An actin-related protein that is most highly expressed in Drosophila testes is critical for embryonic development.

Most actin-related proteins (Arps) are highly conserved and carry out well-defined cellular functions in eukaryotes. However, many lineages like Drosophila and mammals encode divergent non-canonical Arps whose roles remain unknown. To elucidate the function of non-canonical Arps, we focus on Arp53D, which is highly expressed in testes and retained throughout Drosophila evolution. We show that Arp53D localizes to fusomes and actin cones, two germline-specific actin structures critical for sperm maturation, via a unique N-terminal tail. Surprisingly, we find that male fertility is not impaired upon Arp53D loss, yet population cage experiments reveal that Arp53D is required for optimal fitness in Drosophila melanogaster. To reconcile these findings, we focus on Arp53D function in ovaries and embryos where it is only weakly expressed. We find that under heat stress Arp53D-knockout (KO) females lay embryos with reduced nuclear integrity and lower viability; these defects are further exacerbated in Arp53D-KO embryos. Thus, despite its relatively recent evolution and primarily testis-specific expression, non-canonical Arp53D is required for optimal embryonic development in Drosophila.

A Burst of Genetic Innovation in Drosophila Actin-Related Proteins for Testis-Specific Function.

Many cytoskeletal proteins perform fundamental biological processes and are evolutionarily ancient. For example, the superfamily of actin-related proteins (Arps) specialized early in eukaryotic evolution for diverse cellular roles in the cytoplasm and the nucleus. Despite its strict conservation across eukaryotes, we find that the Arp superfamily has undergone dramatic lineage-specific diversification in Drosophila. Our phylogenomic analyses reveal four independent Arp gene duplications that occurred in the common ancestor of the obscura group of Drosophila and have been mostly preserved in this lineage. All four obscura-specific Arp paralogs are predominantly expressed in the male germline and have evolved under positive selection. We focus our analyses on the divergent Arp2D paralog, which arose via a retroduplication event from Arp2, a component of the Arp2/3 complex that polymerizes branched actin networks. Computational modeling analyses suggest that Arp2D can replace Arp2 in the Arp2/3 complex and bind actin monomers. Together with the signature of positive selection, our findings suggest that Arp2D may augment Arp2's functions in the male germline. Indeed, we find that Arp2D is expressed during and following male meiosis, where it localizes to distinct locations such as actin cones-specialized cytoskeletal structures that separate bundled spermatids into individual mature sperm. We hypothesize that this unprecedented burst of genetic innovation in cytoskeletal proteins may have been driven by the evolution of sperm heteromorphism in the obscura group of Drosophila.

Theoretical performance assessment and empirical analysis of super-resolution under unknown affine sensor motion.

This paper deals with super-resolution (SR) processing and associated theoretical performance assessment for under-sampled video data collected from a moving imaging platform with unknown motion and assuming a relatively flat scene. This general scenario requires joint estimation of the high-resolution image and the parameters that determine a projective transform that relates the collected frames to one another. A quantitative assessment of the variance in the random error as achieved through a joint-estimation approach (e.g., SR image reconstruction and motion estimation) is carried out via the general framework of M-estimators and asymptotic statistics. This approach provides a performance measure on estimating the fine-resolution scene when there is a lack of perspective information and represents a significant advancement over previous work that considered only the more specific scenario of mis-registration. A succinct overview of the theoretical framework is presented along with some specific results on the approximate random error for the case of unknown translation and affine motions. A comparison is given between the approximated random error and that actually achieved by an M-estimator approach to the joint-estimation problem. These results provide insight on the reduction in SR reconstruction accuracy when jointly estimating unknown inter-frame affine motion.

Joint estimation of Stokes images and aberrations from phase-diverse polarimetric measurements.

The technique of phase diversity has been used in traditional incoherent imaging systems to jointly estimate an object and optical system aberrations. This paper extends the technique of phase diversity to polarimetric imaging systems. Specifically, we describe penalized-likelihood methods for jointly estimating Stokes images and optical system aberrations from measurements that contain phase diversity. Jointly estimating Stokes images and optical system aberrations involves a large parameter space. A closed-form expression for the estimate of the Stokes images in terms of the aberration parameters is derived and used in a formulation that reduces the dimensionality of the search space to the number of aberration parameters only. We compare the performance of the joint estimator under both quadratic and edge-preserving regularization; we also compare the performance of the reduced parameter search strategy to the full parameter search strategy under quadratic regularization. The joint estimator with edge-preserving regularization yields higher fidelity polarization estimates than with quadratic regularization. With the reduced parameter search strategy, accurate aberration estimates can be obtained without recourse to regularization "tuning."

Joint reconstruction of Stokes images from polarimetric measurements.

In the field of imaging polarimetry Stokes parameters are sought and must be inferred from noisy and blurred intensity measurements. Using a penalized-likelihood estimation framework we investigate reconstruction quality when estimating intensity images and then transforming to Stokes parameters, and when estimating Stokes parameters directly. We define our cost function for reconstruction by a weighted least-squares data fit term and a regularization penalty. We show that for quadratic regularization the estimators of Stokes and intensity images can be made equal by appropriate choice of regularization parameters. It is empirically shown that, when using edge preserving regularization, estimating the Stokes parameters directly leads to lower RMS error. Also, the addition of a cross channel regularization term further lowers the RMS error for both methods, especially in the case of low SNR.