The genomes of most, if not all, flowering plants have undergone whole genome duplication events during their evolution. The impact of such polyploidy events is poorly understood, as is the fate of most duplicated genes. We sequenced an approximately 1 million-bp region in soybean (Glycine max) centered on the Rpg1-b disease resistance gene and compared this region with a region duplicated 10 to 14 million years ago. These two regions were also compared with homologous regions in several related legume species (a second soybean genotype, Glycine tomentella, Phaseolus vulgaris, and Medicago truncatula), which enabled us to determine how each of the duplicated regions (homoeologues) in soybean has changed following polyploidy. The biggest change was in retroelement content, with homoeologue 2 having expanded to 3-fold the size of homoeologue 1. Despite this accumulation of retroelements, over 77% of the duplicated low-copy genes have been retained in the same order and appear to be functional. This finding contrasts with recent analyses of the maize (Zea mays) genome, in which only about one-third of duplicated genes appear to have been retained over a similar time period. Fluorescent in situ hybridization revealed that the homoeologue 2 region is located very near a centromere. Thus, pericentromeric localization, per se, does not result in a high rate of gene inactivation, despite greatly accelerated retrotransposon accumulation. In contrast to low-copy genes, nucleotide-binding-leucine-rich repeat disease resistance gene clusters have undergone dramatic species/homoeologuespecific duplications and losses, with some evidence for partitioning of subfamilies between homoeologues.The comparative approach to studying genes and genomes is a powerful method for addressing both

Impacts of population structure on the evaluation of genomic heritability and prediction were investigated and quantified using high-density markers in diverse panels in rice and maize. Population structure is an important factor affecting estimation of genomic heritability and assessment of genomic prediction in stratified populations. In this study, our first objective was to assess effects of population structure on estimations of genomic heritability using the diversity panels in rice and maize. Results indicate population structure explained 33 and 7.5% of genomic heritability for rice and maize, respectively, depending on traits, with the remaining heritability explained by within-subpopulation variation. Estimates of within-subpopulation heritability were higher than that derived from quantitative trait loci identified in genome-wide association studies, suggesting 65% improvement in genetic gains. The second objective was to evaluate effects of population structure on genomic prediction using cross-validation experiments. When population structure exists in both training and validation sets, correcting for population structure led to a significant decrease in accuracy with genomic prediction. In contrast, when prediction was limited to a specific subpopulation, population structure showed little effect on accuracy and within-subpopulation genetic variance dominated predictions. Finally, effects of genomic heritability on genomic prediction were investigated. Accuracies with genomic prediction increased with genomic heritability in both training and validation sets, with the former showing a slightly greater impact. In summary, our results suggest that the population structure contribution to genomic prediction varies based on prediction strategies, and is also affected by the genetic architectures of traits and populations. In practical breeding, these conclusions may be helpful to better understand and utilize the different genetic resources in genomic prediction.

Few quantitative trait loci (QTL) have been mapped for the expression of partial resistance to Phytophthora sojae in soybean and very little is known about the molecular mechanisms that contribute to this trait. Therefore, the objectives of this study were to identify additional QTL conferring resistance to P. sojae and to identify candidate genes that may contribute to this form of defense. QTL on chromosomes 12, 13, 14, 17, and 19, each explaining 4 to 7% of the phenotypic variation, were identifi ed using 186 RILs from a cross of the partially resistant cultivar 'Conrad' and susceptible cultivar 'Sloan' through composite interval mapping. Microarray analysis identifi ed genes with signifi cant differences in transcript abundances between Conrad and Sloan, both constitutively and following inoculation. Of these genes, 55 mapped to the fi ve QTL regions. Ten genes encoded proteins with unknown functions, while the others encode proteins related to defense or physiological traits. Seventeen genes within the genomic region that encompass the QTL were selected and their transcript abundance was confi rmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR). These results suggest a complex QTL-mediated resistance network. This study will contribute to soybean resistance breeding by providing additional QTL for marker-assisted selection as well as a list of candidate genes which may be manipulated to confer resistance.

The effect of psychosocial stress on distinct memory processes was investigated in 157 college students using a brief film, which enabled comparison of verbal and visual memory by using a single complex stimulus. Participants were stressed either following stimuli presentation (consolidation) or before testing 48 hr later (retrieval) and were compared with no-stress controls. Salivary cortisol was measured before and 20 min after stress. The consolidation group significantly outperformed controls on total and verbal film scores. Stress did not impair retrieval relative to controls. Exploratory analyses revealed a significant correlation between cortisol and verbal scores across all groups (r ϭ .18). Results provide the first evidence of a facilitative effect of a stressor on verbal memory, but failed to replicate retrieval findings.

No abstract

In comparison to conventional marker-assisted selection (MAS), which utilizes only a subset of genetic markers associated with a trait to predict breeding values (BVs), genome-wide selection (GWS) improves prediction accuracies by incorporating all markers into a model simultaneously. This strategy avoids risks of missing quantitative trait loci (QTL) with small effects. Here, we evaluated the accuracy of prediction for three corn flowering traits days to silking, days to anthesis, and anthesis-silking interval with GWS based on cross-validation experiments using a large data set of 25 nested association mapping populations in maize (Zea mays). We found that GWS via ridge regression-best linear unbiased prediction (RR-BLUP) gave significantly higher predictions compared to MAS utilizing composite interval mapping (CIM). The CIM method may be selected over multiple linear regression to decrease over-estimations of the efficiency of GWS over a MAS strategy. The RR-BLUP method was the preferred method for estimating marker effects in GWS with prediction accuracies comparable to or greater than BayesA and BayesB. The accuracy with RR-BLUP increased with training sample proportion, marker density, and heritability until it reached a plateau. In general, gains in accuracy with RR-BLUP over CIM increased with decreases of these factors. Compared to training sample proportion, the accuracy of prediction with RR-BLUP was relatively insensitive to marker density.

The performance of 16 attention-deficit hyperactivity disorder (ADHD)/C, 26 ADHD/IA, and 24 control children was compared using a computer reaction time task designed to measure the effects of Posner's orienting, conflict and alerting attentional systems. No group differences in orienting or conflict were found. In contrast, children with ADHD/IA showed stronger alerting effects than those with ADHD/C, as indicated by relatively greater performance benefits following a warning cue. Although neither ADHD group differed significantly from controls on alerting, effect size comparisons indicated that children with ADHD/IA showed a somewhat larger (d=.57) and children with ADHD/C a somewhat smaller (d=.44) alerting effect relative to control children. The results are among the first to document unique patterns of attentional capacity for ADHD subtypes.

Background: Root system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja.