Efficient estimation for large-scale linkage disequilibrium patterns of the human genome

Genomic analysis of 1,325 Camellia accessions sheds light on agronomic and metabolic traits for tea plant improvement

The tea plant stands as a globally cherished nonalcoholic beverage crop, but the genetic underpinnings of important agronomic and metabolomic traits remain largely unexplored. Here we de novo deep resequenced 802 tea plants and their relative accessions globally. By integrating public Camellia accessions, we constructed a comprehensive genome-wide genetic variation map and annotated deleterious mutations for 1,325 accessions. Population genetic analyses provided insights into genetic divergence from its relatives, different evolutionary bottlenecks, interspecific introgression and conservation of wild relatives. Our findings suggest the pivotal role of southwest China as the origin of tea plants, revealing the genetic diversity and domestication status of ancient tea plants. Genome-wide association studies herein identified thousands of substantial associations with leaf shape and metabolite traits, pinpointing candidate genes for crucial agronomic and flavor traits. This study illuminates the tea plant's evolution and provides references for tea plant design breeding.

Mosaic variegated aneuploidy in development, ageing and cancer

Mosaic variegated aneuploidy (MVA) is a rare condition in which abnormal chromosome counts (that is, aneuploidies), affecting different chromosomes in each cell (making it variegated) are found only in a certain number of cells (making it mosaic). MVA is characterized by various developmental defects and, despite its rarity, presents a unique clinical scenario to understand the consequences of chromosomal instability and copy number variation in humans. Research from patients with MVA, genetically engineered mouse models and functional cellular studies have found the genetic causes to be mutations in components of the spindle-assembly checkpoint as well as in related proteins involved in centrosome dynamics during mitosis. MVA is accompanied by tumour susceptibility (depending on the genetic basis) as well as cellular and systemic stress, including chronic immune response and the associated clinical implications.

Structural variants in linkage disequilibrium with GWAS-significant SNPs

With the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium. The database is composed of (i) SNPs that have exhibited genome-wide significant association with traits, primarily disease phenotypes, (ii) newly released structural variants (SVs), and (iii) linkage disequilibrium values calculated from unphased data. All data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available at the SV-SNP LD Database and can be accessed at 'https://github.com/hliang-SchrodiLab/SV_SNPs. Our analysis results represent a useful fine mapping tool for interrogating SVs in linkage disequilibrium with disease-associated SNPs. We anticipate that this resource may play an important role in subsequent studies which investigate incorporating disease causing SVs into disease risk prediction models.

Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier.