A Cryptic Modifier Causing Transient Self-Incompatibility in Arabidopsis thaliana

SummaryBreakdown of the pollination barrier of self-incompatibility (SI) in older flowers, a phenomenon known as pseudo-self-compatibility or transient SI, has been described as an advantageous reproductive assurance strategy that allows selfing after opportunities for out-crossing have been exhausted [1–9]. Pseudo-self-compatibility is quite prevalent as a mixed mating strategy in nature, but the underlying molecular mechanisms are not known. We had previously shown that Arabidopsis thaliana exhibits cryptic natural variation for pseudo-self-compatibility, which is uncovered by transformation of different accessions with SI specificity-determining SRK and SCR genes from its self-incompatible sister species A. lyrata [10, 11]. Here, by using this transgenic A. thaliana model, we show that pseudo-self-compatibility is caused by a hypomorphic allele of PUB8, an S-locus-linked gene encoding a previously uncharacterized ARM repeat- and U box-containing protein that regulates SRK transcript levels. This is the first gene underlying pseudo-self-compatibility to be identified and the first report in which cryptic natural variation unveiled by a transgene enabled the cloning of a gene for a complex trait

Utility of EST-Derived SSRs as Population Genetics Markers in a Beetle

Microsatellite, or simple sequence repeat (SSR), loci can be identified by mining expressed sequence tag (EST) databases, and where these are available, marker development time and expense can be decreased considerably over conventional strategies of probing the entire genome. However, it is unclear whether they provide information on population structure similar to that generated by anonymous genomic SSRs. We performed comparative population genetic analyses between EST-derived SSRs (EST-SSRs) and anonymous SSRs developed from genomic DNA for the same set of populations of the insect Diabrotica virgifera, a beetle in the family Chrysomelidae. Compared with noncoding, nontranscribed regions, EST-SSRs were generally less polymorphic but had reduced occurrence of null alleles and greater cross-species amplification. Neutrality tests suggested the loci were not under positive selection. Across all populations and all loci, the genomic and EST-SSRs performed similarly in estimating genetic diversity, FIS, FST, population assignment and exclusion tests, and detection of distinct populations. These findings, therefore, indicate that the EST-SSRs examined can be used with confidence in future genetic studies of Diabrotica populations and suggest that EST libraries can be added as a valuable source of markers for population genetics studies in insects and other animals

The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns

The Fire and Smoke Model Evaluation Experiment (FASMEE) is designed to collect integrated observations from large wildland fires and provide evaluation datasets for new models and operational systems. Wildland fire, smoke dispersion, and atmospheric chemistry models have become more sophisticated, and next-generation operational models will require evaluation datasets that are coordinated and comprehensive for their evaluation and advancement. Integrated measurements are required, including ground-based observations of fuels and fire behavior, estimates of fire-emitted heat and emissions fluxes, and observations of near-source micrometeorology, plume properties, smoke dispersion, and atmospheric chemistry. To address these requirements the FASMEE campaign design includes a study plan to guide the suite of required measurements in forested sites representative of many prescribed burning programs in the southeastern United States and increasingly common high-intensity fires in the western United States. Here we provide an overview of the proposed experiment and recommendations for key measurements. The FASMEE study provides a template for additional large-scale experimental campaigns to advance fire science and operational fire and smoke models

A functional variant in the serotonin receptor 7 gene (HTR7), rs7905446, is associated with good response to SSRIs in bipolar and unipolar depression.

Predicting antidepressant response has been a clinical challenge for mood disorder. Although several genome-wide association studies have suggested a number of genetic variants to be associated with antidepressant response, the sample sizes are small and the results are difficult to replicate. Previous animal studies have shown that knockout of the serotonin receptor 7 gene (HTR7) resulted in an antidepressant-like phenotype, suggesting it was important to antidepressant action. In this report, in the first stage, we used a cost-effective pooled-sequencing strategy to sequence the entire HTR7 gene and its regulatory regions to investigate the association of common variants in HTR7 and clinical response to four selective serotonin reuptake inhibitors (SSRIs: citalopram, paroxetine, fluoxetine and sertraline) in a retrospective cohort mainly consisting of subjects with bipolar disorder (n = 359). We found 80 single-nucleotide polymorphisms (SNPs) with false discovery rate < 0.05 associated with response to paroxetine. Among the significant SNPs, rs7905446 (T/G), which is located at the promoter region, also showed nominal significance (P < 0.05) in fluoxetine group. GG/TG genotypes for rs7905446 and female gender were associated with better response to two SSRIs (paroxetine and fluoxetine). In the second stage, we replicated this association in two independent prospective samples of SSRI-treated patients with major depressive disorder: the MARS (n = 253, P = 0.0169) and GENDEP studies (n = 432, P = 0.008). The GG/TG genotypes were consistently associated with response in all three samples. Functional study of rs7905446 showed greater activity of the G allele in regulating expression of HTR7. The G allele displayed higher luciferase activity in two neuronal-related cell lines, and estrogen treatment decreased the activity of only the G allele. Electrophoretic mobility shift assay suggested that the G allele interacted with CCAAT/enhancer-binding protein beta transcription factor (TF), while the T allele did not show any interaction with any TFs. Our results provided novel pharmacogenomic evidence to support the role of HTR7 in association with antidepressant response

Mutations in the Na+/K+-ATPase α3 Gene ATP1A3 Are Associated with Rapid-Onset Dystonia Parkinsonism

AbstractRapid-onset dystonia-parkinsonism (RDP, DYT12) is a distinctive autosomal-dominant movement disorder with variable expressivity and reduced penetrance characterized by abrupt onset of dystonia, usually accompanied by signs of parkinsonism. The sudden onset of symptoms over hours to a few weeks, often associated with physical or emotional stress, suggests a trigger initiating a nervous system insult resulting in permanent neurologic disability. We report the finding of six missense mutations in the gene for the Na+/K+-ATPase α3 subunit (ATP1A3) in seven unrelated families with RDP. Functional studies and structural analysis of the protein suggest that these mutations impair enzyme activity or stability. This finding implicates the Na+/K+ pump, a crucial protein responsible for the electrochemical gradient across the cell membrane, in dystonia and parkinsonism

Soil zinc content, groundwater usage, and prostate cancer incidence in South Carolina

Background Prostate cancer (PrCA) incidence in South Carolina (SC) exceeds the national average, particularly among African Americans (AAs). Though data are limited, low environmental zinc exposures and down-regulation of prostatic zinc transporter proteins among AAs may explain, in part, the racial PrCA disparity. Methods Age-adjusted PrCA rates were calculated by census tract. Demographic data were obtained from the 1990 census. Hazardous waste site locations and soil zinc concentrations were obtained from existing federal and state databases. A geographic information system and Poisson regression were used to test the hypothesis that census tracts with reduced soil zinc concentrations, elevated groundwater use, or more agricultural or hazardous waste sites had elevated PrCA risks. Results Census tracts with high groundwater use and low zinc concentrations had higher PrCA rate ratios (RR: 1.270; 95% confidence interval: 1.079, 1.505). This effect was not more apparent in areas populated primarily by AAs. Conclusion Increased PrCA rates were associated with reduced soil zinc concentrations and elevated groundwater use, although this observation is not likely to contribute to SC’s racial PrCA disparity. Statewide mapping and statistical modeling of relationships between environmental factors, demographics, and cancer incidence can be used to screen hypotheses focusing on novel PrCA risk factors

Failure of Fibrotic Liver Regeneration in Mice Is Linked to a Severe Fibrogenic Response Driven by Hepatic Progenitor Cell Activation

Failure of fibrotic liver to regenerate after resection limits therapeutic options and increases demand for liver transplantation, representing a significant clinical problem. The mechanism underlying regenerative failure in fibrosis is poorly understood. Seventy percent partial hepatectomy (PHx) was performed in C57Bl/6 mice with or without carbon tetrachloride (CCl4)-induced liver fibrosis. Liver function and regeneration was monitored at 1 to 14 days thereafter by assessing liver mass, alanine aminotransferase (ALT), mRNA expression, and histology. Progenitor (oval) cell mitogen tumor necrosis factor-like weak inducer of apoptosis (TWEAK) and TWEAK-neutralizing antibody were used to manipulate progenitor cell proliferation in vivo. In fibrotic liver, hepatocytes failed to replicate efficiently after PHx. Fibrotic livers showed late (day 5) peak of serum ALT (3542 ± 355 IU/L compared to 93 ± 65 IU/L in nonfibrotic livers), which coincided with progenitor cell expansion, increase in profibrogenic gene expression and de novo collagen deposition. In fibrotic mice, inhibition of progenitor activation using TWEAK-neutralizing antibody after PHx resulted in strongly down-regulated profibrogenic mRNA, reduced serum ALT levels and improved regeneration. Failure of hepatocyte-mediated regeneration in fibrotic liver triggers activation of the progenitor (oval) cell compartment and a severe fibrogenic response. Inhibition of progenitor cell proliferation using anti-TWEAK antibody prevents fibrogenic response and augments fibrotic liver regeneration. Targeting the fibrogenic progenitor response represents a promising strategy to improve hepatectomy outcomes in patients with liver fibrosis

Dependence receptor UNC5A restricts luminal to basal breast cancer plasticity and metastasis

BACKGROUND: The majority of estrogen receptor-positive (ERα+) breast cancers respond to endocrine therapies. However, resistance to endocrine therapies is common in 30% of cases, which may be due to altered ERα signaling and/or enhanced plasticity of cancer cells leading to breast cancer subtype conversion. The mechanisms leading to enhanced plasticity of ERα-positive cancer cells are unknown. METHODS: We used short hairpin (sh)RNA and/or the CRISPR/Cas9 system to knockdown the expression of the dependence receptor UNC5A in ERα+ MCF7 and T-47D cell lines. RNA-seq, quantitative reverse transcription polymerase chain reaction, chromatin immunoprecipitation, and Western blotting were used to measure the effect of UNC5A knockdown on basal and estradiol (E2)-regulated gene expression. Mammosphere assay, flow cytometry, and immunofluorescence were used to determine the role of UNC5A in restricting plasticity. Xenograft models were used to measure the effect of UNC5A knockdown on tumor growth and metastasis. Tissue microarray and immunohistochemistry were utilized to determine the prognostic value of UNC5A in breast cancer. Log-rank test, one-way, and two-way analysis of variance (ANOVA) were used for statistical analyses. RESULTS: Knockdown of the E2-inducible UNC5A resulted in altered basal gene expression affecting plasma membrane integrity and ERα signaling, as evident from ligand-independent activity of ERα, altered turnover of phosphorylated ERα, unique E2-dependent expression of genes effecting histone demethylase activity, enhanced upregulation of E2-inducible genes such as BCL2, and E2-independent tumorigenesis accompanied by multiorgan metastases. UNC5A depletion led to the appearance of a luminal/basal hybrid phenotype supported by elevated expression of basal/stem cell-enriched ∆Np63, CD44, CD49f, epidermal growth factor receptor (EGFR), and the lymphatic vessel permeability factor NTN4, but lower expression of luminal/alveolar differentiation-associated ELF5 while maintaining functional ERα. In addition, UNC5A-depleted cells acquired bipotent luminal progenitor characteristics based on KRT14+/KRT19+ and CD49f+/EpCAM+ phenotype. Consistent with in vitro results, UNC5A expression negatively correlated with EGFR expression in breast tumors, and lower expression of UNC5A, particularly in ERα+/PR+/HER2- tumors, was associated with poor outcome. CONCLUSION: These studies reveal an unexpected role of the axon guidance receptor UNC5A in fine-tuning ERα and EGFR signaling and the luminal progenitor status of hormone-sensitive breast cancers. Furthermore, UNC5A knockdown cells provide an ideal model system to investigate metastasis of ERα+ breast cancers

DEEPMIR: A DEEP neural network for differential detection of cerebral Microbleeds and IRon deposits in MRI

Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and neurodegenerative disorders. Particularly, CMBs are small lesions and require multiple neuroimaging modalities for accurate detection. Quantitative susceptibility mapping (QSM) derived from in vivo magnetic resonance imaging (MRI) is necessary to differentiate between iron content and mineralization. We set out to develop a deep learning-based segmentation method suitable for segmenting both CMBs and iron deposits. We included a convenience sample of 24 participants from the MESA cohort and used T2-weighted images, susceptibility weighted imaging (SWI), and QSM to segment the two types of lesions. We developed a protocol for simultaneous manual annotation of CMBs and non-hemorrhage iron deposits in the basal ganglia. This manual annotation was then used to train a deep convolution neural network (CNN). Specifically, we adapted the U-Net model with a higher number of resolution layers to be able to detect small lesions such as CMBs from standard resolution MRI. We tested different combinations of the three modalities to determine the most informative data sources for the detection tasks. In the detection of CMBs using single class and multiclass models, we achieved an average sensitivity and precision of between 0.84-0.88 and 0.40-0.59, respectively. The same framework detected non-hemorrhage iron deposits with an average sensitivity and precision of about 0.75-0.81 and 0.62-0.75, respectively. Our results showed that deep learning could automate the detection of small vessel disease lesions and including multimodal MR data (particularly QSM) can improve the detection of CMB and non-hemorrhage iron deposits with sensitivity and precision that is compatible with use in large-scale research studies