Comparison of single-cell sequencing technologies for allele-specific expression analysis in rabbit spermatids.

Combining allele-specific expression (ASE) analysis with single-cell RNA-seq can elucidate how genomic variation affects RNA expression at the single-cell level. We explore how experimental and computational choices impact the power of ASE-based methods and develop a suite of single-cell ASE computational tools. With single-nucleus RNA-Seq, we extract more ASE information from reads in intronic than exonic regions. We show how read length can increase power and that hybrid selection improves power to detect ASE in targeted genes. We apply our methods to a Parkinson's disease cohort and show that ASE analysis has more power than eQTL analysis.

Structural variants (SVs) are a major source of genetic diversity, yet how they impact cell types in complex brain diseases remains largely unexplored, partially due to limitations of short-read sequencing. Here, we addressed this fundamental question in Parkinson's disease (PD). generating long-read whole-genome sequencing (WGS) data for 100 post-mortem brain samples from a PD cohort, constructing a high-confidence catalog of 74,552 SVs. To resolve their functional impact, we integrated single-nucleus RNA-sequencing data from two brain regions from the same samples and focused functional analyses on SVs proximal to genes previously nominated as cis-regulated, potential causal targets of PD-associated GWAS loci. Using expression quantitative trait locus and allele-specific expression analyses, we uncovered SVs significantly associated with expression in specific cell types as well as effects shared across cell types. This study demonstrates the power of uniting long-read WGS with transcriptomics to uncover SVs underlying complex disease architecture with cell type resolution.

Allele-specific expression (ASE) of somatic mutations can be caused by cis-activation of the mutant allele or silencing of the wild-type allele and has been investigated by examining the enrichment of mutant allele in RNA relative to DNA. Here we show that this mutation-based approach can be confounded by gene expression differences in tumor and normal cells that coexist in most bulk tumor samples. We model mutant allele expression by incorporating tumor/normal expression difference, mutant allele dosage, tumor purity, and nonsense-mediated decay (NMD) efficiency, projecting that such enrichments can occur without ASE. This confounding effect is exacerbated with low tumor purity and is dependent on mutant allele dosage for NMD-triggering mutations. The model predictions are validated by a pancancer bulk tumor analysis with somatic insertions/deletions (indels) from 9101 The Cancer Genome Atlas (TCGA) samples. A single-cell analysis in five cutaneous squamous cell carcinomas demonstrates the robustness of this model to intratumor heterogeneity. As a byproduct of this confounding effect, we evaluate whether the inverse relationship between mutant allele enrichment in RNA and tumor purity could be leveraged to complement DNA-based somatic mutation detection in low purity samples. Indeed, our de novo somatic indel calling from TCGA RNA-seq increases the TCGA driver indel repertoire by ∼14%, especially in samples with purity less than 0.4, including actionable EGFR indels in lung adenocarcinoma and FLT3 in acute myeloid leukemia. Our study not only reveals confounders in somatic mutant ASE analysis but also demonstrates their utility in RNA-based mutation calling.

Single-cell allele-specific expression (ASE) provides valuable insights into gene regulatory mechanisms. However, its utility is limited by the lack of dedicated computational tools. We present DAESC + , a dual-module end-to-end software package for the processing and analysis of single-cell ASE. The preprocessing module, DAESC-P, is a user-friendly bioinformatics pipeline to obtain ASE counts from multiplexed scRNA-seq data. The analysis module, DAESC-GPU, is a scalable tool for differential ASE analysis powered by graphics processing units (GPUs). We demonstrated that DAESC-P is more accurate than the existing SALSA pipeline. DAESC-GPU is dozens of times faster than our previous method (DAESC) and scalable to over a million cells. Applying DAESC + to a subset of the OneK1K cohort, we identified 15 genes exhibiting differential regulatory patterns between naïve and central memory CD4 + T cells, and 2 genes between naïve and memory B cells.

Closely related species often exhibit distinct morphologies that can contribute to species-specific adaptations and reproductive isolation. One example is Lepidopteran caterpillar appendages, such as the “caudal horn” of Bombycoidea moths, which have evolved substantial morphological diversity among species in this group. Using interspecific crosses, we identify the genetic basis of the caudal horn size difference between Bombyx mori and its closest relative Bombyx mandarina. The three largest of eight QTL account for one third the mean horn length difference between the species. The largest of these, on chromosome 4, encompasses a conserved Wnt family gene cluster, key upstream regulators that are well-known for their roles in morphological diversification in animals. Using allele-specific expression analysis and CRISPR/Cas9 knockouts, we show that tissue-specific cis-regulatory changes to Wnt1 and Wnt6 contribute to the species difference in caudal horn size. This kind of modularity enables highly pleiotropic genes, including key upstream growth regulators, to contribute to the evolution of morphological traits without causing widespread deleterious effects.

Closely related species often exhibit distinct morphologies that can contribute to species-specific adaptations and reproductive isolation. One example is Lepidopteran caterpillar appendages, such as the "caudal horn" of Bombycoidea moths, which have evolved substantial morphological diversity among species in this group. Using interspecific crosses, we identify the genetic basis of the caudal horn size difference between Bombyx mori and its closest relative Bombyx mandarina. The three largest of eight QTL account for one third the mean horn length difference between the species. The largest of these, on chromosome 4, encompasses a conserved Wnt family gene cluster, key upstream regulators that are well-known for their roles in morphological diversification in animals. Using allele-specific expression analysis and CRISPR/Cas9 knockouts, we show that tissue-specific cis-regulatory changes to Wnt1 and Wnt6 contribute to the species difference in caudal horn size. This kind of modularity enables highly pleiotropic genes, including key upstream growth regulators, to contribute to the evolution of morphological traits without causing widespread deleterious effects.

Maize breeding has greatly improved yield through single-cross hybrids, but the underlying gene regulatory changes remain unclear. This study analysed transcriptomes of landmark maize hybrids and their parents across developmental stages and planting densities. Compared with their parents, hybrids showed a trade-off in the expression of photosynthesis-related genes and stress-responsive genes. This expression rebalancing suggested a strategy that prioritises photosynthetic efficiency and growth vigour over stress defence mechanisms. Allele-specific expression (ASE) analysis identified 19.9% of heterozygous loci exhibiting significant allelic imbalance, with notable enrichment in photosynthesis and stress response pathways. Importantly, the suppressed expression of deleterious alleles in hybrids not only correlated with phenotypic performance but also exhibited progressive enhancement through decades of breeding, indicating this regulatory mechanism has been selected during improvement. Consistent with this finding, breeding selection preferentially acted on cis-regulatory regions, with stronger correlation between cis-regulatory complementation of deleterious variants and hybrid release year compared to coding regions. Transcriptomic plasticity across environments was evaluated using the concept of entropy. Results showed that hybrids had lower transcriptomic entropy than their parental lines, and this reduction in entropy was significantly associated with heterosis. These findings highlight the critical role of allelic expression optimization in maize hybrid breeding and provide insights into the transcriptomic dynamics that underlie heterosis.

sPaliurus hemsleyanus Rehd., a deciduous shrub or small tree endemic to China, is valued for its hardiness, economic and ornamental importance, and widespread used as a rootstock for Chinese jujube (Ziziphus jujuba Mill.). Despite its ecological and economic significance, genomic resources for this genus remain limited. Here, we assemble a haplotype-resolved, telomere-to-telomere (T2T), gap-free genome of P. hemsleyanus (2n = 24), representing the genus Paliurus. The genome comprises two haplotypes of 306.65 Mb and 306.21 Mb, with contig N50 values of 24.91 Mb and 24.94 Mb, respectively. Each haplotype encodes over 29,000 protein-coding genes, with all centromeres and telomeres fully predicted. Allele-specific expression analysis reveals a positive correlation between gene expression divergence and sequence variation, indicating functional differentiation between haplotypes. Comparative genomic analysis shows relatively stable genome evolution within Rhamnaceae, with all examined extant species containing 12 chromosomes. Disease resistance (NLR) genes exhibit a root-preferred expression pattern, and allelic copies expressed more strongly than non-allelic ones between haplotypes. Ascorbic acid (AsA) metabolic genes show leaf-preferred expression; and moreover MDHAR genes exhibit Rhamnaceae-specific tandem duplications, suggesting lineage-specific adaptive evolution. This high-quality genome provides an essential resources for evolutionary studies, functional genomics, breeding, and the conservation of Rhamnaceae species.

Background:Alternative mRNA splicing is a key mechanism for generating isoform diversity in eukaryotic cells. However, the extent of the splicing changes that occur during complex regulatory processes like neurodevelopment are still incompletely characterized.Results:We performed nanopore-based long-read RNA sequencing on differentiating human stem cell-derived retinal organoids to identify temporal patterns of isoform usage across developmental stages. We found that retinal organoids undergo dynamic shifts in isoform usage throughout differentiation, which were not necessarily accompanied with changes in overall gene expression, as was the case for many genes involved in the regulation of mRNA splicing itself. Further analysis of human stem cell-derived retinal ganglion cells uncovered neuron-specific splicing signatures. Additionally, allele-specific expression analysis revealed extensive allelic imbalance in induced pluripotent stem cell-derived organoid cultures.Conclusions:By combining direct long-read RNA sequencing with human stem cell retinal models we could explore isoform-level changes in differentiating human cells at unprecedented detail. These results uncovered dynamic shifts in transcript usage during retinal differentiation, adding to our knowledge base of post-transcriptional RNA processing in the developing central nervous system and human in vitro culture systems.

Accurate quantification of lowly expressed SBDS by integrating pacbio iso-seq long-read and illumina short-read sequencing

Integrated physiological, transcriptomic and metabolomic analysis revealed heterosis for cadmium tolerance in maize.

Allele-specific expression (ASE) analyses from RNA-Seq data provide quantitative insights into genomic imprinting and the genetic variants that affect transcription. Robust ASE analysis requires the integration of multiple computational steps, including read alignment, read counting, data visualization, and statistical testing—this complexity creates challenges for reproducibility, scalability, and ease of use. Here, we present ASE Toolkit (ASET), an end-to-end pipeline that streamlines SNP-level ASE data generation, visualization, and testing for parent-of-origin (PofO) effect. ASET includes a modular pipeline built with Nextflow for ASE quantification from short-read transcriptome sequencing reads, an R library for data visualization, and a Julia script for PofO testing. ASET performs comprehensive read quality control, SNP-tolerant alignment to reference genomes, read counting with allele and strand resolution, annotation with genes and exons, and estimation of contamination. In sum, ASET provides a complete and easy-to-use solution for molecular and biomedical scientists to identify and interpret patterns of ASE from RNA-Seq data.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12859-025-06282-2.

Triploid breeding is a promising avenue for generating seedless varieties with enhanced vigor, yet the underlying molecular mechanisms, particularly the relative contributions of hybridity, ploidy level, and parent-of-origin effects (POE), remain largely elusive in perennial fruit crops. This study focuses on loquat (Eriobotrya japonica), a highly heterozygous woody perennial, to explore the molecular mechanism of triploid seedling vigor heterosis. RNA-seq across a series of reciprocal diploid (2x), triploid (3x) and tetraploid (4x) hybrids with clear genetic background revealed POE as the predominant driver of triploid heterosis at the transcriptomic level. Specifically, 784 POE-responsive differentially expressed genes (DEGs) were identified between paternal-excess [3x(p)] and maternal-excess [3x(m)] triploids, exceeding the effects of ploidy (218–652 DEGs) and hybridity (8–90 DEGs). For an in-depth investigation, reciprocal crosses between L2 and L4 were further selected for an integrated transcriptome, allele-specific expression (ASE), and allele-specific methylation (ASM) analysis. Our findings demonstrate that POE orchestrates multilayered regulation, including (i) coordinated upregulation of vigor-related pathways (i.e., photosynthesis, starch metabolism, plant circadian rhythm) in 3x(p); (ii) a dual ASE pattern with maternal bias in gene quantity but paternal enhancement in levels, including five paternally expressed imprinted genes (PEGs); (iii) non-classical epigenetic regulation where paternal gene body hypermethylation (mCG) paradoxically enhances transcription, especially in circadian clock genes. Finally, qRT-PCR-based diurnal expression across all crosses validated that POE-dependent reprogramming of key circadian oscillator genes (EjCCA1, EjLHY, EjGI, EjTOC1), suggesting optimized metabolic efficiency through circadian clock modulation might contribute to enhanced vigor in 3x(p) hybrids. This study provides fundamental insights into the dosage-sensitive gene networks and epigenetic regulation underlying POE-driven heterosis in woody perennials, advancing polyploid heterosis theory and offering novel targets for genetic improvement.

Immune molecules such as human leukocyte antigens (HLAs) or killer Ig-like receptors are encoded in the most genetically diverse loci of the human genome. Many of these immune genes exhibit remarkable allelic diversity across populations. Here, we present a novel computational methodology for allele-specific expression quantification of immune genes in single-cell RNA sequencing (scRNA-seq) data. Our quantification method features a novel R/Bioconductor data structure that can handle expression data across multiple immunogenetic annotation layers and enables interactive exploration of immune gene expression. We validate our methodology on multiple scRNA-seq datasets to demonstrate its performance across different experimental setups. We illustrate how these new tools allow us to study loss of HLA expression in tumor cells and to discover differential HLA allele expression in specific immune cell subtypes. By capturing such allele-specific expression patterns and their variation, our methodology offers novel insights into human immunogenomic diversity.

Closely related species often exhibit distinct morphologies that can contribute to species-specific adaptations and reproductive isolation. One example are Lepidopteran caterpillar appendages, such as the “caudal horn” of Bombycoidea moths, which have evolved substantial morphological diversity among species in this group. Using interspecific crosses, we identify the genetic basis of the caudal horn size difference between Bombyx mori and its closest relative B. mandarina. The three largest of eight QTL account for one third the mean horn length difference between the species. The largest of these, on chromosome 4, encompasses a conserved Wnt-family gene cluster, key upstream regulators that are well-known for their roles in morphological diversification in animals. Using allele-specific expression analysis and CRISPR/Cas9 knockouts, we show that tissue-specific cis-regulatory changes to Wnt1 and Wnt6 contribute to the species difference in caudal horn size. This kind of modularity enables highly pleiotropic genes, including key upstream growth regulators, to contribute to the evolution of morphological traits without causing widespread deleterious effects.

Identification of Novel Kidney-Specific Human Imprinted Genes Through Allele-Specific Expression Analysis

Heterosis has been crucial for global food security, particularly in hybrid rice (Oryza sativa L.) development. While indica-japonica intersubspecific hybrids offer a 20% to 30% yield increase over indica-indica hybrids, the mechanisms underlying intersubspecific heterosis remain poorly explored. Here, we sequenced and phenotyped three pairwise crosses and their derived populations from representative japonica and indica varieties. Intersubspecific hybrids exhibited stronger heterosis and superior biomass than intrasubspecific hybrids. Transcriptomic analysis demonstrated that brassinosteroid signaling and flowering-promoting genes are upregulated in intrasubspecific hybrids to accelerate growth, while intersubspecific hybrids display enhanced tillering capacity and yield potential through elevated transcriptional activity and gene expression related to nitrogen use efficiency. Genome-wide allele-specific expression analysis highlighted the regulatory impact of parental genomic divergence on hybrid gene expression, particularly through promoter variations affecting genes involved in flowering, tillering, pollen fertility, and stress response. QTL mapping revealed a greater number of loci associated with heterosis in intersubspecific hybrids than in intrasubspecific hybrids, particularly for spikelets per panicle and plant height, where the Nipponbare and indica alleles function as advantageous alleles across distinct QTLs; their synergistic interactions collectively drive the heterosis between subspecies. Our study reveals that parental genetic diversity combined with dominant expression patterns collectively drives heterosis, providing valuable insights for optimizing intersubspecific hybrid rice breeding to enhance yield and agricultural sustainability.

Single-cell allele-specific expression (ASE) provides valuable insights into gene regulatory mechanisms. However, its utility is limited by the lack of dedicated computational tools. We present DAESC+, an end-to-end software package for the processing and analysis of single-cell ASE. The preprocessing module, DAESC-P, is a user-friendly bioinformatics pipeline to obtain ASE counts from multiplexed scRNA-seq data. The analysis module, DAESC-GPU, is a scalable tool for differential ASE analysis powered by graphics processing units (GPUs). We demonstrated that DAESC-P is more accurate than the existing SALSA pipeline. DAESC-GPU is dozens of times faster than our previous method (DAESC) and scalable to over a million cells. Applying DAESC+ to a subset of the OneK1K cohort, we identified 15 genes exhibiting differential regulatory patterns between naïve and central memory CD4+ T cells, and 2 genes between naïve and memory B cells.

Interspecific hybridization is a common and effective strategy for producing disease resilient citrus cultivars, including those with tolerance to Huanglongbing (HLB) disease. Several HLB-tolerant cultivars have been developed through hybridization of mandarins (Citrus reticulata) with their wild relative Poncirus trifoliata. One such cultivar, ‘US-897’, exhibits robust tolerance to the bacteria causing HLB disease, Candidatus Liberibacter asiaticus (CLas). To explore the genetic architecture of the early transcriptional response to Candidatus Liberibacter asiaticus (CLas) infection in ‘US-897’, we performed transcriptomic analysis of the hybrid and its parents, ‘Cleopatra’ (C. reticulata) and ‘Flying Dragon’ (P. trifoliata). A haplotype-resolved genome for ‘US-897’ was generated using PacBio HiFi sequencing reads to support quantification of the expression of both the Citrus and Poncirus alleles. By profiling gene expression in this parent-offspring trio, we were able to determine the mode of inheritance for genes differentially expressed between parents (‘Cleopatra’ and ‘Flying Dragon’) and their interspecific hybrid (‘US-897’), with the majority genes exhibiting non-additive patterns of gene expression inheritance. Additionally, analysis of allele-specific expression in the hybrid ‘US-897’ revealed the contribution of cis- versus trans-acting regulatory variants on genes with additive and non-additive modes of inheritance. A strong correlation between differential expression between parents and allele-specific expression in ‘US-897’ suggests that cis-regulatory variation is a significant source of expression divergence between species. Finally, genes responsive to infection with CLas were identified to explore how gene regulation associated with tolerance to HLB was rewired between Citrus and its relative Poncirus.