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Dubin, M.

Publications and source records attributed to Dubin, M..

2 recordsLinked to original sources

Modifiers of genetic dominance at the Arabidopsis self-incompatibility locus retain proto-miRNA features and act through non-canonical gene silencing pathways

Self-incompatibility in flowering plants is a common mechanism that prevents self-fertilization and promotes outcrossing. In Brassicaceae, the self-incompatibility locus is highly diverse, with many alleles arranged in a complex dominance hierarchy and exhibiting monoallelic expression in heterozygote individuals. Monoallelic expression of the pollen self-incompatibility gene is achieved through the action of sRNA precursors that resemble miRNAs, although the underlying molecular mechanisms remain elusive. Here, we engineered Arabidopsis thaliana lines expressing components of the Arabidopsis halleri self-incompatibility system, and used a reverse genetics approach to pinpoint the pathways underlying the function of these sRNA precursors. We showed that they trigger a robust decrease in transcript abundance of the recessive self-incompatibility genes, but not through the canonical transcriptional or post-transcriptional gene silencing pathways. Furthermore, we observed that single sRNA precursors are typically processed into hundreds of sRNA molecules with a variety of sizes, abundance levels and ARGONAUTE loading preferences. Our results suggest that these seemingly arbitrary processing characteristics are essential for establishing the self-incompatibility dominance hierarchy, as they enable a single sRNA precursor from a dominant allele to effectively repress multiple recessive alleles, thus providing a unique example of how small RNAs mediate gene silencing within a highly complex regulatory network. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/591913v3_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@b32c02org.highwire.dtl.DTLVardef@10e65d3org.highwire.dtl.DTLVardef@3f14b3org.highwire.dtl.DTLVardef@1682d57_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

Distinctions among real and apparent respiratory motions in human fMRI data

Head motion estimates in functional magnetic resonance imaging (fMRI) scans appear qualitatively different with sub-second image sampling rates compared to the multi-second sampling rates common in the past. Whereas formerly the head appeared still for much of a scan with brief excursions from baseline, the head now appears to be in constant motion, and motion estimates often seem to divulge little information about what is happening in a scan. This constant motion has been attributed to respiratory oscillations that do not alias at faster sampling rates, and investigators are divided on the extent to which such motion is \"real\" motion or only \"apparent\" pseudomotion. Some investigators have abandoned the use of motion estimates entirely due to these considerations. Here we investigate the properties of motion in several fMRI datasets sampled at rates between 720-1160 ms, and describe 5 distinct kinds of respiratory motion: 1) constant real respiratory motion in the form of head nodding most evident in vertical position and pitch, which can be very large; 2) constant pseudomotion at the same respiratory rate as real motion, occurring only in the phase encode direction; 3) punctate real motions occurring at times of very deep breaths; 4) a low-frequency pseudomotion in only the phase encode direction following very deep breaths; 5) slow modulation of vertical and anterior-posterior head position by the respiratory envelope. We reformulate motion estimates in light of these considerations and obtain good concordance between motion estimates, physiologic records, image quality measures, and events evident in the fMRI signals.\n\nHighlights- Examines several fast-TR datasets with sampling rates of 720-1160 ms\n- Identifies 7 kinds of motion in fMRI scans, 5 of them related to respiration\n- Identifies 2 forms of pseudomotion occurring only in phase encode direction\n- Pseudomotion is a function of soft tissue mass, not lung volume\n- Reformulates motion estimates to draw out particular kinds of motion

neuroscience↗