The CDK-Activating Kinase (CAK) Csk1 Is Required for Normal Levels of Homologous Recombination and Resistance to DNA Damage in Fission Yeast

BACKGROUND: Cyclin-dependent kinases (CDKs) perform essential roles in cell division and gene expression in all eukaryotes. The requirement for an upstream CDK-activating kinase (CAK) is also universally conserved, but the fission yeast Schizosaccharomyces pombe appears to be unique in having two CAKs with both overlapping and specialized functions that can be dissected genetically. The Mcs6 complex--orthologous to metazoan Cdk7/cyclin H/Mat1--activates the cell-cycle CDK, Cdk1, but its non-redundant essential function appears to be in regulation of gene expression, as part of transcription factor TFIIH. The other CAK is Csk1, an ortholog of budding yeast Cak1, which activates all three essential CDKs in S. pombe--Cdk1, Mcs6 and Cdk9, the catalytic subunit of positive transcription elongation factor b (P-TEFb)--but is not itself essential. METHODOLOGY/PRINCIPAL FINDINGS: Cells lacking csk1(+) are viable but hypersensitive to agents that damage DNA or block replication. Csk1 is required for normal levels of homologous recombination (HR), and interacts genetically with components of the HR pathway. Tests of damage sensitivity in csk1, mcs6 and cdk9 mutants indicate that Csk1 acts pleiotropically, through Cdk9 and at least one other target (but not through Mcs6) to preserve genomic integrity. CONCLUSIONS/SIGNIFICANCE: The two CAKs in fission yeast, which differ with respect to their substrate range and preferences for monomeric CDKs versus CDK/cyclin complexes as substrates, also support different functions of the CDK network in vivo. Csk1 plays a non-redundant role in safeguarding genomic integrity. We propose that specialized activation pathways dependent on different CAKs might insulate CDK functions important in DNA damage responses from those capable of triggering mitosis

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

Strains used in this study

<p>Strains used in this study</p

A <i>csk1Δ</i> strain is hypersensitive to DNA damaging agents.

<p>Survival was measured after irradiation with UV (A) or IR (B) of the following strains: wild type (JS78), <i>csk1Δ</i> (JS155). (C) 10-fold serial dilutions of the wild-type and <i>csk1Δ</i> strains [as in (A)] in mid-log phase were plated on fresh media containing no drug (top), 0.005% MMS (middle) or 6 mM hydroxyurea (bottom), and incubated 3–5 days before photographing.</p

Epistasis analysis with homologous recombination genes.

<p>(A) Survival after irradiation with UV or IR of the strains: (A) wild type (JS78), <i>csk1Δ</i> (JS155), <i>rhp51Δ</i> (YP6), <i>csk1Δ rhp51Δ</i> (HD4-6); (B) wild type (JS78), <i>csk1Δ</i> (JS155), <i>rhp54Δ</i> (YP25), <i>csk1Δ rhp54Δ</i> (HD2-55). (C) Cells were streaked onto YES plates and incubated for 4 days at 30°C before being photographed. Strains: wild type (JS78), <i>csk1Δ</i> (JS155), <i>rhp57Δ</i> (YP27), <i>csk1Δ rhp57Δ</i> (HG123). (D) Survival after UV irradiation of the strains: wild type (JS78), <i>csk1Δ</i> (JS155), <i>sfr1Δ</i> (HG24), <i>csk1Δ sfr1Δ</i> (HG31).</p

Csk1 is not required for activation of the DNA damage checkpoint or for NER.

<p>(A) WT (JS78), <i>csk1Δ</i> (JS155), <i>rad3Δ</i> (YP46) and <i>csk1Δ rad3Δ</i> (YP68) cells were synchronized in G2 by fractionation in lactose gradients and irradiated with 40 J/m² UV light. Samples were taken every 30 min and the percent of cells passing through mitosis was measured by counting binucleated cells, septated cells and doublets. (B) Survival after UV irradiation of the following strains: wild type (JS78), <i>csk1Δ</i> (JS155), <i>rad13Δ</i> (YP1), <i>csk1Δ rad13Δ</i> (YP85).</p

Analysis of Shared Heritability in Common Disorders of the Brain

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology