Gap-free genome assembly and comparative analysis reveal the evolution and anthocyanin accumulation mechanism of Rhodomyrtus tomentosa

Rhodomyrtus tomentosa is an important f leshy-fruited tree and a well-known medicinal plant of the Myrtaceae family that is widely cultivated in tropical and subtropical areas of the world.However,studies on the evolution and genomic breeding of R.tomentosa were hindered by the lack of a reference genome.Here,we presented a chromosome-level gap-free T2T genome assembly of R.tomentosa using PacBio and ONT long read sequencing.We assembled the genome with size of 470.35 Mb and contig N50 of∼43.80 Mb with 11 pseudochromosomes.A total of 33382 genes and 239.31 Mb of repetitive sequences were annotated in this genome.Phylogenetic analysis elucidated the independent evolution of R.tomentosa starting from 14.37MYA and shared a recent WGD event with other Myrtaceae species.We identified four major compounds of anthocyanins and their synthetic pathways in R.tomentosa.Comparative genomic and gene expression analysis suggested the coloring and high anthocyanin accumulation in R.tomentosa tends to be determined by the activation of anthocyanin synthesis pathway.The positive selection and up-regulation of MYB transcription factors were the implicit factors in this process.The copy number increase of downstream anthocyanin transport-related OMT and GST gene were also detected in R.tomentosa.Expression analysis and pathway identification enriched the importance of starch degradation,response to stimuli,effect of hormones,and cell wall metabolism during the f leshy fruit development in Myrtaceae.Our genome assembly provided a foundation for investigating the origins and differentiation of Myrtaceae species and accelerated the genetic improvement of R.tomentosa.

Application of an Improved 2-Dimensional High-Throughput Soybean Root Phenotyping Platform to Identify Novel Genetic Variants Regulating Root Architecture Traits

Nutrient-efficient root system architecture(RSA)is becoming an important breeding objective for generating crop varieties with improved nutrient and water acquisition efficiency.Genetic variants shaping soybean RSA is key in improving nutrient and water acquisition.Here,we report on the use of an improved 2-dimensional high-throughput root phenotyping platform that minimizes background noise by imaging pouch-grown root systems submerged in water.We also developed a background image cleaning Python pipeline that computationally removes images of small pieces of debris and filter paper fibers,which can be erroneously quantified as root tips.This platform was used to phenotype root traits in 286 soybean lines genotyped with 5.4 million single-nucleotide polymorphisms.There was a substantially higher correlation in manually counted number of root tips with computationally quantified root tips(95%correlation),when the background was cleaned of nonroot materials compared to root images without the background corrected(79%).Improvements in our RSA phenotyping pipeline significantly reduced overestimation of the root traits influenced by the number of root tips.Genome-wide association studies conducted on the root phenotypic data and quantitative gene expression analysis of candidate genes resulted in the identification of 3 putative positive regulators of root system depth,total root length and surface area,and root system volume and surface area of thicker roots(DOF1-like zinc finger transcription factor,protein of unknown function,and C2H2 zinc finger protein).We also identified a putative negative regulator(gibberellin 20 oxidase 3)of the total number of lateral roots.

Improving Smoothing Efficiency of Rigid Conformal Polishing Tool Using Time-Dependent Smoothing Evaluation Model

A rigid conformal （RC） lap can smooth mid-spatial-frequency （MSF） errors, which are naturally smaller than the tool size, while still removing large-scale errors in a short time. However, the RC-lap smoothing efficiency performance is poorer than expected, and existing smoothing models cannot explicitly specify the methods to improve this efficiency. We presented an explicit time-dependent smoothing evaluation model that contained specific smoothing parameters directly derived from the parametric smoothing model and the Preston equation. Based on the time-dependent model, we proposed a strategy to improve the RC-lap smoothing efficiency, which incorporated the theoretical model, tool optimization, and efficiency limit determination. Two sets of smoothing experiments were performed to demonstrate the smoothing efficiency achieved using the time-dependent smoothing model. A high, theory-like tool influence function and a limiting toolspeed of 300 RPM were obtained.