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Hecker, N.

Publications and source records attributed to Hecker, N..

10 recordsLinked to original sources

The evolution of gene regulation in mammalian cerebellum development

Gene regulatory changes are considered major drivers of evolutionary innovations, including the cerebellums expansion during human evolution, yet they remain largely unexplored. In this study, we combined single-nucleus measurements of gene expression and chromatin accessibility from six mammals (human, bonobo, macaque, marmoset, mouse, and opossum) to uncover conserved and diverged regulatory networks in cerebellum development. We identified core regulators of cell identity and developed sequence-based models that revealed conserved regulatory codes. By predicting chromatin accessibility across 240 mammalian species, we reconstructed the evolutionary histories of human cis-regulatory elements, identifying sets associated with positive selection and gene expression changes, including the recent gain of THRB expression in cerebellar progenitor cells. Collectively, our work reveals the shared and mammalian lineage-specific regulatory programs governing cerebellum development.

evolutionary biology↗

Evaluating Methods for the Prediction of Cell Type-Specific Enhancers in the Mammalian Cortex

Identifying cell type-specific enhancers in the brain is critical to building genetic tools for investigating the mammalian brain. Computational methods for functional enhancer prediction have been proposed and validated in the fruit fly and not yet the mammalian brain. We organized the Brain Initiative Cell Census Network (BICCN) Challenge: Predicting Functional Cell Type-Specific Enhancers from Cross-Species Multi-Omics to assess machine learning and feature-based methods designed to nominate enhancer DNA sequences to target cell types in the mouse cortex. Methods were evaluated based on in vivo validation data from hundreds of cortical cell type-specific enhancers that were previously packaged into individual AAV vectors and retro-orbitally injected into mice. We find that open chromatin was a key predictor of functional enhancers, and sequence models improved prediction of non-functional enhancers that can be deprioritized as opposed to pursued for in vivo testing. Sequence models also identified cell type-specific transcription factor codes that can guide designs of in silico enhancers. This community challenge establishes a benchmark for enhancer prioritization algorithms and reveals computational approaches and molecular information that are crucial for identifying functional enhancers in mammalian cortical cell types. The results of this challenge bring us closer to understanding the complex gene regulatory landscape of the mammalian cortex and to designing more efficient genetic tools to target cortical cell types.

genomics↗

Enhancer-driven cell type comparison reveals similarities between the mammalian and bird pallium

Combinations of transcription factors govern the identity of cell types, which is reflected by enhancer codes in cis-regulatory genomic regions. Cell type-specific enhancer codes at nucleotide-level resolution have not yet been characterized for the mammalian neocortex. It is currently unknown whether these codes are conserved in other vertebrate brains, and whether they are informative to resolve homology relationships for species that lack a neocortex such as birds. To compare enhancer codes of cell types from the mammalian neocortex with those from the bird pallium, we generated single-cell multiome and spatially-resolved transcriptomics data of the chicken telencephalon. We then trained deep learning models to characterize cell type-specific enhancer codes for the human, mouse, and chicken telencephalon. We devised three metrics that exploit enhancer codes to compare cell types between species. Based on these metrics, non-neuronal and GABAergic cell types show a high degree of regulatory similarity across vertebrates. Proposed homologies between mammalian neocortical and avian pallial excitatory neurons are still debated. Our enhancer code based comparison shows that excitatory neurons of the mammalian neocortex and the avian pallium exhibit a higher degree of divergence than other cell types. In contrast to existing evolutionary models, the mammalian deep layer excitatory neurons are most similar to mesopallial neurons; and mammalian upper layer neurons to hyper- and nidopallial neurons based on their enhancer codes. In addition to characterizing the enhancer codes in the mammalian and avian telencephalon, and revealing unexpected correspondences between cell types of the mammalian neocortex and the chicken pallium, we present generally applicable deep learning approaches to characterize and compare cell types across species via the genomic regulatory code.

genomics↗

Spatial transcriptomics in adult Drosophila reveals new cell types in the brain and identifies subcellular mRNA patterns in muscles

Recently, we have achieved a significant milestone with the creation of the Fly Cell Atlas. This single-nuclei atlas encompasses the entire fly, covering the entire head and body, in addition to all major organs. This atlas catalogs many hundreds of cell types, of which we annotated 250. Thus, a large number of clusters remain to be fully characterized, in particular in the brain. Furthermore, by applying single-nuclei sequencing, all information about the spatial location of the cells in the body and of about possible subcellular localization of the mRNAs within these cells is lost. Spatial transcriptomics promises to tackle these issues. In a proof-of-concept study, we have here applied spatial transcriptomics using a selected gene panel to pinpoint the locations of 150 mRNA species in the adult fly. This enabled us to map unknown clusters identified in the Fly Cell Atlas to their spatial locations in the fly brain. Additionally, spatial transcriptomics discovered interesting principles of mRNA localization and transcriptional diversity within the large and crowded muscle cells that may spark future mechanistic investigations. Furthermore, we present a set of computational tools that will allow for easier integration of spatial transcriptomics and single-cell datasets.

developmental biology↗

SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks

Joint profiling of chromatin accessibility and gene expression of individual cells provides an opportunity to decipher enhancer-driven gene regulatory networks (eGRN). Here we present a new method for the inference of eGRNs, called SCENIC+. SCENIC+ predicts genomic enhancers along with candidate upstream transcription factors (TF) and links these enhancers to candidate target genes. Specific TFs for each cell type or cell state are predicted based on the concordance of TF binding site accessibility, TF expression, and target gene expression. To improve both recall and precision of TF identification, we curated and clustered more than 40,000 position weight matrices that we could associate with 1,553 human TFs. We validated and benchmarked each of the SCENIC+ components on diverse data sets from different species, including human peripheral blood mononuclear cell types, ENCODE cell lines, human melanoma cell states, and Drosophila retinal development. Next, we exploit SCENIC+ predictions to study conserved TFs, enhancers, and GRNs between human and mouse cell types in the cerebral cortex. Finally, we provide new capabilities that exploit the inferred eGRNs to study the dynamics of gene regulation along differentiation trajectories; to map regulatory activities onto tissues using spatial omics data; and to predict the effect of TF perturbations on cell state. SCENIC+ provides critical insight into gene regulation, starting from multiome atlases of scATAC-seq and scRNA-seq. The SCENIC+ suite is available as a set of Python modules at https://scenicplus.readthedocs.io.

bioinformatics↗

Vision-related convergent gene losses reveal SERPINE3's unknown role in the eye

Despite decades of research, knowledge about the genes that are important for development and function of the mammalian eye and are involved in human eye disorders remains incomplete. During mammalian evolution, mammals that naturally exhibit poor vision or regressive eye phenotypes have independently lost many eye-related genes. This provides an opportunity to predict novel eye-related genes based on specific evolutionary gene loss signatures. Building on these observations, we performed a genome-wide screen across 49 mammals for functionally uncharacterized genes that are preferentially lost in species exhibiting lower visual acuity values. The screen uncovered several genes, including SERPINE3, a putative serine proteinase inhibitor. A detailed investigation of 381 additional mammals revealed that SERPINE3 is independently lost in 18 lineages that typically do not primarily rely on vision, predicting a vision-related function for this gene. To test this, we show that SERPINE3 has the highest expression in eyes of zebrafish and mouse. In the zebrafish retina, serpine3 is expressed in Mueller glia cells, a cell type essential for survival and maintenance of the retina. A CRISPR-mediated knockout of serpine3 in zebrafish resulted in alterations in eye shape and defects in retinal layering. Furthermore, two human polymorphisms that are in linkage with SERPINE3 are associated with eye-related traits. Together, these results suggest that SERPINE3 has a role in vertebrate eyes. More generally, by integrating comparative genomics with experiments in model organisms, we show that screens for specific phenotype-associated gene signatures can predict functions of uncharacterized genes.

evolutionary biology↗

Gene losses in the common vampire bat illuminate molecular adaptations to blood feeding

Feeding exclusively on blood, vampire bats represent the only obligate sanguivorous lineage among mammals. To uncover genomic changes associated with adaptations to this unique dietary specialization, we generated a new haplotype-resolved reference-quality genome of the common vampire bat (Desmodus rotundus) and screened 26 bat species for genes that were specifically lost in the vampire bat lineage. We discovered previously-unknown gene losses that relate to metabolic and physiological changes, such as reduced insulin secretion (FFAR1, SLC30A8), limited glycogen stores (PPP1R3E), and a distinct gastric physiology (CTSE). Other gene losses likely reflect the biased nutrient composition (ERN2, CTRL) and distinct pathogen diversity of blood (RNASE7). Interestingly, the loss of REP15 likely helped vampire bats to adapt to high dietary iron levels by enhancing iron excretion and the loss of the 24S-hydroxycholesterol metabolizing enzyme CYP39A1 could contribute to their exceptional cognitive abilities. Finally, losses of key cone phototransduction genes (PDE6H, PDE6C) suggest that these strictly-nocturnal bats completely lack cone-based vision. These findings enhance our understanding of vampire bat biology and the genomic underpinnings of adaptations to sanguivory.

evolutionary biology↗

Convergent losses of TLR5 suggest altered extracellular flagellin detection in four mammalian lineages

Toll-like receptors (TLRs) play an important role for the innate immune system by detecting pathogen-associated molecular patterns. TLR5 encodes the major extracellular receptor for bacterial flagellin and frequently evolves under positive selection, consistent with coevolutionary arms races between the host and pathogens. Furthermore, TLR5 is inactivated in several vertebrates and a TLR5 stop codon polymorphism is widespread in human populations. Here, we analyzed the genomes of 120 mammals and discovered that TLR5 is convergently lost in four independent lineages, comprising guinea pigs, Yangtze river dolphin, pinnipeds, and pangolins. Validated inactivating mutations, absence of protein-coding transcript expression, and relaxed selection on the TLR5 remnants confirm these losses. PCR analysis further confirmed the loss of TLR5 in the pinniped stem lineage. Finally, we show that TLR11, encoding a second extracellular flagellin receptor, is also absent in these four lineages. Independent losses of TLR5 and TLR11 suggests that a major pathway for detecting flagellated bacteria is not essential for different mammals and predicts an impaired capacity to sense extracellular flagellin

genomics↗

RepeatFiller newly identifies megabases of aligning repetitive sequences and improves annotations of conserved non-exonic elements

Transposons and other repetitive sequences make up a large part of complex genomes. Repetitive sequences can be co-opted into a variety of functions and thus provide a source for evolutionary novelty. However, comprehensively detecting ancestral repeats that align between species is difficult since considering all repeat-overlapping seeds in alignment methods that rely on the seed-and-extend heuristic results in prohibitively high runtimes. Here, we show that ignoring repeat-overlapping alignment seeds when aligning entire genomes misses numerous alignments between repetitive elements. We present a tool - RepeatFiller - that improves genome alignments by incorporating previously-undetected local alignments between repetitive sequences. By applying RepeatFiller to genome alignments between human and 20 other representative mammals, we uncover between 22 and 84 megabases of previously-undetected alignments that mostly overlap transposable elements. We further show that the increased alignment coverage improves the annotation of conserved non-exonic elements, both by discovering numerous novel transposon-derived elements that evolve under constraint and by removing thousands of elements that are not under constraint in placental mammals. In conclusion, RepeatFiller contributes to comprehensively aligning repetitive genomic regions, which facilitates studying transposon co-option and genome evolution.\n\nSource codehttps://github.com/hillerlab/GenomeAlignmentTools

evolutionary biology↗

Genes lost during the transition from land to water in cetaceans highlight genomic changes involved in aquatic adaptations

The transition from land to water in whales and dolphins (cetaceans) was accompanied by remarkable anatomical, physiological and behavioral adaptations. To better understand the genomic changes that occurred during this transition, we systematically screened for protein-coding genes that were inactivated in the ancestral cetacean lineage. We discovered genes whose loss is likely beneficial for cetaceans by reducing the risk of thrombus formation during diving (F12, KLKB1), improving the fidelity of oxidative DNA damage repair (POLM), and protecting from oxidative stress-induced lung inflammation (MAP3K19). Additional gene losses may reflect other diving-related adaptations, such as enhanced vasoconstriction during the diving response (mediated by SLC6A18) and altered pulmonary surfactant composition (SEC14L3), while loss of SLC4A9 relates to a reduced need for saliva in aquatic environments. Finally, the complete loss of melatonin synthesis and receptor genes (AANAT, ASMT, MTNR1A/B) may have been a precondition for the evolution of unihemispheric sleep. Our findings suggest that some genes lost in the ancestral cetacean lineage may have been involved in adapting to a fully-aquatic lifestyle.

evolutionary biology↗