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Oogenesis is a complex process regulated by precise coordination of multiple factors, including maternal genes. Zygote arrest 1 (zar1) has been identified as an ovary-specific maternal gene that is vital for oocyte-to-embryo transition and oogenesis in mouse and zebrafish. However, its function in other species remains to be elucidated. In the present study, zar1 was identified with conserved C-terminal zinc finger domains in Nile tilapia. zar1 was highly expressed in the ovary and specifically expressed in phase I and II oocytes. Disruption of zar1 led to the failed transition from oogonia to phase I oocytes, with somatic cell apoptosis. Down-regulation and failed polyadenylation of figla, gdf9, bmp15 and wee2 mRNAs were observed in the ovaries of zar1􀀀 /􀀀 fish. Cpeb1, a gene essential for polyadenylation that interacts with Zar1, was down-regulated in zar1􀀀 /􀀀 fish. Moreover, decreased levels of serum estrogen and increased levels of androgen were observed in zar1􀀀 /􀀀 fish. Taken together, zar1 seems to be essential for tilapia oogenesis by regulating polyadenylation and estrogen synthesis. Our study shows that Zar1 has different molecular functions during gonadal development by the similar signaling pathway in different species. 

We consider a variant of the vehicle routing problem (VRP) where each customer has a unit demand and the goal is to minimize the total cost of routing a fleet of capacitated vehicles from one or multiple depots to visit all customers. We propose two parallel algorithms to efficiently solve the column-generation-based linear-programming relaxation for this VRP. Specifically, we focus on algorithms for the “pricing problem,” which corresponds to the resource-constrained elementary shortest path problem. The first algorithm extends the pulse algorithm for which we derive a new bounding scheme on the maximum load of any route. The second algorithm is based on random coloring from parameterized complexity which can be also combined with other techniques in the literature for improving VRPs, including cutting planes and column enumeration. We conduct numerical studies using VRP benchmarks (with 50–957 nodes) and instances of a medical home care delivery problem using census data in Wayne County, Michigan. Using parallel computing, both pulse and random coloring can significantly improve column generation for solving the linear programming relaxations and we can obtain heuristic integer solutions with small optimality gaps. Combining random coloring with column enumeration, we can obtain improved integer solutions having less than 2% optimality gaps for most VRP benchmark instances and less than 1% optimality gaps for the medical home care delivery instances, both under a 30-minute computational time limit. The use of cutting planes (e.g., robust cuts) can further reduce optimality gaps on some hard instances, without much increase in the run time. Summary of Contribution: The vehicle routing problem (VRP) is a fundamental combinatorial problem, and its variants have been studied extensively in the literature of operations research and computer science. In this paper, we consider general-purpose algorithms for solving VRPs, including the column-generation approach for the linear programming relaxations of the integer programs of VRPs and the column-enumeration approach for seeking improved integer solutions. We revise the pulse algorithm and also propose a random-coloring algorithm that can be used for solving the elementary shortest path problem that formulates the pricing problem in the column-generation approach. We show that the parallel implementation of both algorithms can significantly improve the performance of column generation and the random coloring algorithm can improve the solution time and quality of the VRP integer solutions produced by the column-enumeration approach. We focus on algorithmic design for VRPs and conduct extensive computational tests to demonstrate the performance of various approaches. 

Abstract Maternal-to-filial nutrition transfer is central to grain development and yield. nitrate transporter 1/peptide transporter (NRT1-PTR)-type transporters typically transport nitrate, peptides, and ions. Here, we report the identification of a maize (Zea mays) NRT1-PTR-type transporter that transports sucrose and glucose. The activity of this sugar transporter, named Sucrose and Glucose Carrier 1 (SUGCAR1), was systematically verified by tracer-labeled sugar uptake and serial electrophysiological studies including two-electrode voltage-clamp, non-invasive microelectrode ion flux estimation assays in Xenopus laevis oocytes and patch clamping in HEK293T cells. ZmSUGCAR1 is specifically expressed in the basal endosperm transfer layer and loss-of-function mutation of ZmSUGCAR1 caused significantly decreased sucrose and glucose contents and subsequent shrinkage of maize kernels. Notably, the ZmSUGCAR1 orthologs SbSUGCAR1 (from Sorghum bicolor) and TaSUGCAR1 (from Triticum aestivum) displayed similar sugar transport activities in oocytes, supporting the functional conservation of SUGCAR1 in closely related cereal species. Thus, the discovery of ZmSUGCAR1 uncovers a type of sugar transporter essential for grain development and opens potential avenues for genetic improvement of seed-filling and yield in maize and other grain crops.