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At least 235 records · Page 13

Bemnifosbuvir: An HCV NS5B Inhibitor With Multiple Modes of Action

Bemnifosbuvir (BEM) is a potent, pan-genotypic inhibitor targeting the hepatitis C virus (HCV) NS5B polymerase. Its antiviral activity was evaluated in an ascending dose phase I clinical trial involving 30 patients treated once a day for 7 days. After treatment initiation, plasma HCV RNA declined in a biphasic manner with a mean reduction of 2.3 log 10 IU/mL after 24 hours and 4.4 log10 IU/mL by day 7 for the highest dose. Alanine aminotransferase (ALT) also normalized in most patients. We employed a multiscale mathematical model fitted to the HCV RNA and ALT dynamics to quantify the antiviral activity and evaluate the modes of action of BEM. We found that models in which BEM only acted as a typical HCV RNA polymerase inhibitor and reduced the intracellular production of HCV RNA did not fit the data as well as models in which BEM had multiple modes of action, including suppressing viral assembly and secretion and enhancing intracellular HCV RNA degradation. BEM's effectiveness in inhibiting intracellular HCV RNA production increased with dose (150 mg/day: 88.2%, 300 mg/day: 98.8%, 600 mg/day: 99.5%), while inhibition of viral assembly and release was ~95% effective regardless of dose. We observed a dose-dependent enhancement in the degradation of intracellular HCV RNA, with degradation rates 1.5-fold higher in patients receiving 300 mg/day and 2.7-fold higher in those receiving 600 mg/day than in patients receiving 150 mg/day. No significant differences in antiviral activity were detected between HCV genotypes 1b and 3 or between patients with and without compensated cirrhosis.

59 BASIC BIOLOGICAL SCIENCES↗

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗

Reclassification of ASFV into 7 Biotypes Using Unsupervised Machine Learning

In 2007, an outbreak of African swine fever (ASF), a deadly disease of domestic swine and wild boar caused by the African swine fever virus (ASFV), occurred in Georgia and has since spread globally. Historically, ASFV was classified into 25 different genotypes. However, a newly proposed system recategorized all ASFV isolates into 6 genotypes exclusively using the predicted protein sequences of p72. However, ASFV has a large genome that encodes between 150–200 genes, and classifications using a single gene are insufficient and misleading, as strains encoding an identical p72 often have significant mutations in other areas of the genome. We present here a new classification of ASFV based on comparisons performed considering the entire encoded proteome. A curated database consisting of the protein sequences predicted to be encoded by 220 reannotated ASFV genomes was analyzed for similarity between homologous protein sequences. Weights were applied to the protein identity matrices and averaged to generate a genome-genome identity matrix that was then analyzed by an unsupervised machine learning algorithm, DBSCAN, to separate the genomes into distinct clusters. We conclude that all available ASFV genomes can be classified into 7 distinct biotypes.

59 BASIC BIOLOGICAL SCIENCES↗

National Prevalence of Caprine Prion Protein Genetic Variability at Codons 146, 211, and 222 in Goat Herds in the United States

Scrapie is a neurodegenerative disease that impacts sheep and goats, characterized by gradual and progressive changes in neurological function. Recent research shows that the scrapie incubation period is significantly influenced by specific variations in amino acids within the prion protein gene (PRNP). The objective of this study was to estimate the national prevalence of caprine PRNP genetic variability at codons 146, 211, and 222 in goat populations across the United States. A total of 3052 blood, ear tissue, and brain tissue samples were collected from goats from 50 states. The participating states were categorized into four Veterinary Service (VS) district regions. The samples underwent DNA extraction, and the PRNP variants corresponding to codons 146, 211, and 222 were amplified and sequenced. The analysis of PRNP variants, when compared to the PRNP reference sequence, revealed seven alleles in twelve genotypes. The homozygous 146NN, 211RR, and 222QQ alleles, which have been linked to an increased risk of scrapie, were found to be the most prevalent among all the goats. The heterozygous 222QK, 211RQ, 146SD, 146ND, and 146NS alleles and the homozygous 222KK, 146SS, and 146DD alleles, known to be associated with reduced scrapie susceptibility and a prolonged incubation period after experimental challenge, were found in 1.098% (222QK), 2.33% (211RQ), 0.58% (146SD), 3.13% (146ND), 20.68% (146NS), 0.005% (222KK), 3.31% (146SS), and 0.67% (146DD) of goats, respectively. The 222QK allele was found most frequently in goats tested from the east (VS District 1, 1.59%) and southwest (VS District 4, 1.08%) regions, whereas the 211RQ allele was found most often in goats tested from the Midwest (VS District 2, 8.03%) and east (VS District 1, 6.53%) regions. The 146NS allele was found most frequently in goats tested from the northwest (VS District 3, 29.02%) and southwest (VS District 4, 20.69%) regions. Our results showed that the prevalence of less susceptible genotypes at PRNP codon 146 may be sufficient to use genetic susceptibility testing in some herds. This may reduce the number of goats removed as part of a herd clean-up plan and may promote the selective breeding goats for less susceptible alleles in high-risk herds at the national level.

59 BASIC BIOLOGICAL SCIENCES↗

Multiple Epstein-Barr virus infections in healthy individuals

We employed a newly developed genotyping technique with direct representational detection of LMP-1 gene sequences to study the molecular epidemiology of Epstein-Barr virus (EBV) infection in healthy individuals. Infections with up to five different EBV genotypes were found in two of nine individuals studied. These results support the hypothesis that multiple EBV infections of healthy individuals are common. The implications for the development of an EBV vaccine are discussed.

Evaluation Studies↗

Abundant raw material for cis-regulatory evolution in humans

Changes in gene expression and regulation--due in particular to the evolution of cis-regulatory DNA sequences--may underlie many evolutionary changes in phenotypes, yet little is known about the distribution of such variation in populations. We present in this study the first survey of experimentally validated functional cis-regulatory polymorphism. These data are derived from more than 140 polymorphisms involved in the regulation of 107 genes in Homo sapiens, the eukaryote species with the most available data. We find that functional cis-regulatory variation is widespread in the human genome and that the consequent variation in gene expression is twofold or greater for 63% of the genes surveyed. Transcription factor-DNA interactions are highly polymorphic, and regulatory interactions have been gained and lost within human populations. On average, humans are heterozygous at more functional cis-regulatory sites (>16,000) than at amino acid positions (<13,000), in part because of an overrepresentation among the former in multiallelic tandem repeat variation, especially (AC)(n) dinucleotide microsatellites. The role of microsatellites in gene expression variation may provide a larger store of heritable phenotypic variation, and a more rapid mutational input of such variation, than has been realized. Finally, we outline the distinctive consequences of cis-regulatory variation for the genotype-phenotype relationship, including ubiquitous epistasis and genotype-by-environment interactions, as well as underappreciated modes of pleiotropy and overdominance. Ordinary small-scale mutations contribute to pervasive variation in transcription rates and consequently to patterns of human phenotypic variation.

NASA Discipline Evolutionary Biology↗

Rootcap structure in wild type and in a starchless mutant of Arabidopsis

Rootcaps of the wild type (WT) and of a starchless, gravitropic mutant (TC7) of Arabidopsis thaliana L. were examined by electron microscopy to identify cellular polarities with respect to gravity. In columella cells, nuclei are located proximally, and the nuclear envelope is continuous with endoplasmic reticulum (ER) that is in turn connected to nearby plasmodesmata. Impregnation of ER with osmium ferricyanide revealed numerous contacts between columella plastids and ER in both genotypes. ER is present mostly in the outer regions of the columella protoplast except in older columella cells that are developing into peripheral cells. In vertical roots, only columella cells that are intermediate in development (story 2 cells) have a higher surface density (S) of ER in the distal compared to proximal regions of the cell. The distal but not the proximal S of the ER is constant throughout columella development. Plastids are less sedimented in TC7 columella cells compared to those of the WT. It is hypothesized that plastid contact with the ER plays a role in gravity perception in both genotypes.

NASA Discipline Plant Biology↗

Accuracy of Tau Positron Emission Tomography as a Prognostic Marker in Preclinical and Prodromal Alzheimer Disease: A Head-to-Head Comparison Against Amyloid Positron Emission Tomography and Magnetic Resonance Imaging

Importance: Tau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear. Objective: To examine the prognostic accuracy of baseline fluorine 18 ( 18 F)-flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers. Design, setting, and participants: This prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ). Exposures: [ 18 F]Flortaucipir PET in the discovery cohort (n = 1135) or [ 18 F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation. Main outcomes and measures: Baseline [ 18 F]flortaucipir/[ 18 F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations. Results: Among 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [ 18 F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R 2 , 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P < .001, bootstrapped for difference) and in the Aβ-positive CU group (R 2 , 0.16 [tau PET] vs 0.08 [MRI] vs 0.08 [amyloid PET]; P < .001, bootstrapped for difference). These findings were replicated in the [ 18 F]RO948 PET cohort. MRI mediated the association between [ 18 F]flortaucipir PET and MMSE in the groups with AD dementia (33.4% [95% CI, 15.5%-60.0%] of the total effect) and Aβ-positive MCI (13.6% [95% CI, 0.0%-28.0%] of the total effect), but not the Aβ-positive CU group (3.7% [95% CI, -17.5% to 39.0%]; P = .71). Age (t = -2.28; P = .02), but not sex (t = 0.92; P = .36) or APOE genotype (t = 1.06; P = .29) modified the association between baseline [ 18 F]flortaucipir PET and cognitive change, such that older individuals showed faster cognitive decline at similar tau PET levels. Conclusions and relevance: The findings of this prognostic study suggest that tau PET is a promising tool for predicting cognitive change that is superior to amyloid PET and MRI and may support the prognostic process in preclinical and prodromal stages of AD.

59 BASIC BIOLOGICAL SCIENCES↗

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics ↗

Switchgrass sward establishment selection is consistent across multiple environments and fertilization levels

Strong selection can occur during switchgrass sward establishment. Differences in establishment selection due to environment or management could provide information on genotype-by-environment variation and could influence strategies for breeding perennial grasses. Leaf samples were collected before sward establishment and from 3-year-old swards for two breeding groups (lowland and hybrid) at three locations. Within two locations, samples were collected from paired fertilized (112 kg N ha –1 ) and unfertilized plots. Allele frequencies from pooled DNA samples were studied through multivariate analysis of variance, genomewide trait predictions (heading date and winter survivorship), and genomically estimated breeding values (GEBVs) for individual sward survival within an independent data set. This study found only minor variations in selection due to location or management. Predicted heading dates of the hybrid population had significant changes due to fertilization and location. There were strong correlations among sward establishment survival GEBVs between growing environments (hybrid r = 0.77; gulf r = 0.97). Interestingly, this study found a small number of genotypes that were over-represented in established swards across all growing environments. This study reinforces a prior report of selection during sward establishment and indicates that only a small degree of establishment selection is location-specific within these diverse growing conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Connectivity, Pathology, and ApoE4 Interactions Predict Longitudinal Tau Spatial Progression and Memory

ABSTRACT Tau pathology spread into neocortex indicates a transition from healthy aging to Alzheimer's disease (AD). Connectivity between tau epicenters and later accumulating regions of cortex has been proposed as a mechanism of tau spread, but how this relationship changes with greater AD pathology burden or genotype is not understood. We investigated tau accumulation in two key regions, precuneus and inferior temporal cortex, using resting state functional connectivity (rsFC) and longitudinal PET imaging from a multicohort sample of cognitively unimpaired older adults. We examined how baseline tau PET, Aβ PET, and ApoE4 genotype status interact with rsFC between hippocampus and these downstream regions to predict rate of tau accumulation in neocortex. We found that the 3‐way interaction between connectivity, baseline tau, and baseline Aβ or ApoE4 status was associated with neocortical tau accumulation in precuneus and inferior temporal cortex. In addition, baseline tau, Aβ, and ApoE4 status also moderated the association between connectivity and rate of memory decline. Together, these results suggest that the extent and distribution of future tau accumulation may be predicted by the interaction of baseline connectivity, AD pathology, and genetic risk.

Neurosciences & Neurology↗

Nodal root diameter and node number in maize ( Zea mays L.) interact to influence plant growth under nitrogen stress

Under nitrogen limitation, plants increase resource allocation to root growth relative to shoot growth. The utility of various root architectural and anatomical phenotypes for nitrogen acquisition are not well understood. Nodal root number and root cross-sectional area were evaluated in maize in field and greenhouse environments. Nodal root number and root cross-sectional area were inversely correlated under both high and low nitrogen conditions. Attenuated emergence of root nodes, as opposed to differences in the number of axial roots per node, was associated with substantially reduced root number. Greater root cross-sectional area was associated with a greater stele area and number of cortical cell files. Genotypes that produced few, thick nodal roots rather than many, thin nodal roots had deeper rooting and better shoot growth in low nitrogen environments. Fewer nodal roots offset the respiratory and nitrogen costs of thicker diameter roots, since total nodal root respiration and nitrogen content was similar for genotypes with many, thin and few, thick nodal roots. We propose that few, thick nodal roots may enable greater capture of deep soil nitrogen and improve plant performance under nitrogen stress. Synergistic interactions between an architectural and anatomical trait may be an important strategy for nitrogen acquisition. Understanding trait interactions among different root nodes has important implications in for improving crop nutrient uptake and stress tolerance.

59 BASIC BIOLOGICAL SCIENCES↗

Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits

Abstract Plant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21 st century. To address this challenge, we conducted linked yield trials of 752 public maize ( Zea mays ) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R 2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.

60 APPLIED LIFE SCIENCES↗

Quantitative trait locus mapping combined with variant and transcriptome analyses identifies a cluster of gene candidates underlying the variation in leaf wax between upland and lowland switchgrass ecotypes

Switchgrass (Panicum virgatum L.) is a promising warm-season candidate energy crop. It occurs in two ecotypes, upland and lowland, which vary in a number of phenotypic traits, including leaf glaucousness. To initiate trait mapping, two F 2 mapping populations were developed by crossing two different F 1 sibs derived from a cross between the tetraploid lowland genotype AP13 and the tetraploid upland genotype VS16, and high-density linkage maps were generated. Quantitative trait locus (QTL) analyses of visually scored leaf glaucousness and of hydrophobicity of the abaxial leaf surface measured using a drop shape analyzer identified highly significant colocalizing QTL on chromosome 7K (Chr07K). Using a multipronged approach, we identified a cluster of genes including Pavir.7KG077009, which encodes a Type III polyketide synthase-like protein, and Pavir.7KG013754 and Pavir.7KG030500, two highly similar genes that encode putative acyl-acyl carrier protein (ACP) thioesterases, as strong candidates underlying the QTL. The lack of homoeologs for any of the three genes on Chr07N, the relatively low level of identity with other switchgrass KCS proteins and thioesterases, as well as the organization of the surrounding region suggest that Pavir.7KG077009 and Pavir.7KG013754/Pavir.7KG030500 were duplicated into a fast-evolving chromosome region, which led to their neofunctionalization. Furthermore, sequence analyses showed all three genes to be absent in the two upland compared to the two lowland accessions analyzed. This study provides an example of and practical guide for trait mapping and candidate gene identification in a complex genetic system by combining QTL mapping, transcriptomics and variant analysis.

59 BASIC BIOLOGICAL SCIENCES↗

Legacies of precipitation influence primary production in Panicum virgatum

Precipitation is a key driver of primary production worldwide, but primary production does not always track year-to-year variation in precipitation linearly. Instead, plant responses to changes in precipitation may exhibit time lags, or legacies of past precipitation. Legacies can be driven by multiple mechanisms, including persistent changes in plant physiological and morphological traits and changes to the physical environment, such as plant access to soil water. Here, we used three precipitation manipulation experiments in central Texas, USA to evaluate the magnitude, duration, and potential mechanisms driving precipitation legacies on aboveground primary production of the perennial C 4 grass, Panicum virgatum. Specifically, we performed a rainout shelter study, where eight genotypes grew under different precipitation regimes; a transplant study, where plants that had previously grown in a rainout shelter under different precipitation regimes were moved to a common environment; and a mesocosm study, where the effect of swapping precipitation regime was examined with a single genotype. Across these experiments, plants previously grown under wet conditions generally performed better than expected when exposed to drought. Panicum virgatum exhibited stronger productivity legacies of past wet years on current-year responses to drought than of past dry years on current-year responses to wet conditions. Additionally, previous year tiller counts, a proxy for meristem availability, were important in determining legacy effects on aboveground production. As climate changes and precipitation extremes—both dry and wet—become more common, these results suggest that populations of P. virgatum may become less resilient.

54 ENVIRONMENTAL SCIENCES↗

Genetic variation in Zea mays influences microbial nitrification and denitrification in conventional agroecosystems

Nitrogenous fertilizers provide a short-lived benefit to crops in agroecosystems, but stimulate nitrification and denitrification, processes that result in nitrate pollution, N 2 O production, and reduced soil fertility. Recent advances in plant microbiome science suggest that genetic variation in plants can modulate the composition and activity of rhizosphere N-cycling microorganisms. Here we attempted to determine whether genetic variation exists in Zea mays for the ability to influence the rhizosphere nitrifier and denitrifier microbiome under “real-world” conventional agricultural conditions. To capture an extensive amount of genetic diversity within maize we grew and sampled the rhizosphere microbiome of a diversity panel of germplasm that included ex-PVP inbreds (Z. mays ssp. mays), ex-PVP hybrids (Z. mays ssp. mays), and teosinte (Z. mays ssp. mexicana and Z. mays ssp. parviglumis). From these samples, we characterized the microbiome, a suite of microbial genes involved in nitrification and denitrification and carried out N-cycling potential assays. Here we are showing that populations/genotypes of a single species can vary in their ecological interaction with denitrifers and nitrifers. Some hybrid and teosinte genotypes supported microbial communities with lower potential nitrification and potential denitrification activity in the rhizosphere, while inbred genotypes stimulated/did not inhibit these N-cycling activities. These potential differences translated to functional differences in N 2 O fluxes, with teosinte plots producing less GHG than maize plots. Taken together, these results suggest that Zea genetic variation can lead to changes in N-cycling processes that result in N leaching and N 2 O production, and thereby are selectable targets for crop improvement. Understanding the underlying genetic variation contributing to belowground microbiome N-cycling into our conventional agricultural system could be useful for sustainability.

59 BASIC BIOLOGICAL SCIENCES↗

Maize tissue culture, transformation, and genome editing

The importance of maize (Zea mays L.) to global agriculture, world economy, and food security is widely known and increasing. Current maize breeding programs are deeply integrated with recent and rapid technological advances in genome sequencing, computational biology, and new genotyping and phenotyping technologies. Transformation and genome editing capabilities are a central hub to an array of advanced molecular and breeding approaches to crop improvement. Tissue culture and somatic embryogenesis play essential and central roles in maize transformation biology. Synergistic applications of maize transformation, advanced genomics, and genome editing provide a potent interdependent triad for functional genomics research and advanced molecular breeding. Implementation of advanced capabilities to transform maize and conduct genome editing will profoundly influence the dynamics of global agriculture ushering in a new era of varietal development and molecular breeding. With over 60.9 Mha planted in 2019 alone, biotech maize accounts for 31% of the world’s maize production. Up to 10% higher yields are achieved using new varieties generated using genetic modification technologies compared to similar conventional varieties. By extension, the impact new varietal releases developed through genome editing will likely be more significant. Further, advances in transformation and genome editing technologies will facilitate an even wider applicability for the development of new varieties with increasingly complex traits. The introduction of biochemical pathways and the use of synthetic biology have become increasingly more attainable. The future is of genotype independent maize transformation and genome editing, as the working platform will impact world agriculture, global food security, and plant science well into the future.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Drought Stress on Sorghum bicolor Yield, Deconstruction, and Microbial Conversion Determined in a Feedstocks-to-Fuels Pipeline

Sorghum is an attractive feedstock for biobased fuel and chemical production because it is familiar to farmers, naturally drought tolerant, and versatile as a food, feed, and fuel crop. Although sorghum is a promising feedstock, particularly in regions that experience drought stress, little is known about how drought conditions impact the ease of conversion of sorghum to fuels and products. This study combines agronomic field trials with a high-throughput experimental pipeline to explore the field performance and liquid biofuel (bisabolene) yields resulting from three sorghum types (photosensitive forage sorghum, optimized grain sorghum, and drought-resistant grain sorghum) grown under pre- and postflowering water limitations in two different California locations. Multiple drought treatments are compared to the control, as the timing (preflowering versus postflowering) of drought stress elicits different survival strategies and corresponding impacts on yield and composition. Forage-type sorghum maintained the highest biomass yields across all irrigation conditions and locations. Glucose and xylose yields resulting from ionic liquid pretreatment and enzymatic saccharification were not significantly impacted by irrigation treatments but differed by location and genotype. However, Rhodosporidium toruloides grown on the resulting plant hydrolysates unexpectedly produced higher titers of bisabolene for drought-stressed sorghum samples regardless of genotype.

09 BIOMASS FUELS↗