Utilizing evolutionary conservation to detect deleterious mutations and improve genomic prediction in cassava.

Introduction: Cassava (Manihot esculenta) is an annual root crop which provides the major source of calories for over half a billion people around the world. Since its domestication ~10,000 years ago, cassava has been largely clonally propagated through stem cuttings. Minimal sexual recombination has led to an accumulation of deleterious mutations made evident by heavy inbreeding depression. Methods: To locate and characterize these deleterious mutations, and to measure selection pressure across the cassava genome, we aligned 52 related Euphorbiaceae and other related species representing millions of years of evolution. With single base-pair resolution of genetic conservation, we used protein structure models, amino acid impact, and evolutionary conservation across the Euphorbiaceae to estimate evolutionary constraint. With known deleterious mutations, we aimed to improve genomic evaluations of plant performance through genomic prediction. We first tested this hypothesis through simulation utilizing multi-kernel GBLUP to predict simulated phenotypes across separate populations of cassava. Results: Simulations showed a sizable increase of prediction accuracy when incorporating functional variants in the model when the trait was determined by<100 quantitative trait loci (QTL). Utilizing deleterious mutations and functional weights informed through evolutionary conservation, we saw improvements in genomic prediction accuracy that were dependent on trait and prediction. Conclusion: We showed the potential for using evolutionary information to track functional variation across the genome, in order to improve whole genome trait prediction. We anticipate that continued work to improve genotype accuracy and deleterious mutation assessment will lead to improved genomic assessments of cassava clones.

Genome-wide imputation using the practical haplotype graph in the heterozygous crop cassava.

Genomic applications such as genomic selection and genome-wide association have become increasingly common since the advent of genome sequencing. The cost of sequencing has decreased in the past two decades; however, genotyping costs are still prohibitive to gathering large datasets for these genomic applications, especially in nonmodel species where resources are less abundant. Genotype imputation makes it possible to infer whole-genome information from limited input data, making large sampling for genomic applications more feasible. Imputation becomes increasingly difficult in heterozygous species where haplotypes must be phased. The practical haplotype graph (PHG) is a recently developed tool that can accurately impute genotypes, using a reference panel of haplotypes. We showcase the ability of the PHG to impute genomic information in the highly heterozygous crop cassava (Manihot esculenta). Accurately phased haplotypes were sampled from runs of homozygosity across a diverse panel of individuals to populate PHG, which proved more accurate than relying on computational phasing methods. The PHG achieved high imputation accuracy, using sparse skim-sequencing input, which translated to substantial genomic prediction accuracy in cross-validation testing. The PHG showed improved imputation accuracy, compared to a standard imputation tool Beagle, especially in predicting rare alleles.

Public perceptions of threats from mosquitoes in the U.S. using online media analytics.

Mosquito-borne illnesses present a public health threat. This analysis quantifies general online mosquito media, and the Zika virus [ZIKV) specifically, from 7-20-2016 to 10-20-2018 in five U.S. geographies. The ZIKV sub-search comprised a shrinking share of online media about mosquitoes over time. Net sentiment, numerical scoring of search result positivity/negativity bounded between -100 and +100, was assessed. Mean net sentiment for the general mosquitoes search was -51; -55 for ZIKV. The ZIKV search revealed more variation in weekly net sentiment with a standard deviation of 14, compared to 10 for mosquitoes. Seventy-seven percent of the weeks had a net sentiment for the mosquito search that was more positive than the ZIKV search. For the 23% of the time the ZIKV search net sentiment was more positive than the general mosquito search, there were mentions of scientific advances, such as the potential for vaccine development associated with the post. Greater emphasis on public health threats from mosquitoes may be necessary to stimulate public action on mosquito-borne illness control. This analysis serves as an illustration of the potential for online/social media analysis to inform health officials of public interest/focus, and perhaps inform effective communication campaigns to combat public health threats.

Two gap-free reference genomes and a global view of the centromere architecture in rice.

Rice (Oryza sativa), a major staple throughout the world and a model system for plant genomics and breeding, was the first crop genome sequenced almost two decades ago. However, reference genomes for all higher organisms to date contain gaps and missing sequences. Here, we report the assembly and analysis of gap-free reference genome sequences for two elite O. sativa xian/indica rice varieties, Zhenshan 97 and Minghui 63, which are being used as a model system for studying heterosis and yield. Gap-free reference genomes provide the opportunity for a global view of the structure and function of centromeres. We show that all rice centromeric regions share conserved centromere-specific satellite motifs with different copy numbers and structures. In addition, the similarity of CentO repeats in the same chromosome is higher than across chromosomes, supporting a model of local expansion and homogenization. Both genomes have over 395 non-TE genes located in centromere regions, of which ∼41% are actively transcribed. Two large structural variants at the end of chromosome 11 affect the copy number of resistance genes between the two genomes. The availability of the two gap-free genomes lays a solid foundation for further understanding genome structure and function in plants and breeding climate-resilient varieties.

Suzuki coupling-based synthesis of VATPase inhibitor archazolid natural product derived fragments.

An archazolid natural product fragment that displays dose-dependent inhibition of the vacuolar-type ATPase (VATPase) has been synthesized by a high-yielding Suzuki coupling of two complex subunits. Similarly, a further simplified fragment was prepared and evaluated for VATPase inhibitory activity. This compound did inhibit the VATPase, as evidenced by growth inhibition of etiolated Arabidopsis seedlings, however at approximately 10× lower potency than the more complex fragment. Cyclooxygenase (COX) enzyme inhibition was not observed for either fragment.

Correction: Suzuki coupling-based synthesis of VATPase inhibitor archazolid natural product derived fragments.

[This corrects the article DOI: 10.1039/C9RA07050H.].

The Genome Sequence of Gossypioides kirkii Illustrates a Descending Dysploidy in Plants.

One of the extraordinary aspects of plant genome evolution is variation in chromosome number, particularly that among closely related species. This is exemplified by the cotton genus (Gossypium) and its relatives, where most species and genera have a base chromosome number of 13. The two exceptions are sister genera that have n = 12 (the Hawaiian Kokia and the East African and Madagascan Gossypioides). We generated a high-quality genome sequence of Gossypioides kirkii (n = 12) using PacBio, Bionano, and Hi-C technologies, and compared this assembly to genome sequences of Kokia (n = 12) and Gossypium diploids (n = 13). Previous analysis demonstrated that the directionality of their reduced chromosome number was through large structural rearrangements. A series of structural rearrangements were identified comparing the de novo G. kirkii genome sequence to genome sequences of Gossypium, including chromosome fusions and inversions. Genome comparison between G. kirkii and Gossypium suggests that multiple steps are required to generate the extant structural differences.

De Novo Genome Sequence Assemblies of Gossypium raimondii and Gossypium turneri.

Cotton is an agriculturally important crop. Because of its importance, a genome sequence of a diploid cotton species (Gossypium raimondii, D-genome) was first assembled using Sanger sequencing data in 2012. Improvements to DNA sequencing technology have improved accuracy and correctness of assembled genome sequences. Here we report a new de novo genome assembly of G. raimondii and its close relative G. turneri The two genomes were assembled to a chromosome level using PacBio long-read technology, HiC, and Bionano optical mapping. This report corrects some minor assembly errors found in the Sanger assembly of G. raimondii We also compare the genome sequences of these two species for gene composition, repetitive element composition, and collinearity. Most of the identified structural rearrangements between these two species are due to intra-chromosomal inversions. More inversions were found in the G. turneri genome sequence than the G. raimondii genome sequence. These findings and updates to the D-genome sequence will improve accuracy and translation of genomics to cotton breeding and genetics.

Genomic Structural Variations Within Five Continental Populations of Drosophila melanogaster.

Chromosomal structural variations (SV) including insertions, deletions, inversions, and translocations occur within the genome and can have a significant effect on organismal phenotype. Some of these effects are caused by structural variations containing genes. Large structural variations represent a significant amount of the genetic diversity within a population. We used a global sampling of Drosophila melanogaster (Ithaca, Zimbabwe, Beijing, Tasmania, and Netherlands) to represent diverse populations within the species. We used long-read sequencing and optical mapping technologies to identify SVs in these genomes. Among the five lines examined, we found an average of 2,928 structural variants within these genomes. These structural variations varied greatly in size and location, included many exonic regions, and could impact adaptation and genomic evolution.

On the importance of specialized radiofrequency filtering for concurrent TMS/MRI.

The concurrent application of TMS and MRI is challenging due to the MR-image artifacts, which are produced by using the two techniques in combination. One such artifact arises from the introduction of radio frequency noise through the lead of the TMS-coil into the scanner. Here we describe four methods used in the literature to integrate TMS into the MR environment and quantify in detail the efficacy of one approach in filtering RF interference. We show that RF filtering has a dramatic effect on the overall signal-to-fluctuation-noise ratio (SfNR) of the acquired echo-planar imaging data. The reduction in SfNR when integrating a TMS system into the MR scanner varies from 20% up to 80% (compared with MR scanner in the absence of TMS system), depending on the configuration used. Using an RF-filter in-line with the TMS-coil eliminates much of this loss in SfNR. However the RF filter also causes a ∼7% decrease in the functional efficacy of TMS. Overall, this study highlights the importance of RF-filtering when designing and installing a concurrent TMS/MRI system.

Comparing the accuracy of ES-BC, EIS-GS, and ES Oxi on body composition, autonomic nervous system activity, and cardiac output to standardized assessments.

BACKGROUND AND PURPOSE: THE ELECTRO SENSOR COMPLEX (ESC) IS SOFTWARE THAT COMBINES THREE DEVICES USING BIOELECTRICAL IMPEDANCE, GALVANIC SKIN RESPONSE, AND SPECTROPHOTOMETRY: (1) ES-BC (Electro Sensor-Body Composition; LD Technology, Miami, FL) to assess body composition, (2) EIS-GS (Electro Interstitial Scan-Galvanic Skin; LD Technology) to predict autonomic nervous system activity, and (3) ES Oxi (Electro Sensor Oxi; LD Technology) to assess cardiac output. The objective of this study was to compare each to a standardized assessment: ES-BC to dual-energy X-ray absorptiometry (DXA), EIS-GS to heart rate variability, and ES Oxi to BioZ Dx Diagnostic System (BioZ Dx; SonoSite Inc, Bothell, WA). PATIENTS AND METHODS: The study was conducted in two waves. Fifty subjects were assessed for body composition and autonomic nervous system activity. Fifty-one subjects were assessed for cardiac output. RESULTS: We found adequate relative and absolute agreement between ES-BC and DXA for fat mass (r = 0.97, P < 0.001) with ES-BC overestimating fat mass by 0.1 kg and for body fat percentage (r = 0.92, P < 0.001) with overestimation of fat percentage by 0.4%. For autonomic nervous system activity, we found marginal relative agreement between EIS-GS and heart rate variability by using EIS-GS as the predictor in a linear regression equation (adjusted R(2) = 0.56, P = 0.03). For cardiac output, adequate relative and absolute agreement was found between ES Oxi and BioZ Dx at baseline (r = 0.60, P < 0.001), after the first exercise stage (r = 0.79, P < 0.001), and after the second exercise stage (r = 0.86, P < 0.001). Absolute agreement was found at baseline and after both bouts of exercise; ES Oxi overestimated baseline and stage 1 exercise cardiac output by 0.3 L/minute and 0.1 L/minute, respectively, but exactly estimated stage 2 exercise cardiac output. CONCLUSION: ES-BC and ES Oxi accurately assessed body composition and cardiac output compared to standardized instruments, whereas EIS-GS showed marginal predictive ability for autonomic nervous system activity. The ESC software managing the three devices would be useful to help detect complications related to metabolic syndrome, diabetes, and cardiovascular disease and to noninvasively and rapidly manage treatment follow-up.