Biology subjects

Clark, R.

Publications and source records attributed to Clark, R..

28 records · Page 2Linked to original sources

bioRxiv2021

A biophotoelectrochemical approach to unravelling the role of cyanobacterial cell structures in exoelectrogenesis

Photosynthetic microorganisms can export electrons outside their cells, a phenomenon called exoelectrogenesis, which can be harnessed for solar energy conversion. However, the route electrons take from thylakoid membranes to the cell exterior is not understood. Electrochemistry is a powerful analytical technique for studying electron transfer pathways. Here, we show how photoelectrochemistry can be used to compare electron flux from cyanobacterial cells of different growth stages, species and with the outer layers systematically removed. We show that the periplasmic space contributes significantly to the photocurrent profile complexity of whole cells, indicating that it gates electron transfer in exoelectrogenesis. We found that although components of the type IV pili machinery do not have a role in exoelectrogenesis, they contribute significantly to cell-electrode adherence. This study establishes that analytical photoelectrochemistry and molecular microbiology provide a powerful combination to study exoelectrogenesis, enabling future studies to answer biological questions and advance solar energy conversion applications.

biochemistry↗

bioRxiv2021

Aureochromes are necessary for maintaining polyunsaturated fatty acid content in Nannochloropsis oceanica

Nannochloropsis oceanica, as other stramenopile microalgae, is rich in long-chain polyunsaturated fatty acids (LC-PUFA) such as eiconsapentaenoic acid (EPA). We observed that fatty acid desaturases (FAD) involved in LC-PUFA biosynthesis were among the strongest blue light induced genes in N. oceanica CCMP1779. Blue light was also necessary for maintaining LC-PUFA levels in CCMP1779 cells, and growth under red light led to a reduction in EPA content. Aureochromes are stramenopile specific proteins that contain a light-oxygen-voltage-sensing (LOV) domain that associates with a flavin mononucleotide and is able to sense blue light. These proteins also contain a bZIP DNA binding motif and can act as blue light regulated transcription factors by associating with a E-box like motif, which we found enriched in the promoters of blue light induced genes. We demonstrated that, in vitro, two CCMP1779 aureochromes were able to absorb blue light. Moreover, the loss or reduction of any of the three aureochromes led to a decrease in the blue light specific induction of several FADs in CCMP1779. EPA content was also significantly reduced in NoAureo 2 and NoAureo 4 mutants. Taken together, our results indicate that aureochromes mediate blue light dependent regulation of LC-PUFA content in N. oceanica CCMP1779 cells.

plant biology↗

bioRxiv2020

Two decades of creating drought tolerant maize and underpinning prediction technologies in the US corn-belt: Review and perspectives on the future of crop design

Over the last decade, society witnessed the largest expansion of agricultural land planted with drought tolerant (DT) maize (Zea mays L.) Dedicated efforts to drought breeding led to development of DT maize. Here we show that after two decades of sustained breeding efforts the rate of crop improvement under drought is in the range 1.0-1.6% yr-1, which is higher than rates (0.7% yr-1) reported prior to drought breeding. Prediction technologies that leverage biological understanding and statistical learning to improve upon the quantitative genetics framework will further accelerate genetic gain. A review of published and unpublished analyses conducted on data including 138 breeding populations and 93 environments between 2009 and 2019 demonstrated an average prediction skill (r) improvement around 0.2. These methods applied to pre-commercial stages showed accuracies higher that current statistical approaches (0.85 vs. 0.70). Improvement in hybrid and management choice can increase water productivity. Digital gap analyses are applicable at field scale suggesting the possibility of transition from evaluating hybrids to designing genotype x management (GxM) technologies for target cropping systems in drought prone areas. Due to the biocomplexity of drought, research and development efforts should be sustained to advance knowledge and iteratively improve models. HighlightCrop improvement rate in maize increased after implementation of drought breeding efforts. Harnessing crop, quantitative genetics and gap models will enable the transition from genetic evaluation to crop design.

plant biology↗

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↗

bioRxiv2020

Global analysis of transcription start sites in the new ovine reference genome (Oar rambouillet v1.0)

The overall aim of the Ovine FAANG project is to provide a comprehensive annotation of the new highly contiguous sheep reference genome sequence (Oar rambouillet v1.0). Mapping of transcription start sites (TSS) is a key first step in understanding transcript regulation and diversity. Using 56 tissue samples collected from the reference ewe Benz2616 we have performed a global analysis of TSS and TSS- Enhancer clusters using Cap Analysis Gene Expression (CAGE) sequencing. CAGE measures RNA expression by 5 cap-trapping and has been specifically designed to allow the characterization of TSS within promoters to single-nucleotide resolution. We have adapted an analysis pipeline that uses TagDust2 for clean-up and trimming, Bowtie2 for mapping, CAGEfightR for clustering and the Integrative Genomics Viewer (IGV) for visualization. Mapping of CAGE tags indicated that the expression levels of CAGE tag clusters varied across tissues. Expression profiles across tissues were validated using corresponding polyA+ mRNA-Seq data from the same samples. After removal of CAGE tags with < 10 read counts, 39.3% of TSS overlapped with 5 ends of 31,113 transcripts that had been previously annotated by NCBI (out of a total of 56,308 from the NCBI annotation). For 25,195 of the transcripts, previously annotated by NCBI, no TSS meeting stringent criteria were identified. A further 14.7% of TSS mapped to within 50bp of annotated promoter regions. Intersecting these predicted TSS regions with annotated promoter regions ({+/-}50bp) revealed 46% of the predicted TSS were novel and previously un-annotated. Using whole genome bisulphite sequencing data from the same tissues we were able to determine that a proportion of these novel TSS were hypo-methylated (32.2%) indicating that they are likely to be reproducible rather than noise. This global analysis of TSS in sheep will significantly enhance the annotation of gene models in the new ovine reference assembly. Our analyses provide one of the highest resolution annotations of transcript regulation and diversity in a livestock species to date.

genomics↗

bioRxiv2020

Whole-organism behavioral profiling reveals a role for dopamine in state-dependent motor program coupling in C. elegans

Animal behaviors are commonly organized into long-lasting states that coordinately impact the generation of diverse motor outputs such as feeding, locomotion, and grooming. However, the neural mechanisms that coordinate these diverse motor programs remain poorly understood. Here, we examine how the distinct motor programs of the nematode C. elegans are coupled together across behavioral states. We describe a new imaging platform that permits automated, simultaneous quantification of each of the main C. elegans motor programs over hours or days. Analysis of these whole-organism behavioral profiles shows that the motor programs coordinately change as animals switch behavioral states. Utilizing genetics, optogenetics, and calcium imaging, we identify a new role for dopamine in coupling locomotion and egg-laying together across states. These results provide new insights into how the diverse motor programs throughout an organism are coordinated and suggest that neuromodulators like dopamine can couple motor circuits together in a state-dependent manner.

neuroscience↗

bioRxiv2019

De novo DNA methyltransferase activity in colorectal cancer is directed towards H3K36me3 marked CpG islands

The aberrant gain of DNA methylation at CpG islands (CGIs) is frequently observed in colorectal tumours and may silence the expression of tumour suppressors such as MLH1. Current models propose that these CGIs are targeted by de novo DNA methyltransferases (DNMTs) in a sequence-specific manner but this has not been tested. Using ectopically integrated CGIs, we find that aberrantly methylated CGIs are subject to low levels of de novo DNMT activity in colorectal cancer cells. By delineating DNMT targets, we find that instead de novo DNMT activity is targeted primarily to CGIs marked by the histone modification H3K36me3, a mark associated with transcriptional elongation. These H3K36me3 marked CGIs are heavily methylated in colorectal tumours and the normal colon suggesting that de novo DNMT activity at CGIs in colorectal cancer is focused on similar targets to normal tissues and not greatly remodelled by tumourigenesis.

genetics↗

bioRxiv2017

Demogenetic simulations reveal fragmenting effects of climate change on insular lizard populations

The extinction risk of insular species with sessile life histories is expected to increase as they may be unable to track habitat in response to global climate change. Demogenetic simulations can couple population demography and niche modeling to produce spatially-explicit genetic and demographic information for all simulated individuals and provide insight into the effects of climate change at demographic and population genetic levels. We used CDMETAPOP to simulate a population of island night lizards (Xantusia riversiana) on Santa Barbara Island to evaluate its sensitivity to climate change to the year 2100 across 8 scenarios based on 2 climate models, 2 emissions pathways, and 2 connectivity models. We found that 1) X. riversiana is sensitive to climate change with SDMs predicting a loss of suitable habitat of 93%-98% by 2038, 2) population genetic structure is expected to increase drastically to 0.209-0.673 from approximately 0.0346, and 3) estimated minimum abundance is expected to declined sharply over the 2007 to 2038 period and reached values of 0-1% of the 2007 population size in all scenarios by 2100. Climate change is expected to decrease census population size and result in extant habitat patches that are isolated from one another with very high levels of genetic divergence over short periods of time. These patterns may drive the Santa Barbara Island population to extinction under certain scenarios. Management plans should address methods to improve connectivity on the island and attempt to create refugial patches. Contingency plans, such as translocation, may be required to prevent population extirpation. This study highlights the utility of demogenetic simulations in evaluating population demographic and genetic patterns under climate change with suggestions on workflows for running simulations in a high-throughput manner.

ecology↗

bioRxiv2017

An Integrative Framework For Detecting Structural Variations In Cancer Genomes

Structural variants can contribute to oncogenesis through a variety of mechanisms, yet, despite their importance, the identification of structural variants in cancer genomes remains challenging. Here, we present an integrative framework for comprehensively identifying structural variation in cancer genomes. For the first time, we apply next-generation optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole genome sequencing to systematically detect SVs in a variety of cancer cells.\n\nUsing this approach, we identify and characterize structural variants in up to 29 commonly used normal and cancer cell lines. We find that each method has unique strengths in identifying different classes of structural variants and at different scales, suggesting that integrative approaches are likely the only way to comprehensively identify structural variants in the genome. Studying the impact of the structural variants in cancer cell lines, we identify widespread structural variation events affecting the functions of non-coding sequences in the genome, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel 3D chromatin structural domains.\n\nThese results underscore the importance of comprehensive structural variant identification and indicate that non-coding structural variation may be an underappreciated mutational process in cancer genomes.

genomics↗

bioRxiv2016

Genomic Rearrangements Considered as Quantitative Traits

To understand the population genetics of structural variants (SVs), and their effects on phenotypes, we developed an approach to mapping SVs, particularly transpositions, segregating in a sequenced population, and which avoids calling SVs directly. The evidence for a potential SV at a locus is indicated by variation in the counts of short-reads that map anomalously to the locus. These SV traits are treated as quantitative traits and mapped genetically, analogously to a gene expression study. Association between an SV trait at one locus and genotypes at a distant locus indicate the origin and target of a transposition. Using ultra-low-coverage (0.3x) population sequence data from 488 recombinant inbred Arabidopsis genomes, we identified 6,502 segregating SVs. Remarkably, 25% of these were transpositions. Whilst many SVs cannot be delineated precisely, PCR validated 83% of 44 predicted transposition breakpoints. We show that specific SVs may be causative for quantitative trait loci for germination, fungal disease resistance and other phenotypes. Further we show that the phenotypic heritability attributable to sequence anomalies differs from, and in the case of time to germination and bolting, exceeds that due to standard genetic variation. Gene expression within SVs is also more likely to be silenced or dysregulated. This approach is generally applicable to large populations sequenced at low-coverage, and complements the prevalent strategy of SV discovery in fewer individuals sequenced at high coverage.

genetics↗