Kismeth: Analyzer of plant methylation states through bisulfite sequencing

<p>Abstract</p> <p>Background</p> <p>There is great interest in probing the temporal and spatial patterns of cytosine methylation states in genomes of a variety of organisms. It is hoped that this will shed light on the biological roles of DNA methylation in the epigenetic control of gene expression. Bisulfite sequencing refers to the treatment of isolated DNA with sodium bisulfite to convert unmethylated cytosine to uracil, with PCR converting the uracil to thymidine followed by sequencing of the resultant DNA to detect DNA methylation. For the study of DNA methylation, plants provide an excellent model system, since they can tolerate major changes in their DNA methylation patterns and have long been studied for the effects of DNA methylation on transposons and epimutations. However, in contrast to the situation in animals, there aren't many tools that analyze bisulfite data in plants, which can exhibit methylation of cytosines in a variety of sequence contexts (CG, CHG, and CHH).</p> <p>Results</p> <p>Kismeth <url>http://katahdin.mssm.edu/kismeth</url> is a web-based tool for bisulfite sequencing analysis. Kismeth was designed to be used with plants, since it considers potential cytosine methylation in any sequence context (CG, CHG, and CHH). It provides a tool for the design of bisulfite primers as well as several tools for the analysis of the bisulfite sequencing results. Kismeth is not limited to data from plants, as it can be used with data from any species.</p> <p>Conclusion</p> <p>Kismeth simplifies bisulfite sequencing analysis. It is the only publicly available tool for the design of bisulfite primers for plants, and one of the few tools for the analysis of methylation patterns in plants. It facilitates analysis at both global and local scales, demonstrated in the examples cited in the text, allowing dissection of the genetic pathways involved in DNA methylation. Kismeth can also be used to study methylation states in different tissues and disease cells compared to a reference sequence.</p

The Lantern Vol. 42, No. 1, Fall 1975

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SDM:A New Data Set on Self-determination Movements with an Application to the Reputational Theory of Conflict

This dataset, of self-determination movements (SDMs) with universal coverage for the period from 1945 to 2012, corrects the selection bias that characterizes previous efforts to code SDMs and significantly expands coverage relative to the extant literature. For a random sample of cases, we add information on state–movement interactions and several attributes of SDM groups. The data can be used to study the causes of SDMs, the escalation of self-determination (SD) conflicts over time, and several other theoretical arguments concerning separatist conflict that have previously been tested with incomplete or inferior data.The creators request that the associated paper is cited in place of this dataset

Power-sharing: Institutions, Behavior, and Peace

This is the author accepted manuscript. The final version is available from Wiley via the DOI in this record.Replication Materials: The data, code, and any additional materials required to replicate all analyses in this article are available on the American Journal of Political Science Dataverse within the Harvard Dataverse Network, at: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/3DK6JAGrievances that derive from the unequal treatment of ethnic groups are a key motivation for civil war. Ethnic power-sharing should therefore reduce the risk of internal conflict. Yet conflict researchers disagree on whether formal power-sharing institutions effectively prevent large-scale violence.We can improve our understanding of the effect of power-sharing institutions by analyzing the mechanisms under which they operate. To this effect, we compare the direct effect of formal power-sharing institutions on peace with their indirect effect through power-sharing behavior. Combining data on inclusive and territorially dispersive institutions with information on power-sharing behavior, we empirically assess this relationship on a global scale. Our causal mediation analysis reveals that formal power-sharing institutions affect the probability of ethnic conflict onset mostly through power-sharing behavior that these institutions induce.Funding: Swiss National Science Foundation (Grant No. 105511- 143213; PI: Cederman, Hug, and Wucherpfennig), the National Science Foundation (Grant No. Q2 SES-081950766b; PI: Strøom), and the Norwegian Research Council (196850/F10; PI: Gates)

Comprehensive splice-site analysis using comparative genomics

We have collected over half a million splice sites from five species—Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana—and classified them into four subtypes: U2-type GT–AG and GC–AG and U12-type GT–AG and AT–AC. We have also found new examples of rare splice-site categories, such as U12-type introns without canonical borders, and U2-dependent AT–AC introns. The splice-site sequences and several tools to explore them are available on a public website (SpliceRack). For the U12-type introns, we find several features conserved across species, as well as a clustering of these introns on genes. Using the information content of the splice-site motifs, and the phylogenetic distance between them, we identify: (i) a higher degree of conservation in the exonic portion of the U2-type splice sites in more complex organisms; (ii) conservation of exonic nucleotides for U12-type splice sites; (iii) divergent evolution of C.elegans 3′ splice sites (3′ss) and (iv) distinct evolutionary histories of 5′ and 3′ss. Our study proves that the identification of broad patterns in naturally-occurring splice sites, through the analysis of genomic datasets, provides mechanistic and evolutionary insights into pre-mRNA splicing

Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe