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Abstract Background Retinoblastoma (RB) a tumour affecting those under 5 years, has a prevalence of 1 in 20,000, with around twenty new diagnoses per year in Sri Lanka. Unilateral and bilateral RB presents around 24 and 15 months respectively. Approximately 10% are familial. Systematic genetic testing for germline pathogenic variants of RB1, the only gene associated with an inherited risk of RB, is unavailable in Sri Lanka. Genetic testing optimizes management of affected children and at-risk siblings. This study aimed to develop accessible genetic testing to identify children with a germline pathogenic variant of RB1 in Sri Lanka. Methods Targeted next generation sequencing (NGS) for detecting pathogenic sequence variants and Gene Ratio Analysis Copy Enumeration PCR (GRACE-PCR) for detecting RB1 copy number variations (CNVs) were performed for 49 consecutive RB patients treated between 2016 and 2020 at the designated RB care unit, Lady Ridgway hospital, Colombo. Patients (bilateral RB (n = 18; 37%), unilateral n = 31) were recruited following ethical clearance and informed consent. Results There were 26 (53%) females. Mean age at diagnosis was 18 months. Thirty-five patients (71%) had undergone enucleation. Germline pathogenic variants of RB1 identified in 22/49 (45%) patients including 18 (37%; 12 bilateral and 6 unilateral) detected by targeted NGS (2 missense, 7 stop gained, 1 splice donor, 8 frameshift variants). Six were previously undescribed, likely pathogenic frameshift variants. Four bilateral RB patients had GRACE-PCR detected CNVs including one whole RB1, two intragenic deletions (exon 12/13; exon 11 and 23) and a partial duplication of exon 27. The only familial case (affected mother and child) shared the duplication. Only 2 of 4 CNVs and 10 of 18 pathogenic variants were confirmed by whole exome sequencing and Sanger sequencing respectively, due to funding limitations. Conclusions The study identified pathogenic or likely pathogenic germline RB1 sequence variants and copy number variants in 16/18 (89%) bilateral and 6/31(19%) unilateral cases, which is comparable to worldwide data (10–15% unilateral, 80–85% bilateral). Targeted NGS combined with GRACE-PCR significantly reduce the cost of RB1 testing in Sri Lanka, and may widen access for genetic diagnosis of RB patients in other low and middle income countries.

Clostridium difficile (C. difficile) is a multi-strain, spore-forming, Gram-positive, opportunistic enteropathogen bacteria, majorly associated with nosocomial infections, resulting in severe diarrhoea and colon inflammation. Several antibiotics including penicillin, tetracycline, and clindamycin have been employed to control C. difficile infection, but studies have suggested that injudicious use of antibiotics has led to the development of resistance in C. difficile strains. However, many proteins from its genome are still considered uncharacterized proteins that might serve crucial functions and assist in the biological understanding of the organism. In this study, we aimed to annotate and characterise the 6 C. difficile strains using in silico approaches. We first analysed the complete genome of 6 C. difficile strains using standardised approaches and analysed hypothetical proteins (HPs) employing various bioinformatics approaches coalescing, including identifying contigs, coding sequences, phage sequences, CRISPR-Cas9 systems, antimicrobial resistance determination, membrane helices, instability index, secretory nature, conserved domain, and vaccine target properties like comparative homology analysis, allergenicity, antigenicity determination along with structure prediction and binding-site analysis. This study provides crucial supporting information about the functional characterization of the HPs involved in the pathophysiology of the disease. Moreover, this information also aims to assist in mechanisms associated with bacterial pathogenesis and further design candidate inhibitors and bona fide pharmaceutical targets.

Prostate cancer (PCa) is the third most common cancer among men in India, and no next-generation sequencing (NGS) studies have been attempted earlier. Recent advances in NGS have heralded the discovery of biomarkers from Caucasian/European and Chinese ancestry, but not much is known about the Indian phenotype/variant of PCa. In a pilot study using the whole exome sequencing of benign/PCa patients, we identified characteristic mutations specific to the Indian sub-population. We observed a large number of mutations in DNA repair genes, viz. helicases, TP53, and BRCA besides the variants of unknown significance with a possibly damaging rare variant (rs730881069/chr19:55154172C/TR136Q) in the TNNI3 gene that has been previously reported as a semi-conservative amino acid substitution. Our pilot study attempts to bring an understanding of PCa prognosis and recurrence for the Indian phenotype.

We performed a systematic analysis of genes implicated in thigh subcutaneous adipose tissue of Asian Indian Type 2 Diabetes Mellitus (AIT2DM) and created a phenome-interactome network. This analysis was performed on 60 subjects specific to limb thigh fat by integrating phenotypic traits and similarity scores associated with AIT2DM. Using a phenotypic attribute, a contextual neighbor was identified across all the traits, viz. body mass index (BMI) statistics, adipocyte size, lipid parameters, homeostatic model assessment- insulin resistance (HOMA-IR), HOMA-ß. In this work, we have attempted to characterize transcription signatures using the phenome-interactome maps where each of the traits under study including the intermediary phenotypes has a distinct set of genes forming the hubs. Furthermore, we have identified various clinical, biochemical, and radiological parameters which show significant correlation with distinct hubs. We observed a number of novel pathways and genes including those that are non-coding RNAs implicated in AIT2DM.We showed that they appear to be associated with pathways, viz. tyrosine kinase JAK2, NOTCH thereby recruiting signaling molecules such as STAT5 and Src family kinases on the cell surface regulated them and our analyses comprising significant hubs suggest that thigh subcutaneous adipose tissue plays a role in pathophysiology of AIT2DM.

Data mining and pattern recognition methods reveal interesting findings in genetic studies, especially on how genetic makeup is associated with inherited diseases. Although researchers have proposed various data mining models for biomedical approaches, there remains a challenge in accurately determining the responsible genetic factors for prioritizing the single nucleotide polymorphisms (SNP) associated with the disease. In this commentary, we review the state-of-art data mining and pattern recognition models for identifying inherited diseases and deliberate the need of binary classification and scoring based prioritization methods for determining causal variants. While we discuss the pros and cons associated with these methods known, we argue that the gene prioritization methods and the protein interaction (PPI) methods in conjunction with the K nearest neighbors’ could be used in accurately categorizing the genetic factors in disease causation