Biology subjects

Cooper, M.

Publications and source records attributed to Cooper, M..

44 records · Page 3Linked to original sources

bioRxiv2020

Back to the future: Implications of genetic complexity for hybrid breeding strategies

Commercial hybrid breeding operations can be described as decentralized networks of smaller, more or less isolated breeding programs. There is further a tendency for the disproportionate use of successful inbred lines for generating the next generation of recombinants, which has led to a series of significant bottlenecks, particularly in the history of the North American and European maize germplasm. Both the decentralization and the disproportionate inbred use reduce effective population size and constrain the accessible genetic space. Under these conditions, long term response to selection is not expected to be optimal under the classical infinitesimal model of quantitative genetics. In this study we therefore aim to propose an alternative rational for the success of large breeding operations in the context of genetic complexity arising from the structure and properties of interactive genetic networks. For this we use simulations based on the NK model of genetic architecture. We indeed found that constraining genetic space and reducing effective population size, through program decentralization and disproportionate inbred use, is required to expose additive genetic variation and thus facilitate heritable genetic gains. These results introduce new insights into why the historically grown structure of hybrid breeding programs was successful in improving the yield potential of hybrid crops over the last century. We also hope that a renewed appreciation for "why things worked" in the past can guide the adoption of novel technologies and the design of future breeding strategies for navigating biological complexity.

genetics↗

bioRxiv2020

Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

Plant breeding programs are designed and operated over multiple cycles to systematically change the genetic makeup of plants to achieve improved trait performance for a Target Population of Environments (TPE). Within each cycle, selection applied to the standing genetic variation within a structured reference population of genotypes (RPG) is the primary mechanism by which breeding programs make the desired genetic changes. Selection operates to change the frequencies of the alleles of the genes controlling trait variation within the RPG. The structure of the RPG and the TPE has important implications for the design of optimal breeding strategies. The breeders equation, together with the quantitative genetic theory behind the equation, informs many of the principles for design of breeding programs. The breeders equation can take many forms depending on the details of the breeding strategy. Through the genetic changes achieved by selection, the cultivated varieties of crops (cultivars) are improved for use in agriculture. From a breeding perspective, selection for specific trait combinations requires a quantitative link between the effects of the alleles of the genes impacted by selection and the trait phenotypes of plants and their breeding value. This gene-to-phenotype link function provides the G2P map for one to many traits. For complex traits controlled by many genes, the infinitesimal model for trait genetic variation is the dominant G2P model of quantitative genetics. Here we consider motivations and potential benefits of using the hierarchical structure of crop models as CGM-G2P trait link functions in combination with the infinitesimal model for the design and optimisation of selection in breeding programs.

genetics↗

bioRxiv2020

Reproductive resilience but not root architecture underpin yield improvement in maize

Plants capture soil resources to produce the grains required to feed a growing population. Because plants capture water and nutrients through roots, it was proposed that changes in root systems architecture (RSA) underpin the three-fold increase in maize grain yield over the last century1,2,3,4. Within this framework, improvements in reproductive resilience due to selection are caused by increased water capture1. Here we show that both root architecture and yield have changed with decades of maize breeding, but not the water capture. Consistent with Darwinian agriculture5 theory, improved reproductive resilience6,7 enabled farmers increase the number of plants per unit land8,9,10, capture soil resources, and produced more dry matter and grain. Throughout the last century, selection operated to adapt roots to crowding, enabling reallocation of C from large root systems to the growing ear and the small roots of plants cultivated in high plant populations in modern agriculture.

plant biology↗

bioRxiv2018

Evaluating the Genome and Resistome of Extensively Drug-Resistant Klebsiella pneumoniae using Native DNA and RNA Nanopore Sequencing

Klebsiella pneumoniae frequently harbour multidrug resistance and current methodologies are struggling to rapidly discern feasible antibiotics to treat these infections. While rapid DNA sequencing has been proposed for prediction of resistance profile; the role of rapid RNA sequencing has yet to be fully explored. The MinION sequencer can sequence native DNA and RNA in real-time, providing an opportunity to contrast the utility of DNA and RNA for prediction of drug susceptibility. This study interrogated the genome and transcriptome of four extensively drug-resistant (XDR) K. pneumoniae clinical isolates. The majority of acquired resistance ([≥]75%) resided on plasmids including several megaplasmids ([≥]100 kbp). DNA sequencing identified most resistance genes ([≥]70%) within 2 hours of sequencing. Direct RNA sequencing (with a [~]6x slower pore translocation) was able to identify [≥]35% of resistance genes, including aminoglycoside, {beta}-lactam, trimethoprim and sulphonamide and also quinolone, rifampicin, fosfomycin and phenicol in some isolates, within 10 hours of sequencing. Polymyxin-resistant isolates showed a heightened transcription of phoPQ ([≥]2-fold) and the pmrHFIJKLM operon ([≥]8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to qRT-PCR across 11 resistance genes. Overall, MinION sequencing rapidly detected the XDR K. pneumoniae resistome and direct RNA sequencing revealed differential expression of these genes.

genomics↗

bioRxiv2018

Motor cortex can modulate somatosensory processing via cortico-thalamo-cortical pathway

The somatosensory and motor systems are intricately linked, providing several routes for the sensorimotor interactions necessary for haptic processing. Here, we used electrical and optogenetic stimulation to study the circuits that enable primary motor cortex (M1) to exert top-down modulation of whisker-evoked responses, at the levels of brain stem, thalamus and somatosensory cortex (S1). We find that activation of M1 drives somatosensory responsive cells at all levels, and that this excitation is followed by a period of tactile suppression, which gradually increases in strength along the ascending somatosensory pathway. Using optogenetic stimulation in the layer-specific Cre driver lines, we find that activation of layer VI cortico-thalamic neurons is sufficient to drive spiking in higher order thalamus, and that this is reliably followed by excitation of S1, suggesting a cross-modal cortico-thalamo-cortical pathway. Cortico-thalamic excitation predicts the degree of subsequent tactile suppression, consistent with a strong role for thalamic circuits in the expression of inhibitory sensorimotor interactions. These results provide evidence of a role for M1 in dynamic modulation of S1, largely under cortico-thalamic control.

neuroscience↗

bioRxiv2018

Microbial subnetworks related to short-term diel O2 fluxes within geochemically distinct freshwater wetlands

O2 concentrations often fluctuate over diel timescales within wetlands, driven by temperature, sunlight, photosynthesis, and respiration. These daily fluxes have been shown to impact biogeochemical transformations (e.g. denitrification), which are mediated by the residing microbial community. However, little is known about how resident microbial communities respond to diel dramatic physical and chemical fluxes in freshwater wetland ecosystems. In this study, total microbial (bacterial and archaeal) community structure was significantly related to diel time points in just one out of four distinct freshwater wetlands sampled. This suggests that daily environmental shifts may influence wetlands differentially based upon the resident microbial community and specific physical and chemical conditions of a freshwater wetland. However, when exploring at finer resolutions of the microbial communities within each wetland, subcommunities within two wetlands were found to correspond to fluctuating O2 levels. Microbial taxa that were found to be susceptible to fluctuating O2 levels within these subnetworks may have intimate ties to metabolism and/or diel redox cycles. This study highlights that freshwater wetland microbial communities are often stable in community structure when confronted with short-term O2 fluxes, however, specialist taxa may be sensitive to these same fluxes.

microbiology↗

bioRxiv2018

Octapeptin C4 Induces Less Resistance and Novel Mutations in an Epidemic Carbapenemase-producing Klebsiella pneumoniae ST258 Clinical Isolate Compared to Polymyxins

Polymyxin B and E (colistin) have been pivotal in the treatment of extensively drug-resistant (XDR) Gram-negative bacterial infections, with increasing use over the past decade. Unfortunately, resistance to these antibiotics is rapidly emerging. The structurally-related octapeptin C4 (OctC4) has shown significant potency against XDR bacteria, including against polymyxin-resistant (Pmx-R) strains, but its mode of action remains undefined. We sought to compare and contrast the acquisition of XDR Klebsiella pneumoniae (ST258) resistance in vitro with all three lipopeptides to help elucidate the mode of action of the drugs and potential mechanisms of resistance evolution. Strikingly, 20 days of exposure to the polymyxins resulted in a dramatic (1000-fold) increase in the minimum inhibitory concentration (MIC) for the polymyxins, reflecting the evolution of resistance seen in clinical isolates, whereas for OctC4 only a 4-fold increase was witnessed. There was no cross-resistance observed between the polymyxin - and octapeptin-induced resistant strains. Sequencing revealed previously known gene alterations for polymyxin resistance, including crrB, mgrB, pmrB, phoPQ and yciM, and novel mutations in qseC. In contrast, mutations in mlaDF and pqiB, 1genes related to phospholipid transport, were found in octapeptin-resistant isolates. Mutation effects were validated via complementation assays. These genetic variations were reflected in phenotypic changes to lipid A. Pmx-R isolates increased 4-amino-4-deoxy-arabinose fortification to phosphate groups of lipid A, whereas OctC4 induced strains harbored a higher abundance of hydroxymyristate and palmitoylate. The results reveal a differing mode of action compared to polymyxins which provides hope for future therapeutics to combat the increasingly threat of XDR bacteria.

microbiology↗

bioRxiv2017

Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP)

A successful strategy for prediction of crop yield that accounts for the effects of genotype and environment will open up many opportunities for enhancing the productivity of agricultural systems. Crop growth models (CGMs) have a history of application for crop management decision support. Recently whole genome prediction (WGP) methodologies have been developed and applied in breeding to enable prediction of crop traits for new genotypes and thus increase the size of plant breeding programs without the need to expand expensive field testing. The presence of Genotype-by-Environment-by-Management (GxExM) interactions for yield presents a significant challenge for the development of prediction technologies for both product development by breeding and product placement within agricultural production systems. The integration of a CGM into the algorithm for whole genome prediction WGP, referred to as CGM-WGP, has opened up the potential for prediction of GxExM interactions for breeding and product placement applications. Here a combination of simulation and empirical studies are used to explain how the CGM-WGP methodology works and to demonstrate successful reduction to practice for applications to maize breeding and product placement recommendation in the US corn belt.

genetics↗