Nick Lauter

Quantitative and qualitative stem rust resistance factors in barley are associated with transcriptional suppression of defense regulons

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host–pathogen interaction with enhancement of R-gene mediated resistance.

Quantitative and temporal definition of the Mla transcriptional regulon during barley-powdery mildew interactions.

Barley Mildew resistance locus a (Mla) is a major determinant of immunity to the powdery mildew pathogen, Blumeria graminis f. sp. hordei. Alleles of Mla encode cytoplasmic- and membrane-localized coiled-coil, nucleotide binding site, leucine-rich repeat proteins that mediate resistance when complementary avirulence effectors (AVR(a)) are present in the pathogen. Presence of an appropriate AVR(a) protein triggers nuclear relocalization of MLA, in which MLA binds repressing host transcription factors. Timecourse expression profiles of plants harboring Mla1, Mla6, and Mla12 wild-type alleles versus paired loss-of-function mutants were compared to discover conserved transcriptional targets of MLA and downstream signaling cascades. Pathogen-dependent gene expression was equivalent or stronger in susceptible plants at 20 h after inoculation (HAI) and was attenuated at later timepoints, whereas resistant plants exhibited a time-dependent strengthening of the transcriptional response, increasing in both fold change and the number of genes differentially expressed. Deregulation at 20 HAI implicated 16 HAI as a crucial point in determining the future trajectory of this interaction and was interrogated by quantitative analysis. In total, 28 potential transcriptional targets of the MLA regulon were identified. These candidate targets possess a diverse set of predicted functions, suggesting that multiple pathways are required to mediate the hypersensitive reaction.

Quantitative Genetic Dissection of Shoot Architecture Traits in Maize: Towards a Functional Genomics Approach

Quantitative trait loci (QTL) affecting the total number of leaves made before flowering and the number of leaves below the uppermost ear (NLBE) were mapped and characterized using the intermated B73 × Mo17 recombinant inbred lines (IBMRILs) of maize (Zea mays L.). B73 and Mo17 typically make 20 and 17 leaves, 14 and 11 of which are below the ear. Total number of leaves and the number of leaves below the uppermost ear are ∼80% heritable in the IBMRILs, which show strongly transgressive phenotypic ranges of 15 to 24 and 10 to 18 leaves for these traits. B73 alleles at loci in chromosome bins 1.06, 3.06, 4.08, 8.04, 8.05, 9.07, and 10.04 increase leaf numbers, with all but the 3.06 QTL affecting both of these highly correlated traits (r = 0.86, p < 0.0001). Conservative QTL confidence intervals were computed and projected onto the draft maize genome sequence, revealing very narrow localizations (∼1 Mb) for four of the seven loci. More than 40% of the heritable variation for both traits is explained by an additive model, squarely accounting for the dramatic parental differences, but leaving the basis of the strong transgression unexplained. In addition, error rate control and confidence interval methods tailored for composite interval mapping are introduced, and their potential for improving QTL reporting is discussed.

A gene encoding maize caffeoyl-CoA O -methyltransferase confers quantitative resistance to multiple pathogens

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement, although the molecular mechanisms underlying their functions remain largely unknown. A quantitative trait locus, qMdr9.02, associated with resistance to three important foliar maize diseases—southern leaf blight, gray leaf spot and northern leaf blight—has been identified on maize chromosome 9. Through fine-mapping, association analysis, expression analysis, insertional mutagenesis and transgenic validation, we demonstrate that ZmCCoAOMT2, which encodes a caffeoyl-CoA O-methyltransferase associated with the phenylpropanoid pathway and lignin production, is the gene within qMdr9.02 conferring quantitative resistance to both southern leaf blight and gray leaf spot. We suggest that resistance might be caused by allelic variation at the level of both gene expression and amino acid sequence, thus resulting in differences in levels of lignin and other metabolites of the phenylpropanoid pathway and regulation of programmed cell death.

MAPPING OF IRON AND ZINC QUANTITATIVE TRAIT LOCI IN SOYBEAN FOR ASSOCIATION TO IRON DEFICIENCY CHLOROSIS RESISTANCE

Iron deficiency chlorosis (IDC) in soybean results in yield losses or in extreme cases death. Breeding for resistance has shown limited success with no cultivar having complete resistance. Mineral content of the soybean could be an indicator of the ability of the plant to withstand the effects of IDC. Iron (Fe) and zinc (Zn) concentration was examined in soybean seed and leaves. SSR, RFLP, and BARCSOYSSR markers were used to construct a linkage map used for mapping of Fe and Zn concentrations. The QTL analysis for the combined data identified one major QTL for seed Fe accumulation on chromosome 20 that explained 21.5% of the variation. This QTL was in the marker interval pa_515-1-Satt239, with marker pa_515-1 previously being used to map an Fe-efficiency QTL. This provides the first evidence of a potential genetic link between Fe-efficiency and Fe accumulation in the soybean seed.

The effect of artificial selection on phenotypic plasticity in maize

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0–5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements.Breeding has increased crop productivity, but whether it has also changed phenotypic plasticity is unclear. Here, the authors find maize genomic regions selected for high productivity show reduced contribution to genotype by environment variation and provide evidence for regulatory control of phenotypic stability.

Hallauer's Tusón: a decade of selection for tropical-to-temperate phenological adaptation in maize.

Crop species exhibit an astounding capacity for environmental adaptation, but genetic bottlenecks resulting from intense selection for adaptation and productivity can lead to a genetically vulnerable crop. Improving the genetic resiliency of temperate maize depends upon the use of tropical germplasm, which harbors a rich source of natural allelic diversity. Here, the adaptation process was studied in a tropical maize population subjected to 10 recurrent generations of directional selection for early flowering in a single temperate environment in Iowa, USA. We evaluated the response to this selection across a geographical range spanning from 43.05° (WI) to 18.00° (PR) latitude. The capacity for an all-tropical maize population to become adapted to a temperate environment was revealed in a marked fashion: on average, families from generation 10 flowered 20 days earlier than families in generation 0, with a nine-day separation between the latest generation 10 family and the earliest generation 0 family. Results suggest that adaptation was primarily due to selection on genetic main effects tailored to temperature-dependent plasticity in flowering time. Genotype-by-environment interactions represented a relatively small component of the phenotypic variation in flowering time, but were sufficient to produce a signature of localized adaptation that radiated latitudinally, in partial association with daylength and temperature, from the original location of selection. Furthermore, the original population exhibited a maladaptive syndrome including excessive ear and plant heights along with later flowering; this was reduced in frequency by selection for flowering time.

QTL Mapping and Candidate Gene Analysis of Telomere Length Control Factors in Maize (Zea mays L.).

Telomere length is a quantitative trait important for many cellular functions. Failure to regulate telomere length contributes to genomic instability, cellular senescence, cancer, and apoptosis in humans, but the functional significance of telomere regulation in plants is much less well understood. To gain a better understanding of telomere biology in plants, we used quantitative trait locus (QTL) mapping to identify genetic elements that control telomere length variation in maize (Zea mays L.). For this purpose, we measured the median and mean telomere lengths from 178 recombinant inbred lines of the IBM mapping population and found multiple regions that collectively accounted for 33–38% of the variation in telomere length. Two-way analysis of variance revealed interaction between the quantitative trait loci at genetic bin positions 2.09 and 5.04. Candidate genes within these and other significant QTL intervals, along with select genes known a priori to regulate telomere length, were tested for correlations between expression levels and telomere length in the IBM population and diverse inbred lines by quantitative real-time PCR. A slight but significant positive correlation between expression levels and telomere length was observed for many of the candidate genes, but Ibp2 was a notable exception, showing instead a negative correlation. A rad51-like protein (TEL-MD_5.04) was strongly supported as a candidate gene by several lines of evidence. Our results highlight the value of QTL mapping plus candidate gene expression analysis in a genetically diverse model system for telomere research.

Genomics of Biotic Interactions in the Triticeae

In the area of Triticeae-pathogen interactions, highly parallel profiling of the transcriptome and proteome has provided entry points to examine host reaction to various pathogens and pests. In particular, the molecular mechanisms underlying gene-for-gene resistance and basal defense have been explored in the contrasting contexts of host vs. nonhost resistance and biotrophic vs. necrotrophic pathogenesis. Capitalizing on a rich history of genetics, molecular biology and plant pathology, recent studies in the Triticeae have provided new insights and characterized previously undescribed phenomena. The unique features of various pathosystems are increasingly leveraged by breakthroughs in genomic technologies, facilitating a community-wide approach to unifying themes of molecular plant-microbe interactions in the Triticeae.

An Empirical Method for Establishing Positional Confidence Intervals Tailored for Composite Interval Mapping of QTL

Background Improved genetic resolution and availability of sequenced genomes have made positional cloning of moderate-effect QTL realistic in several systems, emphasizing the need for precise and accurate derivation of positional confidence intervals (CIs) for QTL. Support interval (SI) methods based on the shape of the QTL likelihood curve have proven adequate for standard interval mapping, but have not been shown to be appropriate for use with composite interval mapping (CIM), which is one of the most commonly used QTL mapping methods. Results Based on a non-parametric confidence interval (NPCI) method designed for use with the Haley-Knott regression method for mapping QTL, a CIM-specific method (CIM-NPCI) was developed to appropriately account for the selection of background markers during analysis of bootstrap-resampled data sets. Coverage probabilities and interval widths resulting from use of the NPCI, SI, and CIM-NPCI methods were compared in a series of simulations analyzed via CIM, wherein four genetic effects were simulated in chromosomal regions with distinct marker densities while heritability was fixed at 0.6 for a population of 200 isolines. CIM-NPCIs consistently capture the simulated QTL across these conditions while slightly narrower SIs and NPCIs fail at unacceptably high rates, especially in genomic regions where marker density is high, which is increasingly common for real studies. The effects of a known CIM bias toward locating QTL peaks at markers were also investigated for each marker density case. Evaluation of sub-simulations that varied according to the positions of simulated effects relative to the nearest markers showed that the CIM-NPCI method overcomes this bias, offering an explanation for the improved coverage probabilities when marker densities are high. Conclusions Extensive simulation studies herein demonstrate that the QTL confidence interval methods typically used to positionally evaluate CIM results can be dramatically improved by accounting for the procedural complexity of CIM via an empirical approach, CIM-NPCI. Confidence intervals are a critical measure of QTL utility, but have received inadequate treatment due to a perception that QTL mapping is not sufficiently precise for procedural improvements to matter. Technological advances will continue to challenge this assumption, creating even more need for the current improvement to be refined.