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April 21, 2020  |  

Full-length mRNA sequencing and gene expression profiling reveal broad involvement of natural antisense transcript gene pairs in pepper development and response to stresses.

Pepper is an important vegetable with great economic value and unique biological features. In the past few years, significant development has been made towards understanding the huge complex pepper genome; however, pepper functional genomics has not been well studied. To better understand the pepper gene structure and pepper gene regulation, we conducted full-length mRNA sequencing by PacBio sequencing and obtained 57862 high-quality full-length mRNA sequences derived from 18362 previously annotated and 5769 newly detected genes. New gene models were built that combined the full-length mRNA sequences and corrected approximately 500 fragmented gene models from previous annotations. Based on the full-length mRNA, we identified 4114 and 5880 pepper genes forming natural antisense transcript (NAT) genes in-cis and in-trans, respectively. Most of these genes accumulate small RNAs in their overlapping regions. By analyzing these NAT gene expression patterns in our transcriptome data, we identified many NAT pairs responsive to a variety of biological processes in pepper. Pepper formate dehydrogenase 1 (FDH1), which is required for R-gene-mediated disease resistance, may be regulated by nat-siRNAs and participate in a positive feedback loop in salicylic acid biosynthesis during resistance responses. Several cis-NAT pairs and subgroups of trans-NAT genes were responsive to pepper pericarp and placenta development, which may play roles in capsanthin and capsaicin biosynthesis. Using a comparative genomics approach, the evolutionary mechanisms of cis-NATs were investigated, and we found that an increase in intergenic sequences accounted for the loss of most cis-NATs, while transposon insertion contributed to the formation of most new cis-NATs. This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.

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April 21, 2020  |  

The genomes of pecan and Chinese hickory provide insights into Carya evolution and nut nutrition.

Pecan (Carya illinoinensis) and Chinese hickory (C. cathayensis) are important commercially cultivated nut trees in the genus Carya (Juglandaceae), with high nutritional value and substantial health benefits.We obtained >187.22 and 178.87 gigabases of sequence, and ~288× and 248× genome coverage, to a pecan cultivar (“Pawnee”) and a domesticated Chinese hickory landrace (ZAFU-1), respectively. The total assembly size is 651.31 megabases (Mb) for pecan and 706.43 Mb for Chinese hickory. Two genome duplication events before the divergence from walnut were found in these species. Gene family analysis highlighted key genes in biotic and abiotic tolerance, oil, polyphenols, essential amino acids, and B vitamins. Further analyses of reduced-coverage genome sequences of 16 Carya and 2 Juglans species provide additional phylogenetic perspective on crop wild relatives.Cooperative characterization of these valuable resources provides a window to their evolutionary development and a valuable foundation for future crop improvement. © The Author(s) 2019. Published by Oxford University Press.

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April 21, 2020  |  

A siphonous macroalgal genome suggests convergent functions of homeobox genes in algae and land plants.

Genome evolution and development of unicellular, multinucleate macroalgae (siphonous algae) are poorly known, although various multicellular organisms have been studied extensively. To understand macroalgal developmental evolution, we assembled the ~26?Mb genome of a siphonous green alga, Caulerpa lentillifera, with high contiguity, containing 9,311 protein-coding genes. Molecular phylogeny using 107 nuclear genes indicates that the diversification of the class Ulvophyceae, including C. lentillifera, occurred before the split of the Chlorophyceae and Trebouxiophyceae. Compared with other green algae, the TALE superclass of homeobox genes, which expanded in land plants, shows a series of lineage-specific duplications in this siphonous macroalga. Plant hormone signalling components were also expanded in a lineage-specific manner. Expanded transport regulators, which show spatially different expression, suggest that the structural patterning strategy of a multinucleate cell depends on diversification of nuclear pore proteins. These results not only imply functional convergence of duplicated genes among green plants, but also provide insight into evolutionary roots of green plants. Based on the present results, we propose cellular and molecular mechanisms involved in the structural differentiation in the siphonous alga. © The Author(s) 2019. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

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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.

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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.

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April 21, 2020  |  

Full-length transcript sequencing and comparative transcriptomic analysis to evaluate the contribution of osmotic and ionic stress components towards salinity tolerance in the roots of cultivated alfalfa (Medicago sativa L.).

Alfalfa is the most extensively cultivated forage legume. Salinity is a major environmental factor that impacts on alfalfa’s productivity. However, little is known about the molecular mechanisms underlying alfalfa responses to salinity, especially the relative contribution of the two important components of osmotic and ionic stress.In this study, we constructed the first full-length transcriptome database for alfalfa root tips under continuous NaCl and mannitol treatments for 1, 3, 6, 12, and 24?h (three biological replicates for each time points, including the control group) via PacBio Iso-Seq. This resulted in the identification of 52,787 full-length transcripts, with an average length of 2551?bp. Global transcriptional changes in the same 33 stressed samples were then analyzed via BGISEQ-500 RNA-Seq. Totals of 8861 NaCl-regulated and 8016 mannitol-regulated differentially expressed genes (DEGs) were identified. Metabolic analyses revealed that these DEGs overlapped or diverged in the cascades of molecular networks involved in signal perception, signal transduction, transcriptional regulation, and antioxidative defense. Notably, several well characterized signalling pathways, such as CDPK, MAPK, CIPK, and PYL-PP2C-SnRK2, were shown to be involved in osmotic stress, while the SOS core pathway was activated by ionic stress. Moreover, the physiological shifts of catalase and peroxidase activity, glutathione and proline content were in accordance with dynamic transcript profiles of the relevant genes, indicating that antioxidative defense system plays critical roles in response to salinity stress.Overall, our study provides evidence that the response to salinity stress in alfalfa includes both osmotic and ionic components. The key osmotic and ionic stress-related genes are candidates for future studies as potential targets to improve resistance to salinity stress via genetic engineering.

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