Correlations between genotype and a patient’s phenotype can help clinical care in rare conditions. Kim et al. report genotype-phenotype correlations in PAX2 related renal-coloboma syndrome and focal segmental glomerulosclerosis [1]. Based upon a series of new patients and a literature review, loss-of-function variants were predominantly associated with renal-coloboma syndrome. Loss-of-function variants were also associated with more severe ocular manifestations than missense variants. Alport syndrome is associated with renal disease and hearing loss, with COL4A3, A4 or A5 variants. Daga et al. report a slowly progessive form of Alport syndrome associated with a splice variant in COL4A3 [2]. Genotype-phenotype correlations are also important in genetic factors contributing to common diseases. Omran et al. report further evidence that a phenotype prediction tool, based on missense structural changes, can predict phenotype in TP53 syndrome [3].

Genomic technologies have been crucial to aid clinical diagnosis of rare conditions, and also aid understanding of mechanisms. Craniofronto-nasal syndrome is an X-linked disorder associated with EFNB1 variants. Kakadia et al. used whole genome sequencing to define cryptic breakpoints that separated EFNB1 from an enhancer element, demonstrating a potential novel mechanism for craniofronto-nasal syndrome [4]. Phenotypic heterogeneity is well recognised in rare genetic conditions. BCL11B variants have been associated both with an immunodeficiency and a neurodevelopmental disorder. In this issue of EJHG, craniosynostosis is reported in a series of people with BCL11B variants, confirming the phenotype association [5]. King-Denborough Syndrome (KDS) is a congenital myopathy with myopathy, dysmorphic features and risk of malignant hyperthermia. Schoonen et al. report the genotype-phenotype correlations in KDS in an African cohort [6]. This underscores the need for ancestry specific genotype-phenotype studies. Hao and colleagues report gene panel screening for 90 hearing loss genes in 7500 Chinese newborns [7].

Offering families diagnostic genome sequencing requires careful counselling and discussion. Ellard and colleagues describe an observational study of the “consent conversation” for genome sequencing in the United Kingdom National Health Service (NHS) [8]. Consultations in which whole genome sequencing was discussed with parents of children with rare diseases, were audio recorded and transcribed. A notable omission from the conversations was clarification and exploration of parents’ values and concerns. Geographic and socioeconomic factors influence access to genetic counselling. Casauria et al. explore this issue in an Australian context [9]. They found that more genomic testing was undertaken in large, urban centres than in remote and rural areas. Taking account of patients and families views on the use of genomic technologies is crucial. Brar et al. surveyed cardiovascular clinic patients’ views on polygenic risk scores [10]. The vast majority had no knowledge or experience of polygenic risk scores. Participants reported a high degree of negative emotions related to high risk polygenic scores. Carrier screening for recessive conditions within families (i.e. cascade testing) is long established as part of genetic counselling. Population screening for recessive conditions, for reproductive purposes, is less well accepted. A position statement from a range of Spanish societies and interest groups states that “preconception GCS services be included in the public healthcare system to support couples’ reproductive autonomy and timely medical decision-making” [11]. However, there remains a diversity of views as to the desirability of population carrier screening and its clinical benefits. Related to carrier and genetic screening is the need for probands to share their genetic information with their family members. In this issue, 2 linked papers explore a model where healthcare professionals directly contact at risk relatives (with patient consent) [12, 13]. There was broad support for this model, with some reservations around privacy.

Of course genomic technologies can achieve more than just clinical testing. Shanmugam and colleagues provide a fascinating insight into the recent demographic history of Great Britain and Ireland using genomics [14]. They report evidence of relatively recent population bottlenecks in Orkney and Wales.