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April 21, 2020  |  

Genome Sequence of Jaltomata Addresses Rapid Reproductive Trait Evolution and Enhances Comparative Genomics in the Hyper-Diverse Solanaceae.

Within the economically important plant family Solanaceae, Jaltomata is a rapidly evolving genus that has extensive diversity in flower size and shape, as well as fruit and nectar color, among its ~80 species. Here, we report the whole-genome sequencing, assembly, and annotation, of one representative species (Jaltomata sinuosa) from this genus. Combining PacBio long reads (25×) and Illumina short reads (148×) achieved an assembly of ~1.45?Gb, spanning ~96% of the estimated genome. Ninety-six percent of curated single-copy orthologs in plants were detected in the assembly, supporting a high level of completeness of the genome. Similar to other Solanaceous species, repetitive elements made up a large fraction (~80%) of the genome, with the most recently active element, Gypsy, expanding across the genome in the last 1-2 Myr. Computational gene prediction, in conjunction with a merged transcriptome data set from 11 tissues, identified 34,725 protein-coding genes. Comparative phylogenetic analyses with six other sequenced Solanaceae species determined that Jaltomata is most likely sister to Solanum, although a large fraction of gene trees supported a conflicting bipartition consistent with substantial introgression between Jaltomata and Capsicum after these species split. We also identified gene family dynamics specific to Jaltomata, including expansion of gene families potentially involved in novel reproductive trait development, and loss of gene families that accompanied the loss of self-incompatibility. This high-quality genome will facilitate studies of phenotypic diversification in this rapidly radiating group and provide a new point of comparison for broader analyses of genomic evolution across the Solanaceae.


April 21, 2020  |  

Computational aspects underlying genome to phenome analysis in plants.

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features. © 2018 The Authors The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.


April 21, 2020  |  

A reference genome for pea provides insight into legume genome evolution.

We report the first annotated chromosome-level reference genome assembly for pea, Gregor Mendel’s original genetic model. Phylogenetics and paleogenomics show genomic rearrangements across legumes and suggest a major role for repetitive elements in pea genome evolution. Compared to other sequenced Leguminosae genomes, the pea genome shows intense gene dynamics, most likely associated with genome size expansion when the Fabeae diverged from its sister tribes. During Pisum evolution, translocation and transposition differentially occurred across lineages. This reference sequence will accelerate our understanding of the molecular basis of agronomically important traits and support crop improvement.


April 21, 2020  |  

The role of genomic structural variation in the genetic improvement of polyploid crops

Many of our major crop species are polyploids, containing more than one genome or set of chromosomes. Polyploid crops present unique challenges, including difficulties in genome assembly, in discriminating between multiple gene and sequence copies, and in genetic mapping, hindering use of genomic data for genetics and breeding. Polyploid genomes may also be more prone to containing structural variation, such as loss of gene copies or sequences (presence–absence variation) and the presence of genes or sequences in multiple copies (copy-number variation). Although the two main types of genomic structural variation commonly identified are presence–absence variation and copy-number variation, we propose that homeologous exchanges constitute a third major form of genomic structural variation in polyploids. Homeologous exchanges involve the replacement of one genomic segment by a similar copy from another genome or ancestrally duplicated region, and are known to be extremely common in polyploids. Detecting all kinds of genomic structural variation is challenging, but recent advances such as optical mapping and long-read sequencing offer potential strategies to help identify structural variants even in complex polyploid genomes. All three major types of genomic structural variation (presence–absence, copy-number, and homeologous exchange) are now known to influence phenotypes in crop plants, with examples of flowering time, frost tolerance, and adaptive and agronomic traits. In this review, we summarize the challenges of genome analysis in polyploid crops, describe the various types of genomic structural variation and the genomics technologies and data that can be used to detect them, and collate information produced to date related to the impact of genomic structural variation on crop phenotypes. We highlight the importance of genomic structural variation for the future genetic improvement of polyploid crops.


April 21, 2020  |  

Transcriptome analysis reveals multiple signal network contributing to the Verticillium wilt resistance in eggplant

Verticillium wilt is a devastating disease in eggplants. In order to understand the molecular mechanism of disease resistance in eggplants, transcriptomes of Verticillium wilt infected eggplants were detected. A total of 480, 518, 887 and 1 046 Verticillium wilt related differentially expressed genes were identified at 6 (V6), 12 (V12), 24 (V24) and 48?h (V48), respectively. COG function classification revealed that most of DEGs functioned in “Amino acid transport and metabolism”, “Cytoskeleton” and “Cell motility”. In addition, compared the control plants (V0) to infected eggplants (V6-V48), a total of 111 common DEGs were identified. Except for “General function prediction only”, most of the DEGs enriched in “Signal transduction”. DEGs associated to different hormone signals, including GID1B, ROPGAP1, OPT3 and CDPK, were identified throughout the whole infection process. Cross-talk among defense signal pathways plays major roles in the Verticillium wilt disease resistance in eggplants.


April 21, 2020  |  

Complete Genome Sequence of Sequevar 14M Ralstonia solanacearum Strain HA4-1 Reveals Novel Type III Effectors Acquired Through Horizontal Gene Transfer.

Ralstonia solanacearum, which causes bacterial wilt in a broad range of plants, is considered a “species complex” due to its significant genetic diversity. Recently, we have isolated a new R. solanacearum strain HA4-1 from Hong’an county in Hubei province of China and identified it being phylotype I, sequevar 14M (phylotype I-14M). Interestingly, we found that it can cause various disease symptoms among different potato genotypes and display different pathogenic behavior compared to a phylogenetically related strain, GMI1000. To dissect the pathogenic mechanisms of HA4-1, we sequenced its whole genome by combined sequencing technologies including Illumina HiSeq2000, PacBio RS II, and BAC-end sequencing. Genome assembly results revealed the presence of a conventional chromosome, a megaplasmid as well as a 143 kb plasmid in HA4-1. Comparative genome analysis between HA4-1 and GMI1000 shows high conservation of the general virulence factors such as secretion systems, motility, exopolysaccharides (EPS), and key regulatory factors, but significant variation in the repertoire and structure of type III effectors, which could be the determinants of their differential pathogenesis in certain potato species or genotypes. We have identified two novel type III effectors that were probably acquired through horizontal gene transfer (HGT). These novel R. solanacearum effectors display homology to several YopJ and XopAC family members. We named them as RipBR and RipBS. Notably, the copy of RipBR on the plasmid is a pseudogene, while the other on the megaplasmid is normal. For RipBS, there are three copies located in the megaplasmid and plasmid, respectively. Our results have not only enriched the genome information on R. solanacearum species complex by sequencing the first sequevar 14M strain and the largest plasmid reported in R. solanacearum to date but also revealed the variation in the repertoire of type III effectors. This will greatly contribute to the future studies on the pathogenic evolution, host adaptation, and interaction between R. solanacearum and potato.


April 21, 2020  |  

A Pathovar of Xanthomonas oryzae Infecting Wild Grasses Provides Insight Into the Evolution of Pathogenicity in Rice Agroecosystems

Xanthomonas oryzae (Xo) are critical rice pathogens. Virulent lineages from Africa and Asia and less virulent strains from the US have been well characterized. X. campestris pv. leersiae (Xcl), first described in 1957, causes bacterial streak on the perennial grass, Leersia hexandra, and is a close relative of Xo. L. hexandra, a member of the Poaceae, is highly similar to rice phylogenetically, is globally ubiquitous around rice paddies, and is a reservoir of pathogenic Xo. We used long read, single molecule, real time (SMRT) genome sequences of five strains of Xcl from Burkina Faso, China, Mali and Uganda to determine the genetic relatedness of this organism with Xo. Novel Transcription Activator-Like Effectors (TALEs) were discovered in all five strains of Xcl. Predicted TALE target sequences were identified in the L. perrieri genome and compared to rice susceptibility gene homologs. Pathogenicity screening on L. hexandra and diverse rice cultivars confirmed that Xcl are able to colonize rice and produce weak but not progressive symptoms. Overall, based on average nucleotide identity, type III effector repertoires and disease phenotype, we propose to rename Xcl to X. oryzae pv. leersiae (Xol) and use this parallel system to improve understanding of the evolution of bacterial pathogenicity in rice agroecosystems.


April 21, 2020  |  

Closing the Yield Gap for Cannabis: A Meta-Analysis of Factors Determining Cannabis Yield.

Until recently, the commercial production of Cannabis sativa was restricted to varieties that yielded high-quality fiber while producing low levels of the psychoactive cannabinoid tetrahydrocannabinol (THC). In the last few years, a number of jurisdictions have legalized the production of medical and/or recreational cannabis with higher levels of THC, and other jurisdictions seem poised to follow suit. Consequently, demand for industrial-scale production of high yield cannabis with consistent cannabinoid profiles is expected to increase. In this paper we highlight that currently, projected annual production of cannabis is based largely on facility size, not yield per square meter. This meta-analysis of cannabis yields reported in scientific literature aimed to identify the main factors contributing to cannabis yield per plant, per square meter, and per W of lighting electricity. In line with previous research we found that variety, plant density, light intensity and fertilization influence cannabis yield and cannabinoid content; we also identified pot size, light type and duration of the flowering period as predictors of yield and THC accumulation. We provide insight into the critical role of light intensity, quality, and photoperiod in determining cannabis yields, with particular focus on the potential for light-emitting diodes (LEDs) to improve growth and reduce energy requirements. We propose that the vast amount of genomics data currently available for cannabis can be used to better understand the effect of genotype on yield. Finally, we describe diversification that is likely to emerge in cannabis growing systems and examine the potential role of plant-growth promoting rhizobacteria (PGPR) for growth promotion, regulation of cannabinoid biosynthesis, and biocontrol.


April 21, 2020  |  

A draft genome for Spatholobus suberectus.

Spatholobus suberectus Dunn (S. suberectus), which belongs to the Leguminosae, is an important medicinal plant in China. Owing to its long growth cycle and increased use in human medicine, wild resources of S. suberectus have decreased rapidly and may be on the verge of extinction. De novo assembly of the whole S. suberectus genome provides us a critical potential resource towards biosynthesis of the main bioactive components and seed development regulation mechanism of this plant. Utilizing several sequencing technologies such as Illumina HiSeq X Ten, single-molecule real-time sequencing, 10x Genomics, as well as new assembly techniques such as FALCON and chromatin interaction mapping (Hi-C), we assembled a chromosome-scale genome about 798?Mb in size. In total, 748?Mb (93.73%) of the contig sequences were anchored onto nine chromosomes with the longest scaffold being 103.57?Mb. Further annotation analyses predicted 31,634 protein-coding genes, of which 93.9% have been functionally annotated. All data generated in this study is available in public databases.


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