Meiosis in the human pathogen Aspergillus fumigatus has the highest known number of crossovers

Evidence from both population genetics and a laboratory sexual cycle indicate that sex is common in the fungus Aspergillus fumigatus. However, the impact of sexual reproduction has remained unclear. Here, we show that meiosis in A. fumigatus involves the highest known recombination rate, producing ~29 crossovers per chromosome. This represents the highest known crossover rate for any Eukaryotic species. We validate this recombination rate by mapping resistance to acriflavine, a common genetic marker. We further show that this recombination rate can produce the commonly encountered TR34/L98H azole-resistant cyp51A haplotype in each sexual event, facilitating its rapid and global spread. Understanding the consequences of this unparalleled crossover rate will not only enrich our genetic understanding of this emergent human pathogen, but of meiosis in general.

Sequence Divergence and Functional Specializations of the Ancient Spliceosomal SF3b: Implications in Flexibility and Adaptations of the Multi-Protein Complex

Multi-protein assemblies are complex molecular systems that perform highly sophisticated biochemical functions in an orchestrated manner. They are subject to changes that are governed by the evolution of individual components. We performed a comparative analysis of the ancient and functionally conserved spliceosomal SF3b complex, to recognize molecular signatures that contribute to sequence divergence and functional specializations. For this, we recognized homologous sequences of individual SF3b proteins distributed across 10 supergroups of eukaryotes and identified all seven protein components of the complex in 578 eukaryotic species. Using sequence and structural analysis, we establish that proteins occurring on the surface of the SF3b complex harbor more sequence variation than the proteins that lie in the core. Further, we show through protein interface conservation patterns that the extent of conservation varies considerably between interacting partners. When we analyze phylogenetic distributions of individual components of the complex, we find that protein partners that are known to form independent subcomplexes are observed to share similar profiles, reaffirming the link between differential conservation of interface regions and their inter-dependence. When we extend our analysis to individual protein components of the complex, we find taxa-specific variability in molecular signatures of the proteins. These trends are discussed in the context of proline-rich motifs of SF3b4, functional and drug binding sites of SF3b1. Further, we report key protein-protein interactions between SF3b1 and SF3b6 whose presence is observed to be lineage-specific across eukaryotes. Together, our studies show the association of protein location within the complex and subcomplex formation patterns with the sequence conservation of SF3b proteins. In addition, our study underscores evolutionarily flexible elements that appear to confer adaptive features in individual components of the multi-protein SF3b complexes and may contribute to its functional adaptability.

ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

Motivation: Transcriptome assembly from RNA sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate reconstruction ability of transcript isoforms. This impedes the study of alternative splicing, in particular for lowly expressed isoforms. Result: We present the de novo transcript isoform assembler ClusTrast, which clusters a set of guiding contigs by similarity, aligns short reads to the guiding contigs, and assembles each clustered set of short reads individually. We tested ClusTrast on datasets from six eukaryotic species, and showed that ClusTrast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. An appreciable fraction were reconstructed to at least 95% of their length. We suggest that ClusTrast will be useful for studying alternative splicing in the absence of a reference genome. Availability and implementation: The code and usage instructions are available at https://github.com/karljohanw/clustrast.

HSDFinder: A BLAST-Based Strategy for Identifying Highly Similar Duplicated Genes in Eukaryotic Genomes

Gene duplication is an important evolutionary mechanism capable of providing new genetic material for adaptive and nonadaptive evolution. However, bioinformatics tools for identifying duplicate genes are often limited to the detection of paralogs in multiple species or to specific types of gene duplicates, such as retrocopies. Here, we present a user-friendly, BLAST-based web tool, called HSDFinder, which can identify, annotate, categorize, and visualize highly similar duplicate genes (HSDs) in eukaryotic nuclear genomes. HSDFinder includes an online heatmap plotting option, allowing users to compare HSDs among different species and visualize the results in different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional categories. The external software requirements are BLAST, InterProScan, and KEGG. The utility of HSDFinder was tested on various model eukaryotic species, including Chlamydomonas reinhardtii, Arabidopsis thaliana, Oryza sativa, and Zea mays as well as the psychrophilic green alga Chlamydomonas sp. UWO241, and was proven to be a practical and accurate tool for gene duplication analyses. The web tool is free to use at http://hsdfinder.com. Documentation and tutorials can be found via the GitHub: https://github.com/zx0223winner/HSDFinder.

Efficient iterative Hi-C scaffolder based on N-best neighbors

Background Efficient and effective genome scaffolding tools are still in high demand for generating reference-quality assemblies. While long read data itself is unlikely to create a chromosome-scale assembly for most eukaryotic species, the inexpensive Hi-C sequencing technology, capable of capturing the chromosomal profile of a genome, is now widely used to complete the task. However, the existing Hi-C based scaffolding tools either require a priori chromosome number as input, or lack the ability to build highly continuous scaffolds. Results We design and develop a novel Hi-C based scaffolding tool, pin_hic, which takes advantage of contact information from Hi-C reads to construct a scaffolding graph iteratively based on N-best neighbors of contigs. Subsequent to scaffolding, it identifies potential misjoins and breaks them to keep the scaffolding accuracy. Through our tests on three long read based de novo assemblies from three different species, we demonstrate that pin_hic is more efficient than current standard state-of-art tools, and it can generate much more continuous scaffolds, while achieving a higher or comparable accuracy. Conclusions Pin_hic is an efficient Hi-C based scaffolding tool, which can be useful for building chromosome-scale assemblies. As many sequencing projects have been launched in the recent years, we believe pin_hic has potential to be applied in these projects and makes a meaningful contribution.

One Hundred Years of Gene Balance: How Stoichiometric Issues Affect Gene Expression, Genome Evolution, and Quantitative Traits

A century ago experiments with the flowering plant <i>Datura stramonium</i> and the fruit fly <i>Drosophila melanogaster</i> revealed that adding an extra chromosome to a karyotype was much more detrimental than adding a whole set of chromosomes. This phenomenon was referred to as gene balance and has been recapitulated across eukaryotic species. Here, we retrace some developments in this field. Molecular studies suggest that the basis of balance involves stoichiometric relationships of multi-component interactions. This concept has implication for the mechanisms controlling gene expression, genome evolution, sex chromosome evolution/dosage compensation, speciation mechanisms, and the underlying genetics of quantitative traits.

Co-evolution based machine-learning for predicting functional interactions between human genes

Over the next decade, more than a million eukaryotic species are expected to be fully sequenced. This has the potential to improve our understanding of genotype and phenotype crosstalk, gene function and interactions, and answer evolutionary questions. Here, we develop a machine-learning approach for utilizing phylogenetic profiles across 1154 eukaryotic species. This method integrates co-evolution across eukaryotic clades to predict functional interactions between human genes and the context for these interactions. We benchmark our approach showing a 14% performance increase (auROC) compared to previous methods. Using this approach, we predict functional annotations for less studied genes. We focus on DNA repair and verify that 9 of the top 50 predicted genes have been identified elsewhere, with others previously prioritized by high-throughput screens. Overall, our approach enables better annotation of function and functional interactions and facilitates the understanding of evolutionary processes underlying co-evolution. The manuscript is accompanied by a webserver available at: https://mlpp.cs.huji.ac.il.

Expanding Interactome Analyses beyond Model Eukaryotes

Interactome analyses have traditionally been applied to yeast, human and other model organisms due to the availability of protein-protein interactions data for these species. Recently these techniques have been applied to more diverse species using computational interaction prediction from genome sequence and other data types. This review describes the various types of computational interactome networks that can be created and how they have been used in diverse eukaryotic species, highlighting some of the key interactome studies in non-model organisms.

Comparison of transcriptional initiation by RNA polymerase II across eukaryotic species

The preinitiation complex (PIC) for transcriptional initiation by RNA polymerase (Pol) II is composed of general transcription factors that are highly conserved. However, analysis of ChIP-seq datasets reveals kinetic and compositional differences in the transcriptional initiation process among eukaryotic species. In yeast, Mediator associates strongly with activator proteins bound to enhancers, but it transiently associates with promoters in a form that lacks the kinase module. In contrast, in human, mouse, and fly cells, Mediator with its kinase module stably associates with promoters, but not with activator-binding sites. This suggests that yeast and metazoans differ in the nature of the dynamic bridge of Mediator between activators and Pol II and the composition of a stable inactive PIC-like entity. As in yeast, occupancies of TATA-binding protein (TBP) and TBP-associated factors (Tafs) at mammalian promoters are not strictly correlated. This suggests that within PICs, TFIID is not a monolithic entity, and multiple forms of TBP affect initiation at different classes of genes. TFIID in flies, but not yeast and mammals, interacts strongly at regions downstream of the initiation site, consistent with the importance of downstream promoter elements in that species. Lastly, Taf7 and the mammalian-specific Med26 subunit of Mediator also interact near the Pol II pause region downstream of the PIC, but only in subsets of genes and often not together. Species-specific differences in PIC structure and function are likely to affect how activators and repressors affect transcriptional activity.