30 research outputs found
Next-Generation Sequencing and Bioinformatics Approaches for Marker-Assisted Selection in Beta vulgaris L.
No full textL'obiettivo principale della tesi è stato quello di integrare dati fenotipici e di sequenziamento del DNA genomico utilizzando pipeline bioinformatiche innovative per l'identificazione di marcatori molecolari associati alla resistenza alla prefioritura, alla Cercospora beticola e alla Rhizoctonia solani in Beta vulgaris L. I marcatori selezionati sono stati ulteriormente validati utilizzando approcci di biologia molecolare.
L'introduzione della tesi riguarda l'origine e la domesticazione della Beta vulgaris L. e un briefing sulle prospettive del miglioramento genetico per la resistenza alla (i) prefioritura, (ii) alla Cercospora e (iii) alla Rhizoctonia.
Nel primo contributo della tesi, i marcatori molecolari associati alla resistenza alla prefioritura sono stati identificati mediante (a) la fenotipizzazione di 13 linee di barbabietola da zucchero in semina autunnale, (b) il restriction site-associated DNA (RAD) sequencing della linea con la percentuale di prefioritura più bassa, (c) l’analisi genome-wide association (GWAS) per identificare alleli associati con la tendenza alla prefioritura e (d) la validazione dei marcatori identificati utilizzando metodi di genotipizzazione di linee e varietà di barbabietola da zucchero.
Nel secondo contributo, l'obiettivo è stato quello di correlare l'abbondanza di specie batteriche endofitiche come fattore predittivo con la suscettibilità o resistenza alla Cercospora Leaf Spot (CLS) allo scopo di supportare i programmi di miglioramento genetico della barbabietola da zucchero. A tal fine, è stato analizzato il contenuto endofitico batterico della barbabietola marittima, il progenitore selvatico della barbabietola da zucchero, utilizzando individui CLS-sintomatici e sintomatici per il sequenziamento del gene rRNA 16s.
Nel terzo contributo riportiamo l’identificazione e la validazione di un marcatore molecolare associato alla resistenza alla Rhizoctonia. In primo luogo, abbiamo effettuato il restriction site-associated DNA (RAD) sequencing di materiali di barbabietola da zucchero dotati di diversi livelli di resistenza/suscettibilità alla Rhizoctonia. Successivamente, l'analisi bioinformatica dei dati di sequenziamento ha portato all'identificazione di loci associati alla resistenza alla Rhizoctonia.The main aim of this thesis was to integrate phenotypes and genomic DNA sequencing data using innovative bioinformatics pipelines to identify molecular markers associated with resistance to bolting, Cercospora beticola, and Rhizoctonia solani in Beta vulgaris L. The selected markers were further validated using molecular biology approaches.
The introduction of the thesis covers the origin and domestication of sugar beets, and a briefing on breeding perspectives of resistance to (i) bolting, (ii) Cercospora, and (iii) Rhizoctonia.
In the first contribution of the thesis, molecular markers associated with bolting resistance were identified by (a) phenotyping 13 sugar beet lines after autumnal sowing, (b) restriction site-associated DNA (RAD) sequencing of the line with the lowest bolting percentage, (c) establishing a genome-wide association study (GWAS) to identify favourable alleles related to low bolting tendency, and (d) validating the identified molecular markers using genotyping methods on sugar beet lines and varieties.
In the second contribution, the goal was to correlate endophytic bacterial abundance as a predictive factor associated with susceptibility or resistance to Cercospora Leaf Spot (CLS) with the purpose to exclusively assist selection in sugar beet breeding programs. To achieve this, the bacterial endophytic content of sea beet, the wild progenitor of sugar beet was analysed including both CLS-symptomatic and symptomatic individuals using 16s rRNA gene sequencing.
In the third contribution, we report the discovery and validation of a molecular marker associated with Rhizoctonia resistance. Firstly, we carried out restriction site-associated DNA (RAD) sequencing of sugar beet materials with different degrees of resistance/susceptibility to Rhizoctonia. Subsequently, the bioinformatics analysis of the sequencing data resulted in the identification of loci associated with Rhizoctonia resistance
Genomic analysis of ionome-related QTLs in Arabidopsis thaliana
No full textIonome 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
Transcriptome-Assisted SNP Marker Discovery for Phytophthora infestans Resistance in Solanum lycopersicum L.
No full textLate 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
Identification and validation of SNP markers linked to seed toxicity in Jatropha curcas L
No full textNot AvailableEdible/non-toxic varieties of Jatropha curcas L. are gaining increasing attention, providing both oil as biofuel feed stock 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.Not Availabl
Microbial Diversity of Reconstituted, Degraded, and Agricultural Soils Assessed by 16S rDNA Multi-Amplicon Sequencing
No full textQuantification of rhizomania virus by automated RNA isolation and PCR based methods in sugar beet
No full textUnlabelled: 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
Bacterial community composition in a soil carrying a resistance-breaking strain of the rhizomania virus BNYVV in comparison to standard soils
No full textDifference in composition and functional analysis of bacterial communities between Mytilus galloprovincialis gills and surrounding water in a brackish inshore bay, analyzed by 16S rDNA multi-amplicon sequencing
No full textBackground. Lagoons are important natural systems, with attractive favorable conditions for aquaculture production, such as shellfish cultivation. Despite their socio-economic relevance for human activity, information on the microbial diversity, community composition, and putative functions of gill-associated microbiota and seawater is still limited, particularly as regards the extent of specific taxa enrichment within the gills and the relative effects of the temporal and spatial variables. In this study, we used a 16S rDNA multi-amplicon sequencing approach using an Ion GeneStudio S5 System and a function prediction method (Functional Annotation of Prokaryotic Taxa (FAPROTAX), to inspect
the springtime dynamics of microbial communities and their inferred metabolic features in an Adriatic lagoon (Po Delta, Italy).
Results. Mussels and surrounding seawater were sampled in two rearing areas three times between April and June 2021. Sequencing results showed significant (p ≤ 0.05) differences in bacterial community composition and diversity between gills and seawater. Gills were dominated by the Methylobacterium-Methylorubrum and Burkholderia-Caballeronia-Paraburkholderia genera, while in seawater samples Izamaplasma, Planktomarina, and Candidatus Aquiluna were detected as being dominant. The microbiota composition did not differ significantly between the two rearing areas. The sampling time, although limited to a 3-month timeframe, instead revealed a structural variation of the bacterial profile both in gills and seawater for alpha and beta diversities respectively. The functional prediction analysis highlighted an overexpression of human gut-associated bacteria in relation to the season-related increase in seawater temperature.
Conclusions. These findings enhance our understanding of the differences between gill-associated and seawater microbiota composition and provide novel insights into the functions carried out by bacteria inhabiting these niches, as well as on the key host-symbiont relationships of bivalves in lagoon environments
