Pooled-DNA sequencing strategies enable fast, accurate, and cost-effect detection of rare variants, but current approaches are not able to accurately identify short insertions and deletions (indels), despite their pivotal role in genetic disease. Furthermore, the sensitivity and specificity of these methods depend on arbitrary, user-selected significance thresholds, whose optimal values change from experiment to experiment. Here, we present a combined experimental and computational strategy that combines a synthetically engineered DNA library inserted in each run and a new computational approach named SPLINTER that detects and quantifies short indels and substitutions in large pools. SPLINTER integrates information from the synthetic library to select the optimal significance thresholds for every experiment. We show that SPLINTER detects indels (up to 4 bp) and substitutions in large pools with high sensitivity and specificity, accurately quantifies variant frequency (r = 0.999), and compares favorably with existing algorithms for the analysis of pooled sequencing data. We applied our approach to analyze a cohort of 1152 individuals, identifying 48 variants and validating 14 of 14 (100%) predictions by individual genotyping. Thus, our strategy provides a novel and sensitive method that will speed the discovery of novel disease-causing rare variants.

Interleukins and neurotrophins levels are altered in the periphery of patients with major depression and suicidal behavior, however it is not clear if similar abnormalities occur in the central nervous system. Our objective was to examine the association of IL-6, IL-1β, BDNF, and GDNF levels between postmortem plasma, cerebrospinal fluid (CSF), and brain tissue in a heterogeneous diagnostic subject groups including normal controls, mood disorders only, mood disorders with AUD/SUD (alcohol abuse disorder, substance abuse disorder), and AUD/SUD without mood disorders. To address these questions we collected postmortem plasma (n = 29), CSF (n = 28), and brain (BA10) (n = 57) samples from individuals with mood disorder, mood disorder with AUD/SUD, AUD/SUD and normal controls. These samples were analyzed using a multiplex based luminex assay with a customized 4-plex cytokine/interleukins- IL-6, IL-1β, BDNF, and GDNF human acute phase based on xMAP technology platform. Protein levels were determined using a Luminex 200 instrument equipped with Xponent-analyzing software. We observed IL-6 (p = 2.1e-07), and GDNF (p = 0.046) were significantly correlated between brain and CSF. In addition, IL-6 (p = 0.031), were significantly correlated between brain and plasma. Overall diagnostic group analysis showed a significant difference with brain GDNF, p = 0.0106. Pairwise comparisons showed that GDNF level is—39.9 ± 12 pg/ml, p = 0.0106, was significantly higher than in the brains derived from mood disorders compared to normal controls, —23.8 ± 5.5 pg/ml, p = 0.034. Brain BDNF was higher in suicide (p = 0.0023), males compared to females (p = 0.017), and psychiatric medication treated vs. non-treated (p = 0.005) individuals. Overall, we demonstrate that blood IL-6, GDNF and BDNF could be informative peripheral biomarkers of brain biology associated with mood disorders, substance disorders, and suicide.

Hypoxanthine phosphoribosyl transferase 1 (HPRT1) is traditionally believed to be a housekeeping gene; however, recent reports suggest that it is upregulated in several cancers and is associated with clinical outcomes. HPRT1 is located on chromosome X and encodes the HPRT enzyme, which functions in recycling nucleotides to supply for DNA and RNA synthesis in actively dividing cells. Here, we used transcriptomic analyses to interrogate its expression across all known cancer types and elucidated its role in regulating gene expression in breast cancer. We observed elevated HPRT1 RNA levels in malignant tissues when compared to normal controls, indicating its potential as a diagnostic and prognostic marker. Further, in breast cancer, the subtype-specific analysis showed that its expression was highest in basal and triple-negative breast cancer, and HPRT1 knockdown in breast cancer cells suggested that HPRT1 positively regulates genes related to cancer pathways. Collectively, our results essentially highlight the importance of and change the way in which HPRT1’s function is studied in biology, warranting careful examination of its role in cancer.