Fine mapping of major QTL qshgd1 for spontaneous haploid genome doubling in maize (Zea mays L.).

KEY MESSAGE: A large-effect QTL was fine mapped, which revealed 79 gene models, with 10 promising candidate genes, along with a novel inversion. In commercial maize breeding, doubled haploid (DH) technology is arguably the most efficient resource for rapidly developing novel, completely homozygous lines. However, the DH strategy, using in vivo haploid induction, currently requires the use of mutagenic agents which can be not only hazardous, but laborious. This study focuses on an alternative approach to develop DH lines-spontaneous haploid genome duplication (SHGD) via naturally restored haploid male fertility (HMF). Inbred lines A427 and Wf9, the former with high HMF and the latter with low HMF, were selected to fine-map a large-effect QTL associated with SHGD-qshgd1. SHGD alleles were derived from A427, with novel haploid recombinant groups having varying levels of the A427 chromosomal region recovered. The chromosomal region of interest is composed of 45 megabases (Mb) of genetic information on chromosome 5. Significant differences between haploid recombinant groups for HMF were identified, signaling the possibility of mapping the QTL more closely. Due to suppression of recombination from the proximity of the centromere, and a newly discovered inversion region, the associated QTL was only confined to a 25 Mb region, within which only a single recombinant was observed among ca. 9,000 BC1 individuals. Nevertheless, 79 gene models were identified within this 25 Mb region. Additionally, 10 promising candidate genes, based on RNA-seq data, are described for future evaluation, while the narrowed down genome region is accessible for straightforward introgression into elite germplasm by BC methods.

Assessing data analysis techniques in a high-throughput meiosis-like induction detection system.

BACKGROUND: Strategies to understand meiotic processes have relied on cytogenetic and mutant analysis. However, thus far in vitro meiosis induction is a bottleneck to laboratory-based plant breeding as factor(s) that switch cells in crops species from mitotic to meiotic divisions are unknown. A high-throughput system that allows researchers to screen multiple candidates for their meiotic induction role using low-cost microfluidic devices has the potential to facilitate the identification of factors with the ability to induce haploid cells that have undergone recombination (artificial gametes) in cell cultures. RESULTS: A data analysis pipeline and a detailed protocol are presented to screen for plant meiosis induction factors in a quantifiable and efficient manner. We assessed three data analysis techniques using spiked-in protoplast samples (simulated gametes mixed into somatic protoplast populations) of flow cytometry data. Polygonal gating, which was considered the "gold standard", was compared to two thresholding methods using open-source analysis software. Both thresholding techniques were able to identify significant differences with low spike-in concentrations while also being comparable to polygonal gating. CONCLUSION: Our study provides details to test and analyze candidate meiosis induction factors using available biological resources and open-source programs for thresholding. RFP (PE.CF594.A) and GFP (FITC.A) were the only channels required to make informed decisions on meiosis-like induction and resulted in detection of cell population changes as low as 0.3%, thus enabling this system to be scaled using microfluidic devices at low costs.

Using machine learning enabled phenotyping to characterize nodulation in three early vegetative stages in soybean.

The symbiotic relationship between soybean [Glycine max L. (Merr.)] roots and bacteria (Bradyrhizobium japonicum) lead to the development of nodules, important legume root structures where atmospheric nitrogen (N2) is fixed into bio-available ammonia (NH3) for plant growth and development. With the recent development of the Soybean Nodule Acquisition Pipeline (SNAP), nodules can more easily be quantified and evaluated for genetic diversity and growth patterns across unique soybean root system architectures. We explored six diverse soybean genotypes across three field year combinations in three early vegetative stages of development and report the unique relationships between soybean nodules in the taproot and non-taproot growth zones of diverse root system architectures of these genotypes. We found unique growth patterns in the nodules of taproots showing genotypic differences in how nodules grew in count, size, and total nodule area per genotype compared to non-taproot nodules. We propose that nodulation should be defined as a function of both nodule count and individual nodule area resulting in a total nodule area per root or growth regions of the root. We also report on the relationships between the nodules and total nitrogen in the seed at maturity, finding a strong correlation between the taproot nodules and final seed nitrogen at maturity. The applications of these findings could lead to an enhanced understanding of the plant-Bradyrhizobium relationship and exploring these relationships could lead to leveraging greater nitrogen use efficiency and nodulation carbon to nitrogen production efficiency across the soybean germplasm.

Overcoming roadblocks for in vitro nurseries in plants: induction of meiosis.

Efforts to increase genetic gains in breeding programs of flowering plants depend on making genetic crosses. Time to flowering, which can take months to decades depending on the species, can be a limiting factor in such breeding programs. It has been proposed that the rate of genetic gain can be increased by reducing the time between generations by circumventing flowering through the in vitro induction of meiosis. In this review, we assess technologies and approaches that may offer a path towards meiosis induction, the largest current bottleneck for in vitro plant breeding. Studies in non-plant, eukaryotic organisms indicate that the in vitro switch from mitotic cell division to meiosis is inefficient and occurs at very low rates. Yet, this has been achieved with mammalian cells by the manipulation of a limited number of genes. Therefore, to experimentally identify factors that switch mitosis to meiosis in plants, it is necessary to develop a high-throughput system to evaluate a large number of candidate genes and treatments, each using large numbers of cells, few of which may gain the ability to induce meiosis.

A Comparison between Inbred and Hybrid Maize Haploid Inducers.

The effectiveness of haploid induction systems is regarded not only for high haploid induction rate (HIR) but also resource savings. Isolation fields are proposed for hybrid induction. However, efficient haploid production depends on inducer traits such as high HIR, abundant pollen production, and tall plants. Seven hybrid inducers and their respective parents were evaluated over three years for HIR, seeds set in cross-pollinations, plant and ear height, tassel size, and tassel branching. Mid-parent heterosis was estimated to quantify how much inducer traits improve in hybrids in comparison to their parents. Heterosis benefits hybrid inducers for plant height, ear height, and tassel size. Two hybrid inducers, BH201/LH82-Ped126 and BH201/LH82-Ped128, are promising for haploid induction in isolation fields. Hybrid inducers offer convenience and resource-effectiveness for haploid induction by means of improving plant vigor without compromising HIR.

The 2020 derecho revealed limited overlap between maize genes associated with root lodging and root system architecture.

Roots anchor plants in soil, and the failure of anchorage (i.e. root lodging) is a major cause of crop yield loss. Anchorage is often assumed to be driven by root system architecture (RSA). We made use of a natural experiment to measure the overlap between the genetic regulation of RSA and anchorage. After one of the most devastating derechos ever recorded in August 2020, we phenotyped root lodging in a maize (Zea mays) diversity panel consisting of 369 genotypes grown in 6 environments affected by the derecho. Genome-wide and transcriptome-wide association studies identified 118 candidate genes associated with root lodging. Thirty-four percent (40/118) of these were homologs of genes from Arabidopsis (Arabidopsis thaliana) that affect traits such as root morphology and lignin content, expected to affect root lodging. Finally, gene ontology enrichment analysis of the candidate genes and their predicted interaction partners at the transcriptional and translational levels revealed the complex regulatory networks of physiological and biochemical pathways underlying root lodging in maize. Limited overlap between genes associated with lodging resistance and RSA in this diversity panel suggests that anchorage depends in part on factors other than the gross characteristics of RSA.

Personalized synthetic MR imaging with deep learning enhancements.

PURPOSE: Personalized synthetic MRI (syn-MRI) uses MR images of an individual subject acquired at a few design parameters (echo time, repetition time, flip angle) to obtain underlying parametric ( ρ , T 1 , T 2 ) $$ \left(\rho, {\mathrm{T}}_1,{\mathrm{T}}_2\right) $$ maps, from where MR images of that individual at other design parameter settings are synthesized. However, classical methods that use least-squares (LS) or maximum likelihood estimators (MLE) are unsatisfactory at higher noise levels because the underlying inverse problem is ill-posed. This article provides a pipeline to enhance the synthesis of such images in three-dimensional (3D) using a deep learning (DL) neural network architecture for spatial regularization in a personalized setting where having more than a few training images is impractical. METHODS: Our DL enhancements employ a Deep Image Prior (DIP) with a U-net type denoising architecture that includes situations with minimal training data, such as personalized syn-MRI. We provide a general workflow for syn-MRI from three or more training images. Our workflow, called DIPsyn-MRI, uses DIP to enhance training images, then obtains parametric images using LS or MLE before synthesizing images at desired design parameter settings. DIPsyn-MRI is implemented in our publicly available Python package DeepSynMRI available at: https://github.com/StatPal/DeepSynMRI. RESULTS: We demonstrate feasibility and improved performance of DIPsyn-MRI on 3D datasets acquired using the Brainweb interface for spin-echo and FLASH imaging sequences, at different noise levels. Our DL enhancements improve syn-MRI in the presence of different intensity nonuniformity levels of the magnetic field, for all but very low noise levels. CONCLUSION: This article provides recipes and software to realistically facilitate DL-enhanced personalized syn-MRI.

Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean.

Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean [Glycine max L. (Merr.)] using disease severity from both visual field ratings and DL-based (using images) severity ratings collected from 473 accessions. Images were processed through a DL framework that identified soybean leaflets with SDS symptoms, and then quantified the disease severity on those leaflets into a few classes with mean Average Precision of 0.34 on unseen test data. Both visual field ratings and image-based ratings identified significant single nucleotide polymorphism (SNP) markers associated with disease resistance. These significant SNP markers are either in the proximity of previously reported candidate genes for SDS or near potentially novel candidate genes. Four previously reported SDS QTL were identified that contained a significant SNPs, from this study, from both a visual field rating and an image-based rating. The results of this study provide an exciting avenue of using DL to capture complex phenotypic traits from images to get comparable or more insightful results compared to subjective visual field phenotyping of traits for disease symptoms.

Investigating the Effect of the Interaction of Maize Inducer and Donor Backgrounds on Haploid Induction Rates.

Doubled haploid technology is a feasible, fast, and cost-efficient way of producing completely homozygous lines in maize. Many factors contribute to the success of this system including the haploid induction rate (HIR) of inducer lines, the inducibility of donor background, and environmental conditions. Sixteen inducer lines were tested on eight different genetic backgrounds of five categories in different environments for the HIR to determine possible interaction specificity. The HIR was assessed using the R1-nj phenotype and corrected using the red root marker or using a gold-standard test that uses plant traits. RWS and Mo-17-derived inducers showed higher average induction rates and the commercial dent hybrid background showed higher inducibility. In contrast, sweet corn and flint backgrounds had a relatively lower inducibility, while non-stiff stalk and stiff stalk backgrounds showed intermediate inducibility. For the poor-performing donors (sweet corn and flint), there was no difference in the HIR among the inducers. Anthocyanin inhibitor genes in such donors were assumed to have increased the misclassification rate in the F1 fraction and, hence, result in a lower HIR.

Chronic Manganese Exposure and the Enteric Nervous System: An in Vitro and Mouse in Vivo Study.

BACKGROUND: Chronic environmental exposure to manganese (Mn) can cause debilitating damage to the central nervous system. However, its potential toxic effects on the enteric nervous system (ENS) have yet to be assessed. OBJECTIVE: We examined the effect of Mn on the ENS using both cell and animal models. METHOD: Rat enteric glial cells (EGCs) and mouse primary enteric cultures were exposed to increasing concentrations of Mn and cell viability and mitochondrial health were assessed using various morphological and functional assays. C57BL/6 mice were exposed daily to a sublethal dose of Mn (15mg/kg/d) for 30 d. Gut peristalsis, enteric inflammation, gut microbiome profile, and fecal metabolite composition were assessed at the end of exposure. RESULTS: EGC mitochondria were highly susceptible to Mn neurotoxicity, as evidenced by lower mitochondrial mass, adenosine triphosphate-linked respiration, and aconitase activity as well as higher mitochondrial superoxide, upon Mn exposure. Minor differences were seen in the mouse model: specifically, longer intestinal transit times and higher levels of colonic inflammation. CONCLUSION: Based on our findings from this study, Mn preferentially induced mitochondrial dysfunction in a rat EGC line and in vivo resulted in inflammation in the ENS. https://doi.org/10.1289/EHP7877.

Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel.

Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich source of protein and other valuable minerals, vitamins, and antioxidants. The main objectives of this research were (1) to study the root traits related with the phenotypic and genetic diversity of 375 mung bean genotypes of the Iowa (IA) diversity panel and (2) to conduct genome-wide association studies of root-related traits using the Automated Root Image Analysis (ARIA) software. We collected over 9,000 digital images at three-time points (days 12, 15, and 18 after germination). A broad sense heritability for days 15 (0.22-0.73) and 18 (0.23-0.87) was higher than that for day 12 (0.24-0.51). We also reported root ideotype classification, i.e., PI425425 (India), PI425045 (Philippines), PI425551 (Korea), PI264686 (Philippines), and PI425085 (Sri Lanka) that emerged as the top five in the topsoil foraging category, while PI425594 (unknown origin), PI425599 (Thailand), PI425610 (Afghanistan), PI425485 (India), and AVMU0201 (Taiwan) were top five in the drought-tolerant and nutrient uptake "steep, cheap, and deep" ideotype. We identified promising genotypes that can help diversify the gene pool of mung bean breeding stocks and will be useful for further field testing. Using association studies, we identified markers showing significant associations with the lateral root angle (LRA) on chromosomes 2, 6, 7, and 11, length distribution (LED) on chromosome 8, and total root length-growth rate (TRL_GR), volume (VOL), and total dry weight (TDW) on chromosomes 3 and 5. We discussed genes that are potential candidates from these regions. We reported beta-galactosidase 3 associated with the LRA, which has previously been implicated in the adventitious root development via transcriptomic studies in mung bean. Results from this work on the phenotypic characterization, root-based ideotype categories, and significant molecular markers associated with important traits will be useful for the marker-assisted selection and mung bean improvement through breeding.

A Matrix-free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian Data.

This paper proposes a novel profile likelihood method for estimating the covariance parameters in exploratory factor analysis of high-dimensional Gaussian datasets with fewer observations than number of variables. An implicitly restarted Lanczos algorithm and a limited-memory quasi-Newton method are implemented to develop a matrix-free framework for likelihood maximization. Simulation results show that our method is substantially faster than the expectation-maximization solution without sacrificing accuracy. Our method is applied to fit factor models on data from suicide attempters, suicide ideators and a control group.

Effects of Farrowing Stall Layout and Number of Heat Lamps on Sow and Piglet Production Performance.

Most farrowing facilities in the United States use stalls and heat lamps to improve sow and piglet productivity. This study investigated these factors by comparing production outcomes for three different farrowing stall layouts (traditional, expanded creep area, expanded sow area) and use of one or two heat lamps. Data were collected on 427 sows and their litters over one year. Results showed no statistical differences due to experimental treatment for any of the production metrics recorded, excluding percent stillborn. Parity one sows had fewer piglets born alive (p < 0.001), lower percent mortality (p = 0.001) and over-lay (p = 0.003), and a greater number of piglets weaned (p < 0.001) with lower average daily weight gain (ADG) (p < 0.001) and more uniform litters (p = 0.001) as compared to higher parity sows. Farrowing turn, associated with group/seasonal changes, had a significant impact on most of the production metrics measured. Number of piglets born influenced the percent stillborn (p < 0.001). Adjusted litter size had a significant impact on percent mortality (p < 0.001), percent over-lay (p < 0.001), and number of piglets weaned (p < 0.001). As the number of piglets weaned per litter increased, both piglet ADG and litter uniformity decreased (p < 0.001). This information can be used to guide producers in farrowing facility design.

MitoPark transgenic mouse model recapitulates the gastrointestinal dysfunction and gut-microbiome changes of Parkinson's disease.

Gastrointestinal (GI) disturbances are one of the earliest symptoms affecting most patients with Parkinson's disease (PD). In many cases, these symptoms are observed years before motor impairments become apparent. Hence, the molecular and cellular underpinnings that contribute to this early GI dysfunction in PD have actively been explored using a relevant animal model. The MitoPark model is a chronic, progressive mouse model recapitulating several key pathophysiological aspects of PD. However, GI dysfunction and gut microbiome changes have not been categorized in this model. Herein, we show that decreased GI motility was one of the first non-motor symptoms to develop, evident as early as 8 weeks with significantly different transit times from 12 weeks onwards. These symptoms were observed well before motor symptoms developed, thereby paralleling PD progression in humans. At age 24 weeks, we observed increased colon transit time and reduced fecal water content, indicative of constipation. Intestinal inflammation was evidenced with increased expression of iNOS and TNFα in the small and large intestine. Specifically, iNOS was observed mainly in the enteric plexi, indicating enteric glial cell activation. A pronounced loss of tyrosine hydroxylase-positive neurons occurred at 24 weeks both in the mid-brain region as well as the gut, leading to a corresponding decrease in dopamine (DA) production. We also observed decreased DARPP-32 expression in the colon, validating the loss of DAergic neurons in the gut. However, the total number of enteric neurons did not significantly differ between the two groups. Metabolomic gas chromatography-mass spectrometry analysis of fecal samples showed increased sterol, glycerol, and tocopherol production in MitoPark mice compared to age-matched littermate controls at 20 weeks of age while 16 s microbiome sequencing showed a transient temporal increase in the genus Prevotella. Altogether, the data shed more light on the role of the gut dopaminergic system in maintaining intestinal health. Importantly, this model recapitulates the chronology and development of GI dysfunction along with other non-motor symptoms and can become an attractive translational animal model for pre-clinical assessment of the efficacy of new anti-Parkinsonian drugs that can alleviate GI dysfunction in PD.

Ante-mortem detection of chronic wasting disease in recto-anal mucosa-associated lymphoid tissues from elk (Cervus elaphus nelsoni) using real-time quaking-induced conversion (RT-QuIC) assay: A blinded collaborative study.

Prion diseases are transmissible spongiform encephalopathies (TSEs) characterized by fatal, progressive neurologic diseases with prolonged incubation periods and an accumulation of infectious misfolded prion proteins. Antemortem diagnosis is often difficult due to a long asymptomatic incubation period, differences in the pathogenesis of different prions, and the presence of very low levels of infectious prion in easily accessible samples. Chronic wasting disease (CWD) is a TSE affecting both wild and captive populations of cervids, including mule deer, white-tailed deer, elk, moose, muntjac, and most recently, wild reindeer. This study represents a well-controlled evaluation of a newly developed real-time quaking-induced conversion (RT-QuIC) assay as a potential CWD diagnostic screening test using rectal biopsy sections from a depopulated elk herd. We evaluated 69 blinded samples of recto-anal mucosa-associated lymphoid tissue (RAMALT) obtained from USDA Veterinary Services. The results were later un-blinded and statistically compared to immunohistochemical (IHC) results from the USDA National Veterinary Services Laboratories (NVSL) for RAMALT, obex, and medial retropharyngeal lymph node (MRPLN). Comparison of RAMALT RT-QuIC assay results with the IHC results of RAMALT revealed 92% relative sensitivity (95% confidence limits: 61.52-99.8%) and 95% relative specificity (95% confidence limits: 85.13-99%). Collectively, our results show a potential utility of the RT-QuIC assay to advance the development of a rapid, sensitive, and specific prion diagnostic assay for CWD prions.

Comparison of treatments in a cataract surgery with circular response.

Circular data are a natural outcome in many biomedical studies, e.g. some measurements in ophthalmologic studies, degrees of rotation of hand or waist, etc. With reference to a real data set on astigmatism induced in two types of cataract surgeries we carry out some two-sample testing problems with the possibility of common or different concentration parameters in the circular set up. Detailed simulation study and the analysis of the data set, including redesigning the cataract surgery data, are carried out.

Response-Adaptive Allocation for Circular Data.

Response-adaptive designs are used in phase III clinical trials to allocate a larger proportion of patients to the better treatment. Circular data is a natural outcome in many clinical trial setup, e.g., some measurements in opthalmologic studies, degrees of rotation of hand or waist, etc. There is no available work on response-adaptive designs for circular data. With reference to a dataset on cataract surgery we provide some response-adaptive designs where the responses are of circular nature and propose some test statistics for treatment comparison under adaptive data allocation procedure. Detailed simulation study and the analysis of the dataset, including redesigning the cataract surgery data, are carried out.