Genomic Prediction Accuracy of Stripe Rust in Six Spring Wheat Populations by Modeling Genotype by Environment Interaction

Some previous studies have assessed the predictive ability of genome-wide selection on stripe (yellow) rust resistance in wheat, but the effect of genotype by environment interaction (GEI) in prediction accuracies has not been well studied in diverse genetic backgrounds. Here, we compared the predictive ability of a model based on phenotypic data only (M1), the main effect of phenotype and molecular markers (M2), and a model that incorporated GEI (M3) using three cross-validations (CV1, CV2, and CV0) scenarios of interest to breeders in six spring wheat populations. Each population was evaluated at three to eight field nurseries and genotyped with either the DArTseq technology or the wheat 90K single nucleotide polymorphism arrays, of which a subset of 1,058- 23,795 polymorphic markers were used for the analyses. In the CV1 scenario, the mean prediction accuracies of the M1, M2, and M3 models across the six populations varied from 0.11 to 0.07, from 0.22 to 0.49, and from 0.19 to 0.48, respectively. Mean accuracies obtained using the M3 model in the CV1 scenario were significantly greater than the M2 model in two populations, the same in three populations, and smaller in one population. In both the CV2 and CV0 scenarios, the mean prediction accuracies of the three models varied from 0.53 to 0.84 and were not significantly different in all populations, except the Attila/CDC Go in the CV2, where the M3 model gave greater accuracy than both the M1 and M2 models. Overall, the M3 model increased prediction accuracies in some populations by up to 12.4% and decreased accuracy in others by up to 17.4%, demonstrating inconsistent results among genetic backgrounds that require considering each population separately. This is the first comprehensive genome-wide prediction study that investigated details of the effect of GEI on stripe rust resistance across diverse spring wheat populations

Development of SSR markers and construction of a linkage map in jute

Jute is an important natural fibre crop, which is only second to cotton in its importance at the global level. It is mostly grown in Indian subcontinent and has been recently used for the development of genomics resources. We recently initiated a programme to develop simple sequence repeat markers and reported a set of 2469 SSR that were developed using four SSR-enriched libraries (Mir et al. 2009). In this communication, we report an additional set of 607 novel SSR in 393 SSR containing sequences. However, primers could be designed for only 417 potentially useful SSR. Polymorphism survey was carried out for 374 primer pairs using two parental genotypes (JRO 524 and PPO4) of a mapping population developed for fibre fineness; only 66 SSR were polymorphic. Owing to a low level of polymorphism between the parental genotypes and a high degree of segregation distortion in recombinant inbred lines, genotypic data of only 53 polymorphic SSR on the mapping population consisting of 120 RIL could be used for the construction of a linkage map; 36 SSR loci were mapped on six linkage groups that covered a total genetic distance of 784.3 cM. Hopefully, this map will be enriched with more SSR loci in future and will prove useful for identification of quantitative trait loci/genes for molecular breeding involving improvement of fibre fineness and other related traits in jute

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

High Density Single Nucleotide Polymorphism (SNP) Mapping and Quantitative Trait Loci (QTL) Analysis in a Biparental Spring Triticale Population Localized Major and Minor Effect Fusarium Head Blight Resistance and Associated Traits QTL

Triticale (xTriticosecale Wittmack) is an important feed crop which suffers severe yield, grade and end-use quality losses due to Fusarium head blight (FHB). Development of resistant triticale cultivars is hindered by lack of effective genetic resistance sources. To dissect FHB resistance, a doubled haploid spring triticale population produced from the cross TMP16315/AC Ultima using a microspore culture method, was phenotyped for FHB incidence, severity, visual rating index (VRI), deoxynivalenol (DON) and some associated traits (ergot, grain protein content, test weight, yield, plant height and lodging) followed by single nucleotide polymorphism (SNP) genotyping. A high-density map consisting of 5274 SNPs, mapped on all 21 chromosomes with a map density of 0.48 cM/SNP, was constructed. Together, 17 major quantitative trait loci were identified for FHB on chromosomes 1A, 2B, 3A, 4A, 4R, 5A, 5R and 6B; two of incidence loci (on 2B and 5R) also co-located with loci for severity and VRI, and two other loci of VRI (on 1A and 4R) with DON accumulation. Major and minor loci were also identified for all other traits in addition to many epistasis loci. This study provides new insight into the genetic basis of FHB resistance and their association with other traits in triticale

Mapping of Major Fusarium Head Blight Resistance from Canadian Wheat cv. AAC Tenacious

Fusarium head blight (FHB) is one of the most devastating wheat disease due to its direct detrimental effects on grain-yield, quality and marketability. Resistant cultivars offer the most effective approach to manage FHB; however, the lack of different resistance resources is still a major bottleneck for wheat breeding programs. To identify and dissect FHB resistance, a doubled haploid wheat population produced from the Canadian spring wheat cvs AAC Innova and AAC Tenacious was phenotyped for FHB response variables incidence and severity, visual rating index (VRI), deoxynivalenol (DON) content, and agronomic traits days to anthesis (DTA) and plant height (PHT), followed by single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker genotyping. A high-density map was constructed consisting of 10,328 markers, mapped on all 21 chromosomes with a map density of 0.35 cM/marker. Together, two major quantitative trait loci for FHB resistance were identified on chromosome 2D from AAC Tenacious; one of these loci on 2DS also colocated with loci for DTA and PHT. Another major locus for PHT, which cosegregates with locus for low DON, was also identified along with many minor and epistatic loci. QTL identified from AAC Tenacious may be useful to pyramid FHB resistance

High Density Single Nucleotide Polymorphism (SNP) Mapping and Quantitative Trait Loci (QTL) Analysis in a Biparental Spring Triticale Population Localized Major and Minor Effect Fusarium Head Blight Resistance and Associated Traits QTL

Triticale (xTriticosecale Wittmack) is an important feed crop which suffers severe yield, grade and end-use quality losses due to Fusarium head blight (FHB). Development of resistant triticale cultivars is hindered by lack of effective genetic resistance sources. To dissect FHB resistance, a doubled haploid spring triticale population produced from the cross TMP16315/AC Ultima using a microspore culture method, was phenotyped for FHB incidence, severity, visual rating index (VRI), deoxynivalenol (DON) and some associated traits (ergot, grain protein content, test weight, yield, plant height and lodging) followed by single nucleotide polymorphism (SNP) genotyping. A high-density map consisting of 5274 SNPs, mapped on all 21 chromosomes with a map density of 0.48 cM/SNP, was constructed. Together, 17 major quantitative trait loci were identified for FHB on chromosomes 1A, 2B, 3A, 4A, 4R, 5A, 5R and 6B; two of incidence loci (on 2B and 5R) also co-located with loci for severity and VRI, and two other loci of VRI (on 1A and 4R) with DON accumulation. Major and minor loci were also identified for all other traits in addition to many epistasis loci. This study provides new insight into the genetic basis of FHB resistance and their association with other traits in triticale

Genetic improvement of grain protein content and other health-related constituents of wheat grain

It is known that nearly one-third of the world population currently suffers from malnutrition due to lack of availability of adequate quantity of protein, vitamins and a number of micronutrients including Fe and Zn in their diet. A lack of other desirable bioactive compounds and dietary fibres (DF) in the diet also causes a variety of diseases. In some regions of the world, occurrence of Cd and As in wheat grain in excess of tolerance limits also adversely affects human health. In this short review, we summarize the current status of knowledge about the genetic control of the accumulation of a variety of nutritional constituents in wheat grain and then describe examples where noticeable improvements have been made using breeding approaches. We also describe the gaps that need to be bridged for better understanding of the genetic architecture of these important traits. The development and use of molecular markers in marker-assisted selection (MAS) for developing wheat varieties with improved grain quality has also been discussed

Analysis of differentially expressed genes in leaf rust infected bread wheat involving seedling resistance gene Lr28

Genome-wide transcriptome analysis of seedling resistance to leaf rust conferred by Lr28 gene in wheat (Triticum aestivum L.) was conducted to identify differentially expressed genes during incompatible interaction. A virulent leaf rust race 77-5 was used for inoculation of resistant (HD2329 + Lr28) and susceptible (HD2329 - Lr28) wheat NILs and cDNA-AFLP analyses was carried out. As many as 223 differential transcripts appeared following leaf rust inoculation; these included 122 transcripts that appeared exclusively in resistant NIL, whereas 39 transcripts appeared both in resistant and susceptible NILs. Sequence analyses of 37 transcripts, which appeared in the resistant NIL revealed that 15 transcripts had homology with genes involved in protein synthesis, signal transduction, transport, disease resistance and metabolism. The functions of remaining 22 transcripts could not be determined; these included six novel genes reported for the first time in wheat. Specific primers could be designed for 18 of the 37 transcripts, which included genes with putative and unknown functions. Quantitative real time PCR analysis was conducted using these 18 pairs of primers. A majority (13) of these transcripts appeared within 48 h reaching a peak value at 96 h in resistant NIL signifying their role in providing leaf rust resistance

Insights of Lr28 mediated wheat leaf rust resistance: transcriptomic approach

Leaf rust is a fungal disease that causes severe yield losses in wheat. Resistant varieties with major and quantitative resistance genes are the most effective method to control the disease. However, the main problem is inadequate information for understanding resistance mechanism and its usefulness. This paper presents Lr28 mediated genome-wide response of known and unknown genes during wheat-Puccinia triticina interaction. In this study, we prepared Serial Analysis of Gene Expression (SAGE) libraries using seedling wheat mRNA for infected and mock conditions. The libraries were sequenced on Sequencing by Oligonucleotide Ligation and Detection (SOLiD) system generating 37-48 million reads. After mapping and gene expression analysis of ~6-12 million trimmed reads/library, we revealed five major categories comprised of Lr28 controlled transcripts in resistant (+Lr28) isoline (39), transcripts specific to susceptible (-Lr28) isoline (785), transcripts specific to hypersensitive-response (HR) (375), transcripts specific for basal-defense (153) and transcripts for establishment of pathogen (1616). We estimated the impact of specific genes and pathways through mapping on plant resistant gene database (PRGdb), reactive oxygen species (ROS) and phytohormone database. Functional annotation results revealed, receptor binding, homeostatic processes and cytoskeletal components as the major discriminating factors between susceptibility and resistance. We validated 28 key genes using qRT-PCR and found positive results. These findings were projected on hypothetical interaction model to demonstrate interaction mechanism. The study might have significant impact on future rust-resistance breeding through knowledge based smart genetic selection of quantitative resistance genes besides major effect R-gene