Person: Lu, Jenny
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Publication Mapping DNA polymerase errors by single-molecule sequencing
(Oxford University Press, 2016) Lee, David; Lu, Jenny; Chang, Seungwoo; Loparo, Joseph; Xie, XiaoliangGenomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replication product is tagged with a unique nucleotide sequence before amplification. This allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.
Publication Transforming a head direction signal into a goal-oriented steering command
(Springer Science and Business Media LLC, 2024-02-07) Westeinde, Elena; Kellogg, Emily; Dawson, Paul; Lu, Jenny; Hamburg, Lydia; Midler, Benjamin; Druckmann, Shaul; Wilson, Rachel I.AbstractTo navigate, we must continuously estimate the direction we are headed in, and we must use this information to guide our path toward our goal1. Direction estimation is accomplished by ring attractor networks in the head direction system2,3. However, we do not understand how the sense of direction is used to guide action. Drosophilaconnectome analyses4,5 recently revealed two cell types (PFL2 and PFL3) that connect the head direction system to the locomotor system. Here we show how both cell types combine an allocentric head direction signal with an internal goal signal to produce an egocentric motor drive. We recorded their activity as flies navigated in a virtual reality environment toward a goal stored in memory. Strikingly, PFL2 and PFL3 populations are both modulated by deviation from the goal direction, but with opposite signs. The amplitude of PFL2 activity is highest when the fly is oriented away from its goal; activating these cells destabilizes the current orientation and drives turning. By contrast, total PFL3 activity is highest around the goal; these cells generate directional turning to correct small deviations from the goal. Our data support a model where the goal is stored as a sinusoidal pattern whose phase represents direction, and whose amplitude represents salience. Variations in goal amplitude can explain transitions between goal-oriented navigation and exploration. Together, these results show how the sense of direction is used for feedback control of locomotion.
Publication Sensorimotor Experience Remaps Visual Input to a Heading-Direction Network
(Springer Science and Business Media LLC, 2019-11-20) Lu, Jenny; Fisher, Yvette; D’Alessandro, Isabel; Wilson, RachelWe can maintain some sense of direction in the dark by keeping track of our own movements, but when visual landmarks are available, our sense of direction is more accurate and stable. Moreover, we can learn new landmarks in new environments. What mechanisms reconcile self-movement information with ever-changing landmarks to generate a coherent sense of direction? Using whole-cell recordings and calcium imaging from Drosophila heading neurons, we show that each heading neuron is inhibited by visual cues in specific horizontal positions, with different visual maps in different individuals. Inhibition arises from presynaptic axons that form an all-to-all matrix of potential connections onto heading neurons. Visual input to the heading network can reorganize over minutes when visuo-motor correlations change, causing persistent changes in the brain’s heading map. Plasticity of sensory inputs, when combined with network attractor dynamics, should allow the brain’s spatial maps to incorporate sensory cues in new environments.