Allele-specific Gene Expression Research Articles

Natural variations of heterosis-related allele-specific expression genes in promoter regions lead to allele-specific expression in maize

BackgroundHeterosis has successfully enhanced maize productivity and quality. Although significant progress has been made in delineating the genetic basis of heterosis, the molecular mechanisms underlying its genetic components remain less explored. Allele-specific expression (ASE), the imbalanced expression between two parental alleles in hybrids, is increasingly being recognized as a factor contributing to heterosis. ASE is a complex process regulated by both epigenetic and genetic variations in response to developmental and environmental conditions.ResultsIn this study, we explored the differential characteristics of ASE by analyzing the transcriptome data of two maize hybrids and their parents under four light conditions. On the basis of allele expression patterns in different hybrids under various conditions, ASE genes were divided into three categories: bias-consistent genes involved in basal metabolic processes in a functionally complementary manner, bias-reversal genes adapting to the light environment, and bias-specific genes maintaining cell homeostasis. We observed that 758 ASE genes (ASEGs) were significantly overlapped with heterosis quantitative trait loci (QTLs), and high-frequency variations in the promoter regions of heterosis-related ASEGs were identified between parents. In addition, 10 heterosis-related ASEGs participating in yield heterosis were selected during domestication.ConclusionsThe comprehensive analysis of ASEGs offers a distinctive perspective on how light quality influences gene expression patterns and gene-environment interactions, with implications for the identification of heterosis-related ASEGs to enhance maize yield.

A phased genome of the highly heterozygous 'Texas' almond uncovers patterns of allele-specific expression linked to heterozygous structural variants

Abstract The vast majority of traditional almond varieties are self-incompatible and the level of variability of the species is very high, resulting in a highly heterozygosity genome. Therefore, information on the different haplotypes is particularly relevant to understand the genetic basis of trait variability in this species. However, although reference genomes for several almond varieties exist, none of them is phased and has genome information at the haplotype level. Here we present a phased assembly of genome of the almond cv. Texas. This new assembly has 13 % more assembled sequence than the previous version of the Texas genome and has an increased contiguity, in particular in repetitive regions such as the centromeres. Our analysis shows that the “Texas” genome has a high degree of heterozygosity, both at SNPs, short indels, and structural variants (SV) level. Many of the SVs are the result of heterozygous Transposable Element (TE) insertions, and in many cases they also contain genic sequences. In addition to the direct consequences of this genic variability on the presence/absence of genes, our results show that variants located close to genes are often associated with allele-specific gene expression (ASE), which highlights the importance of heterozygous SVs in almond.

The OsWRKY72-OsAAT30/OsGSTU26 module mediates reactive oxygen species scavenging to drive heterosis for salt tolerance in hybrid rice.

Hybrid rice (Oryza sativa) generally outperforms its inbred parents in yield and stress tolerance, a phenomenon termed heterosis, but the underlying mechanism is not completely understood. Here, we combined transcriptome, proteome, physiological, and heterosis analyses to examine the salt response of super hybrid rice Chaoyou1000 (CY1000). In addition to surpassing the mean values for its two parents (mid-parent heterosis), CY1000 exhibited a higher reactive oxygen species scavenging ability than both its parents (over-parent heterosis or heterobeltiosis). Nonadditive expression and allele-specific gene expression assays showed that the glutathione S-transferase gene OsGSTU26 and the amino acid transporter gene OsAAT30 may have major roles in heterosis for salt tolerance, acting in an overdominant fashion in CY1000. Furthermore, we identified OsWRKY72 as a common transcription factor that binds and regulates OsGSTU26 and OsAAT30. The salt-sensitive phenotypes were associated with the OsWRKY72paternal genotype or the OsAAT30maternal genotype in core rice germplasm varieties. OsWRKY72paternal specifically repressed the expression of OsGSTU26 under salt stress, leading to salinity sensitivity, while OsWRKY72maternal specifically repressed OsAAT30, resulting in salinity tolerance. These results suggest that the OsWRKY72-OsAAT30/OsGSTU26 module may play an important role in heterosis for salt tolerance in an overdominant fashion in CY1000 hybrid rice, providing valuable clues to elucidate the mechanism of heterosis for salinity tolerance in hybrid rice.

Machine learning on alignment features for parent-of-origin classification of simulated hybrid RNA-seq

BackgroundParent-of-origin allele-specific gene expression (ASE) can be detected in interspecies hybrids by virtue of RNA sequence variants between the parental haplotypes. ASE is detectable by differential expression analysis (DEA) applied to the counts of RNA-seq read pairs aligned to parental references, but aligners do not always choose the correct parental reference.ResultsWe used public data for species that are known to hybridize. We measured our ability to assign RNA-seq read pairs to their proper transcriptome or genome references. We tested software packages that assign each read pair to a reference position and found that they often favored the incorrect species reference. To address this problem, we introduce a post process that extracts alignment features and trains a random forest classifier to choose the better alignment. On each simulated hybrid dataset tested, our machine-learning post-processor achieved higher accuracy than the aligner by itself at choosing the correct parent-of-origin per RNA-seq read pair.ConclusionsFor the parent-of-origin classification of RNA-seq, machine learning can improve the accuracy of alignment-based methods. This approach could be useful for enhancing ASE detection in interspecies hybrids, though RNA-seq from real hybrids may present challenges not captured by our simulations. We believe this is the first application of machine learning to this problem domain.

A haplotype-resolved genome provides insight into allele-specific expression in wild walnut (Juglans regia L.)

Wild germplasm resources are crucial for gene mining and molecular breeding because of their special trait performance. Haplotype-resolved genome is an ideal solution for fully understanding the biology of subgenomes in highly heterozygous species. Here, we surveyed the genome of a wild walnut tree from Gongliu County, Xinjiang, China, and generated a haplotype-resolved reference genome of 562.99 Mb (contig N50 = 34.10 Mb) for one haplotype (hap1) and 561.07 Mb (contig N50 = 33.91 Mb) for another haplotype (hap2) using PacBio high-fidelity (HiFi) reads and Hi-C technology. Approximately 527.20 Mb (93.64%) of hap1 and 526.40 Mb (93.82%) of hap2 were assigned to 16 pseudochromosomes. A total of 41039 and 39744 protein-coding gene models were predicted for hap1 and hap2, respectively. Moreover, 123 structural variations (SVs) were identified between the two haplotype genomes. Allele-specific expression genes (ASEGs) that respond to cold stress were ultimately identified. These datasets can be used to study subgenome evolution, for functional elite gene mining and to discover the transcriptional basis of specific traits related to environmental adaptation in wild walnut.

AStruct: detection of allele-specific RNA secondary structure in structuromic probing data

BackgroundUncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking.ResultsHere, we develop a computational tool called ‘AStruct’ that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease.ConclusionsAStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct.

High-quality genome assembly enables prediction of allele-specific gene expression in hybrid poplar.

Poplar (Populus) is a well-established model system for tree genomics and molecular breeding, and hybrid poplar is widely used in forest plantations. However, distinguishing its diploid homologous chromosomes is difficult, complicating advanced functional studies on specific alleles. In this study, we applied a trio-binning design and PacBio high-fidelity long-read sequencing to obtain haplotype-phased telomere-to-telomere genome assemblies for the 2 parents of the well-studied F1 hybrid "84K" (Populus alba × Populus tremula var. glandulosa). Almost all chromosomes, including the telomeres and centromeres, were completely assembled for each haplotype subgenome apart from 2 small gaps on one chromosome. By incorporating information from these haplotype assemblies and extensive RNA-seq data, we analyzed gene expression patterns between the 2 subgenomes and alleles. Transcription bias at the subgenome level was not uncovered, but extensive-expression differences were detected between alleles. We developed machine-learning (ML) models to predict allele-specific expression (ASE) with high accuracy and identified underlying genome features most highly influencing ASE. One of our models with 15 predictor variables achieved 77% accuracy on the training set and 74% accuracy on the testing set. ML models identified gene body CHG methylation, sequence divergence, and transposon occupancy both upstream and downstream of alleles as important factors for ASE. Our haplotype-phased genome assemblies and ML strategy highlight an avenue for functional studies in Populus and provide additional tools for studying ASE and heterosis in hybrids.

Positive Selection Drives cis-regulatory Evolution Across the Threespine Stickleback Y Chromosome.

Allele-specific gene expression evolves rapidly on heteromorphic sex chromosomes. Over time, the accumulation of mutations on the Y chromosome leads to widespread loss of gametolog expression, relative to the X chromosome. It remains unclear if expression evolution on degrading Y chromosomes is primarily driven by mutations that accumulate through processes of selective interference, or if positive selection can also favor the down-regulation of coding regions on the Y chromosome that contain deleterious mutations. Identifying the relative rates of cis-regulatory sequence evolution across Y chromosomes has been challenging due to the limited number of reference assemblies. The threespine stickleback (Gasterosteus aculeatus) Y chromosome is an excellent model to identify how regulatory mutations accumulate on Y chromosomes due to its intermediate state of divergence from the X chromosome. A large number of Y-linked gametologs still exist across 3 differently aged evolutionary strata to test these hypotheses. We found that putative enhancer regions on the Y chromosome exhibited elevated substitution rates and decreased polymorphism when compared to nonfunctional sites, like intergenic regions and synonymous sites. This suggests that many cis-regulatory regions are under positive selection on the Y chromosome. This divergence was correlated with X-biased gametolog expression, indicating the loss of expression from the Y chromosome may be favored by selection. Our findings provide evidence that Y-linked cis-regulatory regions exhibit signs of positive selection quickly after the suppression of recombination and allow comparisons with recent theoretical models that suggest the rapid divergence of regulatory regions may be favored to mask deleterious mutations on the Y chromosome.

Allele-specific DNA methylation and gene expression during shoot organogenesis in tissue culture of hybrid poplar.

Plant tissue regeneration is critical for genetic transformation and genome editing techniques. During the regeneration process, changes in epigenetic modifications accompany the cell fate transition. However, how allele-specific DNA methylation in two haplotypes contributes to the transcriptional dynamics during regeneration remains elusive. Here we applied an inter-species hybrid poplar (Populus alba × P. glandulosa cv. 84K) as a system to characterize the DNA methylation landscape during de novo shoot organogenesis at allele level. Both direct and indirect shoot organogenesis showed a reduction in genome-wide DNA methylation. At gene level, non-expressed genes were hypermethylated in comparison with expressed genes. Among the genes exhibiting significant correlations between levels of DNA methylation and gene expression, the expression patterns of 75% of genes were negatively correlated with DNA methylation in the CG context, whereas the correlation patterns in the CHH context were the reverse. The allele-biased DNA methylation was consistent during shoot organogenesis, with fewer than one-thousandth of allele-specific methylation regions shifted. Analysis of allele-specific expression revealed that there were only 1909 genes showing phase-dependent allele-biased expression in the regeneration process, among which the allele pairs with greater differences in transcription factor binding sites at promoter regions exhibited greater differences in allele expression. Our results indicated a relatively independent transcriptional regulation in two subgenomes during shoot organogenesis, which was contributed by cis-acting genomic and epigenomic variations.

Regulatory features aid interpretation of 3′UTR variants

Our ability to determine the clinical impact of variants in 3' untranslated regions (UTRs) of genes remains poor. We provide a thorough analysis of 3' UTR variants from several datasets. Variants in putative regulatory elements, including RNA-binding protein motifs, eCLIP peaks, and microRNA sites, are up to 16 times more likely than variants not in these elements to have gene expression and phenotype associations. Variants in regulatory motifs result in allele-specific protein binding in cell lines and allele-specific gene expression differences in population studies. In addition, variants in shared regions of alternatively polyadenylated isoforms and those proximal to polyA sites are more likely to affect gene expression and phenotype. Finally, pathogenic 3' UTR variants in ClinVar are up to 20 times more likely than benign variants to fall in a regulatory site. We incorporated these findings into RegVar, a software tool that interprets regulatory elements and annotations for any 3' UTR variant and predicts whether the variant is likely to affect gene expression or phenotype. This tool will help prioritize variants for experimental studies and identify pathogenic variants in individuals.

Inter-subspecies mouse F1 hybrid embryonic stem cell lines newly established for studies of allelic imbalance in gene expression.

Allele-specific monoallelic gene expression is a unique phenomenon and a great resource for analyzing gene regulation. To study this phenomenon, we established new embryonic stem (ES) cell lines derived from F1 hybrid blastocysts from crosses between four mouse subspecies (Mus musculus domesticus, C57BL/6; M. musculus molossinus, MSM/Ms; M. musculus, PWK; M. musculuscastaneus, HMI/Ms) and analyzed the expression levels of undifferentiated pluripotent stem cell markers and karyotypes of each line. To demonstrate the utility of our cell lines, we analyzed the allele-specific expression pattern of the Inpp5d gene as an example. The allelic expression depended on the parental alleles; this dependence could be a consequence of differences in compatibility between cis- and trans-elements of the Inpp5d gene from different subspecies. The use of parental mice from four subspecies greatly enhanced genetic polymorphism. The F1 hybrid ES cells retained this polymorphism not only in the Inpp5d gene, but also at a genome-wide level. As we demonstrated for the Inpp5d gene, the established cell lines can contribute to the analysis of allelic expression imbalance based on the incompatibility between cis- and trans-elements and of phenotypes related to this incompatibility.

Convergent evolution of allele-specific gene expression that leads to non-small cell lung cancer in different human populations.

Phenotypical innovations during evolution are caused by novel mutations, which are usually heterozygous at the beginning. The gene expressions on two alleles of these mutation sites are not necessarily identical, leading to flexible allele-specific regulation in cell systems. We retrieve the transcriptome data of normal and non-small cell lung cancer (NSCLC) tissues from 47 African Americans (AA) and 50 European Americans (EA). We analyze the differentially expressed genes (DEGs) in NSCLC as well as the tumor-specific mutations. Expression and mutation profiles show convergent evolution in AA and EA populations. The tumor-specific mutations are poorly overlapped, but many of them are located in the same genes, mainly oncogenes and tumor suppressor genes. The DEGs in tumors are majorly caused by the mutated alleles rather than normal alleles. The relative expressions of mutated alleles are highly correlated between AA and EA. The differential expression in NSCLC is predominantly mediated by the mutated alleles on heterozygous sites. This molecular mechanism underlying NSCLC oncogenesis is conserved across different human populations, exhibiting convergent evolution. We present this novel angle that differential expression analysis should be performed separately for different alleles. Our ideas should greatly benefit the cancer community.

Allele-Specific Expression of Leukemia Genes Is Associated with Pathogenicity in Poor Risk AML

Introduction: An imbalance in gene expression of the different alleles of a gene (allele-specific expression or ASE) is an intriguing genome-wide and dynamic phenomenon that could have an important role in tumorigenesis. Little is known about the causes and consequences of the differential cis- and trans-regulation on resultant ASE, aside from the impact of copy number alterations (CNAs) or imprinting. Acute myeloid leukemia (AML) is an aggressive clonal hematopoietic stem cell malignancy, with a low mutational burden in comparison with other cancers, where the impact of ASE may constitute a novel mechanism of pathogenesis. Aim: Application of Whole Genome Sequencing (WGS), RNA-seq and Oxford Nanopore methylation sequencing to study the ASE landscape in a cohort of poor risk AML patients and shed light on the mechanisms triggering this phenomenon as well as its temporal dynamics. Methods: ASE landscape was explored using paired germline and tumour WGS and RNA-seq on diagnostic bone marrow or peripheral blood samples from 33 cytogenetically poor risk AML patients, and additional RNA-seq from 18 samples corresponding to follow-up timepoints (including remission, relapse and refractory samples) from eight of the patients.Heterozygous SNPs were identified in the genomic DNA, and allele frequencies in RNA-seq reads were used to quantify ASE, after filtering for CNAs in the tumor DNA. Cas9-enriched Oxford Nanopore sequencing was then performed on available patient samples at diagnosis and subsequent time points. Allele-specific methylation was determined on the Nanopore sequencing using Guppy v6.3. Results: In the diagnostic cohort, we identified 4,802 protein-coding genes exhibiting ASE in at least one sample, with a median of 169 genes per sample (range 119-468, with one outlier sample showing ASE in 1,705 genes). Overall, 283 protein-coding genes showed ASE in ≥ 20% patients across the 33 samples. These genes included known imprinted genes and the transcription factor GATA2, where ASE was previously associated with AML, validating our ASE pipeline and filtering criteria. We also identified for the first time recurrent ASE in other myeloid genes such as KMT2A (20%), the homeobox genes PBX2 (41%), PBX3 (20%), HOXA6 (20%) and HOXB cluster ( HOXB2 (31%), HOXB3 (27%), HOXB5 (40%), HOXB6 (30%)); and the myeloid differentiation genes CDKN2A (40%), PDGFRB (25%) and PRTN3 (57%). Eighteen primary AML samples from 8/33 patients had paired diagnostic, remission and relapse or refractory material, allowing us to track the dynamic ASE pattern. RNA-seq and Sanger sequencing of cDNA in these samples showed that the ASE observed at diagnosis in HOXB2, HOXB3, HOXB6, PBX3 and GATA2 was lost in the corresponding remission sample (bi-allelic expression), with ASE returning at relapse and maintained in the refractory samples. In order to explore the epigenetic mechanisms underlying these allele-specific changes in expression, Cas9-enriched Oxford Nanopore sequencing was performed in 2 patients with available DNA at diagnosis and sequential time points, to determine the pattern of allele-specific methylation of the promoter region of GATA2 (patient 1) and HOXB2 (patient 2). In patient 1 at diagnosis, 90% of CpG sites were methylated at the GATA2 promoter region on one allele versus 61% in the other allele, with the hypomethylated allele corresponding to the allele that is overexpressed in the ASE sample. However, in the remission sample, the proportion of methylated CpG sites on the two alleles was similar (83% and 73%, respectively), in agreement with the expression of both GATA2 alleles at this stage. Likewise, in the diagnostic sample of patient 2, 6% of CpG sites were methylated in the HOXB2 promoter region of one allele, corresponding to the overexpressed allele in the ASE sample, while the other promoter allele had 17% of CpG sites methylated; with no differences in CpG methylation between alleles in the remission samples (9% versus 9%), again correlating with the bi-allelic expression of HOXB2 at remission. Conclusions: Combining WGS and RNA-seq in AML primary samples, we have identified key leukemia genes showing recurrent dynamic ASE associated with disease evolution: since it is found at diagnosis, lost in remission, but recovered in relapse and persisting in refractory stages. Our results also suggest allele-specific methylation as the potential mechanism orchestrating this phenomenon.

Comprehensive analyses of 435 goat transcriptomes provides insight into male reproduction

A systematic analysis of genes related to reproduction is crucial for obtaining a comprehensive understanding of the molecular mechanisms that underlie male reproductive traits in mammals. Here, we utilized 435 goat transcriptome datasets to unveil the testicular tissue-specific genes (TSGs), allele-specific expression (ASE) genes and their uncharacterized transcriptional features related to male goat reproduction. Results showed a total of 1790 TSGs were identified in goat testis, which was the most among all tissues. GO enrichment analyses suggested that testicular TSGs were mainly involved in spermatogenesis, multicellular organism development, spermatid development, and flagellated sperm motility. Subsequently, a total of 95 highly conserved TSGs (HCTSGs), 508 middle conserved TSGs (MCTSGs) and 42 no conserved TSGs (NCTSGs) were identified in goat testis. GO enrichment analyses suggested that the HCTSGs and MCTSGs has a more important association with male reproduction than NCTSGs. Additionally, we identified 644 ASE genes, including 88 tissue-specific ASE (TS-ASE) genes (e.g., FSIP2, TDRD9). GO enrichment analyses indicated that both ASE genes and TS-ASE genes were associated with goat male reproduction. Overall, this study revealed an extensive gene set involved in the regulation of male goat reproduction and their dynamic transcription patterns. Data reported here provide valuable insights for a further improvement of the economic benefits of goats as well as future treatments for male infertility.

The conservation of allelic DNA methylation and its relationship with imprinting in maize.

Genomic imprinting refers to allele-specific expression of genes depending on parental origin, and it is regulated by epigenetic modifications. Intraspecific allelic variation for imprinting has been detected; however, the intraspecific genome-wide allelic epigenetic variation in maize and its correlation with imprinting variants remain unclear. Here, three reciprocal hybrids were generated by crossing Zea mays inbred lines CAU5, B73, and Mo17 in order to examine the intraspecific conservation of the imprinted genes in the kernel. The majority of imprinted genes exhibited intraspecific conservation, and these genes also exhibited interspecific conservation (rice, sorghum, and Arabidopsis) and were enriched in some specific pathways. By comparing intraspecific allelic DNA methylation in the endosperm, we found that nearly 15% of DNA methylation existed as allelic variants. The intraspecific whole-genome correlation between DNA methylation and imprinted genes indicated that DNA methylation variants play an important role in imprinting variants. Disruption of two conserved imprinted genes using CRISPR/Cas9 editing resulted in a smaller kernel phenotype. Our results shed light on the intraspecific correlation of DNA methylation variants and variation for imprinting in maize, and show that imprinted genes play an important role in kernel development.

Identification of Allele-Specific Expression Genes Associated with Maize Heterosis

Deciphering the molecular basis of heterosis would yield genes and markers for designing improved maize-hybrid varieties. In this study, 481 BC1F3 lines derived from Zheng58 and PH4CV were genotyped with 15,386 polymorphic SNPs markers and testcrossed with two testers (Chang7-2 and PH6WC) to generate 962 testcross lines. The yield of these testcross lines and their parental lines was evaluated across multiple environments. Genetic analysis revealed that dominance is the primary contributor to heterosis. Mapping of midparent heterosis (MPH) identified two dominant QTL, six additive-by-additive interactions, eighteen additive-by-dominance interactions, and fifty-four dominance-by-dominance interactions. These interactions encompassed 104 genetic blocks, including 24 genetic blocks that explained >1% of phenotypic variances for both MPH and hybrid performance. We compared the locations of the allele-specific expression genes (ASEGs) identified from the expression data of two hybrid lines and their parental lines with those of the 24 genetic blocks and found 15 ASEGs related to yield or biomass regulation, including two known genes BT2 and ZmNF-YC4. Fisher’s exact test analysis indicated a significant enrichment of these ASEGs in the 24 blocks, affirming the reliability of the MPH-mapping results. The co-expression network of six ASEGs, including BT2 and ZmNF-YC4, contained many genes related to yield or biomass regulation. This study unravels potential candidate genes and regulatory networks associated with maize heterosis.

Allele-specific expression reveals genetic drivers of tissue regeneration in mice.

In adult mammals, skin wounds typically heal by scarring rather than through regeneration. In contrast, "super-healer" Murphy Roths Large (MRL) mice have the unusual ability to regenerate ear punch wounds; however, the molecular basis for this regeneration remains elusive. Here, in hybrid crosses between MRL and non-regenerating mice, we used allele-specific gene expression to identify cis-regulatory variation associated with ear regeneration. Analyzing three major cell populations (immune, fibroblast, and endothelial), we found that genes with cis-regulatory differences specifically in fibroblasts were associated with wound-healing pathways and also co-localized with quantitative trait loci for ear wound-healing. Ectopic treatment with one of these proteins, complement factor H (CFH), accelerated wound repair and induced regeneration in typically fibrotic wounds. Through single-cell RNA sequencing (RNA-seq), we observed that CFH treatment dramatically reduced immune cell recruitment to wounds, suggesting a potential mechanism for CFH's effect. Overall, our results provide insights into the molecular drivers of regeneration with potential clinical implications.

Haplotype-Resolution Transcriptome Analysis Reveals Important Responsive Gene Modules and Allele-Specific Expression Contributions under Continuous Salt and Drought in Camellia sinensis.

The tea plant, Camellia sinensis (L.) O. Kuntze, is one of the most important beverage crops with significant economic and cultural value. Global climate change and population growth have led to increased salt and drought stress, negatively affecting tea yield and quality. The response mechanism of tea plants to these stresses remains poorly understood due to the lack of reference genome-based transcriptional descriptions. This study presents a high-quality genome-based transcriptome dynamic analysis of C. sinensis' response to salt and drought stress. A total of 2244 upregulated and 2164 downregulated genes were identified under salt and drought stress compared to the control sample. Most of the differentially expression genes (DEGs) were found to involve divergent regulation processes at different time points under stress. Some shared up- and downregulated DEGs related to secondary metabolic and photosynthetic processes, respectively. Weighted gene co-expression network analysis (WGCNA) revealed six co-expression modules significantly positively correlated with C. sinensis' response to salt or drought stress. The MEpurple module indicated crosstalk between the two stresses related to ubiquitination and the phenylpropanoid metabolic regulation process. We identified 1969 salt-responsive and 1887 drought-responsive allele-specific expression (ASE) genes in C. sinensis. Further comparison between these ASE genes and tea plant heterosis-related genes suggests that heterosis likely contributes to the adversity and stress resistance of C. sinensis. This work offers new insight into the underlying mechanisms of C. sinensis' response to salt and drought stress and supports the improved breeding of tea plants with enhanced salt and drought tolerance.

Design, execution, and interpretation of plant RNA-seq analyses.

Genomics has transformed our understanding of the genetic architecture of traits and the genetic variation present in plants. Here, we present a review of how RNA-seq can be performed to tackle research challenges addressed by plant sciences. We discuss the importance of experimental design in RNA-seq, including considerations for sampling and replication, to avoid pitfalls and wasted resources. Approaches for processing RNA-seq data include quality control and counting features, and we describe common approaches and variations. Though differential gene expression analysis is the most common analysis of RNA-seq data, we review multiple methods for assessing gene expression, including detecting allele-specific gene expression and building co-expression networks. With the production of more RNA-seq data, strategies for integrating these data into genetic mapping pipelines is of increased interest. Finally, special considerations for RNA-seq analysis and interpretation in plants are needed, due to the high genome complexity common across plants. By incorporating informed decisions throughout an RNA-seq experiment, we can increase the knowledge gained.

Sex-specific estimation of cis and trans regulation of gene expression in heads and gonads of Drosophila melanogaster.

The regulatory architecture of gene expression is known to differ substantially between sexes in Drosophila, but most studies performed so far used whole-body data and only single crosses, which may have limited their scope to detect patterns that are robust across tissues and biological replicates. Here, we use allele-specific gene expression of parental and reciprocal hybrid crosses between 6 Drosophila melanogaster inbred lines to quantify cis- and trans-regulatory variation in heads and gonads of both sexes separately across 3 replicate crosses. Our results suggest that female and male heads, as well as ovaries, have a similar regulatory architecture. On the other hand, testes display more and substantially different cis-regulatory effects, suggesting that sex differences in the regulatory architecture that have been previously observed may largely derive from testis-specific effects. We also examine the difference in cis-regulatory variation of genes across different levels of sex bias in gonads and heads. Consistent with the idea that intersex correlations constrain expression and can lead to sexual antagonism, we find more cis variation in unbiased and moderately biased genes in heads. In ovaries, reduced cis variation is observed for male-biased genes, suggesting that cis variants acting on these genes in males do not lead to changes in ovary expression. Finally, we examine the dominance patterns of gene expression and find that sex- and tissue-specific patterns of inheritance as well as trans-regulatory variation are highly variable across biological crosses, although these were performed in highly controlled experimental conditions. This highlights the importance of using various genetic backgrounds to infer generalizable patterns.