Young adults typically deactivate specific brain regions during active task performance. Deactivated regions overlap with those that show reduced resting metabolic activity in aging and dementia, raising the possibility of a relation. Here, the magnitude and dynamic temporal properties of these typically deactivated regions were explored in aging by using functional MRI in 82 participants. Young adults (n ‫؍‬ 32), older adults without dementia (n ‫؍‬ 27), and older adults with early-stage dementia of the Alzheimer type (DAT) (n ‫؍‬ 23) were imaged while alternating between blocks of an active semantic classification task and a passive fixation baseline. Deactivation in lateral parietal regions was equivalent across groups; in medial frontal regions, it was reduced by aging but was not reduced further by DAT. Of greatest interest, a medial parietal͞ posterior cingulate region showed differences between young adults and older adults without dementia and an even more marked difference with DAT. The temporal profile of the medial parietal͞posterior cingulate response suggested that it was initially activated by all three groups, but the response in young adults quickly reversed sign, whereas DAT individuals maintained activation throughout the task block. Exploratory whole-brain analyses confirmed the importance of medial parietal͞posterior cingulate cortex differences in aging and DAT. These results introduce important opportunities to explore the functional properties of regions showing deactivations, how their dynamic functional properties relate to their baseline metabolic rates, and how they change with age and dementia.

High density genetic maps are a reliable tool for genetic dissection of complex plant traits. Mapping resolution is often hampered by the variable crossover and non-crossover events occurring across the genome, with pericentromeric regions (pCENR) showing highly suppressed recombination rates. The efficiency of linkage mapping can further be improved by characterizing and understanding the distribution of recombinational activity along individual chromosomes. In order to evaluate the genome wide recombination rate in common beans (Phaseolus vulgaris L.) we developed a SNP-based linkage map using the genotype-by-sequencing approach with a 188 recombinant inbred line family generated from an inter gene pool cross (Andean x Mesoamerican). We identified 1,112 SNPs that were subsequently used to construct a robust linkage map with 11 groups, comprising 513 recombinationally unique marker loci spanning 943 cM (LOD 3.0). Comparative analysis showed that the linkage map spanned >95% of the physical map, indicating that the map is almost saturated. Evaluation of genome-wide recombination rate indicated that at least 45% of the genome is highly recombinationally suppressed, and allowed us to estimate locations of pCENRs. We observed an average recombination rate of 0.25 cM/Mb in pCENRs as compared to the rest of genome that showed 3.72 cM/Mb. However, several hot spots of recombination were also detected with recombination rates reaching as high as 34 cM/Mb. Hotspots were mostly found towards the end of chromosomes, which also happened to be gene-rich regions. Analyzing relationships between linkage and physical map indicated a punctuated distribution of recombinational hot spots across the genome.

The next generation of gene-based crop models offers the potential of predicting crop vegetative and reproductive development based on genotype and weather data as inputs. Here, we illustrate an approach for developing a dynamic modular gene-based model to simulate changes in main stem node numbers, time to first anthesis, and final node number on the main stem of common bean (Phaseolus vulgaris L.). In the modules, these crop characteristics are functions of relevant genes (quantitative trait loci (QTL)), the environment (E), and QTL × E interactions. The model was based on data from 187 recombinant inbred (RI) genotypes and the two parents grown at five sites (Citra, FL; Palmira, Colombia; Popayan, Colombia; Isabela Puerto Rico; and Prosper, North Dakota). The model consists of three dynamic QTL effect models for node addition rate (NAR, No. d− 1), daily rate of progress from emergence toward flowering (RF), and daily maximum main stem node number (MSNODmax), that were integrated to simulate main stem node number vs. time, and date of first flower using daily time steps. Model evaluation with genotypes not used in model development showed reliable predictions across all sites for time to first anthesis (R2 = 0.75) and main stem node numbers during the linear phase of node addition (R2 = 0.93), while prediction of the final main stem node number was less reliable (R2 = 0.27). The use of mixed-effects models to analyze multi-environment data from a wide range of genotypes holds considerable promise for assisting development of dynamic QTL effect models capable of simulating vegetative and reproductive development.

Core Ideas Association analyses of cold‐tolerance traits of white clover revealed 17 quantitative loci Genomic tetraploid parameterization allowed description of population Genomic tetraploid parameterization improved QTL detection in this polyploidy species WSCdr found to be important physiological mechanism conferring cold tolerance Four candidate genes discovered for WSCdr Significant phenotypic variation explained by markers found associated with traits MAS for some tolerance traits now seems possible White clover (Trifolium repens L.) is the most important grazing perennial forage legume in temperate climates. However, its limited capacity to survive and restore growth after low temperatures during winter constrains the productivity and wide adoption of the crop. Despite the importance of cold tolerance for white clover cultivar development, the genetic basis of this trait remains largely unknown. Hence, in this study, we performed the first genome‐wide association study (GWAS) analyses in white clover to identify quantitative trait loci (QTL) for cold‐tolerance‐related traits. Seeds from 192 divergent genotypes from six populations in the Patagonia region of South America were collected and seed‐derived plants were further clonally propagated. Clonal trials were established in three locations representing temperature gradient associated with elevation. Given the allotetraploid nature of the white clover genome, distinct genetic models (diploid and tetraploid) were tested. Only the tetraploid parameterization was able to detect the 53 loci associated with cold‐tolerance traits. Out of the 53 single nucleotide polymorphism (SNP) trait associations, 17 controlled more than one trait or were stable across multiple sites. This work represents the first report of QTL for cold‐tolerance‐related traits, providing insights into its genetic basis and candidate genomic regions for further functional validation studies.