Elucidating the genetic changes underlying the evolution of human traits remains an unfinished puzzle. Structural variants (SVs) account for more genetic differences than single-nucleotide polymorphisms between humans and our closest living relatives, chimpanzees, and are a hallmark of great ape evolution. The genomes of great apes are enriched in large interspersed segmental duplications (SDs), defined as duplications larger than 1 kbp with over 90% sequence identity, that sensitize the genome to further genomic rearrangements, including copy-number variation, via non- allelic homologous recombination. Despite their relevance, the identification and characterization of these SVs has been hindered by short reads lengths as they lack enough sequence context to discover breakpoints and cannot unequivocally be mapped to highly identical duplicates. Long-read sequencing technologies overcome these limitations by providing reads thousands of bases long, but the availability of population cohorts remains limited.This thesis studies primate SVs and SDs characterized using diverse sequencing technologies and assesses their representation in reference genomes, variation across modern populations, their putative molecular impacts, and their roles in evolution and adaptation. We found novel SVs, including 88 deletions and 36 inversions, in two chimpanzee individuals sequenced with nanopore and optical mapping. Deletions and inversion breakpoints were depleted within topologically associated domains but enriched in differentially expressed genes between the two species. Focusing on human SDs, we identified eight Mbp of erroneously collapsed duplications in the human reference genome, impacting 48 protein coding and ten medically relevant genes, that are corrected in the first complete sequence of a human genome, T2T-CHM13. Leveraging this new reference, we identified 417 genes embedded in SDs with over 98% sequence identity (SD-98) that are near copy-number (CN) fixed in modern humans (1000 Genomes Project; 1KGP), 205 genes showing stratification between diverse modern populations (VST>95th percentile), and 22 protein-encoding genes showing consistent Tajima’s D outlier values across all humans examined. Our approach highlighted potential relevant human gene duplications, which are priority candidates for functional studies. Finally, we provide a compendium of tools and practices that we recommend be adopted by computational biologists to increase reproducibility in the field.

Elucidating the genetic modifications that contributed to the evolution of neurodevelopmental features unique to the human lineage has proved challenging. The rise in the availability of higher-quality primate genomes has allowed researchers to perform comparisons to identify genetic variation exclusively found in humans. Such analyses have highlighted different types of genetic variants as potential drivers in species differentiation within primates, where segmental duplications have gained particular attention given the overall increase in duplicated bases observed in primate genomes and the known potential of duplicated genes to gain novel functions. Therefore, recent surveys of human and non-human primate genomes have identified segmental duplications exclusively found in humans that contain genes with protein-coding gene paralogs that are clustered in genomic regions associated with human neurological conditions, making them top candidates for further functional studies. Since there are 30 gene families included in these human-specific segmental duplications, there is a need for higher-throughput and robust methods to functionally screen these genes to highlight candidates for more detailed molecular investigations. To address this need, we propose zebrafish as a model organism with ideal characteristics to screen candidate human-specific duplicated genes potentially impacting neurodevelopment. We first performed a thorough evaluation of current tools for gene editing in zebrafish and define a set of recommendations for general genetic screenings using zebrafish as a model, with a particular focus on the description of cost-efficient methods that provide consistent results across experiments. Then, we optimized a high-throughput phenotyping pipeline that includes rapid morphological and behavioral assessments, which we validated using generated mutants of known genes associated with several neurological conditions. Applying this information, we used zebrafish to functionally test a human-specific duplicated gene with comprehensive studies in mouse (SRGAP2) as a proof-of-concept. Our zebrafish srgap2 knockouts and SRGAP2C-humanized exhibited alterations in the expression of axogenesis-related genes and an imbalance in neuronal populations likely increasing their susceptibility to seizures, all results that are consistent with the findings in mice models. In addition, our data points to a potential novel function never-before-reported for this gene in visual system development. Building off the success of SRGAP2, we expanded our functional screen to an additional nine human-specific duplicated genes using a pipeline that combines CRISPR-based gene editing, temporal expression of human genes, phenotyping platforms, and cellular evaluations at single-cell resolution. This allowed us to highlight candidate genes consistently exhibiting alterations in zebrafish neurodevelopment, warranting follow-up with more detailed molecular functional studies to link these genes to the evolution of human-unique neurological features. Broadly speaking, this dissertation includes a framework to establish zebrafish as an effective model for functional evaluations of genes important in human neurodevelopment using optimized methods.

Genetic structural variation has strong potential to contribute to human evolution and disease, as large deletions, duplications, and inversions alter more base pairs of the human genome than single-nucleotide variants. However, structural variants (SVs) have remained systematically understudied because they are challenging to identify and resolve with short-read sequencing data, upon which modern genomics depends heavily. Nevertheless, targeted efforts and recent technological advances have unveiled a dynamic landscape of structural variation within the human population and between primate species, with examples tied to both genomic disease and adaptive human traits. Of particular interest is a class of SVs called segmental duplications, large blocks of sequence duplicated at low copy number that are enriched on the great ape lineage. Human-specific segmental duplications (HSDs) comprise millions of base pairs of DNA unique to our species and, intriguingly, contain genes that shape cortical development. Beyond the genes themselves, SVs can impact gene regulation by reorganizing genes and regulatory elements throughout the genome, rewiring their interactions or altering their copy number altogether. Gene regulation is itself considered a major driver of evolutionary change, and this work explores the interplay of structural variation and gene regulation to assess how SVs contribute to species-specific features in humans and other primates. We used long read sequencing, optical mapping, and single-cell template strand sequencing to discover novel SVs in chimpanzees and rhesus macaques, demonstrating that deletions and inversions in these species preserve chromatin architecture but also are associated with divergent gene regulation. In addition, we compared mRNA levels of HSD genes and their single chimpanzee orthologs and found that derived, human-specific genes are more likely to exhibit novel expression patterns compared to ancestral paralogs. To understand the molecular mechanisms underlying this divergence, we identified novel candidate cis-regulatory elements in HSDs and demonstrate that promoters and enhancers in these regions have functionally diverged in recent evolutionary time. Finally, we performed a massively parallel reporter assay to quantify the regulatory activity of thousands paralogous HSD variants, finding mostly differences of small effect, but also uncovering variants that may generate human-specific expression patterns. Taken together, these studies highlight the regulatory consequences of SVs; duplicated and rearranged regulatory elements give rise to novel expression patterns that have the potential to underlie the emergence of new traits.

A large proportion of genetic variation underlying differences in behavioral traits and neurodevelopmental disorders remains unknown despite considerable effort. Much work has focused on protein-coding regions, which comprise ~1.5% of primate genomes, compared to functional noncoding elements comprising ~40%. Transcriptional analyses of the developing brain in distantly related primates, such as humans and rhesus macaques, show that spatiotemporal expression patterns are largely conserved across lineages, with minor differences likely contributing to species’ divergence. To delve into genomic mechanisms underlying gene regulation in the developing primate brain, we have generated transcriptional genomic datasets (3’ Tag-Seq (n=3) and single-cell RNA-seq (n=1)) from diverse regions of fetal macaque brains (60 days gestation, late first/early second trimester) representing a time of early neurogenesis. The 3’ Tag-Seq expression levels show correlation with previously published data of the same time point and comparable brain regions and highlights genes important in region-specific development. The single-cell RNA-seq data has revealed a number of different cell types, the majority of which are neuronal in all brain regions with the exception of the cerebellum.We then queried the 3D genome organization of two different brain regions using a targeted protein mediated approach called Proximity Ligation-Assisted ChIP-Seq (PLAC-Seq) to identify DNA interactions within chromatin enriched at active promoters in macaque neural tissue. Our data generated from samples from the prefrontal cortex and cerebellum (n=3, 60 days gestation) shows low enrichment for the H3K4me3 antibody. Despite this low enrichment, we were able to identify 32,959 and 13,814 significant chromatin interactions for prefrontal cortex and cerebellum, respectively. The identified significant interactions in the prefrontal cortex were connected to over half of the genes implicated in ASD from two separate datasets, while significant interactions in the cerebellum connected to about a third of those genes, providing putative cis regulatory elements driving regulation of these disease-associated genes in diverse brain regions.

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