Publications

Jin Zhang, Rongbin Hu, Avinash Sreedasyam, Travis M Garcia, Anna Lipzen, Mei Wang, Pradeep Yerramsetty, Degao Liu, Vivian Ng, Jeremy Schmutz, John C Cushman, Anne M Borland, Asher Pasha, Nicholas J Provart, Jin-Gui Chen, Wellington Muchero, Gerald A Tuskan, Xiaohan Yang

GigaScience 2020 9(3):giaa018. 10.1093/gigascience/giaa018 PMID:32135007

Abstract

Background: Crassulacean acid metabolism (CAM), a specialized mode of photosynthesis, enables plant adaptation to water-limited environments and improves photosynthetic efficiency via an inorganic carbon-concentrating mechanism. Kalanchoë fedtschenkoi is an obligate CAM model featuring a relatively small genome and easy stable transformation. However, the molecular responses to light quality and intensity in CAM plants remain understudied.

Results: Here we present a genome-wide expression atlas of K. fedtschenkoi plants grown under 12 h/12 h photoperiod with different light quality (blue, red, far-red, white light) and intensity (0, 150, 440, and 1,000 μmol m-2 s-1) based on RNA sequencing performed for mature leaf samples collected at dawn (2 h before the light period) and dusk (2 h before the dark period). An eFP web browser was created for easy access of the gene expression data. Based on the expression atlas, we constructed a light-responsive co-expression network to reveal the potential regulatory relationships in K. fedtschenkoi. Measurements of leaf titratable acidity, soluble sugar, and starch turnover provided metabolic indicators of the magnitude of CAM under the different light treatments and were used to provide biological context for the expression dataset. Furthermore, CAM-related subnetworks were highlighted to showcase genes relevant to CAM pathway, circadian clock, and stomatal movement. In comparison with white light, monochrome blue/red/far-red light treatments repressed the expression of several CAM-related genes at dusk, along with a major reduction in acid accumulation. Increasing light intensity from an intermediate level (440 μmol m-2 s-1) of white light to a high light treatment (1,000 μmol m-2 s-1) increased expression of several genes involved in dark CO2 fixation and malate transport at dawn, along with an increase in organic acid accumulation.

Conclusions: This study provides a useful genomics resource for investigating the molecular mechanism underlying the light regulation of physiology and metabolism in CAM plants. Our results support the hypothesis that both light intensity and light quality can modulate the CAM pathway through regulation of CAM-related genes in K. fedtschenkoi.

Doll NM, Just J, Brunaud V, Caïus J, Grimault A, Depège-Fargeix N, Esteban E, Pasha A, Provart NJ, Ingram GC, Rogowsky PM, Widiez T

Plant Cell 2020 32(4):833-852. 10.1105/tpc.19.00756 PMID:32086366

Abstract

Seeds are complex biological systems comprising three genetically distinct tissues nested one inside another (embryo, endosperm, and maternal tissues). However, the complexity of the kernel makes it difficult to understand intercompartment interactions without access to spatially accurate information. Here, we took advantage of the large size of the maize (Zea mays) kernel to characterize genome-wide expression profiles of tissues at different embryo/endosperm interfaces. Our analysis identifies specific transcriptomic signatures in two interface tissues compared with whole seed compartments: the scutellar aleurone layer and the newly named endosperm adjacent to scutellum (EAS). The EAS, which appears around 9 d after pollination and persists for around 11 d, is confined to one to three endosperm cell layers adjacent to the embryonic scutellum. Its transcriptome is enriched in genes encoding transporters. The absence of the embryo in an embryo specific mutant can alter the expression pattern of EAS marker genes. The detection of cell death in some EAS cells together with an accumulation of crushed cell walls suggests that the EAS is a dynamic zone from which cell layers in contact with the embryo are regularly eliminated and to which additional endosperm cells are recruited as the embryo grows.

Bradley Laflamme, Marcus M. Dillon1, Alexandre Martel, Renan N. D. Almeida, Darrell Desveaux, David S. Guttman

Science 2020 367(6479):763-768. 10.1126/science.aax4079 PMID:32054757

Abstract

Effector-triggered immunity (ETI), induced by host immune receptors in response to microbial effectors, protects plants against virulent pathogens. However, a systematic study of ETI prevalence against species-wide pathogen diversity is lacking. We constructed the Pseudomonas syringae Type III Effector Compendium (PsyTEC) to reduce the pan-genome complexity of 5127 unique effector proteins, distributed among 70 families from 494 strains, to 529 representative alleles. We screened PsyTEC on the model plant Arabidopsis thaliana and identified 59 ETI-eliciting alleles (11.2%) from 19 families (27.1%), with orthologs distributed among 96.8% of P. syringaestrains. We also identified two previously undescribed host immune receptors, including CAR1, which recognizes the conserved effectors AvrE and HopAA1, and found that 94.7% of strains harbor alleles predicted to be recognized by either CAR1 or ZAR1.

Ferrari C, Shivhare D, Hansen BO, Pasha A, Esteban E, Provart NJ, Kragler F, Fernie A, Tohge T, Mutwil M.

Plant Cell 2020 32(4):853-870. 10.1105/tpc.19.00780 PMID:31988262

Abstract

Selaginella moellendorffii is a representative of the lycophyte lineage that is studied to understand the evolution of land plant traits such as the vasculature, leaves, stems, roots, and secondary metabolism. However, only a few studies have investigated the expression and transcriptional coordination of Selaginella genes, precluding us from understanding the evolution of the transcriptional programs behind these traits. We present a gene expression atlas comprising all major organs, tissue types, and the diurnal gene expression profiles for S. moellendorffii We show that the transcriptional gene module responsible for the biosynthesis of lignocellulose evolved in the ancestor of vascular plants and pinpoint the duplication and subfunctionalization events that generated multiple gene modules involved in the biosynthesis of various cell wall types. We demonstrate how secondary metabolism is transcriptionally coordinated and integrated with other cellular pathways. Finally, we identify root-specific genes and show that the evolution of roots did not coincide with an increased appearance of gene families, suggesting that the development of new organs does not coincide with increased fixation of new gene functions. Our updated database at conekt.plant.tools represents a valuable resource for studying the evolution of genes, gene families, transcriptomes, and functional gene modules in the Archaeplastida kingdom.

Alexandre Martel, Timothy Lo, Darrell Desveaux, and David S. Guttman

MPMI 2020 33(3):394-401. 10.1094/MPMI-10-19-0295-TA PMID:31851574

Abstract

An understanding of how biological diversity affects plant-microbe interactions is becoming increasingly important, particularly with respect to components of the pathogen effector arsenal and the plant immune system. Although technological improvements have greatly advanced our ability to examine molecular sequences and interactions, relatively few advances have been made that facilitate high-throughput, in vivo pathology screens. Here, we present a high-throughput, microplate-based, nondestructive seedling pathology assay, and apply it to identify Arabidopsis thaliana effector-triggered immunity (ETI) responses against Pseudomonas syringae type III secreted effectors. The assay was carried out in a 48-well microplate format with spray inoculation, and disease symptoms were quantitatively recorded in a semiautomated manner, thereby greatly reducing both time and costs. The assay requires only slight modifications of common labware and uses no proprietary software. We validated the assay by recapitulating known ETI responses induced by P. syringae in Arabidopsis. We also demonstrated that we can quantitatively differentiate responses from a diversity of plant genotypes grown in the same microplate. Finally, we showed that the results obtained from our assay can be used to perform genome-wide association studies to identify host immunity genes, recapitulating results that have been independently obtained with mature plants.

Zhang T, Zhou G, Goring DR, Liang X, Macgregor S, Dai C, Wen J, Yi B, Shen J, Tu J, Fu T, Ma C.

Plants 2019 8(12):570. 10.3390/plants8120570 PMID:31817214

Abstract

Brassicaceae species employ both self-compatibility and self-incompatibility systems to regulate post-pollination events. Arabidopsis halleri is strictly self-incompatible, while the closely related Arabidopsis thaliana has transitioned to self-compatibility with the loss of functional S-locus genes during evolution. The downstream signaling protein, ARC1, is also required for the self-incompatibility response in some Arabidopsis and Brassica species, and its gene is deleted in the A. thaliana genome. In this study, we attempted to reconstitute the SCR-SRK-ARC1 signaling pathway to restore self-incompatibility in A. thaliana using genes from A. halleri and B. napus, respectively. Several of the transgenic A. thaliana lines expressing the A. halleri SCR₁₃-SRK₁₃-ARC1 transgenes displayed self-incompatibility, while all the transgenic A. thaliana lines expressing the B. napusSCR₁-SRK₁-ARC1 transgenes failed to show any self-pollen rejection. Furthermore, our results showed that the intensity of the self-incompatibility response in transgenic A. thaliana plants was not associated with the expression levels of the transgenes. Thus, this suggests that there are differences between the Arabidopsis and Brassica self-incompatibility signaling pathways, which perhaps points to the existence of other factors downstream of B. napus SRK that are absent in Arabidopsis species.

Elbassiouny AA, Lovejoy NR, Chang BSW

Philios Trans R Soc Lond B Biol Sci 2020 375(1790):20190179. 10.1098/rstb.2019.0179 PMID:31787042

Abstract

The ability to generate and detect electric fields has evolved in several groups of fishes as a means of communication, navigation and, occasionally, predation. The energetic burden required can account for up to 20% of electric fishes’ daily energy expenditure. Despite this, molecular adaptations that enable electric fishes to meet the metabolic demands of bioelectrogenesis remain unknown. Here, we investigate the molecular evolution of the mitochondrial oxidative phosphorylation (OXPHOS) complexes in the two most diverse clades of weakly electric fishes-South American Gymnotiformes and African Mormyroidea, using codon-based likelihood approaches. Our analyses reveal that although mitochondrial OXPHOS genes are generally subject to strong purifying selection, this constraint is significantly reduced in electric compared to non-electric fishes, particularly for complexes IV and V. Moreover, analyses of concatenated mitochondrial genes show strong evidence for positive selection in complex I genes on the two branches associated with the independent evolutionary origins of electrogenesis. These results suggest that adaptive evolution of proton translocation in the OXPHOS cellular machinery may be associated with the evolution of bioelectrogenesis. Overall, we find striking evidence for remarkably similar effects of electrogenesis on the molecular evolution of mitochondrial OXPHOS genes in two independently derived clades of electrogenic fishes. This article is part of the theme issue ‘Linking the mitochondrial genotype to phenotype: a complex endeavour’.

Kreiner JM, Giacomini DA, Bemm F, Waithaka B, Regalado J, Lanz C, Hildebrandt J, Sikkema PH, Tranel PJ, Weigel D, Stinchcombe JR, Wright SI.

Proc Natl Acad Sci USA 2019 116(42):21076-21084. 10.1073/pnas.1900870116 PMID:31570613

Abstract

The selection pressure exerted by herbicides has led to the repeated evolution of herbicide resistance in weeds. The evolution of herbicide resistance on contemporary timescales in turn provides an outstanding opportunity to investigate key questions about the genetics of adaptation, in particular the relative importance of adaptation from new mutations, standing genetic variation, or geographic spread of adaptive alleles through gene flow. Glyphosate-resistant Amaranthus tuberculatus poses one of the most significant threats to crop yields in the Midwestern United States, with both agricultural populations and herbicide resistance only recently emerging in Canada. To understand the evolutionary mechanisms driving the spread of resistance, we sequenced and assembled the A. tuberculatus genome and investigated the origins and population genomics of 163 resequenced glyphosate-resistant and susceptible individuals from Canada and the United States. In Canada, we discovered multiple modes of convergent evolution: in one locality, resistance appears to have evolved through introductions of preadapted US genotypes, while in another, there is evidence for the independent evolution of resistance on genomic backgrounds that are historically nonagricultural. Moreover, resistance on these local, nonagricultural backgrounds appears to have occurred predominantly through the partial sweep of a single haplotype. In contrast, resistant haplotypes arising from the Midwestern United States show multiple amplification haplotypes segregating both between and within populations. Therefore, while the remarkable species-wide diversity of A. tuberculatus has facilitated geographic parallel adaptation of glyphosate resistance, more recently established agricultural populations are limited to adaptation in a more mutation-limited framework.

Scott BM, Wybenga-Groot LE, McGlade CJ, Heon E, Peisajovich SG, Chang BSW

SLAS Discovery 2019 24(10):969-977. 10.1177/2472555219875934 PMID:31556794

Abstract

Retinitis pigmentosa (RP) is a degenerative retinal disease, often caused by mutations in the G-protein-coupled receptor rhodopsin. The majority of pathogenic rhodopsin mutations cause rhodopsin to misfold, including P23H, disrupting its crucial ability to respond to light. Previous screens to discover pharmacological chaperones of rhodopsin have primarily been based on rescuing rhodopsin trafficking and localization to the plasma membrane. Here, we present methods utilizing a yeast-based assay to screen for compounds that rescue the ability of rhodopsin to activate an associated downstream G-protein signaling cascade. We engineered a yeast strain in which human rhodopsin variants were genomically integrated, and were able to demonstrate functional coupling to the yeast mating pathway, leading to fluorescent protein expression. We confirmed that a known pharmacological chaperone, 9-cis retinal, could partially rescue light-dependent activation of a disease-associated rhodopsin mutation (P23H) expressed in yeast. These novel yeast strains were used to perform a phenotypic screen of 4280 compounds from the LOPAC1280 library and a peptidomimetic library, to discover novel pharmacological chaperones of rhodopsin. The fluorescence-based assay was robust in a 96-well format, with a Z’ factor of 0.65 and a signal-to-background ratio of above 14. One compound was selected for additional analysis, but it did not appear to rescue rhodopsin function in yeast. The methods presented here are amenable to future screens of small-molecule libraries, as they are robust and cost-effective. We also discuss how these methods could be further modified or adapted to perform screens of more compounds in the future.

Lu AX, Kraus OZ, Cooper S, Moses AM

PLoS Comput Biol 2019 15(9):e1007348. 10.1371/journal.pcbi.1007348 PMID:31479439

Abstract

Cellular microscopy images contain rich insights about biology. To extract this information, researchers use features, or measurements of the patterns of interest in the images. Here, we introduce a convolutional neural network (CNN) to automatically design features for fluorescence microscopy. We use a self-supervised method to learn feature representations of single cells in microscopy images without labelled training data. We train CNNs on a simple task that leverages the inherent structure of microscopy images and controls for variation in cell morphology and imaging: given one cell from an image, the CNN is asked to predict the fluorescence pattern in a second different cell from the same image. We show that our method learns high-quality features that describe protein expression patterns in single cells both yeast and human microscopy datasets. Moreover, we demonstrate that our features are useful for exploratory biological analysis, by capturing high-resolution cellular components in a proteome-wide cluster analysis of human proteins, and by quantifying multi-localized proteins and single-cell variability. We believe paired cell inpainting is a generalizable method to obtain feature representations of single cells in multichannel microscopy images.