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Mitochondria are integral to cellular energy metabolism and ATP production and are involved in regulating many cellular processes. Mitochondria produce reactive oxygen species (ROS), which not only can damage cellular components but also participate in signal transduction. The kinase ATM, which is mutated in the neurodegenerative, autosomal recessive disease ataxia-telangiectasia (A-T), is a key player in the nuclear DNA damage response. However, ATM also performs a redox-sensing function mediated through formation of ROS-dependent disulfide-linked dimers. We found that mitochondria-derived hydrogen peroxide promoted ATM dimerization. In HeLa cells, ATM dimers were localized to the nucleus and inhibited by the redox regulatory protein thioredoxin 1 (TRX1), suggesting the existence of a ROS-mediated, stress-signaling relay from mitochondria to the nucleus. ATM dimer formation did not affect its association with chromatin in the absence or presence of nuclear DNA damage, consistent with the separation of its redox and DNA damage signaling functions. Comparative analysis of U2OS cells expressing either wild-type ATM or the redox sensing-deficient C2991L mutant revealed that one function of ATM redox sensing is to promote glucose flux through the pentose phosphate pathway (PPP) by increasing the abundance and activity of glucose-6-phosphate dehydrogenase (G6PD), thereby increasing cellular antioxidant capacity. The PPP produces the coenzyme NADPH needed for a robust antioxidant response, including the regeneration of TRX1, indicating the existence of a regulatory feedback loop involving ATM and TRX1. We propose that loss of the mitochondrial ROS-sensing function of ATM may cause cellular ROS accumulation and oxidative stress in A-T.

Human globin gene expression during development is modulated by transcription factors in a stage-dependent manner. However, the mechanisms controlling the process are still largely unknown. In this study, we found that a nuclear protein, LYAR (human homologue of mouse Ly-1 antibody reactive clone) directly interacted with the methyltransferase PRMT5 which triggers the histone H4 Arg3 symmetric dimethylation (H4R3me2s) mark. We found that PRMT5 binding on the proximal γ-promoter was LYAR-dependent. The LYAR DNA-binding motif (GGTTAT) was identified by performing CASTing (cyclic amplification and selection of targets) experiments. Results of EMSA and ChIP assays confirmed that LYAR bound to a DNA region corresponding to the 5′-untranslated region of the γ-globin gene. We also found that LYAR repressed human fetal globin gene expression in both K562 cells and primary human adult erythroid progenitor cells. Thus, these data indicate that LYAR acts as a novel transcription factor that binds the γ-globin gene, and is essential for silencing the γ-globin gene.

This paper establishes an asymptotic theory and inference method for quantile treatment effect estimators when the quantile index is close to or equal to zero. Such quantile treatment effects are of interest in many applications, such as the effect of maternal smoking on an infant's adverse birth outcomes. When the quantile index is close to zero, the sparsity of data jeopardizes conventional asymptotic theory and bootstrap inference. When the quantile index is zero, there are no existing inference methods directly applicable in the treatment effect context. This paper addresses both of these issues by proposing new inference methods that are shown to be asymptotically valid as well as having adequate finite sample properties.

In this paper we prove the strong consistency of several methods based on the spectral clustering techniques that are widely used to study the community detection problem in stochastic block models (SBMs). We show that under some weak conditions on the minimal degree, the number of communities, and the eigenvalues of the probability block matrix, the K-means algorithm applied to the eigenvectors of the graph Laplacian associated with its first few largest eigenvalues can classify all individuals into the true community uniformly correctly almost surely. Extensions to both regularized spectral clustering and degree-corrected SBMs are also considered. We illustrate the performance of different methods on simulated networks.