PurposeABCA4-associated disease, a recessive retinal dystrophy, is hallmarked by a large proportion of patients with only one pathogenic ABCA4 variant, suggestive for missing heritability.MethodsBy locus-specific analysis of ABCA4, combined with extensive functional studies, we aimed to unravel the missing alleles in a cohort of 67 patients (p), with one (p = 64) or no (p = 3) identified coding pathogenic variants of ABCA4.ResultsWe identified eight pathogenic (deep-)intronic ABCA4 splice variants, of which five are novel and six structural variants, four of which are novel, including two duplications. Together, these variants account for the missing alleles in 40.3% of patients. Furthermore, two novel variants with a putative cis-regulatory effect were identified. The common hypomorphic variant c.5603A>T p.(Asn1868Ile) was found as a candidate second allele in 43.3% of patients. Overall, we have elucidated the missing heritability in 83.6% of our cohort. In addition, we successfully rescued three deep-intronic variants using antisense oligonucleotide (AON)-mediated treatment in HEK 293-T cells and in patient-derived fibroblast cells.ConclusionNoncoding pathogenic variants, novel structural variants, and a common hypomorphic allele of the ABCA4 gene explain the majority of unsolved cases with ABCA4-associated disease, rendering this retinopathy a model for missing heritability in autosomal recessive disorders.

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Modern distributed applications increasingly replicate data to guarantee both high availability of systems and optimal user experience. Conflict-Free Replicated Data Types (CRDTs) are a family of data types specially designed for highly available systems that guarantee some form of eventual consistency. To ensure state convergence between replicas, CRDT implementations need to keep track of additional meta-data. This is not a scalable strategy, as a growing amount of meta-data has to be kept.In this paper, we show that existing solutions for this problem miss optimisation opportunities and may lead to less reactive CRDTs. For this, we analyse the relation between meta-data and the causality of operations in operation-based CRDTs. We explore a new optimisation strategy for pure operation-based CRDTs and show how it reduces memory overhead. Our approach takes advantage of the communication layer providing reliable delivery to determine causal stability, and as a result, meta-data can be removed sooner. We furthermore propose a solution for improving the reactivity of CRDTs built on a reliable causal broadcasting layer.We apply our strategy to pure-operation based CRDTs and validate our approach by measuring its impact on several different set-ups. The results show how our approach can lead to significant improvements in meta-data cleanup when compared to state-ofthe-art techniques. CCS CONCEPTS• Software and its engineering → Garbage collection; Synchronization; Consistency; Distributed architectures.

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