Autotetraploid Induction of Three A-Genome Wild Peanut Species, Arachis cardenasii, A. correntina, and A. diogoi.

A-genome Arachis species (AA; 2n = 2x = 20) are commonly used as secondary germplasm sources in cultivated peanut breeding, Arachis hypogaea L. (AABB; 2n = 4x = 40), for the introgression of various biotic and abiotic stress resistance genes. Genome doubling is critical to overcoming the hybridization barrier of infertility that arises from ploidy-level differences between wild germplasm and cultivated peanuts. To develop improved genome doubling methods, four trials of various concentrations of the mitotic inhibitor treatments colchicine, oryzalin, and trifluralin were tested on the seedlings and seeds of three A-genome species, A. cardenasii, A. correntina, and A. diogoi. A total of 494 seeds/seedlings were treated in the present four trials, with trials 1 to 3 including different concentrations of the three chemical treatments on seedlings, and trial 4 focusing on the treatment period of 5 mM colchicine solution treatment of seeds. A small number of tetraploids were produced from the colchicine and oryzalin gel treatments of seedlings, but all these tetraploid seedlings reverted to diploid or mixoploid states within six months of treatment. In contrast, the 6-h colchicine solution treatment of seeds showed the highest tetraploid conversion rate (6-13% of total treated seeds or 25-40% of surviving seedlings), and the tetraploid plants were repeatedly tested as stable tetraploids. In addition, visibly and statistically larger leaves and flowers were produced by the tetraploid versions of these three species compared to their diploid versions. As a result, stable tetraploid plants of each A-genome species were produced, and a 5 mM colchicine seed treatment is recommended for A-genome and related wild Arachis species genome doubling.

Initiation of genomics-assisted breeding in Virginia-type peanuts through the generation of a de novo reference genome and informative markers.

Introduction: Virginia-type peanut, Arachis hypogaea subsp. hypogaea, is the second largest market class of peanut cultivated in the United States. It is mainly used for large-seeded, in-shell products. Historically, Virginia-type peanut cultivars were developed through long-term recurrent phenotypic selection and wild species introgression projects. Contemporary genomic technologies represent a unique opportunity to revolutionize the traditional breeding pipeline. While there are genomic tools available for wild and cultivated peanuts, none are tailored specifically to applied Virginia-type cultivar development programs. Methods and respective results: Here, the first Virginia-type peanut reference genome, "Bailey II", was assembled. It has improved contiguity and reduced instances of manual curation in chromosome arms. Whole-genome sequencing and marker discovery was conducted on 66 peanut lines which resulted in 1.15 million markers. The high marker resolution achieved allowed 34 unique wild species introgression blocks to be cataloged in the A. hypogaea genome, some of which are known to confer resistance to one or more pathogens. To enable marker-assisted selection of the blocks, 111 PCR Allele Competitive Extension assays were designed. Forty thousand high quality markers were selected from the full set that are suitable for mid-density genotyping for genomic selection. Genomic data from representative advanced Virginia-type peanut lines suggests this is an appropriate base population for genomic selection. Discussion: The findings and tools produced in this research will allow for rapid genetic gain in the Virginia-type peanut population. Genomics-assisted breeding will allow swift response to changing biotic and abiotic threats, and ultimately the development of superior cultivars for public use and consumption.

The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment.

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

The role of population and quantitative genetics and modern sequencing technologies to understand evolved herbicide resistance and weed fitness.

Evolution of resistance to multiple herbicides with different sites of action and of nontarget site resistance (NTSR) often involves multiple genes. Thus, single-gene analyses, typical in studies of target site resistance, are not sufficient for understanding the genetic architecture and dynamics of NTSR and multiple resistance. The genetics of weed adaptation to varied agricultural environments is also generally expected to be polygenic. Recent advances in whole-genome sequencing as well as bioinformatic and statistical tools have made it possible to use population and quantitative genetics methods to expand our understanding of how resistance and other traits important for weed adaptation are genetically controlled at the individual and population levels, and to predict responses to selection pressure by herbicides and other environmental factors. The use of tools such as quantitative trait loci mapping, genome-wide association studies, and genomic prediction will allow pest management scientists to better explain how pests adapt to control tools and how specific genotypes thrive and spread across agroecosystems and other human-disturbed systems. The challenge will be to use this knowledge in developing integrated weed management systems that inhibit broad resistance to current and future weed-control methods. © 2020 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Molecular Dissection of Quantitative Variation in Bermudagrass Hybrids (Cynodon dactylon x transvaalensis): Morphological Traits.

Bermudagrass (Cynodon (L.)) is the most important warm-season grass grown for forage or turf. It shows extensive variation in morphological characteristics and growth attributes, but the genetic basis of this variation is little understood. Detection and tagging of quantitative trait loci (QTL) affecting above-ground morphology with diagnostic DNA markers would provide a foundation for genetic and molecular breeding applications in bermudagrass. Here, we report early findings regarding genetic architecture of foliage (canopy height, HT), stolon (stolon internode length, ILEN and length of the longest stolon LLS), and leaf traits (leaf blade length, LLEN and leaf blade width, LW) in 110 F1 individuals derived from a cross between Cynodon dactylon (T89) and C. transvaalensis (T574). Separate and joint environment analyses were performed on trait data collected across two to five environments (locations, and/or years, or time), finding significant differences (P < 0.001) among the hybrid progeny for all traits. Analysis of marker-trait associations detected 74 QTL and 135 epistatic interactions. Composite interval mapping (CIM) and mixed-model CIM (MCIM) identified 32 main effect QTL (M-QTL) and 13 interacting QTL (int-QTL). Colocalization of QTL for plant morphology partially explained significant correlations among traits. M-QTL qILEN-3-2 (for ILEN; R2 = 11-19%), qLLS-7-1 (for LLS; R2 = 13-27%), qLEN-1-1 (for LLEN; R2 = 10-11%), and qLW-3-2 (for LW; R2 = 10-12%) were 'stable' across multiple environments, representing candidates for fine mapping and applied breeding applications. QTL correspondence between bermudagrass and divergent grass lineages suggests opportunities to accelerate progress by predictive breeding of bermudagrass.

TAT-BH4 and TAT-Bcl-xL peptides protect against sepsis-induced lymphocyte apoptosis in vivo.

Apoptosis is a key pathogenic mechanism in sepsis that induces extensive death of lymphocytes and dendritic cells, thereby contributing to the immunosuppression that characterizes the septic disorder. Numerous animal studies indicate that prevention of apoptosis in sepsis improves survival and may represent a potential therapy for this highly lethal disorder. Recently, novel cell-penetrating peptide constructs such as HIV-1 TAT basic domain and related peptides have been developed to deliver bioactive cargoes and peptides into cells. In the present study, we investigated the effects of sepsis-induced apoptosis in Bcl-x(L) transgenic mice and in wild-type mice treated with an antiapoptotic TAT-Bcl-x(L) fusion protein and TAT-BH4 peptide. Lymphocytes from Bcl-x(L) transgenic mice were resistant to sepsis-induced apoptosis, and these mice had a approximately 3-fold improvement in survival. TAT-Bcl-x(L) and TAT-BH4 prevented Escherichia coli-induced human lymphocyte apoptosis ex vivo and markedly decreased lymphocyte apoptosis in an in vivo mouse model of sepsis. In conclusion, TAT-conjugated antiapoptotic Bcl-2-like peptides may offer a novel therapy to prevent apoptosis in sepsis and improve survival.