An evolutionary genomics view on neuropeptide genes in Hydrozoa and Endocnidozoa (Myxozoa)

Background The animal phylum Cnidaria consists of six classes or subphyla: Hydrozoa, Scyphozoa, Cubozoa, Staurozoa, Anthozoa, and Endocnidozoa. Cnidarians have an early evolutionary origin, diverging before the emergence of the Bilateria. Extant members from this phylum, therefore, are important resources for understanding the evolution of the nervous system. Cnidarian nervous systems are strongly peptidergic. Using genomics, we have recently shown that three neuropeptide families (the X1PRX2amides, GRFamides, and GLWamides) are wide-spread in four (Scyphozoa, Cubozoa, Staurozoa, Anthozoa) out of six cnidarian classes or subphyla, suggesting that these three neuropeptide families emerged in the common cnidarian ancestor. In the current paper, we analyze the remaining cnidarian class, Hydrozoa, and the subphylum Endocnidozoa, to make firm conclusions about the evolution of neuropeptide genes in Cnidaria. Results We analyzed sixteen hydrozoan species with a sequenced genome or transcriptome, using a recently developed software program for discovering neuropeptide genes. These species belonged to various hydrozoan subclasses and orders, among them the laboratory models Hydra, Hydractinia, and Clytia. We found that each species contained three to five neuropeptide families. A common feature for all hydrozoans was that they contained genes coding for (i) X1PRX2amide peptides, (ii) GRFamide peptides, and (iii) GLWamide peptides. These results support our previous conclusions that these three neuropeptide families evolved early in evolution. In addition to these three neuropeptide families, hydrozoans expressed up to two other neuropeptide gene families, which, however, were only occurring in certain animal groups. Endocnidozoa (Myxozoa) are microscopically small endoparasites, which are strongly reduced. For long, it was unknown to which phylum these parasites belonged, but recently they have been associated with cnidarians. We analyzed nine endocnidozoan species and found that two of them (Polypodium hydriforme and Buddenbrockia plumatellae) expressed neuropeptide genes. These genes coded for neuropeptides belonging to the GRFamide and GLWamide families with structures closely resembling them from hydrozoans. Conclusions We found X1PRX2amide, GRFamide, and GLWamide peptides in all species belonging to the Hydrozoa, confirming that these peptides originated in the common cnidarian ancestor. In addition, we discovered GRFamide and GLWamide peptide genes in some members of the Endocnidozoa, thereby linking these parasites to Hydrozoa.

The Physalis floridana genome provides insights into the biochemical and morphological evolution of Physalis fruits

The fruits of Physalis (Solanaceae) have a unique structure, a lantern-like fruiting calyx known as inflated calyx syndrome (ICS) or the Chinese lantern, and are rich in steroid-related compounds. However, the genetic variations underlying the origin of these characteristic traits and diversity in Physalis remain largely unknown. Here, we present a high-quality chromosome-level reference genome assembly of Physalis floridana (~1.40 Gb in size) with a contig N50 of ~4.87 Mb. Through evolutionary genomics and experimental approaches, we found that the loss of the SEP-like MADS-box gene MBP21 subclade is likely a key mutation that, together with the previously revealed mutation affecting floral MPF2 expression, might have contributed to the origination of ICS in Physaleae, suggesting that the origination of a morphological novelty may have resulted from an evolutionary scenario in which one mutation compensated for another deleterious mutation. Moreover, the significant expansion of squalene epoxidase genes is potentially associated with the natural variation of steroid-related compounds in Physalis fruits. The results reveal the importance of gene gains (duplication) and/or subsequent losses as genetic bases of the evolution of distinct fruit traits, and the data serve as a valuable resource for the evolutionary genetics and breeding of solanaceous crops.

selscan 2.0: scanning for sweeps in unphased data

Haplotype-based scans to identify recent and ongoing positive selection have become commonplace in evolutionary genomics studies of numerous species across the tree of life. However, the most widely adopted approaches require phased haplotypes to compute the key statistics. Here we release a major update to the selscan software that re-defines popular haplotype-based statistics for use with unphased "multi-locus genotype" data. We provide unphased implementations of iHS, nSL, XP-EHH, and XP-nSL and evaluate their performance across a range of important parameters in a generic demographic history. Source code and executables are available at https://www.github.com/szpiech/selscan.

Integrative Pre-Breeding for Biotic Resistance in Forest Trees

Climate change is unleashing novel biotic antagonistic interactions for forest trees that may jeopardize populations’ persistence. Therefore, this review article envisions highlighting major opportunities from ecological evolutionary genomics to assist the identification, conservation, and breeding of biotic resistance in forest tree species. Specifically, we first discuss how assessing the genomic architecture of biotic stress resistance enables us to recognize a more polygenic nature for a trait typically regarded Mendelian, an expectation from the Fisherian runaway pathogen–host concerted arms-race evolutionary model. Secondly, we outline innovative pipelines to capture and harness natural tree pre-adaptations to biotic stresses by merging tools from the ecology, phylo-geography, and omnigenetics fields within a predictive breeding platform. Promoting integrative ecological genomic studies promises a better understanding of antagonistic co-evolutionary interactions, as well as more efficient breeding utilization of resistant phenotypes.

Inter-chromosomal k-mer distances

Background Inversion Symmetry is a generalization of the second Chargaff rule, stating that the count of a string of k nucleotides on a single chromosomal strand equals the count of its inverse (reverse-complement) k-mer. It holds for many species, both eukaryotes and prokaryotes, for ranges of k which may vary from 7 to 10 as chromosomal lengths vary from 2Mbp to 200 Mbp. Building on this formalism we introduce the concept of k-mer distances between chromosomes. We formulate two k-mer distance measures, D1 and D2, which depend on k. D1 takes into account all k-mers (for a single k) appearing on single strands of the two compared chromosomes, whereas D2 takes into account both strands of each chromosome. Both measures reflect dissimilarities in global chromosomal structures. Results After defining the various distance measures and summarizing their properties, we also define proximities that rely on the existence of synteny blocks between chromosomes of different bacterial strains. Comparing pairs of strains of bacteria, we find negative correlations between synteny proximities and k-mer distances, thus establishing the meaning of the latter as measures of evolutionary distances among bacterial strains. The synteny measures we use are appropriate for closely related bacterial strains, where considerable sections of chromosomes demonstrate high direct or reversed equality. These measures are not appropriate for comparing different bacteria or eukaryotes. K-mer structural distances can be defined for all species. Because of the arbitrariness of strand choices, we employ only the D2 measure when comparing chromosomes of different species. The results for comparisons of various eukaryotes display interesting behavior which is partially consistent with conventional understanding of evolutionary genomics. In particular, we define ratios of minimal k-mer distances (KDR) between unmasked and masked chromosomes of two species, which correlate with both short and long evolutionary scales. Conclusions k-mer distances reflect dissimilarities among global chromosomal structures. They carry information which aggregates all mutations. As such they can complement traditional evolution studies , which mainly concentrate on coding regions.

Expanding the MECP2 network using comparative genomics reveals potential therapeutic targets for Rett syndrome

Inactivating mutations in the Methyl-CpG Binding Protein 2 (MECP2) gene are the main cause of Rett syndrome (RTT). Despite extensive research into MECP2 function, no treatments for RTT are currently available. Here, we used an evolutionary genomics approach to construct an unbiased MECP2 gene network, using 1028 eukaryotic genomes to prioritize proteins with strong co-evolutionary signatures with MECP2. Focusing on proteins targeted by FDA-approved drugs led to three promising targets, two of which were previously linked to MECP2 function (IRAK, KEAP1) and one that was not (EPOR). The drugs targeting these three proteins (Pacritinib, DMF, and EPO) were able to rescue different phenotypes of MECP2 inactivation in cultured human neural cell types, and appeared to converge on Nuclear Factor Kappa B (NF-κB) signaling in inflammation. This study highlights the potential of comparative genomics to accelerate drug discovery, and yields potential new avenues for the treatment of RTT.

The utility of genomic prediction models in evolutionary genetics

Variation in complex traits is the result of contributions from many loci of small effect. Based on this principle, genomic prediction methods are used to make predictions of breeding value for an individual using genome-wide molecular markers. In breeding, genomic prediction models have been used in plant and animal breeding for almost two decades to increase rates of genetic improvement and reduce the length of artificial selection experiments. However, evolutionary genomics studies have been slow to incorporate this technique to select individuals for breeding in a conservation context or to learn more about the genetic architecture of traits, the genetic value of missing individuals or microevolution of breeding values. Here, we outline the utility of genomic prediction and provide an overview of the methodology. We highlight opportunities to apply genomic prediction in evolutionary genetics of wild populations and the best practices when using these methods on field-collected phenotypes.