Significance: Phenotypic plasticity is common in nature, yet the mechanisms by which environmental inputs are detected and alter developmental programs are not well understood. Even less explored are the mechanisms underlying transgenerational plasticity. Here we address the problem of how asexual aphids produce winged or wingless offspring in response to external cues. We find that gene expression patterns suggest the importance of the hormone ecdysone in this polyphenism. We show that aphids injected with ecdysone or its analog produce fewer winged offspring, and aphids with inhibited ecdysone signaling produce more winged offspring. Our results provide insight into the hormonal control of alternative aphid morphs, which have long been a textbook example of polyphenism, but whose control mechanisms have long proven elusive.

Background: Alterations in the dopamine transmission and receptor density are hypothesized in the pathophysiology of schizophrenia but ethnic disparities are reported to exist in disease association and therapeutic response to psychotropic medication. Antipsychotics have higher binding affinity to D2 subtype of dopamine receptor. DRD2 Cys311, TaqIB1 and TaqIA1 variants are considered to have either reduced affinity for dopamine and hypo-dopaminergic activity.Methods: We examined the role of Taq1B, Taq1D, S311C, H313H and Taq1A polymorphisms of DRD2 gene in schizophrenia and antipsychotic treatment response in 213 patients and 196 controls from a homogenous South Indian population. A more detailed genotype phenotype association analysis was carried out to understand the disease in terms of its socio-cultural factors.Results: H313HTT genotype was found to be associated with schizophrenia (P = 0.004) while TaqIB1B1 genotype was significantly associated with higher psychopathology score. When treatment response was considered H313HCC, TaqIA2A2 and Taq1D1D1 had higher mean improvement scores. TaqID1D1 and H313HTT genotype were found to be significantly higher in responders than in nonresponder group. Distinct shift in the LD patterns of responder and non-responder group was observed. Certain symptoms were characteristic of our patient population. Following medication the scores and presentation of these symptoms tend to vary in the responder and non-responder groups.Conclusion: Based on genotype phenotype correlations it can be suggested that certain polymorphisms can be defined for their critical functions in disease and their role in treatment response in South Indian population. The present study suggests that in addition to ethnic bias, socio-cultural factors should also be considered while evaluating genotype phenotype correlations, in association and treatment response to complex disorders like schizophrenia.

Gene fusions that contribute to oncogenicity can be explored for identifying cancer biomarkers and potential drug targets. To investigate the nature and distribution of fusion transcripts in cancer, we examined the transcriptome data of about 9,000 primary tumors from 33 different cancers in TCGA (The Cancer Genome Atlas) along with cell line data from CCLE (Cancer Cell Line Encyclopedia) using ChimeRScope, a novel fusion detection algorithm. We identified several fusions with sense (canonical, 39%) or antisense (non-canonical, 61%) transcripts recurrent across cancers. The majority of the recurrent non-canonical fusions found in our study are novel, unexplored, and exhibited highly variable profiles across cancers, with breast cancer and glioblastoma having the highest and lowest rates, respectively. Overall, 4,344 recurrent fusions were identified from TCGA in this study, of which 70% were novel. Additional analysis of 802 tumor-derived cell line transcriptome data across 20 cancers revealed significant variability in recurrent fusion profiles between primary tumors and corresponding cell lines. A subset of canonical and non-canonical fusions was validated by examining the structural variation evidence in whole-genome sequencing (WGS) data or by Sanger sequencing of fusion junctions. Several recurrent fusion genes identified in our study show promise for drug repurposing in basket trials and present opportunities for mechanistic studies.

Wing dimorphisms have long served as models for examining the ecological and evolutionary tradeoffs associated with alternative phenotypes. Here, we investigated the genetic cause of the pea aphid (Acyrthosiphon pisum) male wing dimorphism, wherein males exhibit one of two morphologies that differ in correlated traits that include the presence or absence of wings. We mapped this trait difference to a single genomic region and, using third generation, long-read sequencing, we identified a 120 kb insertion in the wingless allele. This insertion includes a duplicated follistatin gene, which is a strong candidate gene in the minimal mapped interval to cause the dimorphism. We found that both alleles were present prior to pea aphid biotype lineage diversification, we estimated that the insertion occurred millions of years ago, and we propose that both alleles have been maintained in the species, likely due to balancing selection.

The RNA-Seq technology has revolutionized transcriptome characterization not only by accurately quantifying gene expression, but also by the identification of novel transcripts like chimeric fusion transcripts. The ‘fusion’ or ‘chimeric’ transcripts have improved the diagnosis and prognosis of several tumors, and have led to the development of novel therapeutic regimen. The fusion transcript detection is currently accomplished by several software packages, primarily relying on sequence alignment algorithms. The alignment of sequencing reads from fusion transcript loci in cancer genomes can be highly challenging due to the incorrect mapping induced by genomic alterations, thereby limiting the performance of alignment-based fusion transcript detection methods. Here, we developed a novel alignment-free method, ChimeRScope that accurately predicts fusion transcripts based on the gene fingerprint (as k-mers) profiles of the RNA-Seq paired-end reads. Results on published datasets and in-house cancer cell line datasets followed by experimental validations demonstrate that ChimeRScope consistently outperforms other popular methods irrespective of the read lengths and sequencing depth. More importantly, results on our in-house datasets show that ChimeRScope is a better tool that is capable of identifying novel fusion transcripts with potential oncogenic functions. ChimeRScope is accessible as a standalone software at (https://github.com/ChimeRScope/ChimeRScope/wiki) or via the Galaxy web-interface at (https://galaxy.unmc.edu/).