Transcriptome-Assisted SNP Marker Discovery for Phytophthora infestans Resistance in Solanum lycopersicum L.

Late blight, caused by oomycetes Phytophthora infestans is one of the most challenging fungal diseases to manage in tomato plants (Solanum lycopersicum L.). Toward managing the disease, conventional breeding has successfully introgressed genetic loci conferring disease resistance from various wild relatives of tomato into commercial varieties. The cataloging of disease-associated SNP markers and a deeper understanding of disease-resistance mechanisms are needed to keep up with the demand for commercial varieties resistant against emerging pathogen strains. To this end, we performed transcriptome sequencing to evaluate the gene expression dynamics of tomato varieties, resistant and susceptible to Phytophthora infection. Further integrating the transcriptome dataset with large-scale public genomic data of varieties with known disease phenotypes, a panel of single nucleotide polymorphism (SNP) markers correlated with disease resistance was identified. These SNPs were then validated on 31 lines with contrasting phenotypes for late blight. The identified SNPs are located on genes coding for a putative cysteine-rich transmembrane module (CYSTM), Solyc09g098310, and a nucleotide-binding site-leucine-rich repeat protein, Solyc09g098100, close to the well-studied Ph-3 resistance locus known to have a role in plant immunity against fungal infections. The panel of SNPs generated by this study using transcriptome sequencing showing correlation with disease resistance across a broad set of plant material can be used as markers for molecular screening in tomato breeding.

ASV vs OTUs clustering: Effects on alpha, beta, and gamma diversities in microbiome metabarcoding studies.

In microbial community sequencing, involving bacterial ribosomal 16S rDNA or fungal ITS, the targeted genes are the basis for taxonomical assignment. The traditional bioinformatical procedure has for decades made use of a clustering protocol by which sequences are pooled into packages of shared percent identity, typically at 97%, to yield Operational Technical Units (OTUs). Progress in the data processing methods has however led to the possibility of minimizing technical sequencers errors, which were the main reason for the OTU choice, and to analyze instead the exact Amplicon Sequence Variants (ASV) which is a choice yielding much less agglomerated reads. We have tested the two procedures on the same 16S metabarcoded bacterial amplicons dataset encompassing a series of samples from 17 adjacent habitats, taken across a 700 meter-long transect of different ecological conditions unfolding in a gradient spanning from cropland, through meadows, forest and all successional transitions up to the seashore, within the same coastal area. This design allowed to scan a high biodiversity basin and to measure alpha, beta and gamma diversity of the area, to verify the effect of the bioinformatics on the same data as concerns the values of ten different ecological indexes and other parameters. Two levels of progressive OTUs clustering, (99% and 97%) were compared with the ASV data. The results showed that the OTUs clustering proportionally led to a marked underestimation of the ecological indicators values for species diversity and to a distorted behaviour of the dominance and evenness indexes with respect to the direct use of the ASV data. Multivariate ordination analyses resulted also sensitive in terms of tree topology and coherence. Overall, data support the view that reference-based OTU clustering carries several misleading disadvantageous biases, including the risk of missing novel taxa which are yet unreferenced in databases. Since its alternatives as de novo clustering have on the other hand drawbacks due to heavier computational demand and results comparability, especially for environmental studies which contain several yet uncharacterized species, the direct ASV based analysis, at least for prokaryotes, appears to warrant significand advantages in comparison to OTU clustering at every level of percent identity cutoff.

Metataxonomic analysis of endophytic bacteria of blackberry (Rubus ulmifolius Schott) across tissues and environmental conditions.

(1) Background: Endophytic bacteria represent an important component of plant wellness. They have been widely studied for their involvement in plant development and enhancement of stress tolerance. In this work, the endophytic communities of roots, stems, and leaves of blackberry (Rubus ulmifolius Schott) were studied in three different niches: natural, riverside, and human-impacted niches. (2) Results: The microbiome composition revealed that Sphingomonadaceae was the most abundant family in all samples, accounting for 9.4-45.8%. In contrast, other families seem to be linked to a specific tissue or niche. Families Microbacteriaceae and Hymenobacteraceae increased their presence in stem and leaf samples, while Burkholderiaceae abundance was important in riverside samples. Alpha and beta diversity analyses showed that root samples were the most diverse, and they gathered together in the same cluster, apart from the rest of the samples. (3) Conclusions: The analysis of the microbiome of R. ulmifolius plants revealed that the composition was essentially the same in different niches; the differences were primarily influenced by plant tissue factors with a core genome dominated by Sphingomonadaceae. Additionally, it was observed that R. ulmifolius can select its own microbiome, and this remains constant in all tissues evaluated regardless the niche of sampling.

The impact of milk storage temperatures on cheese quality and microbial communities at dairy processing plant scale.

Cheese production is an applied biotechnology whose proper outcome relies strictly on the complex interactive dynamics which unfold within defined microbial groups. These may start being active from the collection of milk and continue up to its final stages of maturation. One of the critical parameters playing a major role is the milk refrigeration temperature before pasteurization as it can affect the proportion of psychrotrophic taxa abundance in the total milk bacterial population. While a standard temperature of 4 °C is the common choice, due to its general growth control effect, it does have a potential drawback. This is due to the fact that some cold-tolerant genera present a proteolytic activity with uncompleted proliferation, which could negatively affect curd clotting and regular cheese maturation. Moreover, accidental thermal variations of milk before cheese-making, in a plus or minus direction, can occur both at farm collection sites and during transfer to dairy plant. This present research, directly commissioned by a major fresh cheese-producing company, includes an in-factory trial. In this trial, a gradient of temperatures from 4 °C to 13 °C, which were subsequently reversed, was purposely adopted to: (a) verify sensory alterations in the resulting product at different maturation stages, and, (b) analyze, in parallel, using DNA extraction and 16S-metabarcoding sequencing from the same samples, the presence, abundance and corresponding taxonomical identity of all the bacteria featured in communities found in milk and cheese samples. Overall, 1,714 different variants were detected and sorted into 394 identified taxa. Significant bacterial community shifts in cheese were observed in response to milk refrigeration temperature and subsequently associated with samples having altered scores in sensory panel tests. In particular, proteolytic psychrotrophes were outcompeted by Enterobacteriales and by other taxa at the peak temperature of 13 °C, but aggressively increased in the descent phases, upon the cooling down of milk to values of 7 °C. Relevant clues have been collected for better anticipation of thermal abuse effects or parameter variations allowing for improved handling of technical processing conditions by the cheese manufacturing industry.

Transcriptomic and physiological approaches to decipher cold stress mitigation exerted by brown-seaweed extract application in tomato.

Chilling temperatures represent a challenge for crop species originating from warm geographical areas. In this situation, biostimulants serve as an eco-friendly resource to mitigate cold stress in crops. Tomato (Solanum lycopersicum L.) is an economically important vegetable crop, but quite sensitive to cold stress, which it encounters in both open field and greenhouse settings. In this study, the biostimulant effect of a brown-seaweed extract (BSE) has been evaluated in tomato exposed to low temperature. To assess the product effects, physiological and molecular characterizations were conducted. Under cold stress conditions, stomatal conductance, net photosynthesis, and yield were significantly (p ≤ 0.05) higher in BSE-treated plants compared to the untreated ones. A global transcriptomic survey after BSE application revealed the impact of the BSE treatment on genes leading to key responses to cold stress. This was highlighted by the significantly enriched GO categories relative to proline (GO:0006560), flavonoids (GO:0009812, GO:0009813), and chlorophyll (GO:0015994). Molecular data were integrated by biochemical analysis showing that the BSE treatment causes greater proline, polyphenols, flavonoids, tannins, and carotenoids contents.The study highlighted the role of antioxidant molecules to enhance tomato tolerance to low temperature mediated by BSE-based biostimulant.

Bacterial endophytes as indicators of susceptibility to Cercospora Leaf Spot (CLS) disease in Beta vulgaris L.

The fungus Cercospora beticola causes Cercospora Leaf Spot (CLS) of sugar beet (Beta vulgaris L.). Despite the global importance of this disease, durable resistance to CLS has still not been obtained. Therefore, the breeding of tolerant hybrids is a major goal for the sugar beet sector. Although recent studies have suggested that the leaf microbiome composition can offer useful predictors to assist plant breeders, this is an untapped resource in sugar beet breeding efforts. Using Ion GeneStudio S5 technology to sequence amplicons from seven 16S rRNA hypervariable regions, the most recurring endophytes discriminating CLS-symptomatic and symptomless sea beets (Beta vulgaris L.ssp. maritima) were identified. This allowed the design of taxon-specific primer pairs to quantify the abundance of the most representative endophytic species in large naturally occurring populations of sea beet and subsequently in sugar beet breeding genotypes under either CLS symptomless or infection stages using qPCR. Among the screened bacterial genera, Methylobacterium and Mucilaginibacter were found to be significantly (p < 0.05) more abundant in symptomatic sea beets with respect to symptomless. In cultivated sugar beet material under CLS infection, the comparison between resistant and susceptible genotypes confirmed that the susceptible genotypes hosted higher contents of the above-mentioned bacterial genera. These results suggest that the abundance of these species can be correlated with increased sensitivity to CLS disease. This evidence can further prompt novel protocols to assist plant breeding of sugar beet in the pursuit of improved pathogen resistance.

Development of an SNP Assay for Marker-Assisted Selection of Soil-Borne Rhizoctonia solani AG-2-2-IIIB Resistance in Sugar Beet.

Rhizoctonia solani, causing Rhizoctonia crown and root rot, is a major risk to sugar beet (Beta vulgaris L.) cultivation. The development of resistant varieties accelerated by marker-assisted selection is a priority of breeding programs. We report the identification of a single-nucleotide polymorphism (SNP) marker linked to Rhizoctonia resistance using restriction site-associated DNA (RAD) sequencing of two geographically discrete sets of plant materials with different degrees of resistance/susceptibility to enable a wider selection of superior genotypes. The variant calling pipeline utilized SAMtools for variant calling and the resulting raw SNPs from RAD sequencing (15,988 and 22,439 SNPs) were able to explain 13.40% and 25.45% of the phenotypic variation in the two sets of material from different sources of origin, respectively. An association analysis was carried out independently on both the datasets and mutually occurring significant SNPs were filtered depending on their contribution to the phenotype using principal component analysis (PCA) biplots. To provide a ready-to-use marker for the breeding community, a systematic molecular validation of significant SNPs distributed across the genome was undertaken to combine high-resolution melting, Sanger sequencing, and rhAmp SNP genotyping. We report that RsBv1 located on Chromosome 6 (9,000,093 bp) is significantly associated with Rhizoctonia resistance (p < 0.01) and able to explain 10% of the phenotypic disease variance. The related SNP assay is thus ready for marker-assisted selection in sugar beet breeding for Rhizoctonia resistance.

Transcriptional and Physiological Analyses to Assess the Effects of a Novel Biostimulant in Tomato.

This work aimed to study the effects in tomato (Solanum lycopersicum L.) of foliar applications of a novel calcium-based biostimulant (SOB01) using an omics approach involving transcriptomics and physiological profiling. A calcium-chloride fertilizer (SOB02) was used as a product reference standard. Plants were grown under well-watered (WW) and water stress (WS) conditions in a growth chamber. We firstly compared the transcriptome profile of treated and untreated tomato plants using the software RStudio. Totally, 968 and 1,657 differentially expressed genes (DEGs) (adj-p-value < 0.1 and |log2(fold change)| ≥ 1) were identified after SOB01 and SOB02 leaf treatments, respectively. Expression patterns of 9 DEGs involved in nutrient metabolism and osmotic stress tolerance were validated by real-time quantitative reverse transcription PCR (RT-qPCR) analysis. Principal component analysis (PCA) on RT-qPCR results highlighted that the gene expression profiles after SOB01 treatment in different water regimes were clustering together, suggesting that the expression pattern of the analyzed genes in well water and water stress plants was similar in the presence of SOB01 treatment. Physiological analyses demonstrated that the biostimulant application increased the photosynthetic rate and the chlorophyll content under water deficiency compared to the standard fertilizer and led to a higher yield in terms of fruit dry matter and a reduction in the number of cracked fruits. In conclusion, transcriptome and physiological profiling provided comprehensive information on the biostimulant effects highlighting that SOB01 applications improved the ability of the tomato plants to mitigate the negative effects of water stress.

Classification of Grain Amaranths Using Chromosome-Level Genome Assembly of Ramdana, A. hypochondriacus.

In the age of genomics-based crop improvement, a high-quality genome of a local landrace adapted to the local environmental conditions is critically important. Grain amaranths produce highly nutritional grains with a multitude of desirable properties including C4 photosynthesis highly sought-after in other crops. For improving the agronomic traits of grain amaranth and for the transfer of desirable traits to dicot crops, a reference genome of a local landrace is necessary. Toward this end, our lab had initiated sequencing the genome of Amaranthus (A.) hypochondriacus (A.hyp_K_white) and had reported a draft genome in 2014. We selected this landrace because it is well adapted for cultivation in India during the last century and is currently a candidate for TILLING-based crop improvement. More recently, a high-quality chromosome-level assembly of A. hypochondriacus (PI558499, Plainsman) was reported. Here, we report a chromosome-level assembly of A.hyp_K_white (AhKP) using low-coverage PacBio reads, contigs from the reported draft genome of A.hyp_K_white, raw HiC data and reference genome of Plainsman (A.hyp.V.2.1). The placement of A.hyp_K_white on the phylogenetic tree of grain amaranths of known accessions clearly suggests that A.hyp_K_white is genetically distal from Plainsman and is most closely related to the accession PI619259 from Nepal (Ramdana). Furthermore, the classification of another accession, Suvarna, adapted to the local environment and selected for yield and other desirable traits, is clearly Amaranthus cruentus. A classification based on hundreds of thousands of SNPs validated taxonomy-based classification for a majority of the accessions providing the opportunity for reclassification of a few.

Association of Plasmodium berghei With the Apical Domain of Hepatocytes Is Necessary for the Parasite's Liver Stage Development.

Plasmodium parasites undergo a dramatic transformation during the liver stage of their life cycle, amplifying over 10,000-fold inside infected hepatocytes within a few days. Such a rapid growth requires large-scale interactions with, and manipulations of, host cell functions. Whereas hepatocyte polarity is well-known to be critical for liver function, little is presently known about its involvement during the liver stage of Plasmodium development. Apical domains of hepatocytes are critical components of their polarity machinery and constitute the bile canalicular network, which is central to liver function. Here, we employed high resolution 3-D imaging and advanced image analysis of Plasmodium-infected liver tissues to show that the parasite associates preferentially with the apical domain of hepatocytes and induces alterations in the organization of these regions, resulting in localized changes in the bile canalicular architecture in the liver tissue. Pharmacological perturbation of the bile canalicular network by modulation of AMPK activity reduces the parasite's association with bile canaliculi and arrests the parasite development. Our findings using Plasmodium-infected liver tissues reveal a host-Plasmodium interaction at the level of liver tissue organization. We demonstrate for the first time a role for bile canaliculi, a central component of the hepatocyte polarity machinery, during the liver stage of Plasmodium development.