Coffea arabica, an allotetraploid hybrid of Coffea eugenioides and Coffea canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000–610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred ~30.5 thousand years ago, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

Recently, the Single-Cut-or-Join (SCJ) operation was proposed as a basis for a new rearrangement distance between multichromosomal genomes, leading to very fast algorithms, both in theory and in practice. However, it was not clear how well this new distance fares when it comes to using it to solve relevant problems, such as the reconstruction of evolutionary history. In this paper, we advance current knowledge, by testing SCJ's ability regarding evolutionary reconstruction in two aspects: 1) How well does SCJ reconstruct evolutionary topologies? and 2) How well does SCJ reconstruct ancestral genomes? In the process of answering these questions, we implemented SCJ-based methods, and made them available to the community. We ran experiments using as many as 200 genomes, with as many as 3,000 genes. For the first question, we found out that SCJ can recover typically between 60 percent and more than 95 percent of the topology, as measured through the Robinson-Foulds distance (a.k.a. split distance) between trees. In other words, 60 percent to more than 95 percent of the original splits are also present in the reconstructed tree. For the second question, given a topology, SCJ's ability to reconstruct ancestral genomes depends on how far from the leaves the ancestral is. For nodes close to the leaves, about 85 percent of the gene adjacencies can be recovered. This percentage decreases as we move up the tree, but, even at the root, about 50 percent of the adjacencies are recovered, for as many as 64 leaves. Our findings corroborate the fact that SCJ leads to very conservative genome reconstructions, yielding very few false-positive gene adjacencies in the ancestrals, at the expense of a relatively larger amount of false negatives. In addition, experiments with real data from the Campanulaceae and Protostomes groups show that SCJ reconstructs topologies of quality comparable to the accepted trees of the species involved. As far as time is concerned, the methods we implemented can find a topology for 64 genomes with 2,000 genes each in about 10.7 minutes, and reconstruct the ancestral genomes in a 64-leaf tree in about 3 seconds, both on a typical desktop computer. It should be noted that our code is written in Java and we made no significant effort to optimize it.

We outline an integrated approach to speciation and whole genome doubling (WGD) to resolve the occurrence of these events in phylogenetic analysis. We propose a more principled way of estimating the parameters of gene divergence and fractionation than the standard mixture of normals analysis. We formulate an algorithm for resolving data on local peaks in the distributions of duplicate gene similarities for a number of related genomes. We illustrate with a comprehensive analysis of WGD-origin duplicate gene data from the family Brassicaceae.

In this text we attempt to unify many results about the K operator based on a new theory involving graphs, families and operators. We are able to build an ''operator algebra'' that helps to unify and automate arguments. In addition, we relate well-known properties, such as the Helly property, to the families and the operators. As a result, we deduce many classic results in clique graph theory from the basic fact that CS = I for conformal, reduced families. This includes Hamelink's construction, Roberts and Spencer theorem, and Ban-delt and Prisner's partial characterization of clique-fixed classes [2]. Furthermore, we show the power of our approach proving general results that lead to polynomial recognition of certain graph classes

One possible model to study genome evolution is to represent genomes as permutations of genes and compute distances based on the minimum number of certain operations (rearrangements) needed to transform one permutation into another. Under this model, the shorter the distance, the closer the genomes are. Two operations that have been extensively studied are the reversal and the transposition. A reversal is an operation that reverses the order of the genes on a certain portion of the permutation. A transposition is an operation that "cuts" a certain portion of the permutation and "pastes" it elsewhere in the same permutation. In this note, we show that the reversal and transposition distance of the signed permutation π_n = (-1 -2...-(n - 1)-n) with respect to the identity is ⌊n/2⌋ + 2 for all n≥3. We conjecture that this value is the diameter of the permutation group under these operations.

Background: Central nervous system (CNS) tumors are the second most frequent type of neoplasm in childhood and adolescence, after leukemia. Despite the incorporation of molecular classification and improvement of protocols combining chemotherapy, surgery, and radiotherapy, CNS tumors are still the most lethal neoplasm in this age group. Mass spectrometry imaging (MSI) is a powerful tool to map the distribution of molecular species in tissue sections. Among MSI techniques, desorption electrospray ionization (DESI-MSI) has been demonstrated to enable reliable agreement with the pathological evaluation of different adult cancer types, along with an acceptable time scale for intraoperative use. Methods: In the present work, we aimed to investigate the chemical profile obtained by DESI-MSI as an intraoperative surgical management tool by profiling 162 pediatric brain biopsies and reporting the results according to the histopathology and molecular profile of the tumors. Results: The 2D chemical images obtained by DESI-MSI allowed us to distinguish tumor-transformed tissue from non-tumor tissue with an accuracy of 96.8% in the training set and 94.3% in the validation set after statistical modeling of our data using Lasso. In addition, high-grade and low-grade tumors also displayed a distinct chemical profile when analyzed by DESI-MSI. We also provided evidence that the chemical profile of brain tumors obtained by DESI-MSI correlates with methylation-based molecular classes and specific immunophenotypes found in brain biopsies. Conclusions: The results presented herein support the incorporation of DESI-MSI analysis as an intraoperative assistive tool in prospective clinical trials for pediatric brain tumors management in the near future.