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Human limbs emerge during the fourth post-conception week as mesenchymal buds, which develop into fully formed limbs over the subsequent months 1 . This process is orchestrated by numerous temporally and spatially restricted gene expression programmes, making congenital alterations in phenotype common 2 . Decades of work with model organisms have defined the fundamental mechanisms underlying vertebrate limb development, but an in-depth characterization of this process in humans has yet to be performed. Here we detail human embryonic limb development across space and time using single-cell and spatial transcriptomics. We demonstrate extensive diversification of cells from a few multipotent progenitors to myriad differentiated cell states, including several novel cell populations. We uncover two waves of human muscle development, each characterized by different cell states regulated by separate gene expression programmes, and identify musculin (MSC) as a key transcriptional repressor maintaining muscle stem cell identity. Through assembly of multiple anatomically continuous spatial transcriptomic samples using VisiumStitcher, we map cells across a sagittal section of a whole fetal hindlimb. We reveal a clear anatomical segregation between genes linked to brachydactyly and polysyndactyly, and uncover transcriptionally and spatially distinct populations of the mesenchyme in the autopod. Finally, we perform single-cell RNA sequencing on mouse embryonic limbs to facilitate cross-species developmental comparison, finding substantial homology between the two species. Using single-cell and spatial transcriptomics, human embryonic limb development across space and time and the diversification and cross-species conservation of cells are demonstrated.

The DDD study recruited more than 13,500 families with probands with severe, probably monogenic disorders in the United Kingdom and Ireland and obtained a genetic diagnosis in approximately 41% of probands.

Absence of part or all of the iris, aniridia, is a feature of several genetically distinct conditions. This review focuses on iris development and then the clinical features and molecular genetics of these iris malformations. Classical aniridia, a panocular eye malformation including foveal hypoplasia, is the archetypal phenotype associated with heterozygous PAX6 loss-of-function mutations. Since this was identified in 1991, many genetic mechanisms of PAX6 inactivation have been elucidated, the commonest alleles being intragenic mutations causing premature stop codons, followed by those causing C-terminal extensions. Rarely, aniridia cases are associated with FOXC1, PITX2 and/or their regulatory regions. Aniridia can also occur as a component of many severe global eye malformations. Gillespie syndrome—a triad of partial aniridia, non-progressive cerebellar ataxia and intellectual disability—is phenotypically and genotypically distinct from classical aniridia. The causative gene has recently been identified as ITPR1. The same characteristic Gillespie syndrome-like iris, with aplasia of the pupillary sphincter and a scalloped margin, is seen in ACTA2-related multisystemic smooth muscle dysfunction syndrome. WAGR syndrome (Wilms tumour, aniridia, genitourinary anomalies and mental retardation/intellectual disability), is caused by contiguous deletion of PAX6 and WT1 on chromosome 11p. Deletions encompassing BDNF have been causally implicated in the obesity and intellectual disability associated with the condition. Lastly, we outline a genetic investigation strategy for aniridia in light of recent developments, suggesting an approach based principally on chromosomal array and gene panel testing. This strategy aims to test all known aniridia loci—including the rarer, life-limiting causes—whilst remaining simple and practical.

There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants 1 . However, patients with the same genetic defect can have different clinical presentations 2 – 4 , and some individuals who carry known disease-causing variants can appear unaffected 5 . Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic. A genome-wide association study of approximately 7,000 patients with neurodevelopmental disorders demonstrates that overall risk and clinical presentation in putative monogenic disorders is also influenced by common genetic variants present in the general population.

Background The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. Methods We convened a panel of nine clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. Results We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for the interpretation of these variants. Conclusions These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.

We previously estimated that 42% of patients with severe developmental disorders carry pathogenic de novo mutations in coding sequences. The role of de novo mutations in regulatory elements affecting genes associated with developmental disorders, or other genes, has been essentially unexplored. We identified de novo mutations in three classes of putative regulatory elements in almost 8,000 patients with developmental disorders. Here we show that de novo mutations in highly evolutionarily conserved fetal brain-active elements are significantly and specifically enriched in neurodevelopmental disorders. We identified a significant twofold enrichment of recurrently mutated elements. We estimate that, genome-wide, 1–3% of patients without a diagnostic coding variant carry pathogenic de novo mutations in fetal brain-active regulatory elements and that only 0.15% of all possible mutations within highly conserved fetal brain-active elements cause neurodevelopmental disorders with a dominant mechanism. Our findings represent a robust estimate of the contribution of de novo mutations in regulatory elements to this genetically heterogeneous set of disorders, and emphasize the importance of combining functional and evolutionary evidence to identify regulatory causes of genetic disorders. Analysis of rare de novo mutations in gene regulatory elements suggests that 1–3% of patients with neurodevelopmental disorders carry such mutations in elements that are active in the fetal brain. Regulatory mutations in developmental disorders Matthew Hurles and colleagues, as part of the Deciphering Developmental Disorders (DDD) project, examine the contribution of rare de novo mutations (DNMs) in regulatory elements—sections of DNA that regulate the expression of genes—to developmental disorders. The authors analysed targeted sequencing data for three classes of potential regulatory elements in 7,930 individuals with a severe, undiagnosed developmental disorder. They find an enrichment of DNMs in highly evolutionarily conserved elements that are active in the fetal brain. The authors previously estimated that 42% of patients with severe developmental disorders carry pathogenic DNMs in coding sequences. They now estimate that 1%–3% of the remaining patients carry pathogenic DNMs in fetal brain-active regulatory elements.

Background Less than two percent of the human genome is protein coding, yet that small fraction harbours the majority of known disease causing mutations. Despite rapidly falling whole genome sequencing (WGS) costs, much research and increasingly the clinical use of sequence data is likely to remain focused on the protein coding exome. We set out to quantify and understand how WGS compares with the targeted capture and sequencing of the exome (exome-seq), for the specific purpose of identifying single nucleotide polymorphisms (SNPs) in exome targeted regions. Results We have compared polymorphism detection sensitivity and systematic biases using a set of tissue samples that have been subject to both deep exome and whole genome sequencing. The scoring of detection sensitivity was based on sequence down sampling and reference to a set of gold-standard SNP calls for each sample. Despite evidence of incremental improvements in exome capture technology over time, whole genome sequencing has greater uniformity of sequence read coverage and reduced biases in the detection of non-reference alleles than exome-seq. Exome-seq achieves 95% SNP detection sensitivity at a mean on-target depth of 40 reads, whereas WGS only requires a mean of 14 reads. Known disease causing mutations are not biased towards easy or hard to sequence areas of the genome for either exome-seq or WGS. Conclusions From an economic perspective, WGS is at parity with exome-seq for variant detection in the targeted coding regions. WGS offers benefits in uniformity of read coverage and more balanced allele ratio calls, both of which can in most cases be offset by deeper exome-seq, with the caveat that some exome-seq targets will never achieve sufficient mapped read depth for variant detection due to technical difficulties or probe failures. As WGS is intrinsically richer data that can provide insight into polymorphisms outside coding regions and reveal genomic rearrangements, it is likely to progressively replace exome-seq for many applications.

We aimed to develop an efficient, flexible and scalable approach to diagnostic genome-wide sequence analysis of genetically heterogeneous clinical presentations. Here we present G2P ( www.ebi.ac.uk/gene2phenotype ) as an online system to establish, curate and distribute datasets for diagnostic variant filtering via association of allelic requirement and mutational consequence at a defined locus with phenotypic terms, confidence level and evidence links. An extension to Ensembl Variant Effect Predictor (VEP), VEP-G2P was used to filter both disease-associated and control whole exome sequence (WES) with Developmental Disorders G2P (G2P DD ; 2044 entries). VEP-G2P DD shows a sensitivity/precision of 97.3%/33% for de novo and 81.6%/22.7% for inherited pathogenic genotypes respectively. Many of the missing genotypes are likely false-positive pathogenic assignments. The expected number and discriminative features of background genotypes are defined using control WES. Using only human genetic data VEP-G2P performs well compared to other freely-available diagnostic systems and future phenotypic matching capabilities should further enhance performance. Diagnostic filtering is an important step to analyze the functional and clinical significance of the large number of genetic variants identified from next-generation genome sequencing data. Here, the authors develop a flexible and scalable system for diagnostic filtering of genetic variants using G2P with Ensembl VEP.

The emergence of retinal progenitor cells and differentiation to various retinal cell types represent fundamental processes during retinal development. Herein, we provide a comprehensive single cell characterisation of transcriptional and chromatin accessibility changes that underline retinal progenitor cell specification and differentiation over the course of human retinal development up to midgestation. Our lineage trajectory data demonstrate the presence of early retinal progenitors, which transit to late, and further to transient neurogenic progenitors, that give rise to all the retinal neurons. Combining single cell RNA-Seq with spatial transcriptomics of early eye samples, we demonstrate the transient presence of early retinal progenitors in the ciliary margin zone with decreasing occurrence from 8 post-conception week of human development. In retinal progenitor cells, we identified a significant enrichment for transcriptional enhanced associate domain transcription factor binding motifs, which when inhibited led to loss of cycling progenitors and retinal identity in pluripotent stem cell derived organoids. Formation of the retina during development involves the coordinated action of retinal progenitor cells and their differentiated cell types, which is key for producing a functioning eye. Here the authors provide a detailed atlas of human retinal development, combining scRNA-seq and spatial transcriptomics, and identify key genetic factors that mediate retinal progenitor cell proliferation and differentiation.

Cornelia de Lange syndrome is a multisystem developmental disorder typically caused by mutations in the gene encoding the cohesin loader NIPBL. The associated phenotype is generally assumed to be the consequence of aberrant transcriptional regulation. Recently, we identified a missense mutation in BRD4 associated with a Cornelia de Lange-like syndrome that reduces BRD4 binding to acetylated histones. Here we show that, although this mutation reduces BRD4-occupancy at enhancers it does not affect transcription of the pluripotency network in mouse embryonic stem cells. Rather, it delays the cell cycle, increases DNA damage signalling, and perturbs regulation of DNA repair in mutant cells. This uncovers a role for BRD4 in DNA repair pathway choice. Furthermore, we find evidence of a similar increase in DNA damage signalling in cells derived from NIPBL-deficient individuals, suggesting that defective DNA damage signalling and repair is also a feature of typical Cornelia de Lange syndrome. Cornelia de Lange syndrome is a developmental disorder typically caused by mutations in the gene encoding the cohesin loader NIPBL. The authors, here, by analysing previously identified mutations in BRD4 associated with the disease, reveal that a BRD4 mutation affects DNA damage signalling, and perturbs regulation of DNA repair in mutant cells.