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Facing constant challenges from various pathogens and pests, plants have evolved different strategies to defend themselves both locally and systemically. A global change in RNA metabolism is one of the necessary steps to mount a long-lasting immunity against present and future invasions.Arabidopsisserine/arginine-rich 45 (SR45) is an evolutionarily conserved RNA-binding protein that regulates multiple steps of RNA metabolism. Our prior study suggested that SR45 acts as a negative regulator of plant immunity. To better understand the molecular mechanism for SR45’s defense role, we examined the metabolic profile in both Col-0 andsr45-1. The results showed a significant accumulation of pipecolic acid (Pip), salicylic acid (SA), and other potential defense compounds insr45-1, indicating an increased systemic immunity. Thesr45–1mutant exhibited an elevated resistance to a wide range of biotrophic pathogen species and insensitivity to Pip, SA, and pathogen pretreatment. Between the two alternatively spliced isoforms, SR45.1 and SR45.2, SR45.1 seemed to be the culprit for the observed immune suppression. Upon examination of the transcriptome profile between Col-0 andsr45-1under either mock orPseudomonas syringae PmaDG3 challenge, we identified 1,125 genes as SR45-suppressed andPmaDG3-induced. Genes that function in SA biosynthesis and systemic acquired resistance were overrepresented, including those coding for WRKY, receptor-like kinases (RLKs), receptor-like proteins (RLPs), protein kinases, and TIR-NBS-LRR proteins. In addition, we identified significant alternative splicing activity in a list of genes due to eithersr45–1alone or bothsr45–1andPmaDG3 challenge. Among them, we characterized the effect of alternative splicing in two candidates,CBRLK1andSRF1. Interestingly, alternative splicing in both exhibited a switch between RLPs and RLKs in the predicted protein products. Overexpressing theirsr45–1dominant isoform in Col-0 led to a partial increase in immunity, suggesting the involvement of both alternative splicing events in SR45-conferred immune suppression. In summary, we hypothesize that SR45 regulates a subset of immune genes at either transcriptional or co-transcriptional pre-mRNA splicing levels to confer its function in systemic immune suppression. 

Abstract Background Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary and secondary contigs are not properly identified, the primary assembly will overrepresent both the size and complexity of the genome, which complicates downstream analysis such as scaffolding. Results Here we illustrate a new method, which we call HapSolo, that identifies secondary contigs and defines a primary assembly based on multiple pairwise contig alignment metrics. HapSolo evaluates candidate primary assemblies using BUSCO scores and then distinguishes among candidate assemblies using a cost function. The cost function can be defined by the user but by default considers the number of missing, duplicated and single BUSCO genes within the assembly. HapSolo performs hill climbing to minimize cost over thousands of candidate assemblies. We illustrate the performance of HapSolo on genome data from three species: the Chardonnay grape ( Vitis vinifera ), with a genome of 490 Mb, a mosquito ( Anopheles funestus ; 200 Mb) and the Thorny Skate ( Amblyraja radiata ; 2650 Mb). Conclusions HapSolo rapidly identified candidate assemblies that yield improvements in assembly metrics, including decreased genome size and improved N50 scores. Contig N50 scores improved by 35%, 9% and 9% for Chardonnay, mosquito and the thorny skate, respectively, relative to unreduced primary assemblies. The benefits of HapSolo were amplified by down-stream analyses, which we illustrated by scaffolding with Hi-C data. We found, for example, that prior to the application of HapSolo, only 52% of the Chardonnay genome was captured in the largest 19 scaffolds, corresponding to the number of chromosomes. After the application of HapSolo, this value increased to ~ 84%. The improvements for the mosquito’s largest three scaffolds, representing the number of chromosomes, were from 61 to 86%, and the improvement was even more pronounced for thorny skate. We compared the scaffolding results to assemblies that were based on PurgeDups for identifying secondary contigs, with generally superior results for HapSolo. 

Abstract “Evolve and resequence” (E&R) studies combine experimental evolution and whole‐genome sequencing to interrogate the genetics underlying adaptation. Due to ease of handling, E&R work with asexual organisms such as bacteria can employ optimized experimental design, with large experiments and many generations of selection. By contrast, E&R experiments with sexually reproducing organisms are more difficult to implement, and design parameters vary dramatically among studies. Thus, efforts have been made to assess how these differences, such as number of independent replicates, or size of experimental populations, impact inference. We add to this work by investigating the role of time sampling—the number of discrete time points sequence data are collected from evolving populations. Using data from an E&R experiment with outcrossingSaccharomyces cerevisiaein which populations were sequenced 17 times over ~540 generations, we address the following questions: (a) Do more time points improve the ability to identify candidate regions underlying selection? And (b) does high‐resolution sampling provide unique insight into evolutionary processes driving adaptation? We find that while time sampling does not improve the ability to identify candidate regions, high‐resolution sampling does provide valuable opportunities to characterize evolutionary dynamics. Increased time sampling reveals three distinct trajectories for adaptive alleles: one consistent with classic population genetic theory (i.e., models assuming constant selection coefficients), and two where trajectories suggest more context‐dependent responses (i.e., models involving dynamic selection coefficients). We conclude that while time sampling has limited impact on candidate region identification, sampling eight or more time points has clear benefits for studying complex evolutionary dynamics.