Biology subjects

Miller, M.

Publications and source records attributed to Miller, M..

8 recordsLinked to original sources

bioRxiv2018

A Versatile Rapture (RAD-Capture) Platform for Genotyping Marine Turtles

Advances in high-throughput sequencing (HTS) technologies coupled with increased interdisciplinary collaboration is rapidly expanding capacity in the scope and scale of wildlife genetic studies. While existing HTS methods can be directly applied to address some evolutionary and ecological questions, certain research goals necessitate tailoring methods to specific study organisms, such as high-throughput genotyping of the same loci that are comparable over large spatial and temporal scales. These needs are particularly common for studies of highly mobile species of conservation concern like marine turtles, where life history traits, limited financial resources and other constraints require affordable, adaptable methods for HTS genotyping to meet a variety of study goals. Here, we present a versatile marine turtle HTS targeted enrichment platform adapted from the recently developed Rapture (RAD-Capture) method specifically designed to meet these research needs. Our results demonstrate consistent enrichment of targeted regions throughout the genome and discovery of candidate variants in all species examined for use in various conservation genetics applications. Accurate species identification confirmed the ability of our platform to genotype over 1,000 multiplexed samples, and identified areas for future methodological improvement such as optimization for low initial concentration samples. Finally, analyses within green turtles supported the ability of this platform to identify informative SNPs for stock structure, population assignment and other applications over a broad geographic range of interest to management. This platform provides an additional tool for marine turtle genetic studies and broadens capacity for future large-scale initiatives such as collaborative global marine turtle genetic databases.

genomics↗

bioRxiv2018

Comprehensive Benchmarking and Integration of Tumour Microenvironment Cell Estimation Methods

The tumour microenvironment comprises complex cellular compositions and interactions between cancer, immune, and stromal components which all play crucial roles in cancer. Various computational approaches have been developed during the last decade that estimate the relative abundance of different cell types in an unbiased manner using bulk tumour RNA data. However, a comparison that objectively evaluates the performance of these approaches against one another has not been conducted. Here we benchmarked six widely used tools and gene sets: Bindea et al. gene sets, Davoli et al. gene sets, CIBERSORT, MCP-counter, TIMER, and xCell. We also introduce ConsensusTME, a consensus approach that uses the union of genes that the six tools used for cell estimation, and corrects for tumour-type specificity. We benchmarked the seven tools using TCGA DNA-derived purity scores (33 tumour-types), methylation-derived leukocyte scores (30 tumour-types), and H&E deep learning derived lymphocyte counts (13 tumour types), and individual benchmark data sets (PBMCs and 2 tumour types). Although none of the seven tools outperformed others in every benchmark, ConsensusTME ranked consistently well in all cancer-related benchmarks making it the top performing method overall. Computational methods that provide robust and accurate estimates of non-cancerous cell populations in the tumour microenvironment from tumour bulk expression data are important tools that can advance our understanding of tumour, immune, and stroma interactions, with potential clinical application if high accuracy estimates are achieved.

bioinformatics↗

bioRxiv2018

Asymmetrically Positioned Flagellar Control Units Regulate Human Sperm Rotation

The ability of sperm to fertilize an egg is controlled by ion channels, one of which is the pH-dependent calcium channel of sperm CatSper. For CatSper to be fully activated, the cytoplasmic pH must be alkaline, which is accomplished by either proton transporters, or a faster mechanism, such as the voltage-gated proton channel Hv1. To ensure effective regulation, these channels and regulatory proteins must be tightly compartmentalized. Here, we characterize human sperm nanodomains that are comprised of Hv1, CatSper and regulatory protein ABHD2. Super-resolution microscopy revealed that Hv1 forms asymmetrically positioned bilaterally distributed longitudinal lines that span the entire length of the sperm tail. Such a distribution provides a direct structural basis for the selective activation of CatSper, and subsequent flagellar rotation along the long axis that, together with hyperactivated motility, enhances sperm fertility. Indeed, Hv1 inhibition leads to a decrease in sperm rotation. Thus, sperm ion channels are organized in distinct regulatory nanodomains that control hyperactivated motility and rotation.

cell biology↗

bioRxiv2018

Detection of race-specific resistance against Puccinia coronata f. sp. avenae in Brachypodium species

Oat crown rust caused by Puccinia coronata f. sp. avenae is the most destructive foliar disease of cultivated oat. Characterization of genetic factors controlling resistance responses to Puccinia coronata f. sp. avenae in non-host species could provide new resources for developing disease protection strategies in oat. We examined symptom development and fungal colonization levels of a collection of Brachypodium distachyon and B. hybridum accessions infected with three North American P. coronata f. sp. avenae isolates. Our results demonstrated that colonization phenotypes are dependent on both host and pathogen genotypes, indicating a role for race-specific responses in these interactions. These responses were independent of the accumulation of reactive oxygen species. Expression analysis of several defense-related genes suggested that salicylic acid and ethylene-mediated signaling, but not jasmonic acid are components of resistance reaction to P. coronata f. sp. avenae. Our findings provide the basis to conduct a genetic inheritance study to examine if effector-triggered immunity contributes to non-host resistance to P. coronata f. sp. avenae in Brachypodium species.

pathology↗

bioRxiv2018

On variational solutions for whole brain serial-section histology using the computational anatomy random orbit model

This paper presents a variational framework for dense diffeomorphic atlas-mapping onto high-throughput histology stacks at the 20 m meso-scale. The observed sections are modelled as Gaussian random fields conditioned on a sequence of unknown section by section rigid motions and unknown diffeomorphic transformation of a three-dimensional atlas. To regularize over the high-dimensionality of our parameter space (which is a product space of the rigid motion dimensions and the diffeomorphism dimensions), the histology stacks are modelled as arising from a first order Sobolev space smoothness prior. We show that the joint maximum a-posteriori, penalized-likelihood estimator of our high dimensional parameter space emerges as a joint optimization interleaving rigid motion estimation for histology restacking and large deformation diffeomorphic metric mapping to atlas coordinates. We show that joint optimization in this parameter space solves the classical curvature non-identifiability of the histology stacking problem. The algorithms are demonstrated on a collection of whole-brain histological image stacks from the Mouse Brain Architecture Project.\n\nAuthor SummaryNew developments in neural tracing techniques have motivated the widespread use of histology as a modality for exploring the circuitry of the brain. Automated mapping of pre-labeled atlases onto modern large datasets of histological imagery is a critical step for elucidating the brains neural circuitry and shape. This task is challenging as histological sections are imaged independently and the reconstruction of the unsectioned volume is nontrivial. Typically, neuroanatomists use reference volumes of the same subject (e.g. MRI) to guide reconstruction. However, obtaining reference imagery is often non-standard, as in high-throughput animal models like mouse histology. Others have proposed using anatomical atlases as guides, but have not accounted for the intrinsic nonlinear shape difference from atlas to subject. Our method addresses these limitations by jointly optimizing reconstruction informed by an atlas simultaneously with the nonlinear change of coordinates that encapsulates anatomical variation. This accounts for intrinsic shape differences and enables rigorous, direct comparisons of atlas and subject coordinates. Using simulations, we demonstrate that our method recovers the reconstruction parameters more accurately than atlas-free models and innately produces accurate segmentations from simultaneous atlas mapping. We also demonstrate our method on the Mouse Brain Architecture dataset, successfully mapping and reconstructing over 500 brains.

neuroscience↗

bioRxiv2017

Morphogen dynamics control patterning in a stem cell model of the human embryo

During embryonic development, diffusible signaling molecules called morphogens are thought to determine cell fates in a concentration-dependent manner1-4, and protocols for directed stem cell differentiation are based on this picture5-8. However, in the mammalian embryo, morphogen concentrations change rapidly compared to the time for making cell fate decisions9-12. It is unknown how changing ligand levels are interpreted, and whether the precise timecourse of ligand exposure plays a role in cell fate decisions. Nodal and BMP4 are morphogens crucial for gastrulation in vertebrates13. Each pathway has distinct receptor complexes that phosphorylate specific signal transducers, known as receptor-Smads, which then complex with the shared cofactor Smad4 to activate target genes14. Here we show in human embryonic stem cells (hESCs) that the response to BMP4 signaling indeed is determined by the ligand concentration, but that unexpectedly, the expression of many mesodermal targets of Activin/Nodal depends on rate of concentration increase. In addition, we use live imaging of hESCs with GFP integrated at the endogenous SMAD4 locus to show that a stem cell model for the human embryo15 generates a wave of Nodal signaling. Cells experience rapidly increasing Nodal specifically in the region of mesendoderm differentiation. We also demonstrate that pulsatile stimulation with Activin induces repeated strong signaling and enhances mesoderm differentiation. Our results break with the paradigm of concentration-dependent differentiation and demonstrate an important role for morphogen dynamics in the cell fate decisions associated with mammalian gastrulation. They suggest a highly dynamic picture of embryonic patterning where some cell fates depend on rapid concentration increase rather than absolute levels, and point to ligand dynamics as a new dimension to optimize protocols for directed stem cell differentiation.

developmental biology↗

bioRxiv2017

A near complete haplotype-phased genome of the dikaryotic wheat stripe rust fungus Puccinia striiformis f. sp. tritici reveals high inter-haplome diversity

A long-standing biological question is how evolution has shaped the genomic architecture of dikaryotic fungi. To answer this, high quality genomic resources that enable haplotype comparisons are essential. Short-read genome assemblies for dikaryotic fungi are highly fragmented and lack haplotype-specific information due to the high heterozygosity and repeat content of these genomes. Here we present a diploidaware assembly of the wheat stripe rust fungus Puccinia striiformis f. sp. tritici based on long-reads using the FALCON-Unzip assembler. RNA-seq datasets were used to infer high quality gene models and identify virulence genes involved in plant infection referred to as effectors. This represents the most complete Puccinia striiformis f. sp. tritici genome assembly to date (83 Mb, 156 contigs, N50 1.5 Mb) and provides phased haplotype information for over 92% of the genome. Comparisons of the phase blocks revealed high inter-haplotype diversity of over 6%. More than 25% of all genes lack a clear allelic counterpart. When investigating genome features that potentially promote the rapid evolution of virulence, we found that candidate effector genes are spatially associated with conserved genes commonly found in basidiomycetes. Yet candidate effectors that lack an allelic counterpart are more distant from conserved genes than allelic candidate effectors, and are less likely to be evolutionarily conserved within the P. striiformis species complex and Pucciniales. In summary, this haplotype-phased assembly enabled us to discover novel genome features of a dikaryotic plant pathogenic fungus previously hidden in collapsed and fragmented genome assemblies.\n\nImportanceCurrent representations of eukaryotic microbial genomes are haploid, hiding the genomic diversity intrinsic to diploid and polyploid life forms. This hidden diversity contributes to the organisms evolutionary potential and ability to adapt to stress conditions. Yet it is challenging to provide haplotype-specific information at a whole-genome level. Here, we take advantage of long-read DNA sequencing technology and a tailored-assembly algorithm to disentangle the two haploid genomes of a dikaryotic pathogenic wheat rust fungus. The two genomes display high levels of nucleotide and structural variations, which leads to allelic variation and the presence of genes lacking allelic counterparts. Non-allelic candidate effector genes, which likely encode important pathogenicity factors, display distinct genome localization patterns and are less likely to be evolutionary conserved than those which are present as allelic pairs. This genomic diversity may promote rapid host adaptation and/or be related to the age of the sequenced isolate since last meiosis.

microbiology↗

bioRxiv2017

Raspberry Pi Powered Imaging for Plant Phenotyping

O_LIPremise of the study: Image-based phenomics is a powerful approach to capture and quantify plant diversity. However, commercial platforms that make consistent image acquisition easy are often cost-prohibitive. To make high-throughput phenotyping methods more accessible, low-cost microcomputers and cameras can be used to acquire plant image data.\nC_LIO_LIMethods and Results: We used low-cost Raspberry Pi computers and cameras to manage and capture plant image data. Detailed here are three different applications of Raspberry Pi controlled imaging platforms for seed and shoot imaging. Images obtained from each platform were suitable for extracting quantifiable plant traits (shape, area, height, color) en masse using open-source image processing software such as PlantCV.\nC_LIO_LIConclusion: This protocol describes three low-cost platforms for image acquisition that are useful for quantifying plant diversity. When coupled with open-source image processing tools, these imaging platforms provide viable low-cost solutions for incorporating high-throughput phenomics into a wide range of research programs.\nC_LI

plant biology↗