SpectroGene: A Tool for Proteogenomic Annotations Using Top-Down Spectra

In the past decade, proteogenomics has emerged as a valuable technique that contributes to the state-of-the-art in genome annotation; however, previous proteogenomic studies were limited to bottom-up mass spectrometry and did not take advantage of top-down approaches. We show that top-down proteogenomics allows one to address the problems that remained beyond the reach of traditional bottom-up proteogenomics. In particular, we show that top-down proteogenomics leads to the discovery of previously unannotated genes even in extensively studied bacterial genomes and present SpectroGene, a software tool for genome annotation using top-down tandem mass spectra. We further show that top-down proteogenomics searches (against the six-frame translation of a genome) identify nearly all proteoforms found in traditional top-down proteomics searches (against the annotated proteome). SpectroGene is freely available at http://github.com/fenderglass/SpectroGene

Deconstructing the PCAOB: Using organizational economics to assess the state of a regulator

Using the principles of organizational economics in this study we assess the quality of the organizational architecture of the Public Companies Accounting Oversight Board (PCAOB). In particular, we use the Four Pillar Framework developed in Brickley et al. (2000) to understand why—according to the SEC’s Chairman Gensler and other stakeholders—the PCAOB may not have entirely realized its mission of investor protection. Our analysis is enabled by the transcripts of the 2019 criminal trial U.S. vs. Middendorf and Wada (i.e., PCAOB-KPMG “steal the inspection data” scandal), which for the first time exposed the inner workings of the PCAOB. Our analysis of the transcripts is augmented by other publicly available documents. Our primary conclusion is that the functioning of the PCAOB has been significantly hampered by misalignment of its tasks (in particular in relation to the SEC), sub-optimally designed performance measurement and employee compensation, and weaknesses in the PCAOB’s organizational culture. These misalignments created an environment susceptible to PCAOB employee criminal misconduct which enabled the PCAOB-KPMG “steal the inspection data” scandal and other Board governance and leadership challenges

Assembly of long error-prone reads using de Bruijn graphs

The recent breakthroughs in assembling long error-prone reads were based on the overlap-layout-consensus (OLC) approach and did not utilize the strengths of the alternative de Bruijn graph approach to genome assembly. Moreover, these studies often assume that applications of the de Bruijn graph approach are limited to short and accurate reads and that the OLC approach is the only practical paradigm for assembling long error-prone reads. We show how to generalize de Bruijn graphs for assembling long error-prone reads and describe the ABruijn assembler, which combines the de Bruijn graph and the OLC approaches and results in accurate genome reconstructions

Erratum: Corrigendum: Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution

International Chicken Genome Sequencing Consortium. The Original Article was published on 09 December 2004. Nature432, 695–716 (2004). In Table 5 of this Article, the last four values listed in the ‘Copy number’ column were incorrect. These should be: LTR elements, 30,000; DNA transposons, 20,000; simple repeats, 140,000; and satellites, 4,000. These errors do not affect any of the conclusions in our paper. Additional information. The online version of the original article can be found at 10.1038/nature0315

Labor adjustment costs and asymmetric cost behavior: An extension

The issue of asymmetric cost behavior has attracted significant interest in the managerial accounting literature. The literature has hypothesized that adjustment costs, particularly labor adjustment costs, play a significant and central role in driving empirically observed cost behavior patterns. Recent studies attempt to empirically test this hypothesis, albeit with distinct limitations. Using a new proxy for labor adjustment costs in a different population of firms, our study takes a fresh look at this hypothesis. We test the robustness of results documented in prior studies to help substantiate the credibility, reliability, and stability of prior findings. Our proxy for labor adjustment costs captures the reliance on skilled labor across industries in a population of US public firms. Prior studies argue that skilled labor is associated with higher adjustment costs than unskilled labor due to greater hiring and firing costs associated with skilled labor. Based on the theoretical underpinnings of asymmetric cost behavior, we expect that a higher reliance on skilled labor will be associated with greater cost asymmetry. Our empirical results support this proposition. In additional subsample tests, we also find that the effect of labor adjustment costs on cost asymmetry is more pronounced when unemployment rates are low, for firms located in high Wrongful Discharge Laws (WDL) states, and for firms situated in low-hiring credit states. Together, these results provide compelling evidence that validates the consequential role of labor adjustment costs in determining asymmetric cost behavior

Conditional accounting conservatism and future negative surprises: An empirical investigation

We investigate whether conditional accounting conservatism has informational benefits to shareholders. We find some evidence that higher current conditional conservatism is associated with lower probability of future bad news, proxied by missing analyst forecasts, earnings decreases, and dividend decreases. Second, we find weak evidence that the stock market reacts stronger (weaker) to good (bad) earnings news of more conditionally conservative firms. Thus, we provide additional evidence that conditional conservatism affects stock prices.

Analyzing rare mutations in metagenomes assembled using long and accurate reads

The advent of long and accurate "HiFi" reads has greatly improved our ability to generate complete metagenome-assembled genomes (MAGs), enabling "complete metagenomics" studies that were nearly impossible to conduct with short reads. In particular, HiFi reads simplify the identification and phasing of mutations in MAGs: It is increasingly feasible to distinguish between positions that are prone to mutations and positions that rarely ever mutate, and to identify co-occurring groups of mutations. However, the problems of identifying rare mutations in MAGs, estimating the false-discovery rate (FDR) of these identifications, and phasing identified mutations remain open in the context of HiFi data. We present strainFlye, a pipeline for the FDR-controlled identification and analysis of rare mutations in MAGs assembled using HiFi reads. We show that deep HiFi sequencing has the potential to reveal and phase tens of thousands of rare mutations in a single MAG, identify hotspots and coldspots of these mutations, and detail MAGs' growth dynamics