Highly efficient capture approach for the identification of diverse inherited retinal disorders.

Our study presents a 319-gene panel targeting inherited retinal dystrophy (IRD) genes. Through a multi-center retrospective cohort study, we validated the assays effectiveness and clinical utility and characterized the mutation spectrum of Taiwanese IRD patients. Between January 2018 and May 2022, 493 patients in 425 unrelated families, all initially suspected of having IRD without prior genetic diagnoses, underwent detailed ophthalmic and physical examinations (with extra-ocular features recorded) and genetic testing with our customized panel. Disease-causing variants were identified by segregation analysis and clinical interpretation, with validation via Sanger sequencing. We achieved a read depth of >200× for 94.2% of the targeted 1.2 Mb region. 68.5% (291/425) of the probands received molecular diagnoses, with 53.9% (229/425) resolved cases. Retinitis pigmentosa (RP) is the most prevalent initial clinical impression (64.2%), and 90.8% of the cohort have the five most prevalent phenotypes (RP, cone-rod syndrome, Ushers syndrome, Lebers congenital amaurosis, Bietti crystalline dystrophy). The most commonly mutated genes of probands that received molecular diagnosis are USH2A (13.7% of the cohort), EYS (11.3%), CYP4V2 (4.8%), ABCA4 (4.5%), RPGR (3.4%), and RP1 (3.1%), collectively accounted for 40.8% of diagnoses. We identify 87 unique unreported variants previously not associated with IRD and refine clinical diagnoses for 21 patients (7.22% of positive cases). We developed a customized gene panel and tested it on the largest Taiwanese cohort, showing that it provides excellent coverage for diverse IRD phenotypes

Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese.

Personalized medical care focuses on prediction of disease risk and response to medications. To build the risk models, access to both large-scale genomic resources and human genetic studies is required. The Taiwan Biobank (TWB) has generated high-coverage, whole-genome sequencing data from 1492 individuals and genome-wide SNP data from 103,106 individuals of Han Chinese ancestry using custom SNP arrays. Principal components analysis of the genotyping data showed that the full range of Han Chinese genetic variation was found in the cohort. The arrays also include thousands of known functional variants, allowing for simultaneous ascertainment of Mendelian disease-causing mutations and variants that affect drug metabolism. We found that 21.2% of the population are mutation carriers of autosomal recessive diseases, 3.1% have mutations in cancer-predisposing genes, and 87.3% carry variants that affect drug response. We highlight how TWB data provide insight into both population history and disease burden, while showing how widespread genetic testing can be used to improve clinical care

Genetic profiles of 103,106 individuals in the Taiwan Biobank provide insights into the health and history of Han Chinese.

Personalized medical care focuses on prediction of disease risk and response to medications. To build the risk models, access to both large-scale genomic resources and human genetic studies is required. The Taiwan Biobank (TWB) has generated high-coverage, whole-genome sequencing data from 1492 individuals and genome-wide SNP data from 103,106 individuals of Han Chinese ancestry using custom SNP arrays. Principal components analysis of the genotyping data showed that the full range of Han Chinese genetic variation was found in the cohort. The arrays also include thousands of known functional variants, allowing for simultaneous ascertainment of Mendelian disease-causing mutations and variants that affect drug metabolism. We found that 21.2% of the population are mutation carriers of autosomal recessive diseases, 3.1% have mutations in cancer-predisposing genes, and 87.3% carry variants that affect drug response. We highlight how TWB data provide insight into both population history and disease burden, while showing how widespread genetic testing can be used to improve clinical care

Towards a reference genome that captures global genetic diversity.

The current human reference genome is predominantly derived from a single individual and it does not adequately reflect human genetic diversity. Here, we analyze 338 high-quality human assemblies of genetically divergent human populations to identify missing sequences in the human reference genome with breakpoint resolution. We identify 127,727 recurrent non-reference unique insertions spanning 18,048,877 bp, some of which disrupt exons and known regulatory elements. To improve genome annotations, we linearly integrate these sequences into the chromosomal assemblies and construct a Human Diversity Reference. Leveraging this reference, an average of 402,573 previously unmapped reads can be recovered for a given genome sequenced to ~40X coverage. Transcriptomic diversity among these non-reference sequences can also be directly assessed. We successfully map tens of thousands of previously discarded RNA-Seq reads to this reference and identify transcription evidence in 4781 gene loci, underlining the importance of these non-reference sequences in functional genomics. Our extensive datasets are important advances toward a comprehensive reference representation of global human genetic diversity

Towards a reference genome that captures global genetic diversity.

The current human reference genome is predominantly derived from a single individual and it does not adequately reflect human genetic diversity. Here, we analyze 338 high-quality human assemblies of genetically divergent human populations to identify missing sequences in the human reference genome with breakpoint resolution. We identify 127,727 recurrent non-reference unique insertions spanning 18,048,877 bp, some of which disrupt exons and known regulatory elements. To improve genome annotations, we linearly integrate these sequences into the chromosomal assemblies and construct a Human Diversity Reference. Leveraging this reference, an average of 402,573 previously unmapped reads can be recovered for a given genome sequenced to ~40X coverage. Transcriptomic diversity among these non-reference sequences can also be directly assessed. We successfully map tens of thousands of previously discarded RNA-Seq reads to this reference and identify transcription evidence in 4781 gene loci, underlining the importance of these non-reference sequences in functional genomics. Our extensive datasets are important advances toward a comprehensive reference representation of global human genetic diversity

CMS : the TriDAS Project Technical Design Report; v.1, the Trigger Systems

CM