Uncovering compounds by synergy of cluster expansion and high-throughput methods.

Predicting from first-principles calculations whether mixed metallic elements phase-separate or form ordered structures is a major challenge of current materials research. It can be partially addressed in cases where experiments suggest the underlying lattice is conserved, using cluster expansion (CE) and a variety of exhaustive evaluation or genetic search algorithms. Evolutionary algorithms have been recently introduced to search for stable off-lattice structures at fixed mixture compositions. The general off-lattice problem is still unsolved. We present an integrated approach of CE and high-throughput ab initio calculations (HT) applicable to the full range of compositions in binary systems where the constituent elements or the intermediate ordered structures have different lattice types. The HT method replaces the search algorithms by direct calculation of a moderate number of naturally occurring prototypes representing all crystal systems and guides CE calculations of derivative structures. This synergy achieves the precision of the CE and the guiding strengths of the HT. Its application to poorly characterized binary Hf systems, believed to be phase-separating, defines three classes of alloys where CE and HT complement each other to uncover new ordered structures.

High-throughput isolation and mapping of C. elegans mutants susceptible to pathogen infection.

We present a novel strategy that uses high-throughput methods of isolating and mapping C. elegans mutants susceptible to pathogen infection. We show that C. elegans mutants that exhibit an enhanced pathogen accumulation (epa) phenotype can be rapidly identified and isolated using a sorting system that allows automation of the analysis, sorting, and dispensing of C. elegans by measuring fluorescent bacteria inside the animals. Furthermore, we validate the use of Amplifluor as a new single nucleotide polymorphism (SNP) mapping technique in C. elegans. We show that a set of 9 SNPs allows the linkage of C. elegans mutants to a 5-8 megabase sub-chromosomal region.

High throughput determination of sequence-function relationships in protein and RNA

Thesis (Ph.D.)--University of Washington, 2016-06

High-throughput sequencing of IL23R reveals a low-frequency, nonsynonymous single-nucleotide polymorphism that is associated with ankylosing spondylitis in a Han Chinese population

Objective Ankylosing spondylitis (AS) is a highly heritable common inflammatory arthritis that targets the spine and sacroiliac joints of the pelvis, causing pain and stiffness and leading eventually to joint fusion. Although previous studies have shown a strong association of IL23R with AS in white Europeans, similar studies in East Asian populations have shown no association with common variants of IL23R, suggesting either that IL23R variants have no role or that rare genetic variants contribute. The present study was undertaken to screen IL23R to identify rare variants associated with AS in Han Chinese. Methods A 170-kb region containing IL23R and its flanking regions was sequenced in 50 patients with AS and 50 ethnically matched healthy control subjects from a Han Chinese population. In addition, the 30-kb region of peak association in white Europeans was sequenced in 650 patients with AS and 1,300 healthy controls. Validation genotyping was undertaken in 846 patients with AS and 1,308 healthy controls. Results We identified 1,047 variants, of which 729 were not found in the dbSNP genomic build 130. Several potentially functional rare variants in IL23R were identified, including one nonsynonomous single-nucleotide polymorphism (nsSNP), Gly149Arg (position 67421184 GA on chromosome 1). Validation genotyping showed that the Gly149Arg variant was associated with AS (odds ratio 0.61, P = 0.0054). Conclusion This is the first study to implicate rare IL23R variants in the pathogenesis of AS. The results identified a low-frequency nsSNP with predicted loss-of-function effects that was protectively associated with AS in Han Chinese, suggesting that decreased function of the interleukin-23 (IL-23) receptor protects against AS. These findings further support the notion that IL-23 signaling has an important role in the pathogenesis of AS.

High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials.

High-throughput Phenotyping of Wheat Seminal Root Traits in a Breeding Context

Water availability is a major limiting factor for wheat (Triticum aestivum L.) in rain-fed agricultural systems worldwide. Root architecture has important functional implications for the timing and extent of soil water extraction, yet selection for root traits in wheat breeding programs has been largely limited due to the lack of suitable phenotyping methods. The aim of this research was to develop a low-cost high-throughput phenotyping method to facilitate selection for desirable root traits. We developed a method to assess ‘seminal root angle’ and ‘seminal root number’ in seedlings – two proxy traits associated to root architecture of mature wheat plants (1). The method involves measuring the angle between the first pair of seminal roots and the number of roots of wheat seedlings grown in transparent pots (Figure 1). Images captured at 5 to 10 days after sowing are analyzed to calculate seminal root angle and number. Performing this technique under “speed breeding” conditions (plants grown at a density of 600 plants / m2, under controlled temperature and constant light) allows the selection based on the desired root traits of up to 5 consecutive generations within 12 months. Alternatively, when focusing only on germplasm screening, up to 52 successive phenotypic assays can be conducted within 12 months. This approach has been shown to be highly reproducible, it requires little resource (time, space, and labour) and can be used to rapidly enrich breeding populations with desirable alleles for narrow root angle and a high number of seminal roots to indirectly target the selection of deeper root system with higher branching at depth. Such root characteristics are highly desirable in wheat to cope with the climate model projections, especially in summer rainfall dominant regions including some Australian, Indian, South American and African cropping regions, where winter crops mainly rely on deep stored water.

Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays

This thesis presents a highly sensitive genome wide search method for recessive mutations. The method is suitable for distantly related samples that are divided into phenotype positives and negatives. High throughput genotype arrays are used to identify and compare homozygous regions between the cohorts. The method is demonstrated by comparing colorectal cancer patients against unaffected references. The objective is to find homozygous regions and alleles that are more common in cancer patients. We have designed and implemented software tools to automate the data analysis from genotypes to lists of candidate genes and to their properties. The programs have been designed in respect to a pipeline architecture that allows their integration to other programs such as biological databases and copy number analysis tools. The integration of the tools is crucial as the genome wide analysis of the cohort differences produces many candidate regions not related to the studied phenotype. CohortComparator is a genotype comparison tool that detects homozygous regions and compares their loci and allele constitutions between two sets of samples. The data is visualised in chromosome specific graphs illustrating the homozygous regions and alleles of each sample. The genomic regions that may harbour recessive mutations are emphasised with different colours and a scoring scheme is given for these regions. The detection of homozygous regions, cohort comparisons and result annotations are all subjected to presumptions many of which have been parameterized in our programs. The effect of these parameters and the suitable scope of the methods have been evaluated. Samples with different resolutions can be balanced with the genotype estimates of their haplotypes and they can be used within the same study.

Ultra high throughput sequencing excludes MDH1 as candidate gene for RP28-linked retinitis pigmentosa

Purpose: Mutations in IDH3B, an enzyme participating in the Krebs cycle, have recently been found to cause autosomal recessive retinitis pigmentosa (arRP). The MDH1 gene maps within the RP28 arRP linkage interval and encodes cytoplasmic malate dehydrogenase, an enzyme functionally related to IDH3B. As a proof of concept for candidate gene screening to be routinely performed by ultra high throughput sequencing (UHTs), we analyzed MDH1 in a patient from each of the two families described so far to show linkage between arRP and RP28. Methods: With genomic long-range PCR, we amplified all introns and exons of the MDH1 gene (23.4 kb). PCR products were then sequenced by short-read UHTs with no further processing. Computer-based mapping of the reads and mutation detection were performed by three independent software packages. Results: Despite the intrinsic complexity of human genome sequences, reads were easily mapped and analyzed, and all algorithms used provided the same results. The two patients were homozygous for all DNA variants identified in the region, which confirms previous linkage and homozygosity mapping results, but had different haplotypes, indicating genetic or allelic heterogeneity. None of the DNA changes detected could be associated with the disease. Conclusions: The MDH1 gene is not the cause of RP28-linked arRP. Our experimental strategy shows that long-range genomic PCR followed by UHTs provides an excellent system to perform a thorough screening of candidate genes for hereditary retinal degeneration.

Ultra high throughput sequencing excludes MDH1 as candidate gene for RP28-linked retinitis pigmentosa

Purpose: Mutations in IDH3B, an enzyme participating in the Krebs cycle, have recently been found to cause autosomal recessive retinitis pigmentosa (arRP). The MDH1 gene maps within the RP28 arRP linkage interval and encodes cytoplasmic malate dehydrogenase, an enzyme functionally related to IDH3B. As a proof of concept for candidate gene screening to be routinely performed by ultra high throughput sequencing (UHTs), we analyzed MDH1 in a patient from each of the two families described so far to show linkage between arRP and RP28. Methods: With genomic long-range PCR, we amplified all introns and exons of the MDH1 gene (23.4 kb). PCR products were then sequenced by short-read UHTs with no further processing. Computer-based mapping of the reads and mutation detection were performed by three independent software packages. Results: Despite the intrinsic complexity of human genome sequences, reads were easily mapped and analyzed, and all algorithms used provided the same results. The two patients were homozygous for all DNA variants identified in the region, which confirms previous linkage and homozygosity mapping results, but had different haplotypes, indicating genetic or allelic heterogeneity. None of the DNA changes detected could be associated with the disease.

High-Throughput Study of the Cu(CH3COO)(2)center dot H2O-5-Nitroisophthalic Acid Heterocyclic Ligand System: Synthesis, Structure, Magnetic, and Heterogeneous Catalytic Studies of Three Copper Nitroisophthalates

A high-throughput screening was employed to identify new compounds in Cu(CH3COO)(2)center dot H2O-NIPA-heterocyclic ligand systems. Of the compounds identified, three compounds, Cu-3{(NO2)-C6H3-(COO)(2)}(3)(C3N6H6)] (1), Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2)}(CN4H)]center dot-(H2O) (II), and Cu-2(mu(3)-OH)(H2O){(NO2)-C6H3-(COO)(2}-)(CN5H2)]center dot 2(H2O) (III), have been isolated as good quality single crystals by employing conventional hydrothermal methods. Three other compounds, Cu-2{(NO2)-C6H3-(COO)(2)}-(CN4H)(H2O) (IIa), Cu-2{(NO2)-C6H3-(COO)(2)}(CN5H2) (IIIa), and Cu-2{(NO2)-C6H3-(COO)(2)}{(CN5H2)(2)}2H(2)O (IIIb), were identified by a combination of elemental analysis, thermogravimetric analysis (TGA), and IR spectroscopic studies, although their structures are yet to be determined. The single crystalline compounds were also characterized by elemental analysis, TGA, IR, UV vis, magnetic, and catalytic studies. The structures of the compounds have paddle wheel (I) and infinite Cu 0(H) Cu chains (II and HI) connected with NLPA and heterocyclic ligands forming two-(II) and three-dimensional (I and III) structures. The bound and lattice water molecules in 11 and 111 could be reversibly removed/inserted without affecting the structure. In the case of II, the removal of water gives rise to a structural transition, but the dehydrated phase reverts back to the original phase on prolonged exposure to atmospheric conditions. Magnetic studies indicate an overall antiferromagnetism in all of the compounds. Lewis acid catalytic studies indicate that compounds II and HI are active for cyanosilylation of imines.