Development of Disease Resistant Rice Using Whole Genome Sequencing and Standard Breeding Methods

Cultivated rice is the most important staple crop in the world, but diseases cause substantial losses in grain yield and quality. Sheath blight disease caused by the fungus Rhizoctonia solani is the second most important disease in rice. Most U.S varieties are tropical japonica type, but known sources of resistance in this subspecies are rare. Silva et al. (2012) identified candidate SNP associated with resistance to sheath blight by whole genome sequencing. The objectives of this study were to develop SNP-based markers from the information reported by Silva et al. (2012), to validate the markers by selective genotyping in the RiceCAP SB2 mapping population, and to develop and evaluate breeding lines resistant to sheath blight by marker-assisted selection coupled with backcrossing, anther culture, and field assessment methods. A total of 136 SNP-based markers were developed and screened in extreme resistant and susceptible phenotypic groups from the RiceCAP SB2 mapping population. SNPs in reported genomic regions for sheath blight resistance were identified including eight markers located on chromosomes 6, 8, 9, and 12 that were used in a marker-assisted backcrossing strategy by crossing seven different resistant lines to four susceptible U.S. commercial varieties. A total of 45 doubled-haploid (DH) lines were developed from 28 BC2F1 individuals containing different combinations of selected SNPs. Field evaluation of selected DH lines was carried out in 2014 and 2015. Additional evaluations were performed using a mist chamber to reproduce optimal conditions for disease development. Fourteen DH lines containing different combinations of resistant alleles from chromosomes 2, 6, 8, 9 and 12 showed high levels of resistance after inoculation with R. solani. Results from this research suggest that development of disease resistant rice can be successfully accomplished using whole genome sequencing information combined with standard breeding approaches

Implementation and modeling of a femtosecond laser-activated streak camera

8 June 2017) A laser-activated streak camera was built to measure the duration of femtosecond electron pulses. The streak velocity of the device is 1.89 mrad/ps, which corresponds to a sensitivity of 34.9 fs/pixels. The streak camera also measures changes in the relative time of arrival between the laser and electron pulses with a resolution of 70 fs RMS. A full circuit analysis of the structure is presented to describe the streaking field and the general behavior of the device. We have developed a general mathematical model to analyze the streaked images. The model provides an accurate method to extract the pulse duration based on the changes of the electron beam profile when the streaking field is applied

SOLUCIONANDO NECESIDADES ESPECIFICAS CON GNU/LINUX

ImagenesZentyal es una distribución de Open Software de código libre, es decir, es un servidor de red unificada de código abierto que permite gestionar la infraestructura en la red por medio de puertas de enlace a internet (Gateway), servidores de oficinas, servidores de comunicaciones unificadas y combinación de estas. Zentyal ofrece la única solución TIC del mercado que sincroniza totalmente la infraestructura TIC local con la nube.El presente proyecto tiene como demostrar las ventajas del Software Zentyal 6.0 en diferentes aspectos descritos en cada temática frente a otras herramientas existentes como ClearOS o FreeNAS, es un Software que permite servicios de Internet, además puede trabajar como Servidor interno sin problema, puede trabajar en entornos multi sistemas, bien sea como servido o cliente Y su desempeño en Linux es Excelente

BOOTSIE – ESTIMATION OF COEFFICIENT OF VARIATION OF AFLP DATA BY BOOTSTRAP ANALYSIS

Bootsie is an English-native replacement for ASG Coelho\u27s “DBOOT” utility for estimating coefficient of variation of a population of AFLP marker data using bootstrapping. Bootsie improves on DBOOT by supporting batch processing, time-to-completion estimation, builtin graphs, and a suite of export tools for creating data files for other population genetics software

Loss of a Premature Stop Codon in the Rice Wall-Associated Kinase 91 (<i>WAK91</i>) Gene Is a Candidate for Improving Leaf Sheath Blight Disease Resistance

Leaf sheath blight disease (SB) of rice caused by the soil-borne fungus Rhizoctonia solani results in 10–30% global yield loss annually and can reach 50% under severe outbreaks. Many disease resistance genes and receptor-like kinases (RLKs) are recruited early on by the host plant to respond to pathogens. Wall-associated receptor kinases (WAKs), a subfamily of receptor-like kinases, have been shown to play a role in fungal defense. The rice gene WAK91 (OsWAK91), co-located in the major SB resistance QTL region on chromosome 9, was identified by us as a candidate in defense against rice sheath blight. An SNP mutation T/C in the WAK91 gene was identified in the susceptible rice variety Cocodrie (CCDR) and the resistant line MCR010277 (MCR). The consequence of the resistant allele C is a stop codon loss, resulting in an open reading frame with extra 62 amino acid carrying a longer protein kinase domain and additional phosphorylation sites. Our genotype and phenotype analysis of the parents CCDR and MCR and the top 20 individuals of the double haploid SB population strongly correlate with the SNP. The susceptible allele T is present in the japonica subspecies and most tropical and temperate japonica lines. Multiple US commercial rice varieties with a japonica background carry the susceptible allele and are known for SB susceptibility. This discovery opens the possibility of introducing resistance alleles into high-yielding commercial varieties to reduce yield losses incurred by the sheath blight disease

Data from: Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection

Current advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops

WGSOryza_CIAT_LSU_USDA_NCGR_Q40_annotated_Chr3_2.vcf

SNPs and small indels identified for the 104 varieties analyzed in this study. All genotypes have an NGSEP genotyping quality score larger or equal than 40. Genomic coordinates are relative to IRGSP1.0. This file contains chromosome 3 from basepairs 30,000,000 to 36,413,81

Whole genome sequencing of elite rice cultivars as a comprehensive information resource for marker assisted selection

International audienceCurrent advances in sequencing technologies and bioinformatics revealed the genomic background of rice, a staple food for the poor people, and provided the basis to develop large genomic variation databases for thousands of cultivars. Proper analysis of this massive resource is expected to give novel insights into the structure, function, and evolution of the rice genome, and to aid the development of rice varieties through marker assisted selection or genomic selection. In this work we present sequencing and bioinformatics analyses of 104 rice varieties belonging to the major subspecies of Oryza sativa. We identified repetitive elements and recurrent copy number variation covering about 200 Mbp of the rice genome. Genotyping of over 18 million polymorphic locations within O. sativa allowed us to reconstruct the individual haplotype patterns shaping the genomic background of elite varieties used by farmers throughout the Americas. Based on a reconstruction of the alleles for the gene GBSSI, we could identify novel genetic markers for selection of varieties with high amylose content. We expect that both the analysis methods and the genomic information described here would be of great use for the rice research community and for other groups carrying on similar sequencing efforts in other crops