Chloroplasts were once free-living cyanobacteria that became endosymbionts, but the genomes of contemporary plastids encode only Ϸ5-10% as many genes as those of their free-living cousins, indicating that many genes were either lost from plastids or transferred to the nucleus during the course of plant evolution. Previous estimates have suggested that between 800 and perhaps as many as 2,000 genes in the Arabidopsis genome might come from cyanobacteria, but genome-wide phylogenetic surveys that could provide direct estimates of this number are lacking. We compared 24,990 proteins encoded in the Arabidopsis genome to the proteins from three cyanobacterial genomes, 16 other prokaryotic reference genomes, and yeast. Of 9,368 Arabidopsis proteins sufficiently conserved for primary sequence comparison, 866 detected homologues only among cyanobacteria and 834 other branched with cyanobacterial homologues in phylogenetic trees. Extrapolating from these conserved proteins to the whole genome, the data suggest that Ϸ4,500 of Arabidopsis protein-coding genes (Ϸ18% of the total) were acquired from the cyanobacterial ancestor of plastids. These proteins encompass all functional classes, and the majority of them are targeted to cell compartments other than the chloroplast. Analysis of 15 sequenced chloroplast genomes revealed 117 nuclear-encoded proteins that are also still present in at least one chloroplast genome. A phylogeny of chloroplast genomes inferred from 41 proteins and 8,303 amino acids sites indicates that at least two independent secondary endosymbiotic events have occurred involving red algae and that amino acid composition bias in chloroplast proteins strongly affects plastid genome phylogeny.

Isopentenyl diphosphate (IPP) is the central intermediate in the biosynthesis of isoprenoids, the most ancient and diverse class of natural products. Two distinct routes of IPP biosynthesis occur in nature: the mevalonate pathway and the recently discovered deoxyxylulose 5-phosphate (DXP) pathway. The evolutionary history of the enzymes involved in both routes and the phylogenetic distribution of their genes across genomes suggest that the mevalonate pathway is germane to archaebacteria, that the DXP pathway is germane to eubacteria, and that eukaryotes have inherited their genes for IPP biosynthesis from prokaryotes. The occurrence of genes specific to the DXP pathway is restricted to plastid-bearing eukaryotes, indicating that these genes were acquired from the cyanobacterial ancestor of plastids. However, the individual phylogenies of these genes, with only one exception, do not provide evidence for a specific affinity between the plant genes and their cyanobacterial homologues. The results suggest that lateral gene transfer between eubacteria subsequent to the origin of plastids has played a major role in the evolution of this pathway.chloroplast ͉ deoxyxylulose 5-phosphate ͉ endosymbiosis ͉ mevalonate ͉ phylogeny

BackgroundDespite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.MethodsWe analyzed 699 cancerous and non-cancerous tissues using a methylation array or reduced representation bisulfite sequencing to discover the most specific OC methylation patterns. A three-DNA-methylation-serum-marker panel was developed using targeted ultra-high coverage bisulfite sequencing in 151 women and validated in 250 women with various conditions, particularly in those associated with high CA125 levels (endometriosis and other benign pelvic masses), serial samples from 25 patients undergoing neoadjuvant chemotherapy, and a nested case control study of 172 UKCTOCS control arm participants which included serum samples up to two years before OC diagnosis.ResultsThe cell-free DNA amount and average fragment size in the serum samples was up to ten times higher than average published values (based on samples that were immediately processed) due to leakage of DNA from white blood cells owing to delayed time to serum separation. Despite this, the marker panel discriminated high grade serous OC patients from healthy women or patients with a benign pelvic mass with specificity/sensitivity of 90.7% (95% confidence interval [CI] = 84.3–94.8%) and 41.4% (95% CI = 24.1–60.9%), respectively. Levels of all three markers plummeted after exposure to chemotherapy and correctly identified 78% and 86% responders and non-responders (Fisher’s exact test, p = 0.04), respectively, which was superior to a CA125 cut-off of 35 IU/mL (20% and 75%). 57.9% (95% CI 34.0–78.9%) of women who developed OC within two years of sample collection were identified with a specificity of 88.1% (95% CI = 77.3–94.3%). Sensitivity and specificity improved further when specifically analyzing CA125 negative samples only (63.6% and 87.5%, respectively).ConclusionsOur data suggest that DNA methylation patterns in cell-free DNA have the potential to detect a proportion of OCs up to two years in advance of diagnosis and may potentially guide personalized treatment. The prospective use of novel collection vials, which stabilize blood cells and reduce background DNA contamination in serum/plasma samples, will facilitate clinical implementation of liquid biopsy analyses.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0500-7) contains supplementary material, which is available to authorized users.

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Breast, ovarian and endometrial cancers cause significant morbidity and mortality. Despite the presence of existing screening, diagnostic and treatment modalities, they continue to pose considerable unsolved challenges. Overdiagnosis is a growing problem in breast cancer screening and neither screening nor early diagnosis of ovarian or endometrial cancer is currently possible. Moreover, treatment of the diversity of these cancers presenting in the clinic is not sufficiently personalized at present. Recent technological advances, including reduced representation bisulfite sequencing, methylation arrays, digital PCR, next-generation sequencing and advanced statistical data analysis, enable the analysis of methylation patterns in cell-free tumor DNA in serum/plasma. Ongoing work is bringing these methods together for the analysis of samples from large clinical trials, which have been collected well in advance of cancer diagnosis. These efforts pave the way for the development of a noninvasive method that would enable us to overcome existing challenges to personalized medicine.