Biology subjects

Barker, M.

Publications and source records attributed to Barker, M..

8 recordsLinked to original sources

bioRxiv2026

Unifying phylogenetic traversal and deep learning to guide tree exploration

Deep learning offers hope for more efficient phylogenetic inference methods. However, it has yet to have the transformative effect on phylogenetics that it has had in other fields. Here we present a novel approach that combines deep learning with concepts behind current successful phylogenetic algorithms. Specifically, we give the deep learning algorithm access to the output of a phylogenetic dynamic program on the sequence alignment, rather than the raw sequence alignment. The algorithm then learns features based on these phylogenetically processed versions of the sequence data, providing information to guide local tree search. For this paper, our goal is simple: predict for each edge in a tree whether it is in a maximum parsimony tree or not. Our model consists of a recurrent neural network that learns features while traversing the input tree, which are used to classify the edge. The model makes high-quality predictions for this NP-complete problem on simulated and empirical datasets for trees of various sizes. We believe it is a stepping stone towards efficient phylogenetic inference using deep learning.

bioinformatics↗

bioRxiv2025

larch: mapping the parsimony-optimal landscape of trees for directed exploration

Phylogenetic inference algorithms for large data sets typically return a single tree. However, there are often many optimal trees, especially when sequence data is closely related. We develop a compact representation of large collections of maximally parsimonious histories--trees with mutations mapped onto tree edges. Our C++ implementation, larch, leverages this representation for a highly parallel search algorithm. The storage component uses our history DAG structure to compactly represent large families of optimal trees. The search algorithm integrates this storage with matOptimize for rapid tree optimization; the DAG structure allows us to accept thousands of conflicting tree rearrangements in parallel. The integration enables a new type of tree search: one that systematically maps out the collection of good trees, enabling moves that are directed away from the current set of optimal trees to cross valleys and increase the diversity of the set of optimal trees. It is able to identify more parsimonious trees than are found by other methods. We find diverse optimality landscapes for viral datasets, including many distinct plateaux. We also find that our implementation produces similar results whether using a variety of single starting trees or an ensemble of starting trees, indicating effective global optimization.

evolutionary biology↗

bioRxiv2025

Lipid Nanoparticles with Aptamers Enable Targeted mRNA Delivery to CD4⁺ T Cells

In vivo genetic engineering of T cells could overcome the logistical, biological, and safety challenges of ex vivo modification, but effective and safe delivery systems remain limited by a lack of cellular specificity. Here, we developed aptamer-functionalized lipid nanoparticles (LNPs) for targeted mRNA delivery to CD4+ T cells, employing both a validated CD4-binding aptamer (Apt62) and novel aptamers generated using our proprietary transformer-based AI language model, AptaBLE. LNPs formulated with ionizable lipid SM102 or MC3 and conjugated with aptamers at controlled densities were physiochemically characterized and assessed for binding, in vitro transfection, in vivo biodistribution, and safety evaluation. Aptamer-functionalized LNPs demonstrated selective nanomolar binding to recombinant CD4, achieved enhanced transfection of CD4+ versus CD4- T cells in vitro, and significantly enriched mRNA delivery to immune-rich tissues in vivo, achieving up to 70-fold spleen signal enhancement with SM102 formulations compared to non-targeted controls, while maintaining suitable safety profiles. Overall, these findings demonstrate aptamer-functionalized LNPs, augmented by AI-guided aptamer design, as a tunable, non-immunogenic platform for in vivo T cell engineering. HighlightsO_LIAptamer-functionalized LNPs enable selective mRNA delivery to CD4+ immune cells rich organs. C_LIO_LIAptamer-functionalized LNPs maintain a favorable systemic safety profile in vivo. C_LIO_LIAI-guided AptaBLE platform generated functional aptamers validated in nanoparticle delivery. C_LI

molecular biology↗

bioRxiv2025

Single cell long-read genotyping of transcriptomes reveals discrete mechanisms of clonal evolution in post-myeloproliferative neoplasm acute myeloid leukemia.

Myeloproliferative neoplasms (MPNs) are caused by acquired mutations in hematopoietic stem and progenitor cells (HSPCs). The acquisition of additional mutations like TP53 and the overall mutational burden influence a patients risk of disease progression toward lethal post-MPN acute myeloid leukemia (AML). Recent technological advancements in linking single-cell gene expression with genotype have improved our understanding of tumor heterogeneity. However, current methodologies have limitations in simultaneously genotyping low-expression genes (such as JAK2) alongside other pathogenic loci. To address this, we developed a novel long read genotyping pipeline of cDNA transcripts called LOTR-Seq, which can genotype the full length of expressed transcripts of 30 genes at once. Using LOTR-Seq, we genotyped HSPCs at the JAK2V617 locus in 9,075 single cells from eight patients with chronic phase MPN (CP-MPN) and in 5,016 cells from four patients with post-MPN AML. We then linked the mutations to the single cell transcriptome of 29,712 JAK2V617F-driven CP-MPN cells and 16,895 post-MPN AML cells. In our analysis of post-MPN AMLs, we identified nine mutated loci across six genes (JAK2, IDH1/2, TP53, SRSF2, U2AF1) and linked these mutations to specific transcriptional phenotypes. Overall, LOTR-Seq provides novel insights into the evolution of post-MPN AML.

cancer biology↗

bioRxiv2025

Phylogenomic synteny analysis tracks conserved ancient polyploid-derived triplicated genomic blocks across Asteraceae genomes

The Asteraceae (Compositae) is the largest flowering plant family, ubiquitous in most terrestrial communities, and morphologically hyper-diverse. An ancient whole genome triplication (paleo-hexaploidization) occurred at approximately the same time as the evolutionary innovation and adaptive radiation of the family during the middle Eocene. Despite its importance, the genomic contents arising from this triplication have yet to be tracked in context of the Asteraceae genome evolution. We applied a synteny oriented phylogenomic analysis of 21 Asterales genomes and to study the paleo-hexaploidization and its consequences to gene, trait, and genome evolution. We identified 15 ancestral linkage groups (ALGs) that date back to the common diploid ancestor of all Asteraceae. Each of these groups was triplicated, resulting in 45 genomic blocks (3x15), which serve as the foundation for cross-family analyses. We demonstrate the complex evolutionary dynamics of the 45 genomic blocks across the Asteraceae phylogeny. We found that modern genomes are genetic mosaics of three progenitor genomes by extensive genomic exchange, chromosomal shuffling and gene fractionation. 157 genes retained three paleo-hexaploid derived syntenic paralogs across most Asteraceae species. Transcription factors (TFs) and auxin-related genes are significantly overrepresented in the conserved triplets, and expression of the paleo-hexaploidy paralogs is spatiotemporally differentiated. These genes are involved in the development of floral capitulum, a remarkable morphological innovation of the family. The discovery of conserved triplicated genes can direct further study to understand the evolutionary innovation, and the synteny-phylogenomic framework and ALGs provide a comparative framework to characterize newly sequenced Asteraceae genomes.

genomics↗

bioRxiv2022

Inhibition of DNA-PKcs impairs the activation and cytotoxicity of CD4+ helper and CD8+ effector T cells

Modulation of T cell activity is an effective strategy for the treatment of autoimmune diseases, immune-related disorders and cancer. This highlights a critical need for continued investigation of proteins that regulate T cell function. The kinase DNA-dependent protein kinase catalytic subunit (DNA-PKcs) is emerging as a potent regulator of the immune system spurring interest in its use as a therapeutic target for immune-related diseases. In murine models of autoimmune disease including asthma and rheumatoid arthritis, treatment with small molecule DNA-PKcs inhibitors, which are in clinical trials for cancer therapy, decreased disease severity. Additionally, DNA-PKcs inhibitors reduced T cell-mediated graft rejection and extended graft survival in a murine allogenic skin graft rejection model. These in vivo studies suggest the therapeutic use of DNA-PKcs inhibitors for autoimmune and T cell-mediated disorders. In this study, we sought to further characterize the effects of DNA-PKcs inhibitors on T cells to better understand their clinical potential. We determined that pharmacological inhibition of DNA-PKcs abrogated activation of murine and human CD4+ and CD8+ T cells as evident by reduced expression of the activation markers CD69 and CD25. Furthermore, inhibition of DNA-PKcs impeded metabolic pathways and proliferation of anti-CD3/CD28 activated CD4+ and CD8+ T cells as well as peptide-stimulated OTI-CD8+ T cells. This reduced the ability of OTI-CD8+ T cells to kill cancer cells and the expression of IFN{gamma} and the cytotoxic genes eomes, perforin and granzyme B. These results suggest a novel role for DNA-PKcs in early T cell activation. Furthermore, our data support the therapeutic potential of DNA-PKcs inhibitors on diseases of immune dysregulation.

immunology↗

bioRxiv2019

Inferring the Demographic History of Inbred Species from Genome-Wide SNP Frequency Data

Demographic inference using the site frequency spectrum (SFS) is a common way to understand historical events affecting genetic variation. However, most methods for estimating demography from the SFS assume random mating within populations, precluding these types of analyses in inbred populations. To address this issue, we developed a model for the expected SFS that includes inbreeding by parameterizing individual genotypes using beta-binomial distributions. We then take the convolution of these genotype probabilities to calculate the expected frequency of biallelic variants in the population. Using simulations, we evaluated the models ability to co-estimate demography and inbreeding using one- and two-population models across a range of inbreeding levels. We also applied our method to two empirical examples, American pumas (Puma concolor) and domesticated cabbage (Brassica oleracea var. capitata), inferring models both with and without inbreeding to compare parameter estimates and model fit. Our simulations showed that we are able to accurately co-estimate demographic parameters and inbreeding even for highly inbred populations (F = 0.9). In contrast, failing to include inbreeding generally resulted in inaccurate parameter estimates in simulated data and led to poor model fit in our empirical analyses. These results show that inbreeding can have a strong effect on demographic inference, a pattern that was especially noticeable for parameters involving changes in population size. Given the importance of these estimates for informing practices in conservation, agriculture, and elsewhere, our method provides an important advancement for accurately estimating the demographic histories of these species.

evolutionary biology↗

bioRxiv2017

Diverse genome organization following 13 independent mesopolyploid events in Brassicaceae contrasts with convergent patterns of gene retention

Hybridization and polyploidy followed by genome-wide diploidization significantly impacted the diversification of land plants. The ancient At- whole-genome duplication (WGD) preceded the diversification of crucifers (Brassicaceae). Some genera and tribes also experienced younger, mesopolyploid WGDs concealed by subsequent genome diploidization. Here we tested if multiple base chromosome numbers originated due to genome diploidization after independent mesopolyploid WGDs and how diploidization impacted post-polyploid gene retention. Sixteen species representing ten Brassicaceae tribes were analyzed by comparative chromosome painting and/or whole-transcriptome analysis of gene age distributions and phylogenetic analyses of gene duplications. Overall, we found evidence for at least 13 independent mesopolyploidies followed by different degrees of diploidization across the Brassicaceae. New mesotetraploid events were uncovered for tribes Anastaticeae, Iberideae and Schizopetaleae, and mesohexaploid WGDs for Cochlearieae and Physarieae. In contrast, we found convergent patterns of gene retention and loss among these independent WGDs. Our combined analyses of Brassicaceae genomic data indicate that the extant chromosome number variation in many plant groups, and especially polybasic but monophyletic taxa, can result from clade-specific genome duplications followed by diploidization. Our observation of parallel gene retention and loss across multiple independent WGDs provides one of the first multi-species tests that post-polyploid genome evolution is predictable.\n\nSignificance statementOur data show that multiple base chromosome numbers in some Brassicaceae clades originated due to genome diploidization following multiple independent whole-genome duplications (WGD). The parallel gene retention/loss across independent WGDs and diploidizations provides one of the first tests that post-polyploid genome evolution is predictable.

evolutionary biology↗