All cancers harbor molecular alterations in their genomes. The transcriptional consequences of these somatic mutations have not yet been comprehensively explored in lung cancer. Here we present the first large scale RNA sequencing study of lung adenocarcinoma, demonstrating its power to identify somatic point mutations as well as transcriptional variants such as gene fusions, alternative splicing events, and expression outliers. Our results reveal the genetic basis of 200 lung adenocarcinomas in Koreans including deep characterization of 87 surgical specimens by transcriptome sequencing. We identified driver somatic mutations in cancer genes including EGFR, KRAS, NRAS, BRAF, PIK3CA, MET, and CTNNB1. Candidates for novel driver mutations were also identified in genes newly implicated in lung adenocarcinoma such as LMTK2, ARID1A, NOTCH2, and SMARCA4. We found 45 fusion genes, eight of which were chimeric tyrosine kinases involving ALK, RET, ROS1, FGFR2, AXL, and PDGFRA. Among 17 recurrent alternative splicing events, we identified exon 14 skipping in the protooncogene MET as highly likely to be a cancer driver. The number of somatic mutations and expression outliers varied markedly between individual cancers and was strongly correlated with smoking history of patients. We identified genomic blocks within which gene expression levels were consistently increased or decreased that could be explained by copy number alterations in samples. We also found an association between lymph node metastasis and somatic mutations in TP53. These findings broaden our understanding of lung adenocarcinoma and may also lead to new diagnostic and therapeutic approaches.

Although massively parallel sequencing approaches have been widely used to study genomic variation, simple alignment of short reads to a reference genome cannot be used to investigate the full range of structural variation and phased diploid architecture, which are important for precision medicine. By contrast, the single-molecule real-time (SMRT) sequencing platform produces long reads that can resolve repetitive structures effectively. We integrated this technology with several other sequencing approaches to construct a high-quality

Colloidal quantum dot (CQD) photovoltaics offer a promising approach to harvest the near-IR region of the solar spectrum, where half of the sun's power reaching the earth resides. High external quantum efficiencies have been obtained in the visible region in lead chalcogenide CQD photovoltaics. However, the corresponding efficiencies for band gap radiation in the near-infrared lag behind because the thickness of CQD photovoltaic layers from which charge carriers can be extracted is limited by short carrier diffusion lengths. Here, we investigate, using a combination of electrical and optical characterization techniques, ligand passivation strategies aimed at tuning the density and energetic distribution of charge trap states at PbS nanocrystal surfaces. Electrical and optical measurements reveal a more than 7-fold enhancement of the mobility-lifetime product of PbS CQD films treated with 3-mercaptopropionic acid (MPA) in comparison to traditional organic passivation strategies that have been examined in the literature. We show by direct head-to-head comparison that the greater mobility-lifetime products of MPA-treated devices enable markedly greater short-circuit current and higher power conversion efficiency under AM1.5 illumination. Our findings highlight the importance of selecting ligand treatment strategies capable of passivating a diversity of surface states to enable shallower and lower density trap distributions for better transport and more efficient CQD solar cells.

The mammalian meiosis-specific KASH protein KASH5 connects the telomere-associated SUN1 protein to the cytoplasmic force–generating mechanism involved in meiotic chromosome movement.