Long non-coding RNAs (lncRNAs) can be important components in gene-regulatory networks 1 , but the exact nature and extent of their involvement in human Mendelian disease is largely unknown. Here we show that genetic ablation of a lncRNA locus on human chromosome 2 causes a severe congenital limb malformation. We identified homozygous 27-63-kilobase deletions located 300 kilobases upstream of the engrailed-1 gene (EN1) in patients with a complex limb malformation featuring mesomelic shortening, syndactyly and ventral nails (dorsal dimelia). Re-engineering of the human deletions in mice resulted in a complete loss of En1 expression in the limb and a double dorsal-limb phenotype that recapitulates the human disease phenotype. Genome-wide transcriptome analysis in the developing mouse limb revealed a four-exon-long non-coding transcript within the deleted region, which we named Maenli. Functional dissection of the Maenli locus showed that its transcriptional activity is required for limb-specific En1 activation in cis, thereby fine-tuning the gene-regulatory networks controlling dorso-ventral polarity in the developing limb bud. Its loss results in the En1-related dorsal ventral limb phenotype, a subset of the full En1-associated phenotype. Our findings demonstrate that mutations involving lncRNA loci can result in human Mendelian disease. There has been enormous progress in exploring disease variants in the human genome. Yet, the interpretation of variants in the non-coding genome remains a challenge owing to the myriad mechanisms by which they can potentially cause disease. Besides disrupting cis-regulatory elements, non-coding variants may interfere with the function of non-coding transcripts. Indeed, a substantial fraction of the human genome is transcribed into RNA, although most transcripts lack protein-coding potential and are referred to as non-coding transcripts 2. Characterization of a small number of these RNA molecules has revealed that they may have roles as regulators of gene expression through diverse modes of action 3. However, the identification of functional non-coding transcript loci remains challenging. Thus, annotating non-coding transcript loci and unravelling their function will substantially improve our knowledge about gene regulation and the identification and interpretation of non-coding genetic variants with respect to disease pathogenesis. Non-coding deletions cause limb malformations We identified 27-63-kb non-coding deletions of chromosome 2 in three unrelated individuals (patients 1-3) with a type of limb malformation that, to our knowledge, remains undescribed. Affected individuals had a severe shortening and deformation of the legs and feet, 3/4 syndactyly of the hands, as well as the presence of nails on the palmar side of fingers IV and V (Fig. 1a, Extended Data Fig. 1a, b, Supplementary Note 1). Radiographs showed normal femora but severely shortened tibiae, triangular fibulae and malformed or absent bones in the feet (Fig. 1a, Extended Data Fig. 1a, Supplementary Note 1). Exome s...

In contrast to recessive conditions with biallelic inheritance, identification of dominant (monoallelic) mutations for Mendelian disorders is more difficult, because of the abundance of benign heterozygous variants that act as massive background noise (typically, in a 400:1 excess ratio). To reduce this overflow of false positives in next-generation sequencing (NGS) screens, we developed DOMINO, a tool assessing the likelihood for a gene to harbor dominant changes. Unlike commonly-used predictors of pathogenicity, DOMINO takes into consideration features that are the properties of genes, rather than of variants. It uses a machine-learning approach to extract discriminant information from a broad array of features (N ¼ 432), including: genomic data, intra-, and interspecies conservation, gene expression, protein-protein interactions, protein structure, etc. DOMINO's iterative architecture includes a training process on 985 genes with well-established inheritance patterns for Mendelian conditions, and repeated cross-validation that optimizes its discriminant power. When validated on 99 newly-discovered genes with pathogenic mutations, the algorithm displays an excellent final performance, with an area under the curve (AUC) of 0.92. Furthermore, unsupervised analysis by DOMINO of real sets of NGS data from individuals with intellectual disability or epilepsy correctly recognizes known genes and predicts 9 new candidates, with very high confidence. In summary, DOMINO is a robust and reliable tool that can infer dominance of candidate genes with high sensitivity and specificity, making it a useful complement to any NGS pipeline dealing with the analysis of the morbid human genome.

Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.