The Chromosome-Based Rubber Tree Genome Provides New Insights into Spurge Genome Evolution and Rubber Biosynthesis

The rubber tree,Hevea brasiliensis,produces natural rubber that serves as an essential industrial raw material.Here,we present a high-quality reference genome for a rubber tree cultivar GT1 using single-molecule real-time sequencing(SMRT)and Hi-C technologies to anchor the～1.47-Gb genome assembly into 18 pseudochromosomes.The chromosome-based genome analysis enabled us to establish a model of spurge chromosome evolution,since the common paleopolyploid event occurred before the split of Hevea and Manihot.We show recent and rapid bursts of the three Hevea-specific LTR-retrotransposon families during the last 10 million years,leading to the massive expansion by～65.88%(～970 Mbp)of the whole rubber tree genome since the divergence from Manihot.We identify large-scale expansion of genes associated with whole rubber biosynthesis processes,such as basal metabolic processes,ethylene biosynthesis,and the activation of polysaccharide and glycoprotein lectin,which are important properties for latex production.A map of genomic variation between the cultivated and wild rubber trees was obtained,which contains～15.7 million high-quality single-nucleotide polymorphisms.We identified hundreds of candidate domestication genes with drastically lowered genomic diversity in the cultivated but not wild rubber trees despite a relatively short domestication history of rubber tree,some of which are involved in rubber biosynthesis.This genome assembly represents key resources for future rubber tree research and breeding,providing novel targets for improving plant biotic and abiotic tolerance and rubber production.

The Chromosome-Level Reference Genome of Tea Tree Unveils Recent Bursts of Nonautonomous LTR Retrotransposons in Driving Genome Size Evolution

Dear Editor,The tea tree Camellia sinensis,a member of the genus Camellia in the Theaceae family,includes two major cultivated varieties,C.sinensis var.assamica(CSA\Assam type)and C.sinensis var.sinensis(CSS;Chinese type)(Ming and Bartholomew,2007).Due to the high economic importance of the tea tree,considerable efforts have been made to explore genetic basis of the biosynthesis of natural metabolites that determine health benefits and diverse tea flavors(Shi et al.,2011;Li et al.,2011;Li et al.,2015;Xia et aL,2017;Liu et al.,2019).

Mako:A Graph-based Pattern Growth Approach to Detect Complex Structural Variants

Complex structural variants(CSVs) are genomic alterations that have more than two breakpoints and are considered as the simultaneous occurrence of simple structural variants.However,detecting the compounded mutational signals of CSVs is challenging through a commonly used model-match strategy.As a result,there has been limited progress for CSV discovery compared with simple structural variants.Here,we systematically analyzed the multi-breakpoint connection feature of CSVs,and proposed Mako,utilizing a bottom-up guided model-free strategy,to detect CSVs from paired-end short-read sequencing.Specifically,we implemented a graph-based pattern growth approach,where the graph depicts potential breakpoint connections,and pattern growth enables CSV detection without pre-defined models.Comprehensive evaluations on both simulated and real datasets revealed that Mako outperformed other algorithms.Notably,validation rates of CSVs on real data based on experimental and computational validations as well as manual inspections are around 70%,where the medians of experimental and computational breakpoint shift are 13 bp and 26 bp,respectively.Moreover,the Mako CSV subgraph effectively characterized the breakpoint connections of a CSV event and uncovered a total of 15 CSV types,including two novel types of adjacent segment swap and tandem dispersed duplication.Further analysis of these CSVs also revealed the impact of sequence homology on the formation of CSVs.Mako is publicly available at https://github.com/xjtu-omics/Mako.