The Influence of Arsenic Co-Exposure in a Model of Alcohol-Induced Neurodegeneration in C57BL/6J Mice.

Both excessive alcohol consumption and exposure to high levels of arsenic can lead to neurodegeneration, especially in the hippocampus. Co-exposure to arsenic and alcohol can occur because an individual with an Alcohol Use Disorder (AUD) is exposed to arsenic in their drinking water or food or because of arsenic found directly in alcoholic beverages. This study aims to determine if co-exposure to alcohol and arsenic leads to worse outcomes in neurodegeneration and associated mechanisms that could lead to cell death. To study this, mice were exposed to a 10-day gavage model of alcohol-induced neurodegeneration with varying doses of arsenic (0, 0.005, 2.5, or 10 mg/kg). The following were examined after the last dose of ethanol: (1) microglia activation assessed via immunohistochemical detection of Iba-1, (2) reactive oxygen and nitrogen species (ROS/RNS) using a colorimetric assay, (3) neurodegeneration using Fluoro-Jade® C staining (FJC), and 4) arsenic absorption using ICP-MS. After exposure, there was an additive effect of the highest dose of arsenic (10 mg/kg) in the dentate gyrus of alcohol-induced FJC+ cells. This additional cell loss may have been due to the observed increase in microglial reactivity or increased arsenic absorption following co-exposure to ethanol and arsenic. The data also showed that arsenic caused an increase in CYP2E1 expression and ROS/RNS production in the hippocampus which could have independently contributed to increased neurodegeneration. Altogether, these findings suggest a potential cyclical impact of co-exposure to arsenic and ethanol as ethanol increases arsenic absorption but arsenic also enhances alcohol's deleterious effects in the CNS.

Repetitive binge-like consumption based on the Drinking-in-the-Dark model alters the microglial population in the mouse hippocampus.

Alcoholism causes various maladaptations in the central nervous system, including the neuroimmune system. Studies of alcohol-induced dysregulation of the neuroimmune system generally focus on alcohol dependence and brain damage, but our previous research indicates that repetitive binge-like consumption perturbs cytokines independent of cell death. This paper extends that research by examining the impact of binge-like consumption on microglia in the hippocampus and the amygdala. Microglia were assessed using immunohistochemistry following binge-like ethanol consumption based on Drinking-in-the-Dark model. Immunohistochemistry results showed that binge-like ethanol consumption caused an increase in Iba-1 immunoreactivity and the number of Iba-1+ cells after one Drinking-in-the-Dark cycle. However, after three Drinking-in-the-Dark cycles, the number of microglia decreased in the hippocampus. We showed that in the dentate gyrus, the average immunoreactivity/cell was increased following ethanol exposure despite the decrease in number after three cycles. Likewise, Ox-42, an indicator of microglia activation, was upregulated after ethanol consumption. No significant effects on microglia number or immunoreactivity (Iba-1 nor Ox-42) were observed in the amygdala. Finally, ethanol caused an increase in the expression of the microglial gene Aif-1 during intoxication and ten days into abstinence, suggesting persistence of ethanol-induced upregulation of microglial genes. Altogether, these findings indicate that repetitive binge-like ethanol is sufficient to elicit changes in microglial reactivity. This altered neuroimmune state may contribute to the development of alcohol use disorders.

Identification of novel QTL governing root architectural traits in an interspecific soybean population.

Cultivated soybean (Glycine max L.) cv. Dunbar (PI 552538) and wild G. soja (PI 326582A) exhibited significant differences in root architecture and root-related traits. In this study, phenotypic variability for root traits among 251 BC2F5 backcross inbred lines (BILs) developed from the cross Dunbar/PI 326582A were identified. The root systems of the parents and BILs were evaluated in controlled environmental conditions using a cone system at seedling stage. The G. max parent Dunbar contributed phenotypically favorable alleles at a major quantitative trait locus on chromosome 8 (Satt315-I locus) that governed root traits (tap root length and lateral root number) and shoot length. This QTL accounted for >10% of the phenotypic variation of both tap root and shoot length. This QTL region was found to control various shoot- and root-related traits across soybean genetic backgrounds. Within the confidence interval of this region, eleven transcription factors (TFs) were identified. Based on RNA sequencing and Affymetrix expression data, key TFs including MYB, AP2-EREBP and bZIP TFs were identified in this QTL interval with high expression in roots and nodules. The backcross inbred lines with different parental allelic combination showed different expression pattern for six transcription factors selected based on their expression pattern in root tissues. It appears that the marker interval Satt315-I locus on chromosome 8 contain an essential QTL contributing to early root and shoot growth in soybean.

Mapping of QTL for Fusarium head blight resistance and morphological and developmental traits in three backcross populations derived from Triticum dicoccum × Triticum durum.

Breeding for resistance to Fusarium head blight (FHB) in durum wheat continues to be hindered by the lack of effective resistance sources. Only limited information is available on resistance QTL for FHB in tetraploid wheat. In this study, resistance to FHB of a Triticum dicoccum line in the background of three Austrian T. durum cultivars was genetically characterized. Three populations of BC(1)F(4)-derived RILs were developed from crosses between the resistant donor line T. dicoccum-161 and the Austrian T. durum recipient varieties DS-131621, Floradur and Helidur. About 130 BC(1)F(4)-derived lines per population were evaluated for FHB response using artificial spray inoculation in four field experiments during two seasons. Lines were genetically fingerprinted using SSR and AFLP markers. Genomic regions on chromosomes 3B, 4B, 6A, 6B and 7B were significantly associated with FHB severity. FHB resistance QTL on 6B and 7B were identified in two populations and a resistance QTL on 4B appeared in three populations. The alleles that enhanced FHB resistance were derived from the T. dicoccum parent, except for the QTL on chromosome 3B. All QTL except the QTL on 6A mapped to genomic regions where QTL for FHB have previously been reported in hexaploid wheat. QTL on 3B and 6B coincided with Fhb1 and Fhb2, respectively. This implies that tetraploid and hexaploid wheat share common genomic regions associated with FHB resistance. QTL for FHB resistance on 4B co-located with a major QTL for plant height and mapped at the position of the Rht-B1 gene, while QTL on 7B overlapped with QTL for flowering time.

Autoantibody signatures as biomarkers to distinguish prostate cancer from benign prostatic hyperplasia in patients with increased serum prostate specific antigen.

BACKGROUND: Serum prostate specific antigen (PSA) concentrations lack the specificity to differentiate prostate cancer from benign prostate hyperplasia (BPH), resulting in unnecessary biopsies. We identified 5 autoantibody signatures to specific cancer targets which might be able to differentiate prostate cancer from BPH in patients with increased serum PSA. METHODS: To identify autoantibody signatures as biomarkers, a native antigen reverse capture microarray platform was used. Briefly, well-characterized monoclonal antibodies were arrayed onto nanoparticle slides to capture native antigens from prostate cancer cells. Prostate cancer patient serum samples (n=41) and BPH patient samples (collected starting at the time of initial diagnosis) with a mean follow-up of 6.56 y without the diagnosis of cancer (n=39) were obtained. One hundred micrograms of IgGs were purified and labeled with a Cy3 dye and incubated on the arrays. The arrays were scanned for fluorescence and the intensity was quantified. Receiver operating characteristic curves were produced and the area under the curve (AUC) was determined. RESULTS: Using our microarray platform, we identified autoantibody signatures capable of distinguishing between prostate cancer and BPH. The top 5 autoantibody signatures were TARDBP, TLN1, PARK7, LEDGF/PSIP1, and CALD1. Combining these signatures resulted in an AUC of 0.95 (sensitivity of 95% at 80% specificity) compared to AUC of 0.5 for serum concentration PSA (sensitivity of 12.2% at 80% specificity). CONCLUSION: Our preliminary results showed that we were able to identify specific autoantibody signatures that can differentiate prostate cancer from BPH, and may result in the reduction of unnecessary biopsies in patients with increased serum PSA.

Single-nucleotide polymorphism discovery by high-throughput sequencing in sorghum.

BACKGROUND: Eight diverse sorghum (Sorghum bicolor L. Moench) accessions were subjected to short-read genome sequencing to characterize the distribution of single-nucleotide polymorphisms (SNPs). Two strategies were used for DNA library preparation. Missing SNP genotype data were imputed by local haplotype comparison. The effect of library type and genomic diversity on SNP discovery and imputation are evaluated. RESULTS: Alignment of eight genome equivalents (6 Gb) to the public reference genome revealed 283,000 SNPs at ≥82% confirmation probability. Sequencing from libraries constructed to limit sequencing to start at defined restriction sites led to genotyping 10-fold more SNPs in all 8 accessions, and correctly imputing 11% more missing data, than from semirandom libraries. The SNP yield advantage of the reduced-representation method was less than expected, since up to one fifth of reads started at noncanonical restriction sites and up to one third of restriction sites predicted in silico to yield unique alignments were not sampled at near-saturation. For imputation accuracy, the availability of a genomically similar accession in the germplasm panel was more important than panel size or sequencing coverage. CONCLUSIONS: A sequence quantity of 3 million 50-base reads per accession using a BsrFI library would conservatively provide satisfactory genotyping of 96,000 sorghum SNPs. For most reliable SNP-genotype imputation in shallowly sequenced genomes, germplasm panels should consist of pairs or groups of genomically similar entries. These results may help in designing strategies for economical genotyping-by-sequencing of large numbers of plant accessions.

Linkage analysis in unconventional mating designs in line crosses.

Linkage estimation and genetic map construction with genotyped DNA markers in plants preferentially employ a few maximally informative early-generation or recombinant-inbred mating designs. Fitting their recombination models to unconventional designs adapted to cultivar development (series of backcrossing, selfing, haploid-doubling, random-intercrossing, and sib-mating steps) distorts single- and multipoint linkage estimates even with dense marker coverage. Two methods are provided for correct linkage estimation in unconventional designs: fitting a correct multigeneration model, or correcting the estimates produced by fitting a one-generation model with any conventional software. These methods also support calculation of multilocus genotype frequencies and QTL-genotype distributions and are available in software.

Evolution of new disease specificity at a simple resistance locus in a crop-weed complex: reconstitution of the Lr21 gene in wheat.

The wheat leaf-rust resistance gene Lr21 was first identified in an Iranian accession of goatgrass, Aegilops tauschii Coss., the D-genome donor of hexaploid bread wheat, and was introgressed into modern wheat cultivars by breeding. To elucidate the origin of the gene, we analyzed sequences of Lr21 and lr21 alleles from 24 wheat cultivars and 25 accessions of Ae. tauschii collected along the Caspian Sea in Iran and Azerbaijan. Three basic nonfunctional lr21 haplotypes, H1, H2, and H3, were identified. Lr21 was found to be a chimera of H1 and H2, which were found only in wheat. We attempted to reconstitute a functional Lr21 allele by crossing the cultivars Fielder (H1) and Wichita (H2). Rust inoculation of 5876 F(2) progeny revealed a single resistant plant that proved to carry the H1H2 haplotype, a result attributed to intragenic recombination. These findings reflect how plants balance the penalty and the necessity of a resistance gene and suggest that plants can reuse "dead" alleles to generate new disease-resistance specificity, leading to a "death-recycle" model of plant-resistance gene evolution at simple loci. We suggest that selection pressure in crop-weed complexes contributes to this process.

Multiple-trait quantitative trait locus mapping with incomplete phenotypic data.

BACKGROUND: Conventional multiple-trait quantitative trait locus (QTL) mapping methods must discard cases (individuals) with incomplete phenotypic data, thereby sacrificing other phenotypic and genotypic information contained in the discarded cases. Under standard assumptions about the missing-data mechanism, it is possible to exploit these cases. RESULTS: We present an expectation-maximization (EM) algorithm, derived for recombinant inbred and F2 genetic models but extensible to any mating design, that supports conventional hypothesis tests for QTL main effect, pleiotropy, and QTL-by-environment interaction in multiple-trait analyses with missing phenotypic data. We evaluate its performance by simulations and illustrate with a real-data example. CONCLUSION: The EM method affords improved QTL detection power and precision of QTL location and effect estimation in comparison with case deletion or imputation methods. It may be incorporated into any least-squares or likelihood-maximization QTL-mapping approach.

QGene 4.0, an extensible Java QTL-analysis platform.

UNLABELLED: Of many statistical methods developed to date for quantitative trait locus (QTL) analysis, only a limited subset are available in public software allowing their exploration, comparison and practical application by researchers. We have developed QGene 4.0, a plug-in platform that allows execution and comparison of a variety of modern QTL-mapping methods and supports third-party addition of new ones. The software accommodates line-cross mating designs consisting of any arbitrary sequence of selfing, backcrossing, intercrossing and haploid-doubling steps that includes map, population, and trait simulators; and is scriptable. AVAILABILITY: Software and documentation are available at http://coding.plantpath.ksu.edu/qgene. Source code is available on request.

Molecular mapping of QTLs for Karnal bunt resistance in two recombinant inbred populations of bread wheat.

Karnal bunt (KB) of wheat, caused by the fungus Tilletia indica, is a challenge to the grain industry, owing not to direct yield loss but to quarantine regulations that may restrict international movement of affected grain. Several different sources of resistance to KB have been reported. Understanding the genetics of resistance will facilitate the introgression of resistance into new wheat cultivars. The objectives of this study were to identify quantitative trait loci (QTLs) associated with KB resistance and to identify DNA markers in two recombinant inbred line populations derived from crosses of the susceptible cultivar WH542 with resistant lines HD29 and W485. Populations were evaluated for resistance against the KB pathogen for 3 years at Punjab Agricultural University, Ludhiana, India. Two new QTLs (Qkb.ksu-5BL.1 and Qkb.ksu-6BS.1) with resistance alleles from HD29 were identified and mapped in the intervals Xgdm116-Xwmc235 on chromosome 5B (deletion bin 5BL9-0.76-0.79) and Xwmc105-Xgwm88 on chromosome 6B (C-6BS5-0.76). They explained up to 19 and 13% of phenotypic variance, respectively. Another QTL (Qkb.ksu-4BL.1) with a resistance allele from W485 mapped in the interval Xgwm6-Xwmc349 on chromosome 4B (4BL5-0.86-1.00) and explained up to 15% of phenotypic variance. Qkb.ksu-6BS.1 showed pairwise interactions with loci on chromosomes 3B and 6A. Markers suitable for marker-assisted selection are available for all three QTLs.

RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection.

Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (> or =2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (> or =10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.

Gene evolution at the ends of wheat chromosomes.

Wheat ESTs mapped to deletion bins in the distal 42% of the long arm of chromosome 4B (4BL) were ordered in silico based on blastn homology against rice pseudochromosome 3. The ESTs spanned 29 cM on the short arm of rice chromosome 3, which is known to be syntenic to long arms of group-4 chromosomes of wheat. Fine-scale deletion-bin and genetic mapping revealed that 83% of ESTs were syntenic between wheat and rice, a far higher level of synteny than previously reported, and 6% were nonsyntenic (not located on rice chromosome 3). One inversion spanning a 5-cM region in rice and three deletion bins in wheat was identified. The remaining 11% of wheat ESTs showed no sequence homology in rice and mapped to the terminal 5% of the wheat chromosome 4BL. In this region, 27% of ESTs were duplicated, and it accounted for 70% of the recombination in the 4BL arm. Globally in wheat, no sequence homology ESTs mapped to the terminal bins, and ESTs rarely mapped to interstitial chromosomal regions known to be recombination hot spots. The wheat-rice comparative genomics analysis indicated that gene evolution occurs preferentially at the ends of chromosomes, driven by duplication and divergence associated with high rates of recombination.

Diversity in nucleotide binding site-leucine-rich repeat genes in cereals.

The diversity of the largest group of plant disease resistance genes, the nucleotide binding site-leucine-rich repeat (NBS-LRR) genes, was examined in cereals following polymerase chain reaction (PCR) cloning and database mining. NBS-LRR genes in rice are a large and diverse class with more than 600 genes, at least three to four times the complement of Arabidopsis. Most occur in small families containing one or a few cross-hybridizing members. Unlike in Arabidopsis and other dicots, the class of NBS-LRR genes coding for a Toll and mammalian interleukin-1 receptor (TIR) domain were not amplified during the evolution of the cereals. Genes coding for TIR domains are present in the rice genome, but have diverged from the NBS-LRR genes. Most cereal genes are similar in structure to the members of the non-TIR class of dicots, although many do not code for a coiled-coil domain in their amino termini. One unique class of cereal genes, with ~50 members, codes for proteins similar to the N-termini and NBS domains of resistance genes but does not code for LRR domains. The resistance gene repertoire of grasses has changed from that of dicots in their independent evolution since the two groups diverged. It is not clear whether this reflects a difference in downstream defense signaling pathways.

Solid-Phase Synthesis of Phenylacetylene Oligomers Utilizing a Novel 3-Propyl-3-(benzyl-supported) Triazene Linkage.

Sequence-specific phenylacetylene oligomers consisting of functionalized monomers (hexyl benzoate, hexyl phenyl ether, benzonitrile, and tert-butylphenyl) are synthesized in gram quantities using solid-phase methods. Growing oligomers are attached to a divinylbenzene cross-linked polystyrene support by the 1-aryl-3-propyl-3-(benzyl-supported) triazene moiety. This linkage is obtained by reaction of arenediazonium tetrafluoroborate salts with a n-propylamino-modified Merrifield resin. Condensation strategies are described, producing oligomers with higher yields and simplified procedures compared to solution-phase methods. Terminal acetylene is protected with a trimethylsilyl group. After deprotection of the resin-bound terminal acetylene, an aryl iodide monomer or an aryl iodide-terminated oligomer is coupled to the supported oligomer using a palladium(0) catalyst. The cycle can be repeated to produce sequence-specific oligomers of varying length and functionality. The resulting oligomers are liberated from the polymer support by cleavage of the 1-aryl-3-propyl-3-(benzyl-supported) triazene group by reaction with iodomethane producing an aryl iodide.