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Background Proteins of the mammalian PYHIN (IFI200/HIN-200) family are involved in defence against infection through recognition of foreign DNA. The family member absent in melanoma 2 (AIM2) binds cytosolic DNA via its HIN domain and initiates inflammasome formation via its pyrin domain. AIM2 lies within a cluster of related genes, many of which are uncharacterised in mouse. To better understand the evolution, orthology and function of these genes, we have documented the range of PYHIN genes present in representative mammalian species, and undertaken phylogenetic and expression analyses. Results No PYHIN genes are evident in non-mammals or monotremes, with a single member found in each of three marsupial genomes. Placental mammals show variable family expansions, from one gene in cow to four in human and 14 in mouse. A single HIN domain appears to have evolved in the common ancestor of marsupials and placental mammals, and duplicated to give rise to three distinct forms (HIN-A, -B and -C) in the placental mammal ancestor. Phylogenetic analyses showed that AIM2 HIN-C and pyrin domains clearly diverge from the rest of the family, and it is the only PYHIN protein with orthology across many species. Interestingly, although AIM2 is important in defence against some bacteria and viruses in mice, AIM2 is a pseudogene in cow, sheep, llama, dolphin, dog and elephant. The other 13 mouse genes have arisen by duplication and rearrangement within the lineage, which has allowed some diversification in expression patterns. Conclusions The role of AIM2 in forming the inflammasome is relatively well understood, but molecular interactions of other PYHIN proteins involved in defence against foreign DNA remain to be defined. The non-AIM2 PYHIN protein sequences are very distinct from AIM2, suggesting they vary in effector mechanism in response to foreign DNA, and may bind different DNA structures. The PYHIN family has highly varied gene composition between mammalian species due to lineage-specific duplication and loss, which probably indicates different adaptations for fighting infectious disease. Non-genomic DNA can indicate infection, or a mutagenic threat. We hypothesise that defence of the genome against endogenous retroelements has been an additional evolutionary driver for PYHIN proteins.

Pancreatic cancer is one of the most deadly cancers affecting the Western world. Because the disease is highly metastatic and difficult to diagnosis until late stages, the 5-y survival rate is around 5%. The identification of molecular cancer drivers is critical for furthering our understanding of the disease and development of improved diagnostic tools and therapeutics. We have conducted a mutagenic screen using Sleeping Beauty (SB) in mice to identify new candidate cancer genes in pancreatic cancer. By combining SB with an oncogenic Kras allele, we observed highly metastatic pancreatic adenocarcinomas. Using two independent statistical methods to identify loci commonly mutated by SB in these tumors, we identified 681 loci that comprise 543 candidate cancer genes (CCGs); 75 of these CCGs, including Mll3 and Ptk2, have known mutations in human pancreatic cancer. We identified point mutations in human pancreatic patient samples for another 11 CCGs, including Acvr2a and Map2k4. Importantly, 10% of the CCGs are involved in chromatin remodeling, including Arid4b, Kdm6a, and Nsd3, and all SB tumors have at least one mutated gene involved in this process; 20 CCGs, including Ctnnd1, Fbxo11, and Vgll4, are also significantly associated with poor patient survival. SB mutagenesis provides a rich resource of mutations in potential cancer drivers for cross-comparative analyses with ongoing sequencing efforts in human pancreatic adenocarcinoma.

Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH) in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 ([Formula: see text]-value=0.0001) between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 ([Formula: see text]-value [Formula: see text] 2.2e-16) between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 ([Formula: see text]-value=0.004) between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.

Newborn screening programs have seen significant evolution since their initial implementation more than 60 years ago, with the primary goal of detecting treatable conditions within the earliest possible timeframe to ensure the optimal treatment and outcomes for the newborn. New technologies have driven the expansion of screening programs to cover additional conditions. In the current era, the breadth of screened conditions could be further expanded by integrating omic technologies such as untargeted metabolomics and genomics. Genomic screening could offer opportunities for lifelong care beyond the newborn period. For genomic newborn screening to be effective and ready for routine adoption, it must overcome barriers such as implementation cost, public acceptability, and scalability. Metabolomics approaches, on the other hand, can offer insight into disease phenotypes and could be used to identify known and novel biomarkers of disease. Given recent advances in metabolomic technologies, alongside advances in genomics including whole-genome sequencing, the combination of complementary multi-omic approaches may provide an exciting opportunity to leverage the best of both approaches and overcome their respective limitations. These techniques are described, along with the current outlook on multi-omic-based NBS research.

The cerebellum is a brain region responsible for motor coordination and for refining motor programs. While a great deal is known about the structure and connectivity of the mammalian cerebellum, fundamental questions regarding its function in behavior remain unanswered. Recently, the zebrafish has emerged as a useful model organism for cerebellar studies, owing in part to the similarity in cerebellar circuits between zebrafish and mammals. While the cell types composing their cerebellar cortical circuits are generally conserved with mammals, zebrafish lack deep cerebellar nuclei, and instead a majority of cerebellar output comes from a single type of neuron: the eurydendroid cell. To describe spatial patterns of cerebellar output in zebrafish, we have used genetic techniques to label and trace eurydendroid cells individually and en masse. We have found that cerebellar output targets the thalamus and optic tectum, and have confirmed the presence of pre-synaptic terminals from eurydendroid cells in these structures using a synaptically targeted GFP. By observing individual eurydendroid cells, we have shown that different medial-lateral regions of the cerebellum have eurydendroid cells projecting to different targets. Finally, we found topographic organization in the connectivity between the cerebellum and the optic tectum, where more medial eurydendroid cells project to the rostral tectum while lateral cells project to the caudal tectum. These findings indicate that there is spatial logic underpinning cerebellar output in zebrafish with likely implications for cerebellar function.

Somatic mutation calling from next-generation sequencing data remains a challenge due to the difficulties of distinguishing true somatic events from artifacts arising from PCR, sequencing errors or mis-mapping. Tumor cellularity or purity, sub-clonality and copy number changes also confound the identification of true somatic events against a background of germline variants. We have developed a heuristic strategy and software (http://www.qcmg.org/bioinformatics/qsnp/) for somatic mutation calling in samples with low tumor content and we show the superior sensitivity and precision of our approach using a previously sequenced cell line, a series of tumor/normal admixtures, and 3,253 putative somatic SNVs verified on an orthogonal platform.

We describe a sibling pair displaying an early infantile-onset, progressive neurodegenerative phenotype, with symptoms of developmental delay and epileptic encephalopathy developing from 12 to 14 months of age. Using whole exome sequencing, compound heterozygous variants were identified in SLC5A6, which encodes the sodium-dependent multivitamin transporter (SMVT) protein. SMVT is an important transporter of the B-group vitamins biotin, pantothenate, and lipoate. The protein is ubiquitously expressed and has major roles in vitamin uptake in the digestive system, as well as transport of these vitamins across the blood–brain barrier. Pathogenicity of the identified variants was demonstrated by impaired biotin uptake of mutant SMVT. Identification of this vitamin transporter as the genetic basis of this disorder guided targeted therapeutic intervention, resulting clinically in improvement of the patient’s neurocognitive and neuromotor function. This is the second report of biallelic mutations in SLC5A6 leading to a neurodegenerative disorder due to impaired biotin, pantothenate and lipoate uptake. The genetic and phenotypic overlap of these cases confirms mutations in SLC5A6 as the genetic cause of this disease phenotype. Recognition of the genetic disorder caused by SLC5A6 mutations is essential for early diagnosis and to facilitate timely intervention by triple vitamin (biotin, pantothenate, and lipoate) replacement therapy.

Critically ill infants and children with rare diseases need equitable access to rapid and accurate diagnosis to direct clinical management. Over 2 years, the Acute Care Genomics program provided whole-genome sequencing to 290 families whose critically ill infants and children were admitted to hospitals throughout Australia with suspected genetic conditions. The average time to result was 2.9 d and diagnostic yield was 47%. We performed additional bioinformatic analyses and transcriptome sequencing in all patients who remained undiagnosed. Long-read sequencing and functional assays, ranging from clinically accredited enzyme analysis to bespoke quantitative proteomics, were deployed in selected cases. This resulted in an additional 19 diagnoses and an overall diagnostic yield of 54%. Diagnostic variants ranged from structural chromosomal abnormalities through to an intronic retrotransposon, disrupting splicing. Critical care management changed in 120 diagnosed patients (77%). This included major impacts, such as informing precision treatments, surgical and transplant decisions and palliation, in 94 patients (60%). Our results provide preliminary evidence of the clinical utility of integrating multi-omic approaches into mainstream diagnostic practice to fully realize the potential of rare disease genomic testing in a timely manner. A report from the Australian Acute Care Genomics programme shows that the integration of rapid whole-genome sequencing and multi-omic analyses informs diagnoses and treatment decisions in a prospective cohort of 290 critically ill infants and children.

Reanalyzing stored genomic data over time is highly effective in increasing diagnostic yield in rare disease. Automation holds the promise of delivering the benefits of reanalysis at scale. Our study aimed to understand current reanalysis practices among Australian clinical and laboratory genetics services and explore attitudes towards large-scale automated re-analysis. We collected audit data regarding testing and reanalysis volumes, policies and procedures from all Australian diagnostic laboratories providing rare disease genomic testing. A genetic health professionals’ survey explored current practices, barriers to reanalysis, preferences and attitudes towards automation. Between 2018 and 2021, Australian diagnostic laboratories performed over 25,000 new genomic tests and 950 reanalyses, predominantly in response to clinician requests. Laboratory and clinical genetic health professionals (N = 134) identified workforce capacity as the principal barrier to reanalysis. No specific laboratory or clinical guidelines for genomic data reanalysis or policies were identified nationally. Perceptions of acceptability and feasibility of automating reanalysis were positive, with professionals emphasizing clinical and workflow benefits. In conclusion, there is a large and rapidly growing unmet need for reanalysis of existing genomic data. Beyond developing scalable automated reanalysis pipelines, leadership and policy are needed to successfully transform service delivery models and maximize clinical benefit.

International Cancer Genome Consortium members review and recommend computational approaches for identifying mutations that drive cancer progression from among the many sequence variants present in tumor genomes. The International Cancer Genome Consortium (ICGC) aims to catalog genomic abnormalities in tumors from 50 different cancer types. Genome sequencing reveals hundreds to thousands of somatic mutations in each tumor but only a minority of these drive tumor progression. We present the result of discussions within the ICGC on how to address the challenge of identifying mutations that contribute to oncogenesis, tumor maintenance or response to therapy, and recommend computational techniques to annotate somatic variants and predict their impact on cancer phenotype.