We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor–binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor–binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.

The accumulation of damaged mitochondria has been proposed as a key factor in aging and the pathogenesis of many common agerelated diseases, including Parkinson disease (PD). Recently, in vitro studies of the PD-related proteins Parkin and PINK1 have found that these factors act in a common pathway to promote the selective autophagic degradation of damaged mitochondria (mitophagy). However, whether Parkin and PINK1 promote mitophagy under normal physiological conditions in vivo is unknown. To address this question, we used a proteomic approach in Drosophila to compare the rates of mitochondrial protein turnover in parkin mutants, PINK1 mutants, and control flies. We found that parkin null mutants showed a significant overall slowing of mitochondrial protein turnover, similar to but less severe than the slowing seen in autophagydeficient Atg7 mutants, consistent with the model that Parkin acts upstream of Atg7 to promote mitophagy. By contrast, the turnover of many mitochondrial respiratory chain (RC) subunits showed greater impairment in parkin than Atg7 mutants, and RC turnover was also selectively impaired in PINK1 mutants. Our findings show that the PINK1-Parkin pathway promotes mitophagy in vivo and, unexpectedly, also promotes selective turnover of mitochondrial RC subunits. Failure to degrade damaged RC proteins could account for the RC deficits seen in many PD patients and may play an important role in PD pathogenesis. U nderstanding the mechanisms of mitochondrial quality control is a critical challenge in research on neurodegeneration and aging. The accumulation of damaged mitochondria has been linked to normal aging and multiple age-related disorders, including Alzheimer's disease, diabetes, and Parkinson disease (PD) (1, 2). Recent research points to two PD-associated proteins as essential mediators of selective autophagic mitochondrial degradation: phosphatase and tensin homolog-induced putative kinase 1 (PINK1), a mitochondrially targeted serine/threonine kinase, and Parkin, a cytosolic E3 ubiquitin ligase. Genetic studies in Drosophila determined that PINK1 acts upstream of Parkin in a common pathway to regulate mitochondrial morphology and integrity (3-8), and led to the hypothesis that this pathway promotes the selective degradation of damaged mitochondria (6, 9). Subsequent experiments, primarily in cultured cells, validated this hypothesis and described the mechanism of action of the pathway (10-12). These studies showed that loss of mitochondrial membrane potential (depolarization) leads to accumulation of PINK1 on the mitochondrial outer membrane, which triggers recruitment of Parkin to the mitochondria. Parkin then ubiquitinates proteins in the outer mitochondrial membrane (13-17), leading to autophagic degradation of the dysfunctional mitochondrion.Although there is substantial support for the role of the PINK1-Parkin pathway in selective mitochondrial degradation, it is still not clear that this pathway promotes mitochondrial degradation in vivo. PINK1-Parkin-dependent mitophagy has been d...

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In mass spectrometry based proteomics, data-independent acquisition (DIA) strategies have the ability to acquire a single dataset useful for identification and quantification of detectable peptides in a complex mixture. Despite this, DIA is often overlooked due to noisier data resulting from a typical five to ten fold reduction in precursor selectivity compared to data dependent acquisition or selected reaction monitoring. We demonstrate a multiplexing technique which improves precursor selectivity five-fold.