associated with tumorigenesis and metastasis. Initial tests confirmed the expression of this gene. Lay a solid foundation for further research learning. FAM83A is a highly expressed gene in breast cancer and can serve as a target for studying molecular mechanisms in breast cancer.

Genetics of autosomal mosaic chromosomal alteration (mCA)

Mosaic chromosomal alterations (mCAs) are frequently observed in cancer cells and are regarded as one of the common features of cancers. Strikingly, accumulating studies demonstrated that mCAs are also prevalent in elderly individuals without cancer, implying mCA could be a feature of aging and not necessarily a cancerous state. However, the genetic basis of mCA has been mostly unknown. Recent studies of autosomal mCA based on biobank-scale datasets, including UK Biobank and Biobank Japan, provided a glimpse into the underlying genetic mechanism. In this concise review, we briefly introduced mCA, its link with cancer and aging, and the emerging genetic mechanisms of this phenomenon. We highlighted the following aspects: (1) the interplay between somatic and inherited germline mutations in generating mosaicism; (2) monogenic and polygenic architectures of mCA; and (3) population-specific profiles of mCA. We provided a future perspective emphasizing the need to understand the connection between mCA and other characteristics of aging, in particular, the epigenetic and immunologic features.

Unique roles of rare variants in the genetics of complex diseases in humans

Genome-wide association studies have identified >10,000 genetic variants associated with various phenotypes and diseases. Although the majority are common variants, rare variants with >0.1% of minor allele frequency have been investigated by imputation and using disease-specific custom SNP arrays. Rare variants sequencing analysis mainly revealed have played unique roles in the genetics of complex diseases in humans due to their distinctive features, in contrast to common variants. Unique roles are hypothesis-free evidence for gene causality, a precise target of functional analysis for understanding disease mechanisms, a new favorable target for drug development, and a genetic marker with high disease risk for personalized medicine. As whole-genome sequencing continues to identify more rare variants, the roles associated with rare variants will also increase. However, a better estimation of the functional impact of rare variants across whole genome is needed to enhance their contribution to improvements in human health.