Ecophysiological Crop Modelling Combined with Genetic Analysis Is a Powerful Tool for Ideotype Design

Improving the grain yield of crops in both favourable and stressful environments is the main breeding objective required to ensure food security. In this review, I outline a genotype-to-phenotype approach that exploits the potential values of quantitative genetics and process-based crop modelling in developing new plant types with high yields. The effects of quantitative trait locus (QTL), for traits typically at the single-organ level over a short time scale, were projected for their impact on crop growth during the whole growing season in the field. This approach can provide more markers for selection programmes for specific environments whilst also allowing for prioritization. Crop modelling is thus a powerful tool for ideotyping under contrasting conditions, i.e., use of single-environment information for predicting phenotypes under different environments.

A More Complete Story of the Genetic Bases of Resistance to the Rice Hoja Blanca Virus

Rice hoja blanca is one of the most serious diseases in rice growing areas in tropical Americas. Its causal agent is the Rice hoja blanca virus (RHBV), transmitted by the planthopper Tagosodes orizicolus Müir. Genetic resistance is the most effective and environment-friendly way of controlling the disease. So far, only one major quantitative trait locus (QTL) of Oryza sativa ssp. japonica origin, qHBV4.1, that alters incidence of the virus symptoms in two Colombian cultivars has been reported. This resistance has already started to be broken, stressing the urgent need for diversifying the resistance sources. In the present study we performed a search for new QTLs of O. sativa indica origin associated with RHBV resistance. We used four F2:3 segregating populations derived from indica resistant varieties crossed with a highly susceptible japonica pivot parent. Beside the standard method for measuring disease incidence, we developed a new method based on computer-assisted image processing to determine the affected leaf area (ALA) as a measure of symptoms severity. Based on the disease severity and incidence scores in the F3 families under greenhouse conditions, and SNP genotyping of the F2 individuals, we identified four new indica QTLs for RHBV resistance on rice chromosomes 4, 6 and 11, namely qHBV4.2WAS208, qHBV6.1PTB25, qHBV11.1 and qHBV11.2. We also confirmed the wide-range action of qHBV4.1. Among the five QTLs, qHBV4.1 and qHBV11.1 had the largest effects on incidence and severity, respectively. These results provide a more complete understanding of the genetic bases of RHBV resistance in the cultivated rice gene pool, and can be used to develop marker-aided breeding strategies to improve RHBV resistance. The power of joint- and meta- analyses allowed precise mapping and candidate genes identification, providing the basis for positional cloning of the two major QTLs qHBV4.1 and qHBV11.1.

Powerful, efficient QTL mapping in Drosophila melanogaster using bulked phenotyping and pooled sequencing

Despite the value of Recombinant Inbred Lines (RILs) for the dissection of complex traits, large panels can be difficult to maintain, distribute, and phenotype. An attractive alternative to RILs for many traits leverages selecting phenotypically extreme individuals from a segregating population, and subjecting pools of selected and control individuals to sequencing. Under a bulked or extreme segregant analysis paradigm, genomic regions contributing to trait variation are revealed as frequency differences between pools. Here we describe such an extreme quantitative trait locus, or X-QTL, mapping strategy that builds on an existing multiparental population, the DSPR (Drosophila Synthetic Population Resource), and involves phenotyping and genotyping a population derived by mixing hundreds of DSPR RILs. Simulations demonstrate that challenging, yet experimentally tractable X-QTL designs ( > =4 replicates, > =5000 individuals/replicate, and selecting the 5-10% most extreme animals) yield at least the same power as traditional RIL-based QTL mapping and can localize variants with sub-centimorgan resolution. We empirically demonstrate the effectiveness of the approach using a 4-fold replicated X-QTL experiment that identifies 7 QTL for caffeine resistance. Two mapped X-QTL factors replicate loci previously identified in RILs, 6/7 are associated with excellent candidate genes, and RNAi knock-downs support the involvement of 4 genes in the genetic control of trait variation. For many traits of interest to drosophilists, a bulked phenotyping/genotyping X-QTL design has considerable advantages.

Variability in an effector gene promoter of a necrotrophic fungal pathogen dictates epistasis and effector-triggered susceptibility in wheat

The fungus Parastagonospora nodorum uses proteinaceous necrotrophic effectors (NEs) to induce tissue necrosis on wheat leaves during infection, leading to the symptoms of septoria nodorum blotch (SNB). The NEs Tox1 and Tox3 induce necrosis on wheat possessing the dominant susceptibility genes Snn1 and Snn3B1/Snn3D1, respectively. We previously observed that Tox1 is epistatic to the expression of Tox3 and a quantitative trait locus (QTL) on chromosome 2A that contributes to SNB resistance/susceptibility. The expression of Tox1 is significantly higher in the Australian strain SN15 compared to the American strain SN4. Inspection of the Tox1 promoter region revealed a 401 bp promoter genetic element in SN4 positioned 267 bp upstream of the start codon that is absent in SN15, called PE401. Analysis of the world-wide P. nodorum population revealed that a high proportion of Northern Hemisphere isolates possess PE401 whereas the opposite was observed in representative P. nodorum isolates from Australia and South Africa. The presence of PE401 removed the epistatic effect of Tox1 on the contribution of the SNB 2A QTL but not Tox3. PE401 was introduced into the Tox1 promoter regulatory region in SN15 to test for direct regulatory roles. Tox1 expression was markedly reduced in the presence of PE401. This suggests a repressor molecule(s) binds PE401 and inhibits Tox1 transcription. Infection assays also demonstrated that P. nodorum which lacks PE401 is more pathogenic on Snn1 wheat varieties than P. nodorum carrying PE401. An infection competition assay between P. nodorum isogenic strains with and without PE401 indicated that the higher Tox1-expressing strain rescued the reduced virulence of the lower Tox1-expressing strain on Snn1 wheat. Our study demonstrated that Tox1 exhibits both ‘selfish’ and ‘altruistic’ characteristics. This offers an insight into a complex NE-NE interaction that is occurring within the P. nodorum population. The importance of PE401 in breeding for SNB resistance in wheat is discussed.

Study on fine mapping of QTL for juice yield traits of sweet sorghum (Sorghum dochna)

The stem juice yield is a key factor that influences both the biological and economic production of sweet sorghum [Sorghum dochna (Forssk.) Snowden]. To elucidate upon the genetic basis of the stem juice yield, an F₅ population developed from a cross between the low juice yielding Xinliang52 (XL52) and high juice yielding W455 lines, were used in a quantitative trait locus (QTL) analysis. A main effect of the QTL controlling stem juice yield was separated with an SSR marker called Xtxp97, which explained 46.7% of the phenotypic variance. In addition, F₅ and F₆ populations were constructed with XL52 and W452 as the parents to further verify the QTLs, and a significant correlation was found between the juice yield trait and the Xtxp97 marker. Based on the progeny tests of 29 recombinants, QJy-sbi06 was located in a region of about 21.2 kb on chromosome 6, where a candidate gene encoding an NAC transcription factor (sobic.006G147400) was identified. Combining the different population association analysis and sequencing technology showed that XL52 inserted a 1.8 kb transposon in the NAC to directly interrupt and inactivate the juice yield gene. This study also demonstrated that the colour of the leaf midribs was controlled by a single gene and was significantly positive correlated with juiciness (r = 0.784, P < 0.01). These results could lay the foundation for map-based cloning of QJy-sbi06 and provide genes or QTLs for breeding sorghum lines with a high juice yield and quality.

Mapping of crown rust (Puccinia coronata f. sp. avenae) resistance gene Pc54 and a novel quantitative trait locus effective against powdery mildew (Blumeria graminis f. sp. avenae) in the oat (Avena sativa) line Pc54

The Pc54 oat line carries the crown rust resistance gene ‘Pc54’ and an unknown gene effective against powdery mildew. In this study two recombinant inbred line populations were developed to identify the genomic locations of the two genes and producing lists of molecular markers with a potential for marker assisted selection. The RILs and parents were phenotyped for crown rust and powdery mildew in a controlled environment. They were also genotyped using the 6K Illumina Infinium iSelect oat SNP chip. Multiple interval mapping placed Pc54 on the linkage group Mrg02 (chromosome 7D) and the novel powdery mildew QTL ‘QPm.18’ on Mrg18 (chromosome 1A) both in the mapping and validating population. A total of nine and 31 significant molecular markers were identified linked with the Pc54 gene and QPm.18, respectively. Reactions to crown rust inoculations have justified separate identity of Pc54 from other genes and QTL that have previously been reported on Mrg02 except for ’qPCRFd’. Pm3 is the only powdery mildew resistance gene previously mapped on Mrg18. However, the pm3 differential line, Mostyn was susceptible to the powdery mildew race used in this study suggesting that Pm3 and QPm.18 are different genes. Determining the chromosomal locations of Pc54 and QPm.18 is helpful for better understanding the molecular mechanism of resistance to crown rust and powdery mildew in oats. Furthermore, SNPs and SSRs that are closely linked with the genes could be valuable for developing PCR based molecular markers and facilitating the utilization of these genes in oat breeding programs.

The Evolution of Larger Size in High Altitude Drosophila melanogaster has a Variable Genetic Architecture

Important uncertainties persist regarding the genetic architecture of adaptive trait evolution in natural populations, including the number of genetic variants involved, whether they are drawn from standing genetic variation, and whether directional selection drives them to complete fixation. Here, we take advantage of a unique natural population of Drosophila melanogaster from the Ethiopian highlands, which has evolved larger body size than any other known population of this species. We apply a bulk segregant quantitative trait locus (QTL) mapping approach to four unique crosses between highland Ethiopian and lowland Zambian populations for both thorax length and wing length. Results indicated a persistently variable genetic basis for these evolved traits (with largely distinct sets of QTLs for each cross), and at least a moderately polygenic architecture with relatively strong effects present. We complemented these mapping experiments with population genetic analyses of QTL regions and gene ontology enrichment analysis, generating strong hypotheses for specific genes and functional processes that may have contributed to these adaptive trait changes. Finally, we find that the genetic architectures our QTL mapping results for size traits mirror those from similar experiments on other recently-evolved traits in this species. Collectively, these studies suggest a recurring pattern of polygenic adaptation in this species, in which causative variants do not approach fixation and moderately strong effect loci are present.

Genome wide association mapping of yield and other agronomic traits in rice: Narrative literature review

Based on previous recombination actions and LD (linkage disequilibrium) throughout the genome, genome wide association mapping studies often are employed to find Quantitative trait locus in varied collections of crop germplasm. Generally, diverse panel’s genotyped using high density Single nucleotide polymorphism (SNP) panels are used to test a broad variety of haplotypes and alleles, as well as to track recombination divisions throughout the genome. GWAS, on the other hand, have rarely been used in breeding populations. We studied association mapping for agricultural parameters such as yield and its constituents in a breeding inhabitants of top irrigated tropical rice progenies so that the findings could be used to breeding more directly than those from a diverse panel. GWAS was undertaken with the specific purpose of accelerating selection in the breeding population, and the sample was genotyped with 71,710 Single nucleotide polymorphisms using genotyping-by-sequencing. We found 52 Quantitative trait locus QTL for 11 agronomic characteristics using this breeding panel, including substantial impact Quantitative trait loci (QTLs) for flowering period as well as grain width, grain length, grain length-breadth ratio. Furthermore we discovered haplotypes that may be applied to choose plants for our population with smaller stature (plant height), fast blooming time, with high yield, demonstrating the value of association mapping for advising breeding choices in breeding populations. Furthermore, we explore at how genomic-assisted selection models might be built using the newly discovered important Single nucleotide polymorphisms (SNPs) and deep insight into the genetic structure of these quantitative traits.