A nearly complete genome assembly for Ginkgo biloba, a plant widely cultivated for its appearance and high resistance to environmental stressors, pests, and disease, is published in Nature Plants this week. G. biloba is a relatively ancient gymnosperm with freely swimming sperm, making it a good model for studying gymnosperm evolution. However, its large genome size and highly repetitive sequence content has limited efforts to assemble a high-quality reference genome. In the report, a team led by scientists from Nanjing Forestry University present a G. biloba genome assembly — based on long-read sequencing technology — with a size of 9.87 Gb, an N50 contig size of 1.58 Mb, and an N50 scaffold size of 775 Mb. They annotated 27,832 protein-coding genes in total, and by analyzing the assembly, suggested that the genome of the extant G. biloba had undergone seed plant whole-genome duplication (WGD) but that no additional round of lineage-specific WGD occurred. They also uncovered several genes linked to sperm flagellum biosynthesis and regulation, as well as the absence of key genes involved in flower development, and more.
A large-scale study of the genomic underpinnings of type 1 diabetes is reported by a University of Virginia-led team in this week's Nature Genetics. The scientists performed discovery and fine-mapping analyses on a dataset of more than 61,000 individuals including ancestrally diverse type 1 diabetics, controls, and members of affected families. They uncovered 78 genome-wide-significant regions, of which 36 are new, and define credible sets of disease-associated variants and show that they are enriched in immune-cell accessible chromatin. The investigators also propose a causal role for a variant of the gene encoding the transcription factor BACH2 in type 1 diabetes and, by integrating the implicated genes with immune protein networks, identify drugs that target disease-linked candidate genes and networks.
A collection containing polygenic indexes (PGIs) for dozens of phenotypes, all developed using consistent methodology, is presented in this week's Nature Human Behavior. PGIs, also known as polygenic scores, are DNA-based predictors of phenotypes derived from genome-wide association study data. Amid a growing application of PGIs in human medicine, a multi-institute team of investigators from the US and Europe developed the Polygenic Index Repository, a resource of 47 PGIs in 11 datasets constructed using genome-wide association studies, including some previously not published, from multiple data sources including 23andMe and the UK Biobank. The scientists also present a theoretical framework to help interpret analyses involving PGIs. They say they will update the repository with additional PGIs as more GWAS summary statistics become more available and methods for constructing PGIs improve.