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1. 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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2. Evolution of a cis -Acting SNP That Controls Type VI Secretion in Vibrio cholerae

   https://doi.org/10.1128/mbio.00422-22  

   Ng, Siu Lung ; Kammann, Sophia ; Steinbach, Gabi ; Hoffmann, Tobias ; Yunker, Peter J. ; Hammer, Brian K. ( May 2022 , mBio)

   Storz, Gisela (Ed.)

   ABSTRACT Mutations in regulatory mechanisms that control gene expression contribute to phenotypic diversity and thus facilitate the adaptation of microbes and other organisms to new niches. Comparative genomics can be used to infer rewiring of regulatory architecture based on large effect mutations like loss or acquisition of transcription factors but may be insufficient to identify small changes in noncoding, intergenic DNA sequence of regulatory elements that drive phenotypic divergence. In human-derived Vibrio cholerae , the response to distinct chemical cues triggers production of multiple transcription factors that can regulate the type VI secretion system (T6), a broadly distributed weapon for interbacterial competition. However, to date, the signaling network remains poorly understood because no regulatory element has been identified for the major T6 locus. Here we identify a conserved cis -acting single nucleotide polymorphism (SNP) controlling T6 transcription and activity. Sequence alignment of the T6 regulatory region from diverse V. cholerae strains revealed conservation of the SNP that we rewired to interconvert V. cholerae T6 activity between chitin-inducible and constitutive states. This study supports a model of pathogen evolution through a noncoding cis -regulatory mutation and preexisting, active transcription factors that confers a different fitness advantage to tightly regulated strains inside a human host and unfettered strains adapted to environmental niches. IMPORTANCE Organisms sense external cues with regulatory circuits that trigger the production of transcription factors, which bind specific DNA sequences at promoters (“ cis ” regulatory elements) to activate target genes. Mutations of transcription factors or their regulatory elements create phenotypic diversity, allowing exploitation of new niches. Waterborne pathogen Vibrio cholerae encodes the type VI secretion system “nanoweapon” to kill competitor cells when activated. Despite identification of several transcription factors, no regulatory element has been identified in the promoter of the major type VI locus, to date. Combining phenotypic, genetic, and genomic analysis of diverse V. cholerae strains, we discovered a single nucleotide polymorphism in the type VI promoter that switches its killing activity between a constitutive state beneficial outside hosts and an inducible state for constraint in a host. Our results support a role for noncoding DNA in adaptation of this pathogen. 

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3. Snake venom gene expression is coordinated by novel regulatory architecture and the integration of multiple co-opted vertebrate pathways

   https://doi.org/10.1101/gr.276251.121  

   Perry, Blair W. ; Gopalan, Siddharth S. ; Pasquesi, Giulia I.M. ; Schield, Drew R. ; Westfall, Aundrea K. ; Smith, Cara F. ; Koludarov, Ivan ; Chippindale, Paul T. ; Pellegrino, Mark W. ; Chuong, Edward B. ; et al ( June 2022 , Genome Research)

   Understanding how regulatory mechanisms evolve is critical for understanding the processes that give rise to novel phenotypes. Snake venom systems represent a valuable and tractable model for testing hypotheses related to the evolution of novel regulatory networks, yet the regulatory mechanisms underlying venom production remain poorly understood. Here, we use functional genomics approaches to investigate venom regulatory architecture in the prairie rattlesnake and identify cis -regulatory sequences (enhancers and promoters), trans -regulatory transcription factors, and integrated signaling cascades involved in the regulation of snake venom genes. We find evidence that two conserved vertebrate pathways, the extracellular signal-regulated kinase and unfolded protein response pathways, were co-opted to regulate snake venom. In one large venom gene family (snake venom serine proteases), this co-option was likely facilitated by the activity of transposable elements. Patterns of snake venom gene enhancer conservation, in some cases spanning 50 million yr of lineage divergence, highlight early origins and subsequent lineage-specific adaptations that have accompanied the evolution of venom regulatory architecture. We also identify features of chromatin structure involved in venom regulation, including topologically associated domains and CTCF loops that underscore the potential importance of novel chromatin structure to coevolve when duplicated genes evolve new regulatory control. Our findings provide a model for understanding how novel regulatory systems may evolve through a combination of genomic processes, including tandem duplication of genes and regulatory sequences, cis -regulatory sequence seeding by transposable elements, and diverse transcriptional regulatory proteins controlled by a co-opted regulatory cascade. 

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4. Molecular Evolution across Mouse Spermatogenesis

   https://doi.org/10.1093/molbev/msac023  

   Kopania, Emily E ; Larson, Erica L ; Callahan, Colin ; Keeble, Sara ; Good, Jeffrey M ( February 2022 , Molecular Biology and Evolution)

   Wittkopp, Patricia (Ed.)

   Abstract Genes involved in spermatogenesis tend to evolve rapidly, but we lack a clear understanding of how protein sequences and patterns of gene expression evolve across this complex developmental process. We used fluorescence-activated cell sorting (FACS) to generate expression data for early (meiotic) and late (postmeiotic) cell types across 13 inbred strains of mice (Mus) spanning ∼7 My of evolution. We used these comparative developmental data to investigate the evolution of lineage-specific expression, protein-coding sequences, and expression levels. We found increased lineage specificity and more rapid protein-coding and expression divergence during late spermatogenesis, suggesting that signatures of rapid testis molecular evolution are punctuated across sperm development. Despite strong overall developmental parallels in these components of molecular evolution, protein and expression divergences were only weakly correlated across genes. We detected more rapid protein evolution on the X chromosome relative to the autosomes, whereas X-linked gene expression tended to be relatively more conserved likely reflecting chromosome-specific regulatory constraints. Using allele-specific FACS expression data from crosses between four strains, we found that the relative contributions of different regulatory mechanisms also differed between cell types. Genes showing cis-regulatory changes were more common late in spermatogenesis, and tended to be associated with larger differences in expression levels and greater expression divergence between species. In contrast, genes with trans-acting changes were more common early and tended to be more conserved across species. Our findings advance understanding of gene evolution across spermatogenesis and underscore the fundamental importance of developmental context in molecular evolutionary studies. 

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5. From telomere to telomere: The transcriptional and epigenetic state of human repeat elements

   https://doi.org/10.1126/science.abk3112  

   Hoyt, Savannah J. ; Storer, Jessica M. ; Hartley, Gabrielle A. ; Grady, Patrick G. ; Gershman, Ariel ; de Lima, Leonardo G. ; Limouse, Charles ; Halabian, Reza ; Wojenski, Luke ; Rodriguez, Matias ; et al ( April 2022 , Science)

   INTRODUCTION Transposable elements (TEs), repeat expansions, and repeat-mediated structural rearrangements play key roles in chromosome structure and species evolution, contribute to human genetic variation, and substantially influence human health through copy number variants, structural variants, insertions, deletions, and alterations to gene transcription and splicing. Despite their formative role in genome stability, repetitive regions have been relegated to gaps and collapsed regions in human genome reference GRCh38 owing to the technological limitations during its development. The lack of linear sequence in these regions, particularly in centromeres, resulted in the inability to fully explore the repeat content of the human genome in the context of both local and regional chromosomal environments. RATIONALE Long-read sequencing supported the complete, telomere-to-telomere (T2T) assembly of the pseudo-haploid human cell line CHM13. This resource affords a genome-scale assessment of all human repetitive sequences, including TEs and previously unknown repeats and satellites, both within and outside of gaps and collapsed regions. Additionally, a complete genome enables the opportunity to explore the epigenetic and transcriptional profiles of these elements that are fundamental to our understanding of chromosome structure, function, and evolution. Comparative analyses reveal modes of repeat divergence, evolution, and expansion or contraction with locus-level resolution. RESULTS We implemented a comprehensive repeat annotation workflow using previously known human repeats and de novo repeat modeling followed by manual curation, including assessing overlaps with gene annotations, segmental duplications, tandem repeats, and annotated repeats. Using this method, we developed an updated catalog of human repetitive sequences and refined previous repeat annotations. We discovered 43 previously unknown repeats and repeat variants and characterized 19 complex, composite repetitive structures, which often carry genes, across T2T-CHM13. Using precision nuclear run-on sequencing (PRO-seq) and CpG methylated sites generated from Oxford Nanopore Technologies long-read sequencing data, we assessed RNA polymerase engagement across retroelements genome-wide, revealing correlations between nascent transcription, sequence divergence, CpG density, and methylation. These analyses were extended to evaluate RNA polymerase occupancy for all repeats, including high-density satellite repeats that reside in previously inaccessible centromeric regions of all human chromosomes. Moreover, using both mapping-dependent and mapping-independent approaches across early developmental stages and a complete cell cycle time series, we found that engaged RNA polymerase across satellites is low; in contrast, TE transcription is abundant and serves as a boundary for changes in CpG methylation and centromere substructure. Together, these data reveal the dynamic relationship between transcriptionally active retroelement subclasses and DNA methylation, as well as potential mechanisms for the derivation and evolution of new repeat families and composite elements. Focusing on the emerging T2T-level assembly of the HG002 X chromosome, we reveal that a high level of repeat variation likely exists across the human population, including composite element copy numbers that affect gene copy number. Additionally, we highlight the impact of repeats on the structural diversity of the genome, revealing repeat expansions with extreme copy number differences between humans and primates while also providing high-confidence annotations of retroelement transduction events. CONCLUSION The comprehensive repeat annotations and updated repeat models described herein serve as a resource for expanding the compendium of human genome sequences and reveal the impact of specific repeats on the human genome. In developing this resource, we provide a methodological framework for assessing repeat variation within and between human genomes. The exhaustive assessment of the transcriptional landscape of repeats, at both the genome scale and locally, such as within centromeres, sets the stage for functional studies to disentangle the role transcription plays in the mechanisms essential for genome stability and chromosome segregation. Finally, our work demonstrates the need to increase efforts toward achieving T2T-level assemblies for nonhuman primates and other species to fully understand the complexity and impact of repeat-derived genomic innovations that define primate lineages, including humans. Telomere-to-telomere assembly of CHM13 supports repeat annotations and discoveries. The human reference T2T-CHM13 filled gaps and corrected collapsed regions (triangles) in GRCh38. Combining long read–based methylation calls, PRO-seq, and multilevel computational methods, we provide a compendium of human repeats, define retroelement expression and methylation profiles, and delineate locus-specific sites of nascent transcription genome-wide, including previously inaccessible centromeres. SINE, short interspersed element; SVA, SINE–variable number tandem repeat– Alu ; LINE, long interspersed element; LTR, long terminal repeat; TSS, transcription start site; pA, xxxxxxxxxxxxxxxx. 

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