Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat.

KEY MESSAGE: The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates. However, CGMs require multiple seasonal environmental records, unlike WGP, which makes CGM-WGP less accurate when applied to historical reference populations that lack crucial environmental inputs. Here, we investigated the ability of CGM-WGP to approximate missing environmental variables to improve prediction accuracy. Two environmental variables in a wheat CGM, initial soil water content (InitlSoilWCont) and initial nitrate profile, were sampled from different normal distributions separately or jointly in each iteration within the CGM-WGP algorithm. Our results showed that sampling InitlSoilWCont alone gave the best results and improved the prediction accuracy of grain number by 0.07, yield by 0.06 and protein content by 0.03. When using the sampled InitlSoilWCont values as an input for the traditional CGM, the average narrow-sense heritability of the genotype-specific parameters (GSPs) improved by 0.05, with GNSlope, PreAnthRes, and VernSen showing the greatest improvements. Moreover, the root mean square of errors for grain number and yield was reduced by about 7% for CGM and 31% for CGM-WGP when using the sampled InitlSoilWCont values. Our results demonstrate the advantage of sampling missing environmental variables in CGM-WGP to improve prediction accuracy and increase the size of the reference population by enabling the utilisation of historical data that are missing environmental records.

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology.

Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM-WGP model introduces environmental information to WGP and genomic relatedness information to the genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM-WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM-WGP framework and compared it with CGM and WGP. The CGM-WGP resulted in more heritable genotype-specific parameters with more biologically realistic correlation structures between genotype-specific parameters and phenology traits compared with CGM-modelled genotype-specific parameters that reflected the correlation of measured phenotypes. Another advantage of CGM-WGP is the ability to infer accurate prediction with much smaller and less diverse reference data compared with that required for CGM. A genome-wide association analysis linked the genotype-specific parameters from the CGM-WGP model to nine significant phenology loci including Vrn-A1 and the three PPD1 genes, which were not detected for CGM-modelled genotype-specific parameters. Selection on genotype-specific parameters could be simpler than on observed phenotypes. For example, thermal time traits are theoretically more independent candidates, compared with the highly correlated heading and maturity dates, which could be used to achieve an environment-specific optimal flowering period. CGM-WGP combines the advantages of CGM and WGP to predict more accurate phenotypes for new genotypes under alternative or future environmental conditions.

Using genomic prediction with crop growth models enables the prediction of associated traits in wheat.

Crop growth models (CGM) can predict the performance of a cultivar in untested environments by sampling genotype-specific parameters. As they cannot predict the performance of new cultivars, it has been proposed to integrate CGMs with whole genome prediction (WGP) to combine the benefits of both models. Here, we used a CGM-WGP model to predict the performance of new wheat (Triticum aestivum) genotypes. The CGM was designed to predict phenology, nitrogen, and biomass traits. The CGM-WGP model simulated more heritable GSPs compared with the CGM and gave smaller errors for the observed phenotypes. The WGP model performed better when predicting yield, grain number, and grain protein content, but showed comparable performance to the CGM-WGP model for heading and physiological maturity dates. However, the CGM-WGP model was able to predict unobserved traits (for which there were no phenotypic records in the reference population). The CGM-WGP model also showed superior performance when predicting unrelated individuals that clustered separately from the reference population. Our results demonstrate new advantages for CGM-WGP modelling and suggest future efforts should focus on calibrating CGM-WGP models using high-throughput phenotypic measures that are cheaper and less laborious to collect.

Simultaneous infection of amoebic liver abscess and hepatitis A infection in a young adult in an endemic region.

Concomitant hepatitis A virus (HAV) and amoebic liver abscess are to be considered in patients with clinical signs and symptoms of fever, jaundice, and right upper quadrant pain, especially in endemic areas. Both diseases had similar epidemiology and identical mode of transmission, i.e., the feco-oral route. We report a case of a young female with simultaneous infection of HAV and amoebic liver abscess, emphasizing the role of dual infection and its clinical manifestations.

A giant NLR gene confers broad-spectrum resistance to Phytophthora sojae in soybean.

Phytophthora root and stem rot caused by P. sojae is a destructive soybean soil-borne disease found worldwide. Discovery of genes conferring broad-spectrum resistance to the pathogen is a need to prevent the outbreak of the disease. Here, we show that soybean Rps11 is a 27.7-kb nucleotide-binding site-leucine-rich repeat (NBS-LRR or NLR) gene conferring broad-spectrum resistance to the pathogen. Rps11 is located in a genomic region harboring a cluster of large NLR genes of a single origin in soybean, and is derived from rounds of unequal recombination. Such events result in promoter fusion and LRR expansion that may contribute to the broad resistance spectrum. The NLR gene cluster exhibits drastic structural diversification among phylogenetically representative varieties, including gene copy number variation ranging from five to 23 copies, and absence of allelic copies of Rps11 in any of the non-Rps11-donor varieties examined, exemplifying innovative evolution of NLR genes and NLR gene clusters.

Identification and molecular mapping of Rps14, a gene conferring broad-spectrum resistance to Phytophthora sojae in soybean.

KEY MESSAGE: A soybean landrace carries broad-spectrum resistance to Phytophthora sojae, which is conferred by a single gene, designated Rps14, on the short arm of chromosome 3. Phytophthora sojae is the causative agent for Phytophthora root and stem rot in soybean [Glycine max (L.) Merr.] and can be managed by deployment of resistance to P. sojae (Rps) genes. PI 340,029 is a soybean landrace carrying broad-spectrum resistance to the pathogen. Analysis of an F2 population derived from a cross between PI 340,029 and a susceptible cultivar 'Williams' reveals that the resistance to P. sojae race 1 is conferred by a single gene, designated Rps14, which was initially mapped to a 4.5-cM region on the short arm of chromosome 3 by bulked segregant analysis (BSA), and subsequently narrowed to a 1.48 cM region corresponding to 229-kb in the Williams 82 reference genome (Wm82 v2.a1), using F3:4 families derived from the F2 population. Further analysis indicates that the broad-spectrum resistance carried by PI 340,029 is fully attributable to Rps14. The genomic sequences corresponding to the defined Rps14 region from a set of diverse soybean varieties exhibit drastic NBS-LRR gene copy number variation, ranging from 3 to 17 copies. Ultimate isolation of Rps14 would be critical for precise selection and deployment of the gene for soybean protection.

Identification and molecular mapping of Rps11, a novel gene conferring resistance to Phytophthora sojae in soybean.

KEY MESSAGE: Rps11 confers excellent resistance to predominant Phytophthora sojae isolates capable of defeating major Rps genes deployed into soybean production, representing a novel source of resistance for soybean cultivar enhancement. ABSTRACT: Phytophthora root and stem rot (PRSR), caused by the soil-borne pathogen Phytophthora sojae, is a devastating disease of soybean [Glycine max (L.) Merr.] throughout the world. Deploying resistant soybean cultivars is the most effective and environmentally friendly approach to managing this disease. The soybean landrace PI 594527 was found to carry excellent resistance to all P. sojae isolates examined, some of which were capable of overcoming the major Rps genesp, such as Rps1-k, Rps1-c, and Rps3-a, predominantly used for soybean protection in the past decades. A mapping population consisting of 58 F2 individuals and 209 F2:3 families derived from a cross between PI 594527 and the susceptible cultivar 'Williams' was used to characterize the inheritance pattern of the resistance to P. soja (Rps) in PI 594527. It was found that the resistance was conferred by a single Rps gene, designated Rps11, which was initially defined as an ~5 Mb genomic region at the beginning of chromosome 7 by bulked segregant analysis (BSA) with a nucleotide polymorphism (SNP) chip comprising 7039 SNP markers. Subsequently, simple sequence repeat (SSR) markers in the defined region were used to genotype the F2:3 mapping population to map Rps11 to a 225.3 kb genomic region flanked by SSR markers BARCSOYSSR_07_0286 and BARCSOYSSR_07_0300, according to the soybean reference genome sequence. Particularly, an SSR marker (i.e., BARCSOYSSR_07_0295) was found to tightly co-segregate with Rps11 in the mapping population and can be effectively used for marker-assisted selection of this gene for development of resistant soybean cultivars.

Avirulence effector discovery in a plant galling and plant parasitic arthropod, the Hessian fly (Mayetiola destructor).

Highly specialized obligate plant-parasites exist within several groups of arthropods (insects and mites). Many of these are important pests, but the molecular basis of their parasitism and its evolution are poorly understood. One hypothesis is that plant parasitic arthropods use effector proteins to defeat basal plant immunity and modulate plant growth. Because avirulence (Avr) gene discovery is a reliable method of effector identification, we tested this hypothesis using high-resolution molecular genetic mapping of an Avr gene (vH13) in the Hessian fly (HF, Mayetiola destructor), an important gall midge pest of wheat (Triticum spp.). Chromosome walking resolved the position of vH13, and revealed alleles that determine whether HF larvae are virulent (survive) or avirulent (die) on wheat seedlings carrying the wheat H13 resistance gene. Association mapping found three independent insertions in vH13 that appear to be responsible for H13-virulence in field populations. We observed vH13 transcription in H13-avirulent larvae and the salivary glands of H13-avirulent larvae, but not in H13-virulent larvae. RNA-interference-knockdown of vH13 transcripts allowed some H13-avirulent larvae to escape H13-directed resistance. vH13 is the first Avr gene identified in an arthropod. It encodes a small modular protein with no sequence similarities to other proteins in GenBank. These data clearly support the hypothesis that an effector-based strategy has evolved in multiple lineages of plant parasites, including arthropods.

Management challenges in a short-range low-velocity gunshot injury.

The use of firearms is becoming more prevalent in the society and hence the number of homicidal and suicidal cases. The severity of gunshot wounds varies depending on the weapons caliber and the distance of firing. Close-range, high-velocity gunshot wounds in the head and neck region can result in devastating esthetic and functional impairment. The complexity in facial skeletal anatomy cause multiple medical and surgical challenges to an operating surgeon, demanding elaborate soft and hard tissue reconstructions. Here we present the successful management of a patient shot by a low-velocity short-range pistol with basic life support measures, wound management, reconstruction, and rehabilitation.

SNP markers and their impact on plant breeding.

The use of molecular markers has revolutionized the pace and precision of plant genetic analysis which in turn facilitated the implementation of molecular breeding of crops. The last three decades have seen tremendous advances in the evolution of marker systems and the respective detection platforms. Markers based on single nucleotide polymorphisms (SNPs) have rapidly gained the center stage of molecular genetics during the recent years due to their abundance in the genomes and their amenability for high-throughput detection formats and platforms. Computational approaches dominate SNP discovery methods due to the ever-increasing sequence information in public databases; however, complex genomes pose special challenges in the identification of informative SNPs warranting alternative strategies in those crops. Many genotyping platforms and chemistries have become available making the use of SNPs even more attractive and efficient. This paper provides a review of historical and current efforts in the development, validation, and application of SNP markers in QTL/gene discovery and plant breeding by discussing key experimental strategies and cases exemplifying their impact.

A neo-sex chromosome that drives postzygotic sex determination in the hessian fly (Mayetiola destructor).

Two nonoverlapping autosomal inversions defined unusual neo-sex chromosomes in the Hessian fly (Mayetiola destructor). Like other neo-sex chromosomes, these were normally heterozygous, present only in one sex, and suppressed recombination around a sex-determining master switch. Their unusual properties originated from the anomalous Hessian fly sex determination system in which postzygotic chromosome elimination is used to establish the sex-determining karyotypes. This system permitted the evolution of a master switch (Chromosome maintenance, Cm) that acts maternally. All of the offspring of females that carry Cm-associated neo-sex chromosomes attain a female-determining somatic karyotype and develop as females. Thus, the chromosomes act as maternal effect neo-W's, or W-prime (W') chromosomes, where ZW' females mate with ZZ males to engender female-producing (ZW') and male-producing (ZZ) females in equal numbers. Genetic mapping and physical mapping identified the inversions. Their distribution was determined in nine populations. Experimental matings established the association of the inversions with Cm and measured their recombination suppression. The inversions are the functional equivalent of the sciarid X-prime chromosomes. We speculate that W' chromosomes exist in a variety of species that produce unisexual broods.

Localization and characterization of 170 BAC-derived clones and mapping of 94 microsatellites in the Hessian fly.

Ninety-four microsatellites from enriched genomic libraries of Hessian fly (Hf, Mayetiola destructor [Say]) were localized to 170 cognate clones in an Hf bacterial artificial chromosome (BAC) library. These microsatellite-positive BAC clones were physically mapped to polytene chromosomes by fluorescent in situ hybridization. The mapped microsatellite loci can be used to study the genetic diversity and population structure of Hf.

A BAC-based physical map of the Hessian fly genome anchored to polytene chromosomes.

BACKGROUND: The Hessian fly (Mayetiola destructor) is an important insect pest of wheat. It has tractable genetics, polytene chromosomes, and a small genome (158 Mb). Investigation of the Hessian fly presents excellent opportunities to study plant-insect interactions and the molecular mechanisms underlying genome imprinting and chromosome elimination. A physical map is needed to improve the ability to perform both positional cloning and comparative genomic analyses with the fully sequenced genomes of other dipteran species. RESULTS: An FPC-based genome wide physical map of the Hessian fly was constructed and anchored to the insect's polytene chromosomes. Bacterial artificial chromosome (BAC) clones corresponding to 12-fold coverage of the Hessian fly genome were fingerprinted, using high information content fingerprinting (HIFC) methodology, and end-sequenced. Fluorescence in situ hybridization (FISH) co-localized two BAC clones from each of the 196 longest contigs on the polytene chromosomes. An additional 70 contigs were positioned using a single FISH probe. The 266 FISH mapped contigs were evenly distributed and covered 60% of the genome (95,668 kb). The ends of the fingerprinted BACs were then sequenced to develop the capacity to create sequenced tagged site (STS) markers on the BACs in the map. Only 3.64% of the BAC-end sequence was composed of transposable elements, helicases, ribosomal repeats, simple sequence repeats, and sequences of low complexity. A relatively large fraction (14.27%) of the BES was comprised of multi-copy gene sequences. Nearly 1% of the end sequence was composed of simple sequence repeats (SSRs). CONCLUSION: This physical map provides the foundation for high-resolution genetic mapping, map-based cloning, and assembly of complete genome sequencing data. The results indicate that restriction fragment length heterogeneity in BAC libraries used to construct physical maps lower the length and the depth of the contigs, but is not an absolute barrier to the successful application of the technology. This map will serve as a genomic resource for accelerating gene discovery, genome sequencing, and the assembly of BAC sequences. The Hessian fly BAC-clone assembly, and the names and positions of the BAC clones used in the FISH experiments are publically available at (http://genome.purdue.edu/WebAGCoL/Hfly/WebFPC/).

The maternal-effect, selfish genetic element Medea is associated with a composite Tc1 transposon.

Maternal-Effect Dominant Embryonic Arrest ("Medea") factors are selfish nuclear elements that combine maternal-lethal and zygotic-rescue activities to gain a postzygotic survival advantage. We show that Medea(1) activity in Tribolium castaneum is associated with a composite Tc1 transposon inserted just downstream of the neurotransmitter reuptake symporter bloated tubules (blot), whose Drosophila ortholog has both maternal and zygotic functions. The 21.5-kb insertion contains defective copies of elongation initiation factor-3, ATP synthase subunit C, and an RNaseD-related gene, as well as a potentially intact copy of a prokaryotic DUF1703 gene. Sequence comparisons suggest that the current distribution of Medea(1) reflects global emanation after a single transpositional event in recent evolutionary time. The Medea system in Tribolium represents an unusual type of intragenomic conflict and could provide a useful vehicle for driving desirable genes into populations.

Genomic analysis of a 1 Mb region near the telomere of Hessian fly chromosome X2 and avirulence gene vH13.

BACKGROUND: To have an insight into the Mayetiola destructor (Hessian fly) genome, we performed an in silico comparative genomic analysis utilizing genetic mapping, genomic sequence and EST sequence data along with data available from public databases. RESULTS: Chromosome walking and FISH were utilized to identify a contig of 50 BAC clones near the telomere of the short arm of Hessian fly chromosome X2 and near the avirulence gene vH13. These clones enabled us to correlate physical and genetic distance in this region of the Hessian fly genome. Sequence data from these BAC ends encompassing a 760 kb region, and a fully sequenced and assembled 42.6 kb BAC clone, was utilized to perform a comparative genomic study. In silico gene prediction combined with BLAST analyses was used to determine putative orthology to the sequenced dipteran genomes of the fruit fly, Drosophila melanogaster, and the malaria mosquito, Anopheles gambiae, and to infer evolutionary relationships. CONCLUSION: This initial effort enables us to advance our understanding of the structure, composition and evolution of the genome of this important agricultural pest and is an invaluable tool for a whole genome sequencing effort.