Dominance and G×E interaction effects improvegenomic prediction and genetic gain inintermediate wheatgrass (Thinopyrumintermedium)

Genomic selection (GS) based recurrent selection methods were developed to accelerate the domestication of intermediate wheatgrass [IWG, Thinopyrum intermedium (Host) Barkworth & D.R. Dewey]. A subset of the breeding population phenotyped at multiple environments is used to train GS models and then predict trait values of the breeding population. In this study, we implemented several GS models that investigated the use of additive and dominance effects and G×E interaction effects to understand how they affected trait predictions in intermediate wheatgrass. We evaluated 451 genotypes from the University of Minnesota IWG breeding program for nine agronomic and domestication traits at two Minnesota locations during 2017–2018. Genet-mean based heritabilities for these traits ranged from 0.34 to 0.77. Using fourfold cross validation, we observed the highest predictive abilities (correlation of 0.67) in models that considered G×E effects. When G×E effects were fitted in GS models, trait predictions improved by 18%, 15%, 20%, and 23% for yield, spike weight, spike length, and free threshing, respectively. Genomic selection models with dominance effects showed only modest increases of up to 3% and were trait-dependent. Crossenvironment predictions were better for high heritability traits such as spike length, shatter resistance, free threshing, grain weight, and seed length than traits with low heritability and large environmental variance such as spike weight, grain yield, and seed width. Our results confirm that GS can accelerate IWG domestication by increasing genetic gain per breeding cycle and assist in selection of genotypes with promise of better performance in diverse environments

Intensification differentially affects the delivery of multiple ecosystem services in subtropical and temperate grasslands

Intensification, the process of intensifying land management to enhance agricultural goods, results in “intensive” pastures that are planted with productive grasses and fertilized. These intensive pastures provide essential ecosystem services, including forage production for livestock. Understanding the synergies and tradeoffs of pasture intensification on the delivery of services across climatic regions is crucial to shape policies and incentives for better management of natural resources. Here, we investigated how grassland intensification affects key components of provisioning (forage productivity and quality), supporting (plant diversity) and regulating services (CO2 and CH4 fluxes) by comparing these services between intensive versus extensive pastures in subtropical and temperate pastures in the USDA Long-term Agroecosystem Research (LTAR) Network sites in Florida and Oklahoma, USA over multiple years. Our results suggest that grassland intensification led to a decrease in measured supporting and regulating services, but increased forage productivity in temperate pastures and forage digestibility in subtropical pastures. Intensification decreased the net CO2 sink of subtropical pastures while it did not affect the sink capacity of temperate pastures; and it also increased environmental CH4 emissions from subtropical pastures and reduced CH4 uptake in temperate pastures. Intensification enhanced the global warming potential associated with C fluxes of pastures in both ecoregions. Our study demonstrates that comparisons of agroecosystems in contrasting ecoregions can reveal important drivers of ecosystem services and general or region-specific opportunities and solutions to maintaining agricultural production and reducing environmental footprints. Further LTAR network-scale comparisons of multiple ecosystem services across croplands and grazinglands intensively vs extensively managed are warranted to inform the sustainable intensification of agriculture within US and beyond. Our results highlight that achieving both food security and environmental stewardship will involve the conservation of less intensively managed pastures while adopting sustainable strategies in intensively managed pastures

Transcriptome characterization and polymorphism detection between subspecies of big sagebrush (Artemisia tridentata)

<p>Abstract</p> <p>Background</p> <p>Big sagebrush (<it>Artemisia tridentata</it>) is one of the most widely distributed and ecologically important shrub species in western North America. This species serves as a critical habitat and food resource for many animals and invertebrates. Habitat loss due to a combination of disturbances followed by establishment of invasive plant species is a serious threat to big sagebrush ecosystem sustainability. Lack of genomic data has limited our understanding of the evolutionary history and ecological adaptation in this species. Here, we report on the sequencing of expressed sequence tags (ESTs) and detection of single nucleotide polymorphism (SNP) and simple sequence repeat (SSR) markers in subspecies of big sagebrush.</p> <p>Results</p> <p>cDNA of <it>A. tridentata </it>sspp. <it>tridentata </it>and <it>vaseyana </it>were normalized and sequenced using the 454 GS FLX Titanium pyrosequencing technology. Assembly of the reads resulted in 20,357 contig consensus sequences in ssp. <it>tridentata </it>and 20,250 contigs in ssp. <it>vaseyana</it>. A BLASTx search against the non-redundant (NR) protein database using 29,541 consensus sequences obtained from a combined assembly resulted in 21,436 sequences with significant blast alignments (≤ 1e^-15). A total of 20,952 SNPs and 119 polymorphic SSRs were detected between the two subspecies. SNPs were validated through various methods including sequence capture. Validation of SNPs in different individuals uncovered a high level of nucleotide variation in EST sequences. EST sequences of a third, tetraploid subspecies (ssp. <it>wyomingensis</it>) obtained by Illumina sequencing were mapped to the consensus sequences of the combined 454 EST assembly. Approximately one-third of the SNPs between sspp. <it>tridentata </it>and <it>vaseyana </it>identified in the combined assembly were also polymorphic within the two geographically distant ssp. <it>wyomingensis </it>samples.</p> <p>Conclusion</p> <p>We have produced a large EST dataset for <it>Artemisia tridentata</it>, which contains a large sample of the big sagebrush leaf transcriptome. SNP mapping among the three subspecies suggest the origin of ssp. <it>wyomingensis </it>via mixed ancestry. A large number of SNP and SSR markers provide the foundation for future research to address questions in big sagebrush evolution, ecological genetics, and conservation using genomic approaches.</p

Beyond the brain: ?-Synuclein and its implications in bone and fat metabolism

Introduction: Pathological form of α-synuclein is the major component of the Lewy body in the brain of Parkinson’s disease (PD) patients. Research efforts have been directed towards understanding the root and progression of the neurodegeneration and its association to symptoms. Physiological α-synuclein is ubiquitously present in the human body, however, its role outside the central nervous system has been poorly studied. PD seriously impairs life quality; symptoms comprehend from locomotor dysfunction including resting tremors, rigidity and bradykinesia to non-motor features such as autonomic dysfunction, cognitive/neurobehavioral abnormalities, sleep and sensory disorders. Additionally, PD patients often experiment weight loss, impaired bone mineral density and increased risk of fracture, which severity increases as the disease progresses. Recently, we have found that α-synuclein is a novel and key regulator of bone homeostasis. Moreover, we showed in mice that absence of α-synuclein partially protects against bone loss induced by estrogen-deficiency and weight gain. Our central hypothesis is that α-synuclein exerts these effects by acting cell autonomously in fat and bone cells, thus, our work aims to improve the understanding of α-synuclein regulating body fat mass and bone health to shed light of potential therapeutic targets