Gerardo D. L. Cervigni

Hygromycin resistance as an efficient selectable marker for wheat stable transformation.

SummaryA highly efficient method for stable wheat transformation using hygromycin resistance as a selectable marker is described. Young embryogenic calli growing from immature wheat embryos were transformed using a gunpowder-driven microparticle accelerator. Transgenic wheat plants were determined by PCR amplification of transgene fragments and confirmed by Southern hybridization, activity of the transgene expression and by analysis of the progeny. The hpt gene was as good as or a better selectable marker than the bar gene with an average efficiency (number of transgenic plants relative to the number of bombarded calli) of 5.5% compared with 2.6% for the bar gene.

Stable wheat transformation obtained without selectable markers

Transgenic wheat plants without the selectable marker gene were obtained either in the presence or in the absence of selective pressure during the transformation protocol. When using hygromycin as selective agent in a co-transformation experiment involving a mixture of plasmids pGL2, containing the hpt gene, and pAI1Gus, containing the uidA gene, 3 out of 19 transgenic wheat plants had the uidA gene alone as shown by Southern blots. The gene was transmitted to the progeny following Mendelian rules. Segregation and loss of the selectable marker gene was also found in three out of six events from other experiments where high-molecular-weight glutenin genes were expressed or over-expressed. On the other hand, in 7 experiments where no selective pressure was applied and that involved 1016 bombarded explants, 23 transgenic wheat plants were obtained. The uidA gene was stably integrated as suggested by its transmission to the progeny.

Frequencies and variation in cytosine methylation patterns in diploid and tetraploid cytotypes of Paspalum notatum

Paspalum notatum Flügge is a grass species organized as an agamic complex. The objective of the current research was to survey the frequencies and variation of cytosine methylation at CCGG sequences in diploid and tetraploid genotypes, and to determine the occurrence of methylation changes associated with tetraploidization by using methylation-sensitive amplification polymorphism (MSAP) markers. No differences were found in the average proportions of methylated CCGG sites between cytotypes, but methylation patterns were significantly more variable in tetraploids. In both groups of plants, epigenetic and non-epigenetic variation correlated significantly when compared by Mantel tests. The evaluation of 159 common MSAP markers showed that 18.86 % of them differed in their methylation status in the different ploidies. Dendrogram analysis, reflecting epigenetic distances, showed that the four diploids and one experimentally-obtained sexually-reproducing tetraploid, grouped together. MSAP analysis performed on a diploid plant and its autotetraploid derivative showed that new epialleles emerged after tetraploidization. Sequencing of several MASP markers showed homologies with low copy genes, non-coding sequences and transposon/retrotransposon elements.

High frequency somatic embryogenesis with a pampeana-derived genotype of alfalfa (Medicago sativa L.)

SummarySomatic embryos of genotype R11 of the alfalfa variety Pampeana were produced from embryogenic calli derived from leaf sections. They were induced by an auxin shock and its development was attempted on six different media. The best condition for somatic embryo production was inducing callus on MS medium plus 10 μM 2,4-D and 4,6 μM KIN and transferring them, after the auxin shock, to MS with 10–20 mM NH4+ and 30 mM proline. More than 500 somatic embryos per plate were produced. Embryos were grown to plants on MS or half strength MS media and all regenerated plants resembled the original R11 genotype. This technique could be useful in alfalfa Pampeana improvement using genetic modification.

Applications of Machine Learning in Breeding for Stress Tolerance in Maize

Corn is one of the world’s most important cereals and a major source of calories for humanity, along with rice and wheat. Climate change and the use of marginal land for crop production require the development of genotypes adapted to stressful environments, particularly drought tolerant plants. Among the new technologies currently available for accelerate the releasing of new genotypes there is an emerging discipline called Machine Learning (ML). A primary goal of ML algorithms is to automatically learn to recognize complex patterns and make intelligent decisions based on data. This work reviews several strategic applications of ML in maize breeding. Quantitative trait loci mapping, heterotic group assignment and the popular genome-wide selection are some of the key areas currently addressed by the literature. Results are encouraging and propose ML algorithms as a valuable alternative to traditional statistical techniques applied in maize, even the more recently introduced linear mixed models.

Main and epistatic QTL analyses for Sclerotinia Head Rot resistance in sunflower

Sclerotinia Head Rot (SHR), a disease caused by Sclerotinia sclerotiorum, is one of the most limiting factors in sunflower production. In this study, we identified genomic loci associated with resistance to SHR to support the development of assisted breeding strategies. We genotyped 114 Recombinant Inbred Lines (RILs) along with their parental lines (PAC2 –partially resistant–and RHA266 –susceptible–) by using a 384 single nucleotide polymorphism (SNP) Illumina Oligo Pool Assay to saturate a sunflower genetic map. Subsequently, we tested these lines for SHR resistance using assisted inoculations with S. sclerotiorum ascospores. We also conducted a randomized complete-block assays with three replicates to visually score disease incidence (DI), disease severity (DS), disease intensity (DInt) and incubation period (IP) through four field trials (2010–2014). We finally assessed main effect quantitative trait loci (M-QTLs) and epistatic QTLs (E-QTLs) by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM), respectively. As a result of this study, the improved map incorporates 61 new SNPs over candidate genes. We detected a broad range of narrow sense heritability (h2) values (1.86–59.9%) as well as 36 M-QTLs and 13 E-QTLs along 14 linkage groups (LGs). On LG1, LG10, and LG15, we repeatedly detected QTLs across field trials; which emphasizes their putative effectiveness against SHR. In all selected variables, most of the identified QTLs showed high determination coefficients, associated with moderate to high heritability values. Using markers shared with previous Sclerotinia resistance studies, we compared the QTL locations in LG1, LG2, LG8, LG10, LG11, LG15 and LG16. This study constitutes the largest report of QTLs for SHR resistance in sunflower. Further studies focusing on the regions in LG1, LG10, and LG15 harboring the detected QTLs are necessary to identify causal alleles and contribute to unraveling the complex genetic basis governing the resistance.