BMC Genomics

BackgroundUnderstanding the role of non-coding genomic variation in speciation remains a major challenge in evolutionary biology. Here, we investigated whether regulatory elements contribute to this process between Atlantic and Mediterranean lineages of European sea bass (Dicentrarchus labrax), a well-characterized case-study near speciation where barriers to introgression exist in the presence of connectivity between diverging populations. ResultsWe generated a novel, highly contiguous genome assembly, which was annotated at the epigenomic level using ATAC-seq and ChIP-seq with six embryonic developmental stages and five tissue types in adult fish, identifying thousands of promoters, enhancers, and open chromatin regions. Integrating this annotation with whole-genome sequence data from 65 individuals across three geographically distinct populations, we identified 57,505 outlier SNPs and 332 structural variants (SVs) showing elevated differentiation between Atlantic and East Mediterranean lineages. Outlier SVs affected key regulatory elements and coding genes, while outlier SNPs were enriched in regulatory elements, particularly enhancers active in adult tissues. Local genomic divergence correlated positively with regulatory element density, especially on chromosomes 1, 9, and 18, which are enriched in genes related to osmoregulation, immune response, and oxidative stress -- processes relevant to adaptation across contrasting marine environments. ConclusionsThese findings support a major role for regulatory variation in driving deep lineage divergence through local adaptation.

Background Identifying deleterious DNA changes underpins efforts to improve animal health, welfare, and sustainable breeding. In cattle, current variant prioritization focuses on coding changes, uses single annotation types, and gives limited resolution in non-coding sequence. Results We developed BovCADD (bovine Combined Annotation-Dependent Depletion), a nucleotide-level deleteriousness score for substitutions in Bos taurus and Bos indicus, combining evolutionary constraint, sequence context, epigenetic and regulatory annotations, and gene and protein features. A logistic regression model trained on 41.9 million high-frequency derived alleles from about 3,700 cattle, contrasted with context-matched simulated variants, scored all 8.1 billion possible substitutions. BovCADD distinguished known pathogenic variants from background variation, discriminated among variants within the same consequence class, and scored intronic and intergenic sites. Aggregating scores identified genes carrying rare deleterious variation and revealed elevated genetic load at trait-relevant loci and in bottlenecked, intensively selected populations. Conclusions BovCADD provides the first genome-wide, nucleotide-resolution measure of deleteriousness in cattle, extending variant interpretation to non-coding sequences and linking variant-level prioritization to population-level patterns of mutational burden. Precomputed scores for all substitutions are publicly available.

Variant intolerance methods score the essentiality of genes based on large datasets of genetic variants and have been used in population genomics of humans and model organisms. In this paper, we estimated Residual Variation Intolerance Scores for protein-coding genes and predicted protein domains in cattle. In agreement with results from other species, the most variant-tolerant genes and domains included genes related to olfaction and adaptive immunity, whereas the least-variant tolerant genes and domains included genes involved in fundamental cellular processes. There was a moderate positive correlation with estimates from orthologous human genes. We provide estimates of variant intolerance for cattle may be useful for genomic analyses of deleterious variants and population genomics in cattle.

Understanding the underlying neuronal function in non-model organisms requires accurate resolution of gene structure and transcript diversity. Here, we present a comprehensive genome annotation tor the Jonah crab (Cancer borealis), a key experimental system in crustacean neurobiology, with a particular focus on transcriptome-supported neuronal gene architecture. By integrating long-read genome assembly with extensive transcriptomic evidence, we reconstructed gene models with high confidence, enabling detailed characterization of exon-intron organization, alternative splicing, and isotorm diversity across gene families. Functional classification revealed extensive representation of neural-associated gene classes, including ion channels and receptors, transporters, enzymes, zinc finger proteins, histones, structural proteins, and cell adhesion molecules, alongside a large set of previously uncharacterized genes. In this study we particularly focused on the neuronal and ion channel gene families known to underlie circuit-level neuronal function in C. borealis. We provide an in-depth analysis of 87 genes spanning 17 neural-related gene families and 41 neuropeptides, detailing chromosomal localization, gene length, exon-intron configuration, and transcript-supported isotorm structure. For many of these genes, transcriptomic data confirmed expression and refined coding boundaries. Comparisons with existing transcriptomic datasets demonstrate strong concordance in gene expression patterns while also revealing novel transcripts and expanded gene family members not previously annotated. Together, this genome and transcriptome-integrated annotation establishes a high-resolution framework tor studying neuronal gene organization in C. borealis. T his resource enables direct connections between gene architecture, transcript diversity, and neural function, supporting future investigations in crustacean neurogenomics, comparative genomics, and the evolution of nervous system complexity.

Dermo disease caused by the protist Perkinsus marinus poses a major threat to Eastern oyster aquaculture. We previously conducted genomic selection for dermo resistance and found increased effectiveness over phenotypic selection. Here, we report improved genomic predictions using combined data from three successive generations. We evaluated nine different genomic selection models, including three supervised machine learning architectures: gradient boosting, logistic regression, and random forest. Combining data across multiple generations did not, by itself, substantially improve the accuracy of most models, but the increased sample size provided genotyping confidence of loci with rare alleles. Correlation accuracy of all models significantly increased with the inclusion of low-frequency variants and strong-effect markers identified through a genome-wide association study. Gradient boosting machine learning models outperformed other genomic selection models across all training scenarios, suggesting enhanced capacity to learn generalizable genomic signals associated with dermo resistance. The best gradient boosting model achieved a peak correlation accuracy of 0.410, a substantial improvement over the previous peak accuracy of 0.274 from traditional models. Together, our results highlight the potential of machine learning for genomic selection and the significance of rare variants in determining dermo resistance.

BackgroundHi-C experiments produce genome-wide chromatin contact maps from which structural features can be quantified across multiple genomic scales, ranging from megabase-scale compartments to kilobase-scale boundaries and chromatin loops. Although high-resolution analyses commonly rely on hundreds of millions of sequenced read pairs, the minimum sequencing depth required for different classes of Hi-C-derived features has not been systematically established. We therefore sought to determine these depth requirements systematically. ResultsWe performed progressive random subsampling of twelve Hi-C libraries representing multiple cell types and experimental protocols. Loop-density and loop-size inference from the P(s) log-derivative was evaluated across all libraries, whereas compartment, insulation, and boundary analyses were performed on a subset of nine libraries with comparable full-depth coverage. Rather than defining sufficient depth as an arbitrary fraction of the full-depth value, we introduced a biologically motivated criterion based on the variability between independent biological replicates. The required sequencing depth for each metric was defined as the point at which subsampling scatter first reached the variability observed between independent biological replicates, representing the accuracy that additional sequencing cannot improve upon. Using this criterion, loop-density estimation reached its biological floor at approximately 10 million read pairs, loop-size estimation at approximately 20 million, insulation scores and boundary detection at approximately 30 million, and compartment eigenvectors at 100-kilobase resolution at approximately 60 million read pairs. ConclusionsDifferent Hi-C-derived metrics require substantially different sequencing depths to achieve biologically meaningful accuracy. For all metrics, depth-induced variability fell below biological replicate variability well before full sequencing depth was reached. These thresholds provide practical guidance for experimental design and sequencing budget allocation, suggesting that, in many studies, increasing the number of biological replicates is likely to improve reproducibility more effectively than sequencing individual libraries to greater depth.

Alternative splicing (AS) can generate multiple RNA isoforms from a single gene and is thought to contribute to phenotypic divergence, including differences between the sexes. Studies in several organisms have documented sex differences in splicing, however these have been largely reliant on short-read RNA sequencing which requires complex algorithms to assemble full-length transcripts and may underestimate both isoform diversity and sex differences in splicing. We used long-read, single molecule RNA-Seq to build a more complete catalog of sex-biased splicing in Poecilia reticulata, a focal species for studies of sexual dimorphism. Pairing long-read sequencing with isoform-level analyses, we identified a sixfold higher proportion of sex-biased splicing genes (37%) compared with short and long-read event-level approaches (6%, 11%). AS was common (70% genes) but only 54% of isoforms produced unique open-reading frames (ORFs). We found that males exhibited greater isoform richness than females in both tail and gonad tissues but produced a smaller proportion of isoforms with unique ORFs, suggesting that much of the increased isoform variation is unlikely to expand proteomic complexity and may instead reflect stochasticity during splicing rather than intentional transcriptional products intended for translation. Despite widespread AS, we found only 2.3% of genes exhibited sex-biased isoform switching, and only 52% of these switches generated distinct sex-biased ORFs. Together, our long-read data suggest that although isoform diversity is more extensive than previously appreciated, most alternative isoforms are unlikely to generate novel proteins. Instead, a relatively small number of sex-biased isoforms may disproportionately contribute to proteomic divergence between the sexes.

Genomic signatures of selection can reveal loci underlying adaptation and disease resistance in livestock populations, but such analyses in water buffalo (Bubalus bubalis) have historically been constrained by the absence of a chromosome-level, species-native reference genome for SNP array data. We re-analyzed genotype data from 85 Nili-Ravi buffalo (Axiom Buffalo Genotyping 90K array, originally positioned using bovine (Bos taurus, UMD3.1) proxy coordinates, by performing a full coordinate liftover to the buffalo-native UOA_WB_1 assembly using an independently published SNP remapping resource. Following quality control (51,209 markers retained), haplotype phasing, and genome-wide integrated haplotype score (iHS) and Wrights Fst (case/control) selection scans, we evaluated 14 classical bovine-tuberculosis (bTB) candidate genes and identified six additional genes with putative immune function through an unbiased genome-wide screen. None of the 14 classical candidates (including SLC11A1, the Toll-like receptors, and IFNG) reached genome-wide significance in either scan. In contrast, six novel loci TNFSF18, IL2RB, TNFRSF19, IRF2, IL15, and CD28 showed significant iHS or Fst signals, four of which (TNFSF18, IL2RB, IL15, CD28) converge functionally on T-cell costimulation and cytokine receptor signaling (KEGG pathways map04660 and map04060, Bos taurus proxy annotation). Using extended haplotype homozygosity (EHH) decay, haplotype furcation structure, and per-marker haplotype counts as three independent lines of corroborating evidence, we classified these six genes into confidence tiers: TNFSF18 and IL2RB showed the strongest, most balanced support, while CD28 and IL15 signals were driven by very few haplotypes (3 and 5 of 30, respectively) and should be interpreted cautiously pending replication. These findings suggest that adaptive, cell-mediated immune signaling rather than the innate/macrophage-centred mechanisms emphasized by existing bTB candidate gene panels may be a more productive avenue for future selection studies in Nili-Ravi buffalo, while underscoring the value of buffalo-native coordinate systems for accurate genomic inference in this species.

Domesticated dogs present a unique case in nature where mutualism with and selective breeding by humans has led to profound changes in their environment, physiology, and behaviour compared to their wolf-like ancestors. Dog tameness, sociability, and trainability have likely evolved due to significant alterations to brain function. Exploring the effects of domestication on the dog brain will be facilitated by the characterisation of dog brain cell diversity, a task which is not yet complete. To fill this gap, we use single-nucleus RNA sequencing and survey cell types across the dog brain. We present transcriptomes from almost 60,000 cells sampled from the cerebellum, thalamus, and three regions of the cerebrum. Our analysis identified 24 major clusters representing 21 broad cell types, and 131 subclusters revealing regional variation. Comparisons with human and mouse datasets revealed a high level of conservation in neurons across mammalian brains, and greater divergence in glial cells, particularly oligodendrocytes. We demonstrate the utility of the dataset for interrogating specific gene expression patterns across the brain, including genes implicated in dog domestication, behavioural traits, and disease. We discover distinct differences in the expression of opioid receptors in the brains of dogs, compared to humans and mice, providing a potential explanation for dogs' higher tolerance and lower risk of severe adverse effects of opioid drugs. The data from this project are released via a web application for use by the wider community.

Perkinsus marinus is a protist that causes the wasting disease dermo in the Eastern oyster, Crassostrea virginica. The disease causes high mortality of both wild and cultured oysters, impacting ecosystem health and aquaculture. Despite decades of research, the genetic mechanisms of dermo resistance remain poorly understood. Traditional selective breeding based on phenotypes has yielded improvements in dermo resistance, but progress has been slow, likely due to the trait's complex genetic architecture. Understanding the genetic mechanisms underlying dermo resistance may facilitate advanced breeding to accelerate improvement. This study conducted genome-wide association studies (GWAS) of dermo resistance, leveraging a multi-generational dataset comprising 2,423 oysters phenotyped for survival following a dermo challenge and genotyped using a high-density 66K SNP array. A two-stage GWAS with more inclusive quality control identified 48 dermo-resistance markers, including many associated with genes for innate immune response and energy metabolism. Most dermo-resistance markers showed rare minor alleles occurring at higher frequencies in oysters that died after challenge, suggesting that these rare alleles are deleterious and associated with dermo susceptibility. The strongest association was with a polymorphism in the mucin-5AC-like gene, explaining 8.1% of phenotypic variation and suggesting that mucus production plays a crucial role in dermo resistance. The inclusion of these markers has improved genomic prediction accuracy, and their identification provides new insights into genomic variation and the architecture of dermo resistance, informing future strategies for genetic improvement.

PurposeWe introduce GO_SCPLOWRAC_SCPLOWNPA, standing for Graph Node-Phenotype Association, a method performing a GWAS-like analysis on a pangenome variation graph (PVG) built using a small number of individual genome sequences, without the need for additional population materials or kinship information for qualitative phenotypes. This method reduces the number of individuals required for association studies and prevents reference bias from variant calling in these types of analyses. BackgroundA PVG represents the multiple alignment of a set of complete genomes. It contains all variations, from single nucleotide polymorphisms (SNPs) to large structural variations (SVs), which are represented as nodes in the graph. By integrating phenotype information within nodes, we can assign a Phenotype Score (PS) to each node in the PVG and identify phenotype-related regions directly within it. These regions represent statistically significant shifts in PS distribution, highlighting their implication in the phenotype. Finally, GO_SCPLOWRAC_SCPLOWNPA provides their positions and scores for further analysis. ResultsThis method was tested using simulated data and two publicly available datasets: the Sub1A gene locus for Oryza sativa in a 13 individuals PVG, and the insertion responsible for the white-headed cattle with a PVG of 24 individuals. Source code of GO_SCPLOWRAC_SCPLOWNPA is available here https://forge.ird.fr/diade/graphgwas/granpa under GNU GPLv3. ConclusionGO_SCPLOWRAC_SCPLOWNPA was able to identify the expected area in two simulated datasets and the responsible loci for these two known traits using only a few dozen complete genomes in these PVGs. While currently limited to qualitative phenotypes, this method opens the way to more efficient ones relying on PVGs and few individuals.

Formalin-fixed, paraffin-embedded (FFPE) tissues remain an essential resource for molecular studies, yet formalin-induced cytosine deamination introduces characteristic C>T/G>A artifacts that compromise the accuracy of next-generation sequencing (NGS) analyses. Numerous computational methods and enzymatic DNA repair strategies have been proposed to reduce these artifacts, but no systematic comparison across tools and experimental conditions exists. Here, we evaluate the performance of seven computational approaches (SOBDetector, Ideafix, MicroSEC, FFPolish, DeepOmics FFPE/FFPE-PLUS, FFPErase) together with the NEBNext(R) FFPE DNA Repair Mix v2, a multi-enzyme repair system applied during DNA preparation. Using three independent datasets, one based on whole genome sequencing (CGCI-BL) and two on whole exome sequencing (TCGA-PC and SUT-LUAD, the latter containing enzymatically repaired samples), and matched fresh-frozen samples as the gold standard, we assess precision, sensitivity, and artifact reduction efficiency across all methods. We further examine the potential synergy between enzymatic repair and post-sequencing computational filtering. Our results provide practical guidelines for FFPE artifact correction and demonstrate that enzymatic treatment provides the best results, while among the computational methods, FFPErase offers the most robust reduction of cytosine deamination artifacts while maximizing the retention of true somatic variants. KEY MESSAGESO_LIFormalin fixation in FFPE samples introduces artifacts that can significantly affect the accuracy of NGS analyses. C_LIO_LIAmong the evaluated approaches, enzymatic repair using NEBNext(R) FFPE DNA Repair Mix v2 achieves the most effective reduction of sequencing artifacts. C_LIO_LIComputational methods vary in performance, with FFPErase showing the most robust balance between artifact removal and retention of true somatic variants. C_LIO_LICombining enzymatic repair with computational filtering did not lead to consistent improvements in performance across datasets. C_LI

Vibrio harveyi is a primary causative agent of vibriosis, leading to catastrophic economic losses in the blackspotted croaker (Protonibea diacanthus) aquaculture. However, the genetic architecture underlying its resistance remains poorly understood. In this study, we conducted the first integrated genome-wide association study (GWAS) and genetic differentiation analysis (F_ST) to investigate the genetic basis of V. harveyi resistance. A total of 450 juveniles were challenged, and 300 individuals (comprising 150 resistant and 150 susceptible) were selected for whole-genome resequencing. Genomic heritability (h^2) was estimated at 0.374+/-0.29 for survival time (ST) and 0.237+/-0.185 for survival status (SS), indicating moderate genetic control. Notably, an exceptionally high genetic correlation (r_g = 0.999) was observed between ST and SS, while resistance traits were genetically independent of growth performance (r_g < 0.03). Through the convergence of GWAS and selection sweep signals, a major-effect QTL was identified on chromosome 4. Candidate gene prioritization identified high-confidence targets involved in post-transcriptional regulation and mRNA stability, specifically elavl4 (harboring a top-tier exon variant), rorb, cbpc6, and epn4. Functional enrichment analysis further revealed that resistance is significantly associated with "rRNA processing", "mRNA surveillance pathway", and "nucleocytoplasmic transport", suggesting that efficient RNA metabolic control is a critical determinant of host survival. These findings provide novel insights into the non-canonical immune mechanisms of P. diacanthus and offer robust molecular markers for marker-assisted selection and genomic selection, facilitating the development of disease-resistant strains in the sciaenid industry.

Generating high-quality genome assemblies for small animals with large genomes is complex due to their small body size, DNA contamination, and repetitive elements. Ticks exemplify these complexities, while also being a global health threat to humans, domestic animals, and wildlife. Advances in long-read sequencing platforms now make it feasible to obtain large amounts of raw sequence data from individual specimens, but challenges remain. Key genome workflow challenges include error correction, assembly, transposable element annotation, and chromosome assignment and synteny. Here we examine three individual Dermacentor reticulatus ticks using deep Oxford Nanopore sequencing. Comparing and contrasting bioinformatic tools for raw read and assembly manipulation allows us to identify the parameters that provide a high-quality haploid genome assembly among 38 assemblies. We find Dorado error corrected raw read data from approximately two flow cells are needed, but limiting assembly coverage to 40x produces the highest quality assemblies. Then we examined the effects of optimal workflow parameters on downstream analyses of gene synteny and manual transposable element annotation of the three tick assemblies in comparison to an independent assembly of a fourth D. reticulatus individual from a different country. Gene synteny analysis allows chromosome assignment of scaffolds and transposable element identification was improved markedly with manual curation. Finally, we compared the genetic variation of D. reticulatus across two populations and found similar genetic diversity. Our study provides a clear workflow to obtain high-quality assemblies from Oxford Nanopore sequences and genetic characterization of a species with a large, complex, and repetitive genome.

Developments in Nanopore sequencing have enabled telomere to telomere genomic assembly as a routine technique in genomic research. Nanopore DNA sequencing for genomic assembly is typically performed on native DNA molecules, making it particularly sensitive to the quality of input DNA, with contaminating molecules limiting data yields and reducing read quality. As pangenome analysis gains interest, particularly in non-model plant species which are often rich in inhibitory secondary metabolites, the development of methods which can improve the quality and throughput of nanopore sequencing is essential. Here we describe a method for isolation of total DNA from the leaf tissues of diverse Viridiplantae species. The initial lysis buffer consists of a modified CTAB buffer, incorporating dimethyl sulfoxide for the reduction of viscosity, which can be problematic in many plant DNA preparations. An organic extraction with 2-butoxyethanol is utilized to further extract phenolic compounds which may be sufficiently hydrophilic to evade chloroform extraction, while reducing aqueous phase volume. Further cleanup via cesium chloride (CsCl) ultracentrifugation is performed to minimize the carryover of residual contaminating macromolecules. Samples prepared using this method are of consistent high quality, even when extracted from challenging late season leaf tissue or secondary metabolite rich species. Sequencing results from samples prepared by this method outperform those obtained from typical modified CTAB DNA isolation techniques in both quantity and quality. We tested sequencing performance from Vitis DNA isolated using a modified CTAB method and Vitis DNA isolated using the CsCl ultracentrifugation-based method described here. DNA isolated via the method described here produced 83% more >Q10 sequence data (52.61 Gb vs. 28.8 Gb), resulted in a 60% greater read N50 despite more handling steps (32.78kb vs. 20.45kb), and resulted in a higher modal read quality (Q27 vs. Q24). The consistency of this method across diverse plant taxa suggests its use as a general method for DNA isolation prior to Nanopore sequencing and genomic assembly for diverse plant taxa.

Information about segregating haplotypes and structural variation (SV) can be extremely rich for a variety of applications in population genomics but remains largely inaccessible for many non-model species. Of the available methods, linked-read sequencing is especially promising for its low cost and scalability, but its adoption remains limited. One existing linked-read method is Haplotagging, which barcodes sequencing reads to reconstruct long molecules that encode haplotype information, with the potential to generate phased whole-genome data and detect structural variants. In this study, we present BLink-seq, a novel Haplotagging method that is compatible with standard short-read next-generation sequencing platforms, is locally reproducible with low-cost reagents, and is scalable for high-throughput sample processing. We optimized library preparation parameters, explored their relationship to linked-read library metrics, and validated phasing performance and structural variant detection in two evolutionary extremes: an experimental Drosophila melanogaster cross of inbred lines carrying known inversions, and four Atlantic silverside (Menidia menidia) parent-offspring trios sourced from highly outbred, wild-caught populations. We then applied our protocol to a cohort of 376 silversides to demonstrate its scalability and potential for SV detection and genotype imputation. Using BLink-seq, we generated chromosome-scale phased blocks and identified known inversions in both validation datasets. We discovered previously uncharacterized structural complexity within a known adaptive inversion on silverside chromosome 11, demonstrating that linked-read data can refine our understanding of SV architecture beyond what short reads alone can resolve. Finally, we provide a user guide for researchers interested in using BLink-seq.

Transposable elements (TEs) are major contributors to genomic and regulatory variation and can influence the expression of nearby genes in response to environmental stress. The invasive fruit fly Drosophila suzukii, whose genome is composed of nearly 50% TE-derived sequences, provides an excellent model to investigate the regulatory impact of TEs on stress responses. Although previous studies found no global association between TEs and oxidative stress transcriptomic response in this species, the effects of individual TE insertions remain largely unexplored. Here, we investigated the role of two polymorphic intronic TE insertions, Mrp4-TE and inaE-TE, located within genes implicated in the oxidative stress response in D. melanogaster. Using wild-type strains of D. suzukii, we assessed the effect of these insertions on gene expression following oxidative stress induced by paraquat exposure. We found that their corresponding nearby genes Mrp4 and inaE were upregulated after paraquat treatment and that this response was significantly stronger in flies carrying the corresponding TE insertions. Allele-specific expression analyses further showed that the alleles containing the TE insertions exhibited a tendency towards higher expression levels than alleles lacking the insertions, both under control and oxidative stress conditions, supporting a cis-regulatory effect. In addition, Mrp4-TE was associated with increased sensitivity to oxidative stress. Together, our results provide the first evidence that TE insertions can modulate oxidative stress-responsive gene expression in D. suzukii. These findings highlight the importance of investigating individual TE insertions to understand the genetic and regulatory mechanism underlying stress responses, adaptation, and invasion success in this species.

BackgroundPlasmodium falciparum field isolates exhibit genomic variation, including copy number variation and sequence divergence. In contrast, the P. falciparum 3D7 reference genome (Pf3D7) was derived from a long-term laboratory-adapted strain and does not fully reflect the genomic variation among field isolates. The extent to which the reference genome influences RNA-seq mapping and expression inference in natural infections remains unclear. ResultsWe generated both a reference genome and single cell RNA sequencing (scRNAseq) data from a P. falciparum-infected carrier in Mali. This new ML52 assembly was annotated using Companion with Pf3D7 as the reference. scRNAseq reads from the natural infection isolate were aligned to both the Pf3D7 genome and the isolate-specific ML52 genome, followed by locus-level alignment inspection. For most conserved genes, expression inference was concordant for both references, while genes showing reference-genome-dependent differences were investigated further. Some discrepancies were attributed to mapping artefacts or to reads aligning to unplaced genomic contigs that reflected divergent haplotypes from the co-infecting strains in the naturally infected carrier. While most multigene family loci showed concordant gene expression across both references, var genes exhibited considerable mis-mapping against 3D7 var loci as well as 2/3 of var reads not mapping at all to 3D7. ConclusionscRNAseq expression inference in P. falciparum is robust for conserved genes and most multigene families when comparing to a matched vs unmatched reference genome, but the extremely polymorphic var genes require a matched assembly in order to evaluate expression. These findings highlight the importance of the reference genome for var gene studies and should be considered when interpreting transcriptomic analyses in other organisms possessing highly variable antigenic loci.

Changes in gene regulation are central to developmental evolution, yet how transcription-initiation architecture contributes to developmental expression divergence remains poorly understood. Here, we integrated chromosome-level genome assemblies, developmental RNA-seq, and STRIPE-seq-based transcription start site (TSS) profiling to examine regulatory divergence between two lineages of the Daphnia pulex complex, KAP4 and CON21, across embryonic, juvenile, and adult stages. The two lineages shared a broadly conserved developmental transcriptional program, but KAP4 consistently expressed more protein-coding genes and long non-coding RNAs than CON21. Genes with stage-specific expression were weakly expressed and showed elevated nucleotide diversity and sequence divergence relative to persistently expressed genes, consistent with relaxed purifying selection. Comparative transcriptomic analyses revealed strong stage-dependent expression divergence between the two lineages: the greatest similarity occurred during late embryonic to early juvenile development rather than mid-embryogenesis, providing limited support for a canonical developmental hourglass pattern. STRIPE-seq uncovered a conserved two-peak TSS organization upstream of annotated translation-start sites, but the relative use of distal and proximal initiation regions differed between lineages. Motif analyses further indicated that these initiation regions are associated with distinct cis-regulatory sequence environments. Promoter shape was closely linked to transcriptional output, with broad promoters showing the highest expression, peaked promoters the lowest, and intermediate promoters occupying an intermediate state. Together, these findings suggest that developmental regulatory divergence in the D. pulex complex is shaped by fine-scale remodeling of TSS usage and promoter architecture.

Daphnia magna is a widely used model organism in ecological genomics, ecotoxicology, and evolutionary biology. While a few genome assemblies of this species of freshwater crustacean are available, disagreements in their chromosomal arrangements point toward scaffolding problems. We present the most contiguous chromosome-level genome assembly of D. magna, the first based on PacBio HiFi sequencing technology. The assembly spans 184.38 Mb and has a scaffold N50 of 12.4 Mb. Eight of ten chromosomal scaffolds consist of mainly two contigs, representing one chromosome arm each. Eleven of 20 telomeric regions are fully resolved. Using a genomic map and comparative genomics, we were able to not only resolve the problems of previous assemblies, but also to demonstrate that some of the scaffolding errors followed a systematic pattern, most likely resulting from mis-joins during Hi-C scaffolding. Additionally, we provide expression profiles for annotated genes derived from different D. magna RNA-seq datasets, enabling rapid assessment of predicted gene expression and identification of potential pseudogenes. The new genomic and transcriptomic resource enables comparative genomic studies on genome architecture, structural variation, and gene family evolution in this important model organism.