A global alliance declaring war on cassava viruses in Africa

[Without Abstract

Genomic prediction in a multiploid crop: genotype by environment interaction and allele dosage effects on predictive ability in banana

Open Access Journal; Published online: 2 March 2018Improving the efficiency of selection in conventional crossbreeding is a major priority in banana (Musa spp.) breeding. Routine application of classical marker assisted selection (MAS) is lagging in banana due to limitations in MAS tools. Genomic selection (GS) based on genomic prediction models can address some limitations of classical MAS, but the use of GS in banana has not been reported to date. The aim of this study was to evaluate the predictive ability of six genomic prediction models for 15 traits in a multi-ploidy training population. The population consisted of 307 banana genotypes phenotyped under low and high input field management conditions for two crop cycles. The single nucleotide polymorphism (SNP) markers used to fit the models were obtained from genotyping by sequencing (GBS) data. Models that account for additive genetic effects provided better predictions with 12 out of 15 traits. The performance of BayesB model was superior to other models particularly on fruit filling and fruit bunch traits. Models that included averaged environment data were more robust in trait prediction even with a reduced number of markers. Accounting for allele dosage in SNP markers (AD-SNP) reduced predictive ability relative to traditional bi-allelic SNP (BA-SNP), but the prediction trend remained the same across traits. The high predictive values (0.47– 0.75) of fruit filling and fruit bunch traits show the potential of genomic prediction to increase selection efficiency in banana breeding

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Interval Mapping of Quantitative Trait Loci for Corky Ringspot Disease Resistance in a Tetraploid Population of Potato (\u3ci\u3eSolanum tuberosum\u3c/i\u3e subsp. \u3ci\u3etuberosum\u3c/i\u3e)

Corky ringspot disease (CRS) resistance is an ideal target trait for breeding using marker-assisted selection (MAS) due to the high variability in field disease incidence that complicates screening for resistance. To develop molecular marker(s) associated with CRS resistance, a linkage map was constructed for a tetraploid population of 92 genotypes in order to conduct quantitative trait locus (QTL) analysis. The population was tested for CRS resistance in an infested screening field for four years. Broad sense heritability and its standard error of CRS disease resistance were 0.80 (±0.16). A total of 892 AFLP, 95 SSR, and 5 SSCP markers were scored and used for testing marker-trait association. One major QTL that explained 43% of the phenotypic variation in CRS resistance was localized on chromosome IX, with flanking AFLP markers AAC-CGT-0347 and ACG-CTG-0588. A minor QTL that explained 12% of CRS resistance was also detected. This minor QTL was associated with distorted marker GGT-CAC-0259, which remained unlinked. Polygenetic nature of CRS resistance was explained by major and minor QTLs association. Conversion of the three AFLP markers associated with this quantitative trait to simple PCR markers will benefit resistance breeding by enabling MAS

Transgenic expression of the rice Xa21 pattern‐recognition receptor in banana (Musa sp.) confers resistance to Xanthomonas campestris pv. musacearum

Banana Xanthomonas wilt (BXW), caused by the bacterium Xanthomonas campestris pv. musacearum (Xcm), is the most devastating disease of banana in east and central Africa. The spread of BXW threatens the livelihood of millions of African farmers who depend on banana for food security and income. There are no commercial chemicals, biocontrol agents or resistant cultivars available to control BXW. Here, we take advantage of the robust resistance conferred by the rice pattern-recognition receptor (PRR), XA21, to the rice pathogen Xanthomonas oryzae pv. oryzae (Xoo). We identified a set of genes required for activation of Xa21-mediated immunity (rax) that were conserved in both Xoo and Xcm. Based on the conservation, we hypothesized that intergeneric transfer of Xa21 would confer resistance to Xcm. We evaluated 25 transgenic lines of the banana cultivar 'Gonja manjaya' (AAB) using a rapid bioassay and 12 transgenic lines in the glasshouse for resistance against Xcm. About 50% of the transgenic lines showed complete resistance to Xcm in both assays. In contrast, all of the nontransgenic control plants showed severe symptoms that progressed to complete wilting. These results indicate that the constitutive expression of the rice Xa21 gene in banana results in enhanced resistance against Xcm. Furthermore, this work demonstrates the feasibility of PRR gene transfer between monocotyledonous species and provides a valuable new tool for controlling the BXW pandemic of banana, a staple food for 100 million people in east Africa

National Oceanic and Atmospheric Administration Report 119

The following document is a report taken during a three-day workshop to estimate natural mortality for use in stock assessment applications. The workshop covered biological aspects of mortality, methods for estimation of mortality, and best practices for use of mortality in assessment models. This document presents the findings during this workshop