Aging Predisposes Oocytes to Meiotic Nondisjunction When the Cohesin Subunit SMC1 Is Reduced

In humans, meiotic chromosome segregation errors increase dramatically as women age, but the molecular defects responsible are largely unknown. Cohesion along the arms of meiotic sister chromatids provides an evolutionarily conserved mechanism to keep recombinant chromosomes associated until anaphase I. One attractive hypothesis to explain age-dependent nondisjunction (NDJ) is that loss of cohesion over time causes recombinant homologues to dissociate prematurely and segregate randomly during the first meiotic division. Using Drosophila as a model system, we have tested this hypothesis and observe a significant increase in meiosis I NDJ in experimentally aged Drosophila oocytes when the cohesin protein SMC1 is reduced. Our finding that missegregation of recombinant homologues increases with age supports the model that chiasmata are destabilized by gradual loss of cohesion over time. Moreover, the stage at which Drosophila oocytes are most vulnerable to age-related defects is analogous to that at which human oocytes remain arrested for decades. Our data provide the first demonstration in any organism that, when meiotic cohesion begins intact, the aging process can weaken it sufficiently and cause missegregation of recombinant chromosomes. One major advantage of these studies is that we have reduced but not eliminated the SMC1 subunit. Therefore, we have been able to investigate how aging affects normal meiotic cohesion. Our findings that recombinant chromosomes are at highest risk for loss of chiasmata during diplotene argue that human oocytes are most vulnerable to age-induced loss of meiotic cohesion at the stage at which they remain arrested for several years

Systematic Evaluation of Factors Influencing ChIP-Seq Fidelity

We performed a systematic evaluation of how variations in sequencing depth and other parameters influence interpretation of Chromatin immunoprecipitation (ChIP) followed by sequencing (ChIP-seq) experiments. Using Drosophila S2 cells, we generated ChIP-seq datasets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin state bias, open chromatin regions yielded higher coverage, which led to false positives if not corrected and had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP library complexity at high coverage. The removal of reads originating at the same base reduced false-positives while having little effect on detection sensitivity. Even at a depth of ~1 read/bp coverage of mappable genome, ~1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely-used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle datasets with deep coverage

Lawson criterion for ignition exceeded in an inertial fusion experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion

Lateral and End-On Kinetochore Attachments Are Coordinated to Achieve Bi-orientation in Drosophila Oocytes

In oocytes, where centrosomes are absent, the chromosomes direct the assembly of a bipolar spindle. Interactions between chromosomes and microtubules are essential for both spindle formation and chromosome segregation, but the nature and function of these interactions is not clear. We have examined oocytes lacking two kinetochore proteins, NDC80 and SPC105R, and a centromere-associated motor protein, CENP-E, to characterize the impact of kinetochore-microtubule attachments on spindle assembly and chromosome segregation in Drosophila oocytes. We found that the initiation of spindle assembly results from chromosome-microtubule interactions that are kinetochore-independent. Stabilization of the spindle, however, depends on both central spindle and kinetochore components. This stabilization coincides with changes in kinetochore-microtubule attachments and bi-orientation of homologs. We propose that the bi-orientation process begins with the kinetochores moving laterally along central spindle microtubules towards their minus ends. This movement depends on SPC105R, can occur in the absence of NDC80, and is antagonized by plus-end directed forces from the CENP-E motor. End-on kinetochore-microtubule attachments that depend on NDC80 are required to stabilize bi-orientation of homologs. A surprising finding was that SPC105R but not NDC80 is required for co-orientation of sister centromeres at meiosis I. Together, these results demonstrate that, in oocytes, kinetochore-dependent and -independent chromosome-microtubule attachments work together to promote the accurate segregation of chromosomes

Quantifying protection level of a noise candidate for noise multiplication masking scheme

When multiplicative noises are used to perturb a set of original data, the data provider needs to ensure that the original values are not likely to be learned by data intruders from the noise-multiplied data. Different attacking strategies for unveiling the original values have been recognised in the literature, and the data provider needs to ensure that the noise-multiplied data is protected against these attacking strategies by selecting an appropriate noise generating variable. However, there are many potential attacking strategies, which makes the quantification of the protection level of a noise candidate difficult. In this paper, we argue that, to quantify the protection level a noise candidate offers to the original data against an attacking strategy, the data provider might look at the average value disclosure risk it produces. Correspondingly, we propose an optimal estimator which maximizes the average value disclosure risk. As a result, the data provider could use the maximized average value disclosure risk as a single measure for quantifying the protection level a noise candidate offers to the original data. The measure could help the data provider with the process of noise generating variable selection in practice

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

When multiplicative noises are used to perturb a set of original data, the data provider needs to ensure that the original values are not likely to be learned by data intruders from the noise-multiplied data. Different attacking strategies for unveiling the original values have been recognised in the literature, and the data provider needs to ensure that the noise-multiplied data is protected against these attacking strategies by selecting an appropriate noise generating variable. However, there are many potential attacking strategies, which makes the quantification of the protection level of a noise candidate difficult. In this paper, we argue that, to quantify the protection level a noise candidate offers to the original data against an attacking strategy, the data provider might look at the average value disclosure risk it produces. Correspondingly, we propose an optimal estimator which maximizes the average value disclosure risk. As a result, the data provider could use the maximized average value disclosure risk as a single measure for quantifying the protection level a noise candidate offers to the original data. The measure could help the data provider with the process of noise generating variable selection in practice