QTL for resistance to root lesion nematode (Pratylenchus thornei) from a synthetic hexaploid wheat source

Key message

A whole genome average interval mapping approach identified eight QTL associated with P. thornei resistance in a DH population from a cross between the synthetic-derived wheat Sokoll and cultivar Krichauff.

Abstract

Pratylenchus thornei are migratory nematodes that feed and reproduce within the wheat root cortex, causing cell death (lesions) resulting in severe yield reductions globally. Genotypic selection using molecular markers closely linked to Pratylenchus resistance genes will accelerate the development of new resistant cultivars by reducing the need for laborious and expensive resistance phenotyping. A doubled haploid wheat population (150 lines) from a cross between the synthetic-derived cultivar Sokoll (P. thornei resistant) and cultivar Krichauff (P. thornei moderately susceptible) was used to identify quantitative trait loci (QTL) associated with P. thornei resistance. The resistance identified in the glasshouse was validated in a field trial. A genetic map was constructed using Diversity Array Technology and the QTL regions identified were further targeted with simple sequence repeat (SSR) and single-nucleotide polymorphism (SNP) markers. Six significant and two suggestive P. thornei resistance QTL were detected using a whole genome average interval mapping approach. Three QTL were identified on chromosome 2B, two on chromosome 6D, and a single QTL on each of chromosomes 2A, 2D and 5D. The QTL on chromosomes 2BS and 6DS mapped to locations previously identified to be associated with Pratylenchus resistance. Together, the QTL on 2B (QRlnt.sk-2B.1–2B.3) and 6D (QRlnt.sk-6D.1 and 6D.2) explained 30 and 48 % of the genotypic variation, respectively. Flanking PCR-based markers based on SSRs and SNPs were developed for the major QTL on 2B and 6D and provide a cost-effective high-throughput tool for marker-assisted breeding of wheat with improved P. thornei resistance.     

Insights into the Effects of Long-Term Artificial Selection on Seed Size in Maize

Grain produced from cereal crops is a primary source of human food and animal feed worldwide. To understand the genetic basis of seed-size variation, a grain yield component, we conducted a genome-wide scan to detect evidence of selection in the maize Krug Yellow Dent long-term divergent seed-size selection experiment. Previous studies have documented significant phenotypic divergence between the populations. Allele frequency estimates for ∼3 million single nucleotide polymorphisms (SNPs) in the base population and selected populations were estimated from pooled whole-genome resequencing of 48 individuals per population. Using F_ST values across sliding windows, 94 divergent regions with a median of six genes per region were identified. Additionally, 2729 SNPs that reached fixation in both selected populations with opposing fixed alleles were identified, many of which clustered in two regions of the genome. Copy-number variation was highly prevalent between the selected populations, with 532 total regions identified on the basis of read-depth variation and comparative genome hybridization. Regions important for seed weight in natural variation were identified in the maize nested association mapping population. However, the number of regions that overlapped with the long-term selection experiment did not exceed that expected by chance, possibly indicating unique sources of variation between the two populations. The results of this study provide insights into the genetic elements underlying seed-size variation in maize and could also have applications for other cereal crops.     

A Genome-Wide Scan for Evidence of Selection in a Maize Population Under Long-Term Artificial Selection for Ear Number

A genome-wide scan to detect evidence of selection was conducted in the Golden Glow maize long-term selection population. The population had been subjected to selection for increased number of ears per plant for 30 generations, with an empirically estimated effective population size ranging from 384 to 667 individuals and an increase of more than threefold in the number of ears per plant. Allele frequencies at >1.2 million single-nucleotide polymorphism loci were estimated from pooled whole-genome resequencing data, and F_ST values across sliding windows were employed to assess divergence between the population preselection and the population postselection. Twenty-eight highly divergent regions were identified, with half of these regions providing gene-level resolution on potentially selected variants. Approximately 93% of the divergent regions do not demonstrate a significant decrease in heterozygosity, which suggests that they are not approaching fixation. Also, most regions display a pattern consistent with a soft-sweep model as opposed to a hard-sweep model, suggesting that selection mostly operated on standing genetic variation. For at least 25% of the regions, results suggest that selection operated on variants located outside of currently annotated coding regions. These results provide insights into the underlying genetic effects of long-term artificial selection and identification of putative genetic elements underlying number of ears per plant in maize.     

Estimating the Aboveground Biomass of Bornean Forest

We apply a process‐based model, called 3‐PG (physiological principles for predicting growth), to estimate aboveground biomass for the primary forests of Borneo. Using publicly available soil and climate data, and parameterized with physiological traits of Bornean forest, the modeled aboveground biomass and basal area showed statistically significant relationships with field‐measured data from 85 sites across four major forest types. Our results highlight the possibility to expand the application of 3‐PG to forests of varying condition, which would facilitate inclusion of modeled forest biomass data for developing a Tier 3 carbon inventory system for Borneo.     

Tool use in animals: Cognition and ecology. Edited by Crickette M. Sanz,Josep Call,and Christophe Boesch. New York,NJ: Cambridge University Press. 2013. 313 pp. ISBN 978‐1‐107–01119‐9. $110 (hardcover).

Enamel thickness has been linked to functional aspects of masticatory biomechanics and has been demonstrated to be an evolutionary plastic trait, selectively responsive to dietary changes, wear and tooth fracture. European Late Paleolithic and Mesolithic hunter‐gatherers mainly show a flat wear pattern, while oblique molar wear has been reported as characteristic of Neolithic agriculturalists. We investigate the relationships between enamel thickness distribution and molar wear pattern in two Neolithic and medieval populations. Under the assumption that dietary and/or non‐dietary constraints result in directional selective pressure leading to variations in enamel thickness, we test the hypothesis that these two populations will exhibit significant differences in wear and enamel thickness patterns. Occlusal wear patterns were scored in upper permanent second molars (UM2) of 64 Neolithic and 311 medieval subadult and adult individuals. Enamel thickness was evaluated by microtomography in subsamples of 17 Neolithic and 25 medieval individuals. Eight variables describing enamel thickness were assessed. The results show that oblique molar wear is dominant in the Neolithic sample (87%), while oblique wear affects only a minority (42%) of the medieval sample. Moreover, in the Neolithic molars, where buccolingually directed oblique wear is dominant and greatest enamel lost occurs in the distolingual quadrant, thickest enamel is found where occlusal stresses are the most important—on the distolingual cusp. These results reveal a correlation between molar wear pattern and enamel thickness that has been associated to dietary changes. In particular, relatively thicker molar enamel may have evolved as a plastic response to resist wear. Am J Phys Anthropol 155:162–172, 2014. © 2014 Wiley Periodicals, Inc.     

Bayesian latent trait modeling of migraine symptom data

Definition of disease phenotype is a necessary preliminary to research into genetic causes of a complex disease. Clinical diagnosis of migraine is currently based on diagnostic criteria developed by the International Headache Society. Previously, we examined the natural clustering of these diagnostic symptoms using latent class analysis (LCA) and found that a four-class model was preferred. However, the classes can be ordered such that all symptoms progressively intensify, suggesting that a single continuous variable representing disease severity may provide a better model. Here, we compare two models: item response theory and LCA, each constructed within a Bayesian context. A deviance information criterion is used to assess model fit. We phenotyped our population sample using these models, estimated heritability and conducted genome-wide linkage analysis using Merlin-qtl. LCA with four classes was again preferred. After transformation, phenotypic trait values derived from both models are highly correlated (correlation = 0.99) and consequently results from subsequent genetic analyses were similar. Heritability was estimated at 0.37, while multipoint linkage analysis produced genome-wide significant linkage to chromosome 7q31-q33 and suggestive linkage to chromosomes 1 and 2. We argue that such continuous measures are a powerful tool for identifying genes contributing to migraine susceptibility.     

Tradeoffs of different types of species occurrence data for use in systematic conservation planning

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.     

Acute actions of marine toxin latrunculin A on the electrophysiological properties of cultured dorsal root ganglion neurones

The effects of latrunculin A, isolated from the nudibranch Chromodoris sp., on the excitability of neonatal rat cultured dorsal root ganglion neurones were investigated using patch-clamp recording and Ca(2+) imaging techniques. Under current-clamp conditions, acute application of latrunculin A (100 microM) reversibly induced multiple action potential firing and significantly increased action potential duration. No significant effects on action potential peak amplitude, threshold of action potential firing, resting membrane potential and input resistance were observed. Under voltage-clamp conditions, significant and dose-dependent suppression of K(+) current was seen with 10-100 microM latrunculin A. Additionally, a significant difference between inhibition of the current measured at the peak and the end of a 100 ms voltage step was seen with 100 microM latrunculin A. Fura-2 fluorescence Ca(2+) imaging revealed that latrunculin A (100 microM) significantly inhibited Ca(2+) transients evoked by KCl-induced depolarisation in all neurones. In 36% of DRG neurones, latrunculin A alone had no effect on intracellular Ca(2+). In 64% of neurones, latrunculin A alone evoked a transient rise in intracellular Ca(2+). Moreover, latrunculin A (10-100 microM) significantly inhibited the mean high voltage-activated Ca(2+) current. The effects of latrunculin A on action potential firing and K(+) currents were attenuated by intracellular phalloidin, an indication that these effects are mediated through actin disruption.