A major challenge remaining in drug design efforts towards protein kinase is due to the development of drug resistance initiated by the missense mutations in the kinase catalytic domain. Gain or loss of function mutations in the REarranged during Transfection (RET) tyrosine kinase gene have been associated with the development of a wide range of human associated cancers and Hirschsprung's disease. However, to what extent these mutations might affect bio-molecular functions remains unclear. In this article, the functionally significant mutations in RET were screened with the aid of various sequence and structure based in silico prediction methods. We mapped the deleterious mutants, modelled mutant proteins and deciphered the impact of mutations on drug binding mechanisms in the RET crystal structure of PDB ID: with the potential inhibitor vandetanib by docking analysis. Furthermore, molecular dynamics simulations were undertaken to understand the mechanistic action of cancer associated mutations in altering the protein kinase structure, dynamics, and stability. According to our results, the overall effect of V804M, M918T and S922Y were destabilizing and mostly alter the electrostatic component of the binding energy. Specifically, the mutation of gatekeeper residue valine 804 present in the ATP binding pocket affects the protein stability and confers resistance to the drug vandetanib, which was consistent with previously published experimental results. Overall, our findings may provide useful structural insights for in-depth understanding of the molecular mechanism underlying RET mutation and developing effective drugs.

Recent studies have suggested that individual variants do not sufficiently explain the variable expressivity of phenotypes observed in complex disorders. For example, the 16p12.1 deletion is associated with developmental delay and neuropsychiatric features in affected individuals, but is inherited in >90% of cases from a mildly-affected parent. While children with the deletion are more likely to carry additional "second-hit" variants than their parents, the mechanisms for how these variants contribute to phenotypic variability are unknown. We performed detailed clinical assessments, whole-genome sequencing, and RNA sequencing of lymphoblastoid cell lines for 32 individuals in five large families with multiple members carrying the 16p12.1 deletion. We found that the deletion dysregulates multiple autism and brain development genes such as FOXP1, ANK3, and MEF2. Carrier children also showed expression changes that were inherited as well as de novo compared with their parents, which matched with 39/47 observed developmental phenotypes. We identified significant enrichments for 13/25 classes of "second-hit" variants in genes with expression changes, where 7/25 variant classes were only enriched when inherited from the non-carrier parent, including missense SNVs and large deletions. In 11 instances, including for ZEB2 and SYNJ1, gene expression was synergistically altered by both the deletion and inherited "second-hits" in carrier children. Finally, brain-specific interaction network analysis showed strong connectivity between genes carrying "second-hits" and genes with transcriptome alterations, including differential expression, alternative splicing, and allele-specific expression. Our study shows that family-based assessments of transcriptome data are highly relevant towards understanding the genetic mechanisms associated with complex disorders.

Background Recent studies have suggested that individual variants do not sufficiently explain the variable expressivity of phenotypes observed in complex disorders. For example, the 16p12.1 deletion is associated with developmental delay and neuropsychiatric features in affected individuals, but is inherited in > 90% of cases from a mildly-affected parent. While children with the deletion are more likely to carry additional “second-hit” variants than their parents, the mechanisms for how these variants contribute to phenotypic variability are unknown. Methods We performed detailed clinical assessments, whole-genome sequencing, and RNA sequencing of lymphoblastoid cell lines for 32 individuals in five large families with multiple members carrying the 16p12.1 deletion. We identified contributions of the 16p12.1 deletion and “second-hit” variants towards a range of expression changes in deletion carriers and their family members, including differential expression, outlier expression, alternative splicing, allele-specific expression, and expression quantitative trait loci analyses. Results We found that the deletion dysregulates multiple autism and brain development genes such as FOXP1, ANK3, and MEF2. Carrier children also showed an average of 5323 gene expression changes compared with one or both parents, which matched with 33/39 observed developmental phenotypes. We identified significant enrichments for 13/25 classes of “second-hit” variants in genes with expression changes, where 4/25 variant classes were only enriched when inherited from the noncarrier parent, including loss-of-function SNVs and large duplications. In 11 instances, including for ZEB2 and SYNJ1, gene expression was synergistically altered by both the deletion and inherited “second-hits” in carrier children. Finally, brain-specific interaction network analysis showed strong connectivity between genes carrying “second-hits” and genes with transcriptome alterations in deletion carriers. Conclusions Our results suggest a potential mechanism for how “second-hit” variants modulate expressivity of complex disorders such as the 16p12.1 deletion through transcriptomic perturbation of gene networks important for early development. Our work further shows that family-based assessments of transcriptome data are highly relevant towards understanding the genetic mechanisms associated with complex disorders.

High-throughput methods such as RNA-seq, ChIP-seq and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying activity of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. Further, the assay is long with >250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control checkpoints necessary for reproducibility of the assay. We also provide guidelines for assay design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve reproducibility of results.

High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.