Familial Clonal Hematopoiesis in a Long Telomere Syndrome.

BACKGROUND: Telomere shortening is a well-characterized cellular aging mechanism, and short telomere syndromes cause age-related disease. However, whether long telomere length is advantageous is poorly understood. METHODS: We examined the clinical and molecular features of aging and cancer in persons carrying heterozygous loss-of-function mutations in the telomere-related gene POT1 and noncarrier relatives. RESULTS: A total of 17 POT1 mutation carriers and 21 noncarrier relatives were initially included in the study, and a validation cohort of 6 additional mutation carriers was subsequently recruited. A majority of the POT1 mutation carriers with telomere length evaluated (9 of 13) had long telomeres (>99th percentile). POT1 mutation carriers had a range of benign and malignant neoplasms involving epithelial, mesenchymal, and neuronal tissues in addition to B- and T-cell lymphoma and myeloid cancers. Five of 18 POT1 mutation carriers (28%) had T-cell clonality, and 8 of 12 (67%) had clonal hematopoiesis of indeterminate potential. A predisposition to clonal hematopoiesis had an autosomal dominant pattern of inheritance, as well as penetrance that increased with age; somatic DNMT3A and JAK2 hotspot mutations were common. These and other somatic driver mutations probably arose in the first decades of life, and their lineages secondarily accumulated a higher mutation burden characterized by a clocklike signature. Successive generations showed genetic anticipation (i.e., an increasingly early onset of disease). In contrast to noncarrier relatives, who had the typical telomere shortening with age, POT1 mutation carriers maintained telomere length over the course of 2 years. CONCLUSIONS: POT1 mutations associated with long telomere length conferred a predisposition to a familial clonal hematopoiesis syndrome that was associated with a range of benign and malignant solid neoplasms. The risk of these phenotypes was mediated by extended cellular longevity and by the capacity to maintain telomeres over time. (Funded by the National Institutes of Health and others.).

Haplotype-aware inference of human chromosome abnormalities.

Extra or missing chromosomes-a phenomenon termed aneuploidy-frequently arise during human meiosis and embryonic mitosis and are the leading cause of pregnancy loss, including in the context of in vitro fertilization (IVF). While meiotic aneuploidies affect all cells and are deleterious, mitotic errors generate mosaicism, which may be compatible with healthy live birth. Large-scale abnormalities such as triploidy and haploidy also contribute to adverse pregnancy outcomes, but remain hidden from standard sequencing-based approaches to preimplantation genetic testing for aneuploidy (PGT-A). The ability to reliably distinguish meiotic and mitotic aneuploidies, as well as abnormalities in genome-wide ploidy, may thus prove valuable for enhancing IVF outcomes. Here, we describe a statistical method for distinguishing these forms of aneuploidy based on analysis of low-coverage whole-genome sequencing data, which is the current standard in the field. Our approach overcomes the sparse nature of the data by leveraging allele frequencies and linkage disequilibrium (LD) measured in a population reference panel. The method, which we term LD-informed PGT-A (LD-PGTA), retains high accuracy down to coverage as low as 0.05 × and at higher coverage can also distinguish between meiosis I and meiosis II errors based on signatures spanning the centromeres. LD-PGTA provides fundamental insight into the origins of human chromosome abnormalities, as well as a practical tool with the potential to improve genetic testing during IVF.

Transcriptomics and chromatin accessibility in multiple African population samples.

Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

A complete reference genome improves analysis of human genetic variation.

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.

Local adaptation and archaic introgression shape global diversity at human structural variant loci.

Large genomic insertions and deletions are a potent source of functional variation, but are challenging to resolve with short-read sequencing, limiting knowledge of the role of such structural variants (SVs) in human evolution. Here, we used a graph-based method to genotype long-read-discovered SVs in short-read data from diverse human genomes. We then applied an admixture-aware method to identify 220 SVs exhibiting extreme patterns of frequency differentiation - a signature of local adaptation. The top two variants traced to the immunoglobulin heavy chain locus, tagging a haplotype that swept to near fixation in certain southeast Asian populations, but is rare in other global populations. Further investigation revealed evidence that the haplotype traces to gene flow from Neanderthals, corroborating the role of immune-related genes as prominent targets of adaptive introgression. Our study demonstrates how recent technical advances can help resolve signatures of key evolutionary events that remained obscured within technically challenging regions of the genome.

Archaic hominin genomics provides a window into gene expression evolution.

Differences in gene expression are thought to account for most phenotypic differences within and between species. Consequently, gene expression is a powerful lens through which to study divergence between modern humans and our closest evolutionary relatives, the Neanderthals and Denisovans. Such insights complement biological knowledge gleaned from the fossil record, while also revealing general features of the mode and tempo of regulatory evolution. Because of the degradation of ancient RNA, gene expression profiles of archaic hominins must be studied by indirect means. As such, conclusions drawn from these studies are often laden with assumptions about the genetic architecture of gene expression, the complexity of which is increasingly apparent. Despite these challenges, rapid technical and conceptual advances in the fields of ancient genomics, functional genomics, statistical genomics, and genome engineering are revolutionizing understanding of hominin gene expression evolution.