Biology subjects

Joubert, P. M.

Publications and source records attributed to Joubert, P. M..

7 recordsLinked to original sources

bioRxiv2026

Using Deep Learning to predict replication timing reveals baseline control of genomic DNA sequence

Human DNA replicates according to a precise schedule: certain regions are replicated early, while others replicate later in the cell cycle. The DNA sequence and the epigenome are both indicative for replication timing (RT), their relative contributions and potential complementarity yet remain unclear. Here, we utilize Repli-Seq data and machine learning to investigate these relationships in seven human cell lines. We show that GROVER (Genome Rules Obtained Via Extracted Representations), a DNA language model, trained purely on DNA sequence can be fine-tuned for RT, which indicates that information on DNA sequence is largely sufficient to predict RT. Integrating GROVERs sequence predictions as an additional feature with diverse epigenetic sequencing data, yields a multimodal model that outperforms approaches that use exclusively the DNA sequence or the epigenome, which demonstrates predictive synergy. By evaluating input feature contributions, we find that epigenetic features vary in their RT prediction contribution. Some epigenetic features see their contribution diminish in the presence of DNA sequence information, others remain predictive. GROVERs sequence representations emerge as the most dominant feature. Furthermore, to assess cell-type specificity of RT, we partitioned the genome into constitutive domains that replicate uniformly across cell lines and cell-type-specific domains that shift during differentiation. While DNA sequence features contribute more to constitutive predictions, they also remain informative within cell-type-specific regions. Together, our findings dissect the relationship between DNA sequence and the epigenome relative to RT and suggest that primary DNA sequence instructions exert a powerful baseline control over constitutive and cell-type-specific RT, fine-tuned by regulatory cues beyond the DNA sequence.

genomics↗

bioRxiv2025

Using the DNA language model, GROVER, to parse sequence and epigenetic effects on genome stability

AbstractGenome stability is shaped by DNA sequence and chromatin context, but their relative contributions to double-strand break (DSB) sensitivity remain unclear. We show that the DNA language model, GROVER, can infer DSB location based on sequence. DSB hotspots tend to contain GC-rich sequences that belong to promoters, genes and short interspersed nuclear elements (SINEs). Additionally, we identified several specific short sequences (tokens) that are associated with modulating DSB sensitivity. Another model using chromatin and genome regulatory features outperforms the sequence-only model, highlighting complementary and cell-type specific information. Integrating sequence and genome biological features yields the best performance, demonstrating their synergy. Analyzing this model revealed that, dependent on the sample, genome stability information encoded in H3K36me3 and DNase-seq can be learned from the sequence, but not H3K27ac or H3K9me3. Embedding chromatin data directly into the GROVER architecture enabled cell-type specific modeling with performance matching the full chromatin feature model. Our results suggest that while chromatin and regulatory context provides important information, such as cell-type specificity, much of the information shaping DSB patterns is already encoded in the DNA sequence itself. Our integrative modeling approach not only reveals DSB patterns but also provides a generalizable strategy for tracing predictions in genomic data. O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/666402v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@af3ea5org.highwire.dtl.DTLVardef@139d159org.highwire.dtl.DTLVardef@df455borg.highwire.dtl.DTLVardef@428e20_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2023

Distinct genomic contexts predict gene presence-absence variation in different pathotypes of a fungal plant pathogen

BackgroundFungi use the accessory segments of their pan-genomes to adapt to their environments. While gene presence-absence variation (PAV) contributes to shaping these accessory gene reservoirs, whether these events happen in specific genomic contexts remains unclear. Additionally, since pan-genome studies often group together all members of the same species, it is uncertain whether genomic or epigenomic features shaping pan-genome evolution are consistent across populations within the same species. Fungal plant pathogens are useful models for answering these questions because members of the same species often infect distinct hosts, and they frequently rely on gene PAV to adapt to these hosts. ResultsWe analyzed gene PAV in the rice and wheat blast fungus, Magnaporthe oryzae, and found that PAV of disease-causing effectors, antibiotic production, and non-self-recognition genes may drive the adaptation of the fungus to its environment. We then analyzed genomic and epigenomic features and data from available datasets for patterns that might help explain these PAV events. We observed that proximity to transposable elements (TEs), gene GC content, gene length, expression level in the host, and histone H3K27me3 marks were different between PAV genes and conserved genes, among other features. We used these features to construct a random forest classifier that was able to predict whether a gene is likely to experience PAV with high precision (86.06%) and recall (92.88%) in rice-infecting M. oryzae. Finally, we found that PAV in wheat- and rice-infecting pathotypes of M. oryzae differed in their number and their genomic context. ConclusionsOur results suggest that genomic and epigenomic features of gene PAV can be used to better understand and even predict fungal pan-genome evolution. We also show that substantial intra-species variation can exist in these features.

genomics↗

bioRxiv2022

Evolutionary dynamics of transposable elements in Magnaporthe oryzae reveal evidence of genomic transfer and key differences between rice and wheat blast pathotypes

Transposable elements (TEs) contribute to intraspecific variation and play important roles in the evolution of fungal genomes. However, our understanding of the processes that shape TE landscapes is limited, as is our understanding of the relationship between TE content, population structure, and evolutionary history of fungal species. Fungal plant pathogens, which often have host-specific populations, are useful systems in which to study intraspecific TE content diversity. Here, we describe TE dynamics in five lineages of Magnaporthe oryzae, the fungus that causes blast disease of rice, wheat, and many other grasses. We identified differences in TE content across these lineages, and showed that recent lineage-specific expansions of certain TEs have contributed to overall greater TE content in rice-infecting and Setaria-infecting lineages. We reconstructed the evolutionary histories of LTR-retrotransposon expansions and found that in some cases they were caused by complex proliferation dynamics of one element, and in others by multiple elements from an older population of TEs multiplying in parallel. Additionally, we found evidence suggesting the recent transfer of a DNA transposon between rice and wheat-infecting M. oryzae lineages, and a region showing evidence of homologous recombination between those lineages, which could have facilitated such a transfer. By investigating intraspecific TE content variation, we uncovered key differences in the proliferation dynamics of TEs in various pathotypes of a fungal plant pathogen, giving us a better understanding of the evolutionary history of the pathogen itself.

genomics↗

bioRxiv2021

The extrachromosomal circular DNAs of the rice blast pathogen Magnaporthe oryzae contain a wide variety of LTR retrotransposons, genes, and effectors

BackgroundOne of the ways genomes respond to stress is by producing extrachromosomal circular DNAs (eccDNAs). EccDNAs can contain genes and dramatically increase their copy number. They can also reinsert into the genome, generating structural variation. They have been shown to provide a source of phenotypic and genotypic plasticity in several species. However, whole circularome studies have so far been limited to a few model organisms. Fungal plant pathogens are a serious threat to global food security in part because of their rapid adaptation to disease prevention strategies. Understanding the mechanisms fungal pathogens use to escape disease control is paramount to curbing their threat. ResultsWe present a whole circularome sequencing study of the rice blast pathogen Magnaporthe oryzae. We find that M. oryzae has a highly diverse circularome containing many genes and showing evidence of large LTR retrotransposon activity. We find that genes enriched on eccDNAs in M. oryzae occur in genomic regions prone to presence-absence variation and that disease associated genes are frequently on eccDNAs. Finally, we find that a subset of genes is never present on eccDNAs in our data, which indicates that the presence of these genes on eccDNAs is selected against. ConclusionsOur study paves the way to understanding how eccDNAs contribute to adaptation in M. oryzae. Our analysis also reveals how M. oryzae eccDNAs differ from those of other species and highlights the need for further comparative characterization of eccDNAs across species to gain a better understanding of these molecules.

genomics↗

bioRxiv2020

Molecular and evolutionary mechanisms of yeast thermotolerance

Many familiar traits in the natural world--from lions manes to the longevity of bristlecone pine trees--arose in the distant past, and have long since fixed in their respective species. A key challenge in evolutionary genetics is to figure out how and why species-defining traits have come to be. We used the thermotolerance growth advantage of the yeast Saccharomyces cerevisiae over its sister species Saccharomyces paradoxus as a model for addressing these questions. Analyzing loci at which the S. cerevisiae allele promotes thermotolerance, we detected robust evidence for positive selection, including amino acid divergence between the species and conservation within S. cerevisiae populations. Since such signatures were particularly strong at the chromosome segregation gene ESP1, we used this locus as a case study for focused mechanistic follow-up. Experiments revealed that, in culture at high temperature, the S. paradoxus ESP1 allele conferred a qualitative defect in biomass accumulation and cell division relative to the S. cerevisiae allele. Only genetic divergence in the ESP1 coding region mattered phenotypically, with no functional impact detectable from the promoter. Together, these data support a model in which an ancient ancestor of S. cerevisiae, under selection to boost viability at high temperature, acquired amino acid variants at ESP1 and many other loci, which have been constrained since then. Complex adaptations of this type hold promise as a paradigm for interspecies genetics, especially in deeply diverged traits that may have taken millions of years to evolve.

evolutionary biology↗

bioRxiv2019

Successive passaging of a plant-associated microbiome reveals robust habitat and host genotype-dependent selection

There is increasing interest in the plant microbiome as it relates to both plant health and agricultural sustainability. One key unanswered question is whether we can select for a plant microbiome that is robust after colonization of target hosts. We used a successive passaging experiment to address this question by selecting upon the tomato phyllosphere microbiome. Beginning with a diverse microbial community generated from field-grown tomato plants, we inoculated replicate plants across five plant genotypes for four eight-week long passages, sequencing the microbial community at each passage. We observed consistent shifts in both the bacterial (16S amplicon sequencing) and fungal (ITS amplicon sequencing) communities across replicate lines over time, as well as a general loss of diversity over the course of the experiment suggesting that much of the naturally observed microbial community in the phyllosphere is likely transient or poorly adapted. We found that both host genotype and environment shape microbial composition, but the relative importance of genotype declines through time. Furthermore, using a community coalescence experiment, we found that the bacterial community from the end of the experiment was robust to invasion by the starting bacterial community. These results highlight that selecting for a stable microbiome that is well adapted to a particular host environment is indeed possible, emphasizing the great potential of this approach in agriculture and beyond.\n\nSignificance StatementThere is great interest in selecting for host-associated microbiomes that confer particular functions to their host, and yet it remains unknown whether selection for a robust and stable microbiome is possible. Here, we use a microbiome passaging approach to measure the impact of host-mediated selection on the tomato phyllosphere (above ground) microbiome. We find robust community selection across replicate lines that is shaped by plant host genotype in early passages, but changes in a genotype-independent manner in later passages. Work such as ours is crucial to understanding the general principles governing microbiome assembly and adaptation, and is widely applicable to both sustainable agriculture and microbiome-related medicine.

microbiology↗