Background Triple-negative breast cancer (TNBC) is associated with poor survival rate and high genomic instability, generating complex tumour genomes. However, the processes that generate this complexity are poorly studied in longitudinal samples. Here, we study the temporal dynamics of TNBC somatic mutations, revealing major transitions in tumour genome evolution, from diagnostic biopsies, through treatment, to cancer remission or recurrence. Methods Deep whole exome sequencing and CUTseq, a reduced representation whole genome sequencing approach, were performed in parallel, to comprehensively identify short nucleotide variants (SNVs), copy number alterations (CNAs) and aneuploidies. Tumour samples (N=74) from 22 patients were profiled before and after neoadjuvant chemotherapy (NACT), and encompassed spatially diverse samples from multiple primary breast tumours, to allow tracking of the gain and loss of candidate driver variants over time. Results Genome-wide SNV mutational burden remained stable across disease progression and RCB classes. However, recurrent SNVs were identified in several known TNBC driver genes in response to treatment, with TP53, MICA, CYP2D6, BRCA1, and BRCA2 being frequently altered. The candidate driver variants in these genes frequently exhibited dynamic changes throughout the course of a patient’s treatment, with the original SNVs in pre-treatment samples often lost, while novel variants in the same genes emerged at subsequent time points. In contrast to the stable genome-wide SNV burdens, dramatic changes in chromosome structure were seen in all tumours, with abundant CNAs and chromosome arm aneuploidies seen in pre-treatment samples, followed by frequent loss of these alterations post-treatment, and their re-emergence at recurrence. Whole genome duplication (WGD) events appear to drive these dynamics, with a higher frequency of pre-treatment WGD seen in patients with the best response to NACT. Conclusions Comprehensive longitudinal profiling of the TNBC genome demonstrates the complex interplay of SNVs and structural alterations during tumour progression, leading to diverse evolutionary trajectories impacting patient outcomes. Complex mutational patterns encompassing entire chromosomes emerge during progression, with WGD events making major contributions to intra-tumour heterogeneity, and emerging as a potential candidate biomarker of response at both tumour establishment and recurrence. ### Competing Interest Statement The authors have declared no competing interest. Genomic data generated in this study have been submitted to the European Genome/ Phenome Archive, with accession numbers EGAD00001015684 (CUTseq data) and EGAD00001015687 (WES data).

Leavening dough is one of the most widespread applications of fermentative yeast and the most common practice for the general public to come into contact with microbial cultures. Saccharomyces cerevisiae is the typical species used for dough making, but the evolutionary origin of strains isolated from dough is mixed. Here, using 49 newly sequenced and 183 previously described isolates from the bakery environment, we show that the traditional strains used in Europe for sourdough making are more closely related to Chinese Mantou sourdough lineages than to commercially used baker yeast strains. Surprisingly, the expansion of these traditional European strains into other human-associated niches, including the human body, has been very limited. This is in stark contrast to the Mixed-origin clade commercial baking yeasts, which consists of only a few globally distributed clonal lineages that dominate the yeast market and recurrently colonize sourdoughs and human hosts. These clonal lineages consistently maintain their ploidy, unique heterozygous chromosomal rearrangements, and stable aneuploidies in addition to several diverse structural variants. In addition to the previously known diploid and tetraploid groups of commercial isolates, we describe a widely distributed stable triploid aneuploid clonal lineage. We show that company practices and global trade help the distribution of these clonal clusters and that these yeasts are characterized by their exclusively mitotic reproduction. ### Competing Interest Statement Adam Fulep is an employee of the bakery company from which the Hungarian sourdoughs were sourced. The company had no influence on interpreting and publishing the results. Other authors declare no conflict of interest.

Deciphering the structural variation across tumour genomes is crucial to determine the events driving tumour progression and better understand tumour adaptation and evolution. High grade serous ovarian cancer (HGSOC) is an exemplar tumour type showing extreme, but poorly characterised structural diversity. Here, we comprehensively describe the mutational landscape driving HGSOC, exploiting a large (N = 324), deeply whole genome sequenced dataset. We reveal two divergent evolutionary trajectories, affecting patient survival and involving differing genomic environments. One involves homologous recombination repair deficiency (HRD) while the other is dominated by whole genome duplication (WGD) with frequent chromothripsis, breakage-fusion-bridges and extra-chromosomal DNA. These trajectories contribute to structural variation hotspots, containing candidate driver genes with significantly altered expression. While structural variation predominantly drives tumorigenesis, we find high mtDNA mutation loads associated with shorter patient survival. We show that a combination of mutations in the mitochondrial and nuclear genomes impact prognosis, suggesting strategies for patient stratification.

Populations evolving independently in divergent environments accumulate genetic differences and potentially evolve reproductive isolation as a by-product of divergence. The speed and mechanisms underlying this process are difficult to investigate because we rarely get the opportunity to witness them in natural settings, and histories of selection and gene flow between populations are often unknown. Here, we experimentally evolved yeast for 1000 generations of evolution in both divergent and parallel environments. At regular time points during experimental evolution, we made crosses between parallel- and divergent-evolving populations to measure postzygotic reproductive isolation (gamete viability). We used whole genome population sequencing to determine the mutational load, the number and types of structural variation, and other genomic features of the parent, F1, and F2 intraspecific hybrids. We found evidence for large scale phenotypic and genome-wide differentiation in response to divergent laboratory selection. Divergent-selected populations produced hybrids with reduced gamete viability - a classic signature of postzygotic reproductive isolation in the form of hybrid breakdown. Parallel-selected populations on the other hand remained reproductively compatible. We found that F2 hybrid genomes contained vast genomic instability, i.e., new structural variants (especially insertions, deletions, and interchromosomal translocations) that were not observed in parent and F1 genomes, which is likely a result of chromosome missegregation and recombination errors in hybrid meiosis. Our results provide phenotypic and genomic evidence that partial reproductive isolation evolved due to adaptation to divergent environments, consistent with predictions of ecological speciation theory. ### Competing Interest Statement The authors have declared no competing interest.

Populations evolving independently in divergent environments accumulate genetic differences and potentially evolve reproductive isolation as a by-product of divergence. The speed and mechanisms underlying this process are difficult to investigate because we rarely get the opportunity to witness them in natural settings, and histories of selection and gene flow between populations are often unknown. Here, we experimentally evolved yeast for 1000 generations of evolution in both divergent and parallel environments. At regular time points during experimental evolution, we made crosses between parallel- and divergent-evolving populations to measure postzygotic reproductive isolation (gamete viability). We used whole genome population sequencing to determine the mutational load, the number and types of structural variation, and other genomic features of the parent, F1 and F2 intraspecific hybrids. We found evidence for large-scale phenotypic and genome-wide differentiation in response to divergent laboratory selection. Divergent-selected populations produced hybrids with reduced gamete viability-a classic signature of postzygotic reproductive isolation in the form of hybrid breakdown. Parallel-selected populations, on the other hand, remained more reproductively compatible (with exceptions). We found that F2 hybrid genomes contained vast genomic instability, that is, new structural variants (especially insertions, deletions and interchromosomal translocations) that were not observed in parent and F1 genomes, which is likely a result of chromosome missegregation and recombination errors in hybrid meiosis. Our results provide phenotypic and genomic evidence that partial reproductive isolation evolved due to adaptation to divergent environments, consistent with predictions of ecological speciation theory.

Background: Triple Negative Breast Cancer (TNBC) is characterised by extensive intra-tumour heterogeneity (ITH) where clonal lineages diverge from distinct subpopulations over time, impacting treatment resistance and influencing metastasis. However, the mutational dynamics underlying these lineages are poorly studied. Most TNBC patients with early or locally advanced disease receive neoadjuvant chemotherapy (NACT). Pathological complete response (pCR) to NACT is considered as a surrogate for good prognosis but patient response differs greatly. Both SNVs (short nucleotide variants) and copy number variants (CNVs) have been implicated as drivers of the adaptive response to chemotherapy and metastasis in TNBC. Here, we comprehensively investigated the mutational landscapes in a longitudinally sampled TNBC cohort, relating SNV and CNV patterns during the course of the disease to patient outcomes. Methods: All TNBC patients selected for the study were undergoing NACT. Samples included preNACT treatment (PreT), surgical postNACT treatment (PostT) and recurrence samples. Residual Cancer Burden (RCB) scores and tumour infiltrating lymphocytes (TILs) were reported by a breast cancer pathologist. DNA was extracted from FFPE tumour samples where homogenous tumour regions had been identified by the pathologist. Multiple regions of the PostT recurrence samples were selected for DNA extraction, resulting in 96 samples in total. Following whole exome sequencing, the raw sequencing reads were processed to identify germline and somatic variants. In addition, we optimised an affordable approach to profile genome wide CNVs in longitudinal samples. Bioinformatic analysis of SNV and CNV data then studied the dominant mutational patterns over time, and identified likely driver variants and disrupted pathways. Results: Our results demonstrate that low RCB score correlates with higher levels of TILs in the PreT samples. Tumour mutational burden (TMB) varied from 1-27 per Mb and was lowest in 2 patients with known germline mutations. SNV analysis identified variants in 69 genes previously reported to play roles in the progression of TNBC, the most frequently mutated being TP53. We also found suggestive evidence for novel driver variants under positive selection in the MICA gene. Overall, we identified an enrichment of mutations in genes associated with nucleic acid metabolic processes. The longitudinal sampling also allowed the detection of relatively early PreT mutations, showing enrichment in pathways involved in double-strand break repair and apoptotic signaling. Subsequently many of these early variants were found to be ‘conserved’ as mutations retained from PreT to PostT in samples from the same patient. In addition, we identified a novel class of SNVs that appear to arise only at later stages of the disease. In the CNV landscape, we identified regions that were commonly amplified or deleted in PreT samples, particularly a recurrent amplification of 8q. For some patients, the CNV landscape changed dramatically over the course of TNBC disease progression, with frequently altered genes differing markedly from those impacted by SNVs. Conclusions: We have developed relatively inexpensive profiling techniques to identify disease-associated variants in TNBC patients, allowing us to study their dynamics over the course of the disease. We present mutational profiles from before and after NACT from the same patient, which can be compared to reveal the variants that are gained or lost genome-wide during the evolution of a tumour. Ultimately, specific SNVs and CNVs associated with survival, recurrence and metastasis can be identified. These data will direct larger scale follow-up studies for biomarker validation and treatment stratification. Citation Format: Olga O|ikonomidou, Fiona Semple, Devin Bendixsen, Alastair Ironside, Natalie Wilson, Ailith Ewing, Colin Semple. Charting the longitudinal mutational landscape of triple negative breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2024; 2024 Dec 10-13; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(12 Suppl):Abstract nr P2-03-23.

Hybrids between species exhibit plastic genomic architectures that could foster or slow down their adaptation. When challenged to evolve in an environment containing a UV mimetic drug, yeast hybrids have reduced adaptation rates compared to parents. We find that hybrids and their parents converge onto similar molecular mechanisms of adaptation by mutations in pleiotropic transcription factors, but at a different pace. After 100 generations, mutations in these genes tend to be homozygous in the parents but heterozygous in the hybrids. We hypothesize that a lower rate of loss of heterozygosity (LOH) in hybrids could limit fitness gain. Using genome editing, we first demonstrate that mutations display incomplete dominance, requiring homozygosity to show full impact and to entirely circumvent Haldane’s sieve, which favors the fixation of dominant mutations. Second, tracking mutations in earlier generations confirmed a different rate of LOH in hybrids. Together, these findings show that Haldane’s sieve slows down adaptation in hybrids, revealing an intrinsic constraint of hybrid genomic architecture that can limit the role of hybridization in adaptive evolution. Hybrids have complex genomes that influence their adaptive potential. This study reveals that yeast hybrids adapt slower than their parental species in a new environment, primarily due to a reduced rate of loss of heterozygosity in key genes.

Self-cleaving ribozymes are RNA molecules that catalyze the cleavage of their own phosphodiester backbones. These ribozymes are found in all domains of life and are also a tool for biotechnical and synthetic biology applications. Self-cleaving ribozymes are also an important model of sequence-to-function relationships for RNA because their small size simplifies synthesis of genetic variants and self-cleaving activity is an accessible readout of the functional consequence of the mutation. Here, we used a high-throughput experimental approach to determine the relative activity for every possible single and double mutant of five self-cleaving ribozymes. From this data, we comprehensively identified non-additive effects between pairs of mutations (epistasis) for all five ribozymes. We analyzed how changes in activity and trends in epistasis map to the ribozyme structures. The variety of structures studied provided opportunities to observe several examples of common structural elements, and the data was collected under identical experimental conditions to enable direct comparison. Heatmap-based visualization of the data revealed patterns indicating structural features of the ribozymes including paired regions, unpaired loops, non-canonical structures, and tertiary structural contacts. The data also revealed signatures of functionally critical nucleotides involved in catalysis. The results demonstrate that the data sets provide structural information similar to chemical or enzymatic probing experiments, but with additional quantitative functional information. The large-scale data sets can be used for models predicting structure and function and for efforts to engineer self-cleaving ribozymes.

Recent findings in yeast genetics and genomics have advanced our understanding of the evolutionary potential unlocked by hybridization, especially in the genus Saccharomyces. We now have a clearer picture of the prevalence of yeast hybrids in the environment, their ecological and evolutionary history, and the genetic mechanisms driving (and constraining) their adaptation. Here, we describe how the instability of hybrid genomes determines fitness across large evolutionary scales, highlight new hybrid strain engineering techniques, and review tools for comparative hybrid genome analysis. The recent push to take yeast research back 'into the wild' has resulted in new genomic and ecological resources. These provide an arena for quantitative genetics and allow us to investigate the architecture of complex traits and mechanisms of adaptation to rapidly changing environments. The vast genetic diversity of hybrid populations can yield insights beyond those possible with isogenic lines. Hybrids offer a limitless supply of genetic variation that can be tapped for industrial strain improvement but also, combined with experimental evolution, can be used to predict population responses to future climate change — a fundamental task for biologists.

AbstractAdaptation from standing genetic variation is an important process underlying evolution in natural populations but we rarely get the opportunity to observe the dynamics of fitness changes in real time. Here, we used the power of microbial experimental evolution and whole population sequencing to track the phenotypic and genomic changes of genetically diverse yeast populations in environments with different stress levels. We found that populations rapidly and in parallel increased in fitness in stressful environments. The founder’s genetic diversity was quickly depleted, however, not to the same degree in all populations and environments. Some populations fixed all ancestral variation in < 30 generations while others maintained diversity across hundreds of generations. We also observed parallelism at the gene and pathway level. Specifically, we detected up to seven genes harbouring multiple independent mutations in different populations, and a general enrichment for mutations affecting downstream effectors of the high-osmolarity-glycerol pathway in three out of four environments. Adaptation to the most stressful environment was characterised by the fast evolution of functional haploidy, likely driven by standing genetic variation. Almost 40% of all populations contained aneuploidies (losses or gains of chromosomes) at least once during experimental evolution. Some aneuploidies were maintained for hundreds of generations in parallel in different replicates, suggesting they were adaptive. This work shows that experimental evolution is a great tool to address the interplay between standing variation and the influx ofde novomutations, leading to a better understanding of the demographic and environmental drivers and constraints of a population’s capacity to adapt to environmental change.

Abstract Motivation DNA barcodes are short, random nucleotide sequences introduced into cell populations to track the relative counts of hundreds of thousands of individual lineages over time. Lineage tracking is widely applied, e.g. to understand evolutionary dynamics in microbial populations and the progression of breast cancer in humans. Barcode sequences are unknown upon insertion and must be identified using next-generation sequencing technology, which is error prone. In this study, we frame the barcode error correction task as a clustering problem with the aim to identify true barcode sequences from noisy sequencing data. We present Shepherd, a novel clustering method that is based on an indexing system of barcode sequences using k-mers, and a Bayesian statistical test incorporating a substitution error rate to distinguish true from error sequences. Results When benchmarking with synthetic data, Shepherd provides barcode count estimates that are significantly more accurate than state-of-the-art methods, producing 10–150 times fewer spurious lineages. For empirical data, Shepherd produces results that are consistent with the improvements seen on synthetic data. These improvements enable higher resolution lineage tracking and more accurate estimates of biologically relevant quantities, e.g. the detection of small effect mutations. Availability and implementation A Python implementation of Shepherd is freely available at: https://www.github.com/Nik-Tavakolian/Shepherd. Supplementary information Supplementary data are available at Bioinformatics online.

Adaptation from standing genetic variation is an important process underlying evolution in natural populations, but we rarely get the opportunity to observe the dynamics of fitness and genomic changes in real time. Here, we used experimental evolution and Pool-Seq to track the phenotypic and genomic changes of genetically diverse asexual populations of the yeast Saccharomyces cerevisiae in four environments with different fitness costs. We found that populations rapidly and in parallel increased in fitness in stressful environments. In contrast, allele frequencies showed a range of trajectories, with some populations fixing all their ancestral variation in <30 generations and others maintaining diversity across hundreds of generations. We detected parallelism at the genomic level (involving genes, pathways, and aneuploidies) within and between environments, with idiosyncratic changes recurring in the environments with higher stress. In particular, we observed a tendency of becoming haploid-like in one environment, whereas the populations of another environment showed low overall parallelism driven by standing genetic variation despite high selective pressure. This work highlights the interplay between standing genetic variation and the influx of de novo mutations in populations adapting to a range of selective pressures with different underlying trait architectures, advancing our understanding of the constraints and drivers of adaptation.

Self-cleaving ribozymes are genetic elements found in all domains of life, but their evolution remains poorly understood. A ribozyme located in the second intron of the cytoplasmic polyadenylation binding protein 3 gene (CPEB3) shows high sequence conservation in mammals, but little is known about the functional conservation of self-cleaving ribozyme activity across the mammalian tree of life or during the course of mammalian evolution. Here, we use a phylogenetic approach to design a mutational library and a deep sequencing assay to evaluate the in vitro self-cleavage activity of numerous extant and resurrected CPEB3 ribozymes that span over 100 My of mammalian evolution. We found that the predicted sequence at the divergence of placentals and marsupials is highly active, and this activity has been conserved in most lineages. A reduction in ribozyme activity appears to have occurred multiple different times throughout the mammalian tree of life. The in vitro activity data allow an evaluation of the predicted mutational pathways leading to extant ribozyme as well as the mutational landscape surrounding these ribozymes. The results demonstrate that in addition to sequence conservation, the self-cleavage activity of the CPEB3 ribozyme has persisted over millions of years of mammalian evolution.

Saccharomyces hybrid yeasts are receiving increasing attention as a powerful model system to understand adaptation to environmental stress and speciation mechanisms, using experimental evolution and omics techniques. We compiled all genomic resources available from public repositories of the eight recognized Saccharomyces species and their interspecific hybrids. We present the newest numbers on genomes sequenced, assemblies, annotations, and sequencing runs, and an updated species phylogeny using orthogroup inference. While genomic resources are highly skewed towards Saccharomyces cerevisiae, there is a noticeable movement to use wild, recently discovered yeast species in recent years. To illustrate the degree and potential causes of reproductive isolation, we reanalyzed published data on hybrid spore viabilities across the entire genus and tested for the role of genetic, geographic, and ecological divergence within and between species (28 cross types and 371 independent crosses). Hybrid viability generally decreased with parental genetic distance likely due to antirecombination and negative epistasis, but notable exceptions emphasize the importance of strain-specific structural variation and ploidy differences. Surprisingly, the viability of crosses within species varied widely, from near reproductive isolation to near-perfect viability. Geographic and ecological origins of the parents predicted cross viability to an extent, but with certain caveats. Finally, we highlight publication trends in the field and point out areas of special interest, where hybrid yeasts are particularly promising for innovation through research and development, and experimental evolution and fermentation.

Comparative genome analyses have suggested East Asia to be the cradle of the domesticated microbe Brewer's yeast (Saccharomyces cerevisiae), used in the food and biotechnology industry worldwide. Here, we provide seven new, high-quality long-read genomes of nondomesticated yeast strains isolated from primeval forests and other natural environments in China and Taiwan. In a comprehensive analysis of our new genome assemblies, along with other long-read Saccharomycetes genomes available, we show that the newly sequenced East Asians trains are amongthe closest living relatives of the ancestors of the global diversity of Brewer's yeast, confirming predictionsmade from short-read genomic data. Three of these strains (termed the East Asian Clade IX Complex here) share a recent ancestry and evolutionary history suggesting an early divergence from other S. cerevisiae strains before the larger radiation of the species, and prior to its domestication. Our genomic analyses reveal that the wild East Asian strains contain elevated levels of structural variations. The new genomic resources provided here contribute to our understanding of the natural diversity of S. cerevisiae, expand the intraspecific genetic variation found in this heavily domesticated microbe, and provide a foundation for understanding its origin and global colonization history.

The genomes of hybrids often show substantial deviations from the features of the parent genomes, including genomic instabilities characterized by chromosomal rearrangements, gains, and losses. This plastic genomic architecture generates phenotypic diversity, potentially giving hybrids access to new ecological niches. It is however unclear if there are any generalizable patterns and predictability in the type and prevalence of genomic variation and instability across hybrids with different genetic and ecological backgrounds. Here, we analyzed the genomic architecture of 204 interspecific Saccharomyces yeast hybrids isolated from natural, industrial fermentation, clinical, and laboratory environments. Synchronous mapping to all eight putative parental species showed significant variation in read depth indicating frequent aneuploidy, affecting 44% of all hybrid genomes and particularly smaller chromosomes. Early generation hybrids with largely equal genomic content from both parent species were more likely to contain aneuploidies than introgressed genomes with an older hybridization history, which presumably stabilized the genome. Shared k-mer analysis showed that the degree of genomic diversity and variability varied among hybrids with different parent species. Interestingly, more genetically distant crosses produced more similar hybrid genomes, which may be a result of stronger negative epistasis at larger genomic divergence, putting constraints on hybridization outcomes. Mitochondrial genomes were typically inherited from the species also contributing the majority nuclear genome, but there were clear exceptions to this rule. Together, we find reliable genomic predictors of instability in hybrids, but also report interesting cross- and environment-specific idiosyncrasies. Our results are an important step in understanding the factors shaping divergent hybrid genomes and their role in adaptive evolution.

Extreme F2 phenotypes known as transgressive segregants can cause increased or decreased fitness in hybrids beyond the ranges seen in parental populations. Despite the usefulness of transgression for plant and animal breeding and its potential role in hybrid speciation, the genetic mechanisms and predictors of transgressive segregation remain largely untested. We generated seven hybrid crosses between five widely divergent Saccharomyces yeast species and measured the fitness of the parents and their viable F1 and F2 hybrids in seven stressful environments. We found that on average 16.6% of all replicate F2 hybrids had higher fitness than both parents. Against our predictions, transgression frequency was not a function of parental genetic and phenotypic distances across test environments. Within environments, some relationships were significant, but not in the predicted direction; for example, genetic distance was negatively related to transgression in ethanol and hydrogen peroxide. Significant effects of hybrid cross, test environment, and cross × environment interactions suggest that the amount of transgression produced in a hybrid cross is highly context specific and that outcomes of hybridization differ even among crosses made from the same two parents. If the goal is to reliably predict hybrid fitness and forecast the evolutionary potential of admixed populations, we need more efforts to identify patterns beyond the idiosyncrasies caused by specific genomic or environmental contexts.

Corrigendum to: Genomic Evidence of an Ancient East Asian Divergence Event in Wild Saccharomyces cerevisiae Devin P Bendixsen , Noah Gettle, Ciaran Gilchrist, Zebin Zhang, Rike Stelkens Genome Biology and Evolution, Volume 13, Issue 2, evab001, https://doi.org/10.1093/gbe/evab001 In the originally published version of this manuscript, Figure 3 and Figure 4 in the manuscript were swapped although the captions for each of the figures were correct and in the correct location. This has now been corrected.

Forest vulnerability to drought is expected to increase under anthropogenic climate change, and drought-induced mortality and community dynamics following drought have major ecological and societal impacts. Here, we show that tree mortality concomitant with drought has led to short-term (mean 5 y, range 1 to 23 y after mortality) vegetation-type conversion in multiple biomes across the world (131 sites). Self-replacement of the dominant tree species was only prevalent in 21% of the examined cases and forests and woodlands shifted to nonwoody vegetation in 10% of them. The ultimate temporal persistence of such changes remains unknown but, given the key role of biological legacies in long-term ecological succession, this emerging picture of postdrought ecological trajectories highlights the potential for major ecosystem reorganization in the coming decades. Community changes were less pronounced under wetter postmortality conditions. Replacement was also influenced by management intensity, and postdrought shrub dominance was higher when pathogens acted as codrivers of tree mortality. Early change in community composition indicates that forests dominated by mesic species generally shifted toward more xeric communities, with replacing tree and shrub species exhibiting drier bioclimatic optima and distribution ranges. However, shifts toward more mesic communities also occurred and multiple pathways of forest replacement were observed for some species. Drought characteristics, species-specific environmental preferences, plant traits, and ecosystem legacies govern postdrought species turnover and subsequent ecological trajectories, with potential far-reaching implications for forest biodiversity and ecosystem services.