Quantum-enhanced greedy combinatorial optimization solver.

Combinatorial optimization is a broadly attractive area for potential quantum advantage, but no quantum algorithm has yet made the leap. Noise in quantum hardware remains a challenge, and more sophisticated quantum-classical algorithms are required to bolster their performance. Here, we introduce an iterative quantum heuristic optimization algorithm to solve combinatorial optimization problems. The quantum algorithm reduces to a classical greedy algorithm in the presence of strong noise. We implement the quantum algorithm on a programmable superconducting quantum system using up to 72 qubits for solving paradigmatic Sherrington-Kirkpatrick Ising spin glass problems. We find the quantum algorithm systematically outperforms its classical greedy counterpart, signaling a quantum enhancement. Moreover, we observe an absolute performance comparable with a state-of-the-art semidefinite programming method. Classical simulations of the algorithm illustrate that a key challenge to reaching quantum advantage remains improving the quantum device characteristics.

Exon-independent recruitment of SRSF1 is mediated by U1 snRNP stem-loop 3.

SRSF1 protein and U1 snRNPs are closely connected splicing factors. They both stimulate exon inclusion, SRSF1 by binding to exonic splicing enhancer sequences (ESEs) and U1 snRNPs by binding to the downstream 5' splice site (SS), and both factors affect 5' SS selection. The binding of U1 snRNPs initiates spliceosome assembly, but SR proteins such as SRSF1 can in some cases substitute for it. The mechanistic basis of this relationship is poorly understood. We show here by single-molecule methods that a single molecule of SRSF1 can be recruited by a U1 snRNP. This reaction is independent of exon sequences and separate from the U1-independent process of binding to an ESE. Structural analysis and cross-linking data show that SRSF1 contacts U1 snRNA stem-loop 3, which is required for splicing. We suggest that the recruitment of SRSF1 to a U1 snRNP at a 5'SS is the basis for exon definition by U1 snRNP and might be one of the principal functions of U1 snRNPs in the core reactions of splicing in mammals.

The transition in spliceosome assembly from complex E to complex A purges surplus U1 snRNPs from alternative splice sites.

Spliceosomes are assembled in stages. The first stage forms complex E, which is characterized by the presence of U1 snRNPs base-paired to the 5' splice site, components recognizing the 3' splice site and proteins thought to connect them. The splice sites are held in close proximity and the pre-mRNA is committed to splicing. Despite this, the sites for splicing appear not to be fixed until the next complex (A) forms. We have investigated the reasons why 5' splice sites are not fixed in complex E, using single molecule methods to determine the stoichiometry of U1 snRNPs bound to pre-mRNA with one or two strong 5' splice sites. In complex E most transcripts with two alternative 5' splice sites were bound by two U1 snRNPs. However, the surplus U1 snRNPs were displaced during complex A formation in an ATP-dependent process requiring an intact 3' splice site. This process leaves only one U1 snRNP per complex A, regardless of the number of potential sites. We propose a mechanism for selection of the 5' splice site. Our results show that constitutive splicing components need not be present in a fixed stoichiometry in a splicing complex.

Tomographic quantification of branching morphogenesis and renal development.

Branching morphogenesis is a central process in renal development, but imaging and quantifying this process beyond early organogenesis presents challenges due to growth of the kidney preventing ready imaging of the complex structures. Current analysis of renal development relies heavily on explant organ culture and visualization by confocal microscopy, as a more developmentally advanced native tissue is too thick for conventional microscopic imaging. Cultured renal primordia lack vascularization and a supportive matrix for normal growth, resulting in tissue compression and distortion of ureteric branching. To overcome this, we used optical projection tomography to image and reconstruct the branching ureter epithelium of ex vivo embryonic kidneys and developed software to quantify these three-dimensional (3D) data. Ureteric branching was assessed by measuring tree and terminal branch length, tip number, branching iterations, branch angles, and inter-tip distances in 3D space. To validate this approach for analyzing genetic influences on renal development, we assessed branching and organ morphology in Tgfbeta2(+/-) embryos from E12.5 through E15.5. We found decreased branching, contrary to previous findings using organ culture, and quantified a primary defect in renal pelvic formation. Our approach offers many advantages from improved throughput, analysis, and observation of in vivo branching states, and has demonstrated its utility in studying the basis of renal developmental disease.