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.

Brown Seaweed Extract (BSE) Application Influences Auxin- and ABA-Related Gene Expression, Root Development, and Sugar Yield in Beta vulgaris L.

The molecular and phenotypic effects of a brown seaweed extract (BSE) were assessed in sugar beet (Beta vulgaris L.). Transcript levels of BSE-treated and untreated plants were studied by RNA-seq and validated by quantitative real-time PCR analysis (RT-qPCR). Root morphology, sugar yield, and processing quality traits were also analyzed to better elucidate the treatment effects. RNA-seq revealed 1019 differentially expressed genes (DEGs) between the BSE-treated and untreated plants. An adjusted p-value < 0.1 and an absolute value of log2 (fold change) greater than one was used as criteria to select the DEGs. Gene ontology (GO) identified hormone pathways as an enriched biological process. Six DEGs involved in auxin and ABA pathways were validated using RT-qPCR. The phenotypic characterization indicated that BSE treatment led to a significant increase (p < 0.05) in total root length and the length of fine roots of plants grown under hydroponics conditions. The sugar yield of plants grown under field conditions was higher (p < 0.05) in the treated field plots compared with the control treatment, without impacting the processing quality. Our study unveiled the relevant effects of BSE application in regulating auxin- and ABA-related gene expression and critical traits related to sugar beet development and yield.

A dual-omics approach for profiling plant responses to biostimulant applications under controlled and field conditions.

A comprehensive approach using phenomics and global transcriptomics for dissecting plant response to biostimulants is illustrated with tomato (Solanum lycopersicum cv. Micro-Tom and Rio Grande) plants cultivated in the laboratory, greenhouse, and open field conditions. Biostimulant treatment based on an Ascophyllum nodosum extract (ANE) was applied as a foliar spray with two doses (1 or 2 l ha-1) at three different phenological stages (BBCH51, BBCH61, and BBCH65) during the flowering phase. Both ANE doses resulted in greater net photosynthesis rate, stomatal conductance, and fruit yield across all culture conditions. A global transcriptomic analysis of leaves from plants grown in the climate chamber, revealed a greater number of differentially expressed genes (DEGs) with the low ANE dose compared to the greater one. The second and third applications induced broader transcriptome changes compared to the first one, indicating a cumulative treatment effect. The functional enrichment analysis of DEGs highlighted pathways related to stimulus-response and photosynthesis, consistent with the morpho-physiological observations. This study is the first comprehensive dual-omics approach for profiling plant responses to biostimulants across three different culture conditions.

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.

Genomic analysis of ionome-related QTLs in Arabidopsis thaliana.

Ionome contributes to maintain cell integrity and acts as cofactors for catalyzing regulatory pathways. Identifying ionome contributing genomic regions provides a practical framework to dissect the genetic architecture of ionomic traits for use in biofortification. Meta-QTL (MQTL) analysis is a robust method to discover stable genomic regions for traits regardless of the genetic background. This study used information of 483 QTLs for ionomic traits identified from 12 populations for MQTL analysis in Arabidopsis thaliana. The selected QTLs were projected onto the newly constructed genetic consensus map and 33 MQTLs distributed on A. thaliana chromosomes were identified. The average confidence interval (CI) of the drafted MQTLs was 1.30 cM, reduced eight folds from a mean CI of 10.88 cM for the original QTLs. Four MQTLs were considered as stable MQTLs over different genetic backgrounds and environments. In parallel to the gene density over the A. thaliana genome, the genomic distribution of MQTLs over the genetic and physical maps indicated the highest density at non- and sub-telomeric chromosomal regions, respectively. Several candidate genes identified in the MQTLs intervals were associated with ion transportation, tolerance, and homeostasis. The genomic context of the identified MQTLs suggested nine chromosomal regions for Zn, Mn, and Fe control. The QTLs for potassium (K) and phosphorus (P) were the most frequently co-located with Zn (78.3%), Mn (76.2%), and Fe (88.2% and 70.6%) QTLs. The current MQTL analysis demonstrates that meta-QTL analysis is cheaper than, and as informative as genome-wide association study (GWAS) in refining the known QTLs.

SNP Alleles Associated With Low Bolting Tendency in Sugar Beet.

The identification of efficient molecular markers related to low bolting tendency is a priority in sugar beet (Beta vulgaris L.) breeding. This study aimed to identify SNP markers associated with low bolting tendency by establishing a genome-wide association study. An elaborate 3-year field trial comprising 13 sugar beet lines identified L14 as the one exhibiting the lowest bolting tendency along with an increased survival rate after autumnal sowing. For SNP discovery following phenotyping, contrasting phenotypes of 24 non-bolting and 15 bolting plants of the L14 line were sequenced by restriction site-associated DNA sequencing (RAD-seq). An association model was established with a set of 10,924 RAD-based single nucleotide polymorphism (SNP) markers. The allelic status of the most significantly associated SNPs ranked based on their differential allelic status between contrasting phenotypes (p < 0.01) was confirmed on three different validation datasets comprising diverse sugar beet lines and varieties adopting a range of SNP detection technologies. This study has led to the identification of SNP_36780842 and SNP_48607347 linked to low bolting tendency and can be used for marker-assisted breeding and selection in sugar beet.

Endophytic Microbiome Responses to Sulfur Availability in Beta vulgaris (L.).

Sulfur is an essential plant macronutrient, and its adequate supply allows an efficient root storage and sugar extractability in sugar beets (Beta vulgaris L.). In this study, we investigated the effect of changes in sulfur availability on the endophytic community structure of sugar beets. Plants were hydroponically grown in a complete nutrient solution (S-supplied), a nutrient solution without MgSO4 (S-deprived), and a nutrient solution without MgSO4 for six days and resupplied with 100 µM MgSO4 for 48 h (S-resupplied). The sulfur status was monitored by inductively coupled plasma ICP-OES, and combustion analysis together with the evaluation of microRNA395 as a biomarker for sulfate status. Metabarcoding of the bacterial 16S rRNA gene was carried out in order to determine leaf endophytic community structure. The Shannon diversity index significantly differed (p < 0.05) between sulfate-supplied and sulfate-deprived seedlings. Validation by Real-Time PCR showed a significant increase (p < 0.05) of Burkholderia spp. in sulfate-deprived plants as compared to sulfate-supplied ones. The study sheds new light on the effects of nutrient deficiency on the microbiome of sugar beet plants.

Novel Effects of Leonardite-Based Applications on Sugar Beet.

The present study aimed to explore the effects of foliar application of a leonardite-based product on sugar beet (Beta vulgaris L.) plants grown in the field. The approach concerned the evaluation of the community compositional structure of plant endophytic bacteria through a metabarcoding approach, the expression level of a gene panel related to hormonal metabolism and signaling, and the main sugar beet productivity traits. Results indicated that plants treated with leonardite (dosage of 2,000 ml ha-1, dilution 1:125, 4 mg C l-1) compared with untreated ones had a significant increase (p < 0.05) in (i) the abundance of Oxalicibacterium spp., recognized to be an endophyte bacterial genus with plant growth-promoting activity; (ii) the expression level of LAX2 gene, coding for auxin transport proteins; and (iii) sugar yield. This study represents a step forward to advance our understanding of the changes induced by leonardite-based biostimulant in sugar beet.

Quantification of rhizomania virus by automated RNA isolation and PCR based methods in sugar beet.

Rhizomania is a grave disease affecting sugar beet (Beta vulgaris L.). It is caused by the Beet Necrotic Yellow Vein Virus (BNYVV), an RNA virus transmitted by the plasmodiophorid vector Polymyxa betae. Genetic resistance to the virus has been accomplished mostly using phenotype-genotype association studies. As yet, the most convenient method to ascertain plant resistance has been the quantification of viral titer in roots through the ELISA test. This method is particularly time-consuming and clashes with the necessities of modern plant breeding. Here, we propose an alternative and successful phenotyping method based on the automatic extraction of the viral RNA from sugar beet roots and its relative and absolute quantification by quantitative real-time PCR (qRT-PCR) and digital PCR (dPCR), respectively. Such a method enables an improved standardization of the study, as well as an accurate quantification of the virus also in those samples presenting low virus titer, with respect to the ELISA test. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13337-021-00674-7.

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.

A Near-Chromosome Level Genome Assembly of Anopheles stephensi.

Malaria remains a major healthcare risk to growing economies like India, and a chromosome-level reference genome of Anopheles stephensi is critical for successful vector management and understanding of vector evolution using comparative genomics. We report chromosome-level assemblies of an Indian strain, STE2, and a Pakistani strain SDA-500 by combining draft genomes of the two strains using a homology-based iterative approach. The resulting assembly IndV3/PakV3 with L50 of 9/12 and N50 6.3/6.9 Mb had scaffolds long enough for building 90% of the euchromatic regions of the three chromosomes, IndV3s/PakV3s, using low-resolution physical markers and enabled the generation of the next version of genome assemblies, IndV4/PakV4, using HiC data. We have validated these assemblies using contact maps against publicly available HiC raw data from two strains including STE2 and another lab strain of An. stephensi from UCI and compare the quality of the assemblies with other assemblies made available as preprints since the submission of the manuscript. We show that the IndV3s and IndV4 assemblies are sensitive in identifying a homozygous 2Rb inversion in the UCI strain and a 2Rb polymorphism in the STE2 strain. Multiple tandem copies of CYP6a14, 4c1, and 4c21 genes, implicated in insecticide resistance, lie within this inversion locus. Comparison of assembled genomes suggests a variation of 1 in 81 positions between the UCI and STE2 lab strains, 1 in 82 between SDA-500 and UCI strain, and 1 in 113 between SDA-500 and STE2 strains of An. stephensi, which are closer than 1 in 68 variations among individuals from two other lab strains sequenced and reported here. Based on the developmental transcriptome and orthology of all the 54 olfactory receptors (ORs) to those of other Anopheles species, we identify an OR with the potential for host recognition in the genus Anopheles. A comparative analysis of An. stephensi genomes with the completed genomes of a few other Anopheles species suggests limited inter-chromosomal gene flow and loss of synteny within chromosomal arms even among the closely related species.

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.

Genotyping by RAD Sequencing Analysis Assessed the Genetic Distinctiveness of Experimental Lines and Narrowed Down the Genomic Region Responsible for Leaf Shape in Endive (Cichorium endivia L.).

The characterization of genetic diversity in elite breeding stocks is crucial for the registration and protection of new varieties. Moreover, experimental population structure analysis and information about the genetic distinctiveness of commercial materials are essential for crop breeding programs. The purpose of our research was to assess the genetic relationships of 32 endive (Cichorium endivia L.) breeding lines, 18 from var. latifolium (escarole) and 14 from var. crispum (curly), using heterologous Cichorium intybus-derived simple sequence repeats (SSR) markers and single-nucleotide polymorphisms (SNP) markers. We found that 14 out of 29 SSR markers were successfully amplified, but only 8 of them were related to polymorphic loci. To overcome the limitation of the low number of informative SSR marker loci, an alternative SNP-based approach was employed. The 4621 SNPs produced by a restriction site-associated DNA marker sequencing approach were able to fully discriminate the 32 endive accessions; most importantly, as many as 50 marker loci were found to distinguish the curly group from the escarole group. Interestingly, 24 of the marker loci mapped within a peripheral segment of chromosome 8 of lettuce (Lactuca sativa L.), spanning a chromosomal region of 49.6 Mb. Following Sanger sequencing-based validation, three genes were determined to carry nonsynonymous SNPs, and one of them matched a putative ortholog of AtELP1, subunit 1 of the Elongator complex. Considering that several previously characterized Elongator complex subunit mutants exhibited elongated and/or curly leaf phenotypes, this gene should be taken into consideration for a better understanding of the underlying mechanism controlling leaf shape in endive.

Identification and validation of SNP markers linked to seed toxicity in Jatropha curcas L.

Edible/non-toxic varieties of Jatropha curcas L. are gaining increasing attention, providing both oil as biofuel feedstock or even as edible oil and the seed kernel meal as animal feed ingredient. They are a viable alternative to the limitation posed by the presence of phorbol esters in toxic varieties. Accurate genotyping of toxic/non-toxic accessions is critical to breeding management. The aim of this study was to identify SNP markers linked to seed toxicity in J. curcas. For SNP discovery, NGS technology was used to sequence the whole genomes of a toxic and non-toxic parent along with a bulk of 51 toxic and 30 non-toxic F2 plants. To ascertain the association between SNP markers and seed toxicity trait, candidate SNPs were genotyped on 672 individuals segregating for seed toxicity and two collections of J. curcas composed of 96 individuals each. In silico SNP discovery approaches led to the identification of 64 candidate SNPs discriminating non-toxic and toxic samples. These SNPs were mapped on Chromosome 8 within the Linkage Group 8 previously identified as a genomic region important for phorbol ester biosynthesis. The association study identified two new SNPs, SNP_J22 and SNP_J24 significantly linked to low toxicity with R2 values of 0.75 and 0.54, respectively. Our study released two valuable SNP markers for high-throughput, marker-assisted breeding of seed toxicity in J. curcas.

A novel molecular mechanism for a long non-coding RNA PCAT92 implicated in prostate cancer.

The role of many lncRNAs in cancer remains elusive including that for a Prostate Cancer Associated Transcript 92 (PCAT92). PCAT92 shares the locus on chromosome 13 with ABCC4 gene, known to be implicated in prostate cancer. It has been shown that PCAT92 and ABCC4 are up-regulated in prostate cancer samples from multiple transcriptome datasets. Among the prostate cancer cell-lines LNCaP showed maximum overexpression of PCAT92 compared to control cell-line RWPE-1. We have shown that knockdown of PCAT92 in LNCaP cells reduces cell viability and proliferation and down-regulates ABCC4 transcript/protein expression. The shared region between PCAT92 and ABCC4 has a binding site for an oncogenic transcription factor (ZIC2) which is also upregulated in the majority of datasets studied here. ZIC2 binding to the predicted ABCC4 promoter has been confirmed using pull-down assay. Interestingly, under PCAT92 knockdown condition, there is a reduction in the ZIC2 binding to ABCC4 promoter indicating the potential involvement of PCAT92 in the recruitment of ZIC2. We have identified distinct regions on PCAT92 with potential to bind to ZIC2 non-DNA binding Zinc-finger domain and potential for triplex formation near ABCC4 promoter region, which have been experimentally validated. Together, these observations and localization in the nucleus suggests that PCAT92 may play a role in prostate cancer by increasing the local concentration of ZIC2 by forming RNA-DNA triplex near ABCC4 promoter thus helping in recruitment of ZIC2 for ABCC4 regulation.

A novel loss-of-function mutation in HACE1 is linked to a genetic disorder in a patient from India.

A large number of congenital disorders are very rare and localized to rural areas in India, a country that practices both endogamy and consanguinity. Recent advances in genomics can aid in the identification of causative genomic elements when exploring therapeutic interventions and developing neonatal screening to assign novel functions. Here, we report a novel loss-of-function mutation (p.Trp370*) in the HACE1 gene that is associated with a rare congenital neurodevelopmental disorder in a boy from a remote village in southern India.

TCF7L2 rs7903146 polymorphism and diabetic nephropathy association is not independent of type 2 diabetes--a study in a south Indian population and meta-analysis.

Diabetic nephropathy (DN) is a chronic microangiopathic complication of both type 1 (T1DM) and type 2 diabetes mellitus (T2DM). The TCF7L2 gene has been reported to be associated with type 2 diabetes risk. We aimed to investigate the impact of TCF7L2 gene on the susceptibility of T2DM and DN in a south Indian population. Plus to evaluate the association of rs7903146 in the TCF7L2 gene with T2DM in the Indian population. The subjects recruited for this included 55 diabetic cases with diabetic nephropathy, 68 diabetic cases without nephropathy, and 82 non-diabetic healthy controls. Genomic DNA was isolated from blood and genotyping of TCF7L2 rs7903146 was performed by PCR-RFLP analysis. A literature survey was carried out into the effect of rs7903146 on genetic susceptibility to T2DM in Indian populations and we then performed a meta-analysis in order to evaluate its association with T2DM. Analysis of TCF7L2 rs7903146 in normal controls and diabetics with or without nephropathy demonstrated that the 'T' allele is associated with both diabetes (p = 0.049) and DN (p = 0.024), but this association is not independent of T2DM. Meta-analysis showed that the mutant allele and genotypes are associated with T2DM in Indian populations. In summary, a significant association exists between the 'T' allele and DN, but this association is not independent of T2DM. Pooled meta-analysis of studies on rs7903146 and T2DM confirmed that rs7903146 is significantly associated with susceptibility to T2DM in Indian populations.