Biology subjects

Starr, A. L.

Publications and source records attributed to Starr, A. L..

9 recordsLinked to original sources

bioRxiv2026

A human transcriptomic deletion links cortical expansion and cancer

Alternative splicing represents a major source of potential evolutionary novelty in protein sequence. Despite this, relatively few studies have investigated the functional impacts of human-specific alternative splicing. Here, we analyze RNA-sequencing data from nine iPSC-derived cell types and identify dozens of human transcriptomic conserved deletions (htCONDELs): evolutionary divergence in splicing that leads to the partial or full removal of conserved protein-coding sequence from the human transcriptome. We investigated one example in detail: an htCONDEL in the gene HMMR, which encodes a centrosomal protein that binds microtubules and regulates mitosis. We found that this htCONDEL, which produces a human-specific isoform lacking a conserved microtubule-binding domain, enables cells to flexibly divide with a broader range of mitotic spindle orientations in vitro. Introducing the human HMMR isoform into mice similarly alters the orientation of cell division in the developing neocortex and increases the production of outer radial glia-like cells, the expansion of which played an essential role in increasing human brain size. Combined with previous work implicating the same HMMR isoform in carcinoma progression, our results suggest that evolution of HMMR splicing in humans increased plasticity in cell division, potentially leading to tradeoffs between advantageous effects on brain development and deleterious effects on cancer risk later in life.

evolutionary biology↗

bioRxiv2026

Adaptive loss of function accelerated the evolution of ancient and modern human cognition

Methods to detect accelerated evolution have identified many genomic regions with unexpectedly rapid evolution in the human lineage-significantly more than in chimpanzees, our closest living relatives. However, these methods focus on accelerated sequence evolution of short non-coding regions, leaving open the questions of how to identify accelerated evolution of molecular function, as opposed to sequence, and whether accelerated evolution has shaped the human genome more broadly. Here, we introduce a new approach to detect accelerated evolution: Function Aware Statistical Test for Evolutionary Rates (FASTER). In contrast to previous methods, FASTER can detect not only accelerated evolution of sequence, but also of predicted function, and can be applied to any set of genomic regions. Applying this method to humans and chimpanzees, we identified protein-coding, untranslated (UTR), and non-coding regions with accelerated evolution of function. Across all these genomic levels, we consistently found more rapid evolution in conserved sites in the human lineage compared to chimpanzee, many of which are predicted to reduce protein stability or chromatin accessibility. Multiple lines of evidence suggest this human-acceleration was driven in part by positive selection on brain development and cognition which has continued to shape human evolution even in the past several thousand years. Collectively, these results demonstrate the power of genome-wide scans for the evolution of predicted function and specifically suggest that a higher rate of reduction in function-including widespread decreases in cis-regulatory activity-may have been an important driver of both ancient and recent human evolution.

genomics↗

bioRxiv2026

The causes and consequences of human-specific DNA methylation

The vast collection of human-specific traits- such as our unique morphology, cognition, behavior, and diseases- has long been attributed to gene expression divergence between us and our closest living relatives, chimpanzees. Theory suggests that changes to cis-regulatory elements such as promoters and enhancers may drive evolutionary adaptation, and DNA methylation is a key factor in transcriptional cis-regulation. However, we still lack an understanding of 1) how species-specific methylation patterns arise; 2) their downstream effects; and 3) whether they are a common target of natural selection. In this study, we investigated these three questions. By combining a novel hypothesis testing framework with DNA methylation data from six human and chimpanzee cell types, as well as fused interspecies hybrid cells, we disentangled cis- vs. trans-acting methylation divergence across the genome. Across cell types, we found that methylation divergence is primarily driven in cis, which can be linked in some cases to nearby sequence variants such as CpG gains and losses. Although less common, regions with trans-acting methylation divergence were enriched for specific transcription factor (TF) binding motifs, suggesting a role of TFs such as FOXM1 in these differences. Having established these causes of methylation divergence, we then examined the functional consequences of differential methylation. Although methylation lacks a consistent relationship with transcription, we observed that associations between methylation and gene expression are stronger for genes with cis-regulatory divergence. Moreover, we identified lineage-specific selection shaping promoter methylation at the level of entire pathways including those associated with human-specific traits such as speech, cognition, and susceptibility to infection with hepatitis C. Collectively, our findings provide a mechanistic framework suggesting that DNA methylation may occupy a key position, mediating the effects of both cis- and trans-acting factors on transcriptional networks, including those contributing to human-specific traits.

evolutionary biology↗

bioRxiv2025

A framework to detect positive selection using variant effect predictions reveals widespread adaptive evolution of human neurons

Detecting positive selection is essential to understanding evolution. Many methods to detect positive selection use simple classifications of genetic variants (e.g. synonymous/nonsynonymous). Here, we propose that these methods can be considered special cases of a more general framework to detect positive selection with any variant effect prediction method. Using evolutionary conservation and deep learning-based variant effect predictions, we apply this framework genome-wide in the human lineage and identify positive selection on protein sequences of genes involved in brain and heart development, chromatin accessibility in binding sites of dozens of transcription factors, and non-coding substitutions in compact genomic regions with reinforcing cell type-specific effects on cis-regulatory activity. Consistently, the dominant theme was positive selection on genes regulating neuronal connectivity, suggesting that fine-scale changes in brain wiring were essential to the evolution of human cognition. Overall, this framework represents a powerful, versatile tool to investigate adaptive evolution across the tree of life.

genomics↗

bioRxiv2024

sc-SPLASH provides ultra-efficient reference-free discovery in barcoded single-cell sequencing

Typical high-throughput single-cell RNA-sequencing (scRNA-seq) analyses are primarily conducted by (pseudo)alignment, through the lens of annotated gene models, and aimed at detecting differential gene expression. This misses diversity generated by other mechanisms that diversify the transcriptome such as splicing and V(D)J recombination, and is blind to sequences missing from imperfect reference genomes. Here, we present sc-SPLASH, a highly efficient pipeline that extends our SPLASH framework for statistics-first, reference-free discovery to barcoded scRNA-seq (10x Chromium) and spatial transcriptomics (10x Visium); we also provide its optimized module for preprocessing and k-mer counting in barcoded data, BKC, as a standalone tool. sc-SPLASH rediscovers known biology including V(D)J recombination and cell-type-specific alternative splicing in human and trans-splicing in tunicate (Ciona) and when applied to spatial datasets, detects sequence variation including tumor-specific somatic mutation. In sponge (Spongilla) and tunicate (Ciona), we uncover secreted repeat proteins expressed in immune-type cells and regulated during development; the sponge genes were absent from the reference assembly. sc-SPLASH provides a powerful alternative tool for exploring transcriptomes that is applicable to the breadth of lifes diversity.

bioinformatics↗

bioRxiv2024

A general principle governing neuronal evolution reveals a human-accelerated neuron type potentially underlying the high prevalence of autism in humans

The remarkable ability of a single genome sequence to encode a diverse collection of distinct cell types, including the thousands of cell types found in the mammalian brain, is a key characteristic of multicellular life. While it has been observed that some cell types are far more evolutionarily conserved than others, the factors driving these differences in evolutionary rate remain unknown. Here, we hypothesized that highly abundant neuronal cell types may be under greater selective constraint than rarer neuronal types, leading to variation in their rates of evolution. To test this, we leveraged recently published cross-species single-nucleus RNA-sequencing datasets from three distinct regions of the mammalian neocortex. We found a strikingly consistent relationship where more abundant neuronal subtypes show greater gene expression conservation between species, which replicated across three independent datasets covering >106 neurons from six species. Based on this principle, we discovered that the most abundant type of neocortical neurons--layer 2/3 intratelencephalic excitatory neurons--has evolved exceptionally quickly in the human lineage compared to other apes. Surprisingly, this accelerated evolution was accompanied by the dramatic down-regulation of autism-associated genes, which was likely driven by polygenic positive selection specific to the human lineage. In sum, we introduce a general principle governing neuronal evolution and suggest that the exceptionally high prevalence of autism in humans may be a direct result of natural selection for lower expression of a suite of genes that conferred a fitness benefit to our ancestors while also rendering an abundant class of neurons more sensitive to perturbation.

neuroscience↗

bioRxiv2024

Disentangling cell-intrinsic and extrinsic factors underlying gene expression evolution

A key goal of developmental biology is to determine the extent to which cells and organs develop autonomously, as opposed to requiring interactions with other cells or environmental factors. Chimeras have played a foundational role in this by enabling qualitative classification of cell-intrinsically vs. extrinsically driven processes. Here, we extend this framework to precisely decompose evolutionary divergence in any quantitative trait into cell-intrinsic, extrinsic, and intrinsic-extrinsic interaction components. Applying this framework to thousands of gene expression levels in reciprocal rat-mouse chimeras, we found that the majority of their divergence is attributable to cell-intrinsic factors, though extrinsic factors also play an integral role. For example, a rat-like extracellular environment extrinsically up-regulates the expression of a key transcriptional regulator of the endoplasmic reticulum (ER) stress response in some but not all cell types, which in turn strongly predicts extrinsic up-regulation of its target genes and of the ER stress response pathway as a whole. This effect is also seen at the protein level, suggesting propagation through multiple regulatory levels. Applying our framework to a cellular trait, neuronal differentiation, revealed a complex interaction of intrinsic and extrinsic factors. Finally, we show that imprinted genes are dramatically mis-expressed in species-mismatched environments, suggesting that mismatch between rapidly evolving intrinsic and extrinsic mechanisms controlling gene imprinting may contribute to barriers to interspecies chimerism. Overall, our conceptual framework opens new avenues to investigate the mechanistic basis of developmental processes and evolutionary divergence across myriad quantitative traits in any multicellular organism.

evolutionary biology↗

bioRxiv2023

Cell type-specific cis-regulatory divergence in gene expression and chromatin accessibility revealed by human-chimpanzee hybrid cells

Although gene expression divergence has long been postulated to be the primary driver of human evolution, identifying the genes and genetic variants underlying uniquely human traits has proven to be quite challenging. Theory suggests that cell type-specific cis-regulatory variants may fuel evolutionary adaptation due to the specificity of their effects. These variants can precisely tune the expression of a single gene in a single cell type, avoiding the potentially deleterious consequences of trans-acting changes and non-cell type-specific changes that can impact many genes and cell types, respectively. It has recently become possible to quantify human-specific cis-acting regulatory divergence by measuring allele-specific expression in human-chimpanzee hybrid cells--the product of fusing induced pluripotent stem (iPS) cells of each species in vitro. However, these cis-regulatory changes have only been explored in a limited number of cell types. Here, we quantify human-chimpanzee cis-regulatory divergence in gene expression and chromatin accessibility across six cell types, enabling the identification of highly cell type-specific cis-regulatory changes. We find that cell type-specific genes and regulatory elements evolve faster than those shared across cell types, suggesting an important role for genes with cell type-specific expression in human evolution. Furthermore, we identify several instances of lineage-specific natural selection that may have played key roles in specific cell types, such as coordinated changes in the cis-regulation of dozens of genes involved in neuronal firing in motor neurons. Finally, using novel metrics and a machine learning model, we identify genetic variants that likely alter chromatin accessibility and transcription factor binding, leading to neuron-specific changes in the expression of the neurodevelopmentally important genes FABP7 and GAD1. Overall, our results demonstrate that integrative analysis of cis-regulatory divergence in chromatin accessibility and gene expression across cell types is a promising approach to identify the specific genes and genetic variants that make us human.

evolutionary biology↗

bioRxiv2022

Accounting for cis-regulatory constraint prioritizes genes likely to affect species-specific traits

Measuring allele-specific expression in interspecies hybrids is a powerful way to detect cis-regulatory changes underlying adaptation. However, it remains difficult to identify genes most likely to explain species-specific traits. Here, we outline a simple strategy that leverages population-scale allele-specific RNA-seq data to identify genes that have constrained cis- regulation within species yet show divergence between species. Applying this strategy to data from human-chimpanzee hybrid cortical spheroids, we identify signatures of lineage-specific selection on genes related to cellular proliferation, speech, and glucose metabolism. We also highlight cis-regulatory divergence in CUX1 and EDNRB that may shape the unique trajectory of human brain development.

evolutionary biology↗