Imaging-derived phenotypes (IDPs) developed from medical imaging data, such as magnetic resonance imaging, computed tomography and X-ray scans, are traits that provide quantitative information on anatomical and functional properties of organs and tissues. IDPs are powerful tools for identifying biomarkers and studying disease mechanisms. When coupled with genetic data, IDPs can be analysed as heritable phenotypes using modern gene mapping methods to uncover genotype–phenotype relationships. The field of imaging genomics is rapidly maturing, with the emergence of high-quality imaging datasets collected in biobank-scale cohorts and sophisticated computational methods for extracting IDPs from imaging data, including tools that leverage machine learning. Here we review common imaging modalities and analytical approaches for developing IDPs, discuss biological insights gleaned from the large-scale genetic analysis of imaging traits and highlight emerging areas and remaining challenges that

American researchers have successfully completed the full sequencing of a human chromosome for the first time. This achievement was made on chromosome X, one of the…

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Human recombination maps are a valuable resource for association and linkage studies and crucial for many inferences of population history and natural selection. Existing maps1–5 are based solely on cross-over (CO) recombination, omitting non-cross-overs (NCOs)—the more common form of recombination6—owing to the difficulty in detecting them. Using whole-genome sequence data in families, we estimate the number of NCOs transmitted from parent to offspring and derive complete, sex-specific recombination maps including both NCOs and COs. Mothers have fewer but longer NCOs than fathers, and oocytes accumulate NCOs in a non-regulated fashion with maternal age. Recombination, primarily NCO, is responsible for 1.8% (95% confidence interval: 1.3–2.3) and 11.3% (95% confidence interval: 9.0–13.6) of paternal and maternal de novo mutations, respectively, and may drive the increase in de novo mutations with maternal age. NCOs are substantially more prominent than COs in centromeres, possibly to av

Many human diseases are the result of early developmental defects. As most paediatric diseases and disorders are rare, children are critically underrepresented in research. Functional genomics studies primarily rely on adult tissues and lack critical cell states in specific developmental windows. In parallel, little is known about the conservation of developmental programmes across non-human primate (NHP) species, with implications for human evolution. Here we introduce the developmental Genotype-Tissue Expression (dGTEx) projects, which span humans and NHPs and aim to integrate gene expression, regulation and genetics data across development and species. The dGTEx cohort will consist of 74 tissue sites across 120 human donors from birth to adulthood, and developmentally matched NHP age groups, with additional prenatal and adult animals, with 126 rhesus macaques (Macaca mulatta) and 72 common marmosets (Callithrix jacchus). The data will comprise whole-genome sequencing, extensive bulk

The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states1. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific ‘on switches’ that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based

The North Pontic Region was the meeting point of the farmers of Old Europe and the foragers and pastoralists of the Eurasian steppe1,2, and the source of migrations deep into Europe3–5. Here we report genome-wide data from 81 prehistoric North Pontic individuals to understand the genetic makeup of its people. North Pontic foragers had ancestry from Balkan and Eastern hunter-gatherers6 as well as European farmers and, occasionally, Caucasus hunter-gatherers. During the Eneolithic period, a wave of migrants from the Caucasus–Lower Volga area7 bypassed local foragers to mix in equal parts with Trypillian farmers, forming the people of the Usatove culture around 4500 bce. A temporally overlapping wave of migrants from the Caucasus–Lower Volga blended with foragers instead of farmers to form Serednii Stih people7. The third wave was the Yamna—descendants of the Serednii Stih who formed by mixture around 4000 bce and expanded during the Early Bronze Age (3300 bce). The temporal gap between S