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1. Analysis of Fungal Genomes Reveals Commonalities of Intron Gain or Loss and Functions in Intron-Poor Species

   https://doi.org/10.1093/molbev/msab094  

   Lim, Chun Shen ; Weinstein, Brooke N ; Roy, Scott W ; Brown, Chris M ( March 2021 , Molecular Biology and Evolution)

   Ouangraoua, Aida (Ed.)

   Abstract Previous evolutionary reconstructions have concluded that early eukaryotic ancestors including both the last common ancestor of eukaryotes and of all fungi had intron-rich genomes. By contrast, some extant eukaryotes have few introns, underscoring the complex histories of intron–exon structures, and raising the question as to why these few introns are retained. Here, we have used recently available fungal genomes to address a variety of questions related to intron evolution. Evolutionary reconstruction of intron presence and absence using 263 diverse fungal species supports the idea that massive intron reduction through intron loss has occurred in multiple clades. The intron densities estimated in various fungal ancestors differ from zero to 7.6 introns per 1 kb of protein-coding sequence. Massive intron loss has occurred not only in microsporidian parasites and saccharomycetous yeasts, but also in diverse smuts and allies. To investigate the roles of the remaining introns in highly-reduced species, we have searched for their special characteristics in eight intron-poor fungi. Notably, the introns of ribosome-associated genes RPL7 and NOG2 have conserved positions; both intron-containing genes encoding snoRNAs. Furthermore, both the proteins and snoRNAs are involved in ribosome biogenesis, suggesting that the expression of the protein-coding genes and noncoding snoRNAs may be functionally coordinated. Indeed, these introns are also conserved in three-quarters of fungi species. Our study shows that fungal introns have a complex evolutionary history and underappreciated roles in gene expression. 

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2. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning

   https://doi.org/10.1126/science.abm7993  

   Kaplow, Irene M. ; Lawler, Alyssa J. ; Schäffer, Daniel E. ; Srinivasan, Chaitanya ; Sestili, Heather H. ; Wirthlin, Morgan E. ; Phan, BaDoi N. ; Prasad, Kavya ; Brown, Ashley R. ; Zhang, Xiaomeng ; et al ( April 2023 , Science)

   INTRODUCTION Diverse phenotypes, including large brains relative to body size, group living, and vocal learning ability, have evolved multiple times throughout mammalian history. These shared phenotypes may have arisen repeatedly by means of common mechanisms discernible through genome comparisons. RATIONALE Protein-coding sequence differences have failed to fully explain the evolution of multiple mammalian phenotypes. This suggests that these phenotypes have evolved at least in part through changes in gene expression, meaning that their differences across species may be caused by differences in genome sequence at enhancer regions that control gene expression in specific tissues and cell types. Yet the enhancers involved in phenotype evolution are largely unknown. Sequence conservation–based approaches for identifying such enhancers are limited because enhancer activity can be conserved even when the individual nucleotides within the sequence are poorly conserved. This is due to an overwhelming number of cases where nucleotides turn over at a high rate, but a similar combination of transcription factor binding sites and other sequence features can be maintained across millions of years of evolution, allowing the function of the enhancer to be conserved in a particular cell type or tissue. Experimentally measuring the function of orthologous enhancers across dozens of species is currently infeasible, but new machine learning methods make it possible to make reliable sequence-based predictions of enhancer function across species in specific tissues and cell types. RESULTS To overcome the limits of studying individual nucleotides, we developed the Tissue-Aware Conservation Inference Toolkit (TACIT). Rather than measuring the extent to which individual nucleotides are conserved across a region, TACIT uses machine learning to test whether the function of a given part of the genome is likely to be conserved. More specifically, convolutional neural networks learn the tissue- or cell type–specific regulatory code connecting genome sequence to enhancer activity using candidate enhancers identified from only a few species. This approach allows us to accurately associate differences between species in tissue or cell type–specific enhancer activity with genome sequence differences at enhancer orthologs. We then connect these predictions of enhancer function to phenotypes across hundreds of mammals in a way that accounts for species’ phylogenetic relatedness. We applied TACIT to identify candidate enhancers from motor cortex and parvalbumin neuron open chromatin data that are associated with brain size relative to body size, solitary living, and vocal learning across 222 mammals. Our results include the identification of multiple candidate enhancers associated with brain size relative to body size, several of which are located in linear or three-dimensional proximity to genes whose protein-coding mutations have been implicated in microcephaly or macrocephaly in humans. We also identified candidate enhancers associated with the evolution of solitary living near a gene implicated in separation anxiety and other enhancers associated with the evolution of vocal learning ability. We obtained distinct results for bulk motor cortex and parvalbumin neurons, demonstrating the value in applying TACIT to both bulk tissue and specific minority cell type populations. To facilitate future analyses of our results and applications of TACIT, we released predicted enhancer activity of >400,000 candidate enhancers in each of 222 mammals and their associations with the phenotypes we investigated. CONCLUSION TACIT leverages predicted enhancer activity conservation rather than nucleotide-level conservation to connect genetic sequence differences between species to phenotypes across large numbers of mammals. TACIT can be applied to any phenotype with enhancer activity data available from at least a few species in a relevant tissue or cell type and a whole-genome alignment available across dozens of species with substantial phenotypic variation. Although we developed TACIT for transcriptional enhancers, it could also be applied to genomic regions involved in other components of gene regulation, such as promoters and splicing enhancers and silencers. As the number of sequenced genomes grows, machine learning approaches such as TACIT have the potential to help make sense of how conservation of, or changes in, subtle genome patterns can help explain phenotype evolution. Tissue-Aware Conservation Inference Toolkit (TACIT) associates genetic differences between species with phenotypes. TACIT works by generating open chromatin data from a few species in a tissue related to a phenotype, using the sequences underlying open and closed chromatin regions to train a machine learning model for predicting tissue-specific open chromatin and associating open chromatin predictions across dozens of mammals with the phenotype. [Species silhouettes are from PhyloPic] 

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3. CHD chromatin remodeling protein diversification yields novel clades and domains absent in classic model organisms

   https://doi.org/10.1093/gbe/evac066  

   Trujillo, Joshua T. ; Long, Jiaxin ; Aboelnour, Erin ; Ogas, Joseph ; Wisecaver, Jennifer H. ( May 2022 , Genome Biology and Evolution)

   Hoffmann, Federico (Ed.)

   Chromatin remodelers play a fundamental role in the assembly of chromatin, regulation of transcription, and DNA repair. Biochemical and functional characterization of the CHD family of chromatin remodelers from a variety of model organisms have shown that these remodelers participate in a wide range of activities. However, because the evolutionary history of CHD homologs is unclear, it is difficult to predict which of these activities are broadly conserved and which have evolved more recently in individual eukaryotic lineages. Here, we performed a comprehensive phylogenetic analysis of 8,042 CHD homologs from 1,894 species to create a model for the evolution of this family across eukaryotes with a particular focus on the timing of duplications that gave rise to the diverse copies observed in plants, animals, and fungi. Our analysis confirms that the three major subfamilies of CHD remodelers originated in the eukaryotic last common ancestor, and subsequent losses occurred independently in different lineages. Improved taxon sampling identified several subfamilies of CHD remodelers in plants that were absent or highly divergent in the model plant Arabidopsis thaliana. Whereas the timing of CHD subfamily expansions in vertebrates correspond to whole genome duplication events, the mechanisms underlying CHD diversification in land plants appears more complicated. Analysis of protein domains reveals that CHD remodeler diversification has been accompanied by distinct transitions in domain architecture, contributing to the functional differences observed between these remodelers. This study demonstrates the importance of proper taxon sampling when studying ancient evolutionary events to prevent misinterpretation of subsequent lineage-specific changes and provides an evolutionary framework for functional and comparative analysis of this critical chromatin remodeler family across eukaryotes. 

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4. Opinion: Genetic Conflict With Mobile Elements Drives Eukaryotic Genome Evolution, and Perhaps Also Eukaryogenesis

   https://doi.org/10.1093/jhered/esaa060  

   Collens, Adena B ; Katz, Laura A ( January 2021 , Journal of Heredity)

   Orive, Maria (Ed.)

   Abstract Through analyses of diverse microeukaryotes, we have previously argued that eukaryotic genomes are dynamic systems that rely on epigenetic mechanisms to distinguish germline (i.e., DNA to be inherited) from soma (i.e., DNA that undergoes polyploidization, genome rearrangement, etc.), even in the context of a single nucleus. Here, we extend these arguments by including two well-documented observations: (1) eukaryotic genomes interact frequently with mobile genetic elements (MGEs) like viruses and transposable elements (TEs), creating genetic conflict, and (2) epigenetic mechanisms regulate MGEs. Synthesis of these ideas leads to the hypothesis that genetic conflict with MGEs contributed to the evolution of a dynamic eukaryotic genome in the last eukaryotic common ancestor (LECA), and may have contributed to eukaryogenesis (i.e., may have been a driver in the evolution of FECA, the first eukaryotic common ancestor). Sex (i.e., meiosis) may have evolved within the context of the development of germline–soma distinctions in LECA, as this process resets the germline genome by regulating/eliminating somatic (i.e., polyploid, rearranged) genetic material. Our synthesis of these ideas expands on hypotheses of the origin of eukaryotes by integrating the roles of MGEs and epigenetics. 

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5. Globins in the marine annelid Platynereis dumerilii shed new light on hemoglobin evolution in bilaterians

   https://doi.org/10.1186/s12862-020-01714-4  

   Song, Solène ; Starunov, Viktor ; Bailly, Xavier ; Ruta, Christine ; Kerner, Pierre ; Cornelissen, Annemiek J. M. ; Balavoine, Guillaume ( December 2020 , BMC Evolutionary Biology)

   How vascular systems and their respiratory pigments evolved is still debated. While many animals present a vascular system, hemoglobin exists as a blood pigment only in a few groups (vertebrates, annelids, a few arthropod and mollusk species). Hemoglobins are formed of globin sub-units, belonging to multigene families, in various multimeric assemblages. It was so far unclear whether hemoglobin families from different bilaterian groups had a common origin.

   To unravel globin evolution in bilaterians, we studied the marine annelidPlatynereis dumerilii,a species with a slow evolving genome.Platynereisexhibits a closed vascular system filled with extracellular hemoglobin.Platynereisgenome and transcriptomes reveal a family of 19 globins, nine of which are predicted to be extracellular. Extracellular globins are produced by specialized cells lining the vessels of the segmental appendages of the worm, serving as gills, and thus likely participate in the assembly of a previously characterized annelid-specific giant hemoglobin. Extracellular globin mRNAs are absent in smaller juveniles, accumulate considerably in growing and more active worms and peak in swarming adults, as the need for O₂culminates. Next, we conducted a metazoan-wide phylogenetic analysis of globins using data from complete genomes. We establish that five globin genes (stem globins) were present in the last common ancestor of bilaterians. Based on these results, we propose a new nomenclature of globins, with five clades. All five ancestral stem-globin clades are retained in some spiralians, while some clades disappeared early in deuterostome and ecdysozoan evolution.All known bilaterian blood globin families are grouped in a single clade (clade I) together with intracellular globins of bilaterians devoid of red blood.

   We uncover a complex “pre-blood” evolution of globins, with an early gene radiation in ancestral bilaterians. Circulating hemoglobins in various bilaterian groups evolved convergently, presumably in correlation with animal size and activity. However, all hemoglobins derive from a clade I globin, or cytoglobin, probably involved in intracellular O₂transit and regulation. The annelidPlatynereisis remarkable in having a large family of extracellular blood globins, while retaining all clades of ancestral bilaterian globins.

    

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