Uniform Coverage of High-loading Sulfur on Cross-linked Carbon Nanofiber for High Reaction Kinetics in the Li-S Batteries with Low Electrolyte/Sulfur Ratio

The aggregation of high loading sulfur on host materials at low carbon/sulfur (C/S) ratio results in the limited S↔Li2S reaction kinetics and shuttle effect of polysulfide, which is the bottleneck...

SHERRY2: A method for rapid and sensitive single cell RNA-seq

Many single cell RNA-seq applications aim to probe a wide dynamic range of gene expression, but most of them are still challenging to accurately quantify low-aboundance transcripts. Based on our previous finding that Tn5 transposase can directly cut-and-tag DNA/RNA hetero-duplexes, we present SHERRY2, an optimized protocol for sequencing transcriptomes of single cells or single nuclei. SHERRY2 is robust and scalable, and it has higher sensitivity and more uniform coverage in comparison with prevalent scRNA-seq methods. With throughput of a few thousand cells per batch, SHERRY2 can reveal the subtle transcriptomic differences between cells and facilitate important biological discoveries.

Evaluation of sequencing strategies for whole-genome imputation with hybrid peeling

BackgroundFor assembling large whole-genome sequence datasets to be used routinely in research and breeding, the sequencing strategy should be adapted to the methods that will later be used for variant discovery and imputation. In this study we used simulation to explore the impact that the sequencing strategy and level of sequencing investment have on the overall accuracy of imputation using hybrid peeling, a pedigree-based imputation method well-suited for large livestock populations.MethodsWe simulated marker array and whole-genome sequence data for fifteen populations with simulated or real pedigrees that had different structures. In these populations we evaluated the effect on imputation accuracy of seven methods for selecting which individuals to sequence, the generation of the pedigree to which the sequenced individuals belonged, the use of variable or uniform coverage, and the trade-off between the number of sequenced individuals and their sequencing coverage. For each population we considered four levels of investment in sequencing that were proportional to the size of the population.ResultsImputation accuracy largely depended on pedigree depth. The distribution of the sequenced individuals across the generations of the pedigree underlay the performance of the different methods used to select individuals to sequence. Additionally, it was critical to balance high imputation accuracy in early generations as well as in late generations. Imputation accuracy was highest with a uniform coverage across the sequenced individuals of around 2x rather than variable coverage. An investment equivalent to the cost of sequencing 2% of the population at 2x provided high imputation accuracy. The gain in imputation accuracy from additional investment diminished with larger populations and larger levels of investment. However, to achieve the same imputation accuracy, a proportionally greater investment must be used in the smaller populations compared to the larger ones.ConclusionsSuitable sequencing strategies for subsequent imputation with hybrid peeling involve sequencing around 2% of the population at a uniform coverage around 2x, distributed preferably from the third generation of the pedigree onwards. Such sequencing strategies are beneficial for generating whole-genome sequence data in populations with deep pedigrees of closely related individuals.

Identification of significant chromatin contacts from HiChIP data by FitHiChIP

HiChIP/PLAC-seq is increasingly becoming popular for profiling 3D chromatin contacts among regulatory elements and for annotating functions of genetic variants. Here we describe FitHiChIP, a computational method for loop calling from HiChIP/PLAC-seq data, which jointly models the non-uniform coverage and genomic distance scaling of contact counts to compute statistical significance estimates. We also develop a technique to filter putative bystander loops that can be explained by stronger adjacent loops. Compared to existing methods, FitHiChIP performs better in recovering contacts reported by Hi-C, promoter capture Hi-C and ChIA-PET experiments and in capturing previously validated promoter-enhancer interactions. FitHiChIP loop calls are reproducible among replicates and are consistent across different experimental settings. Our work also provides a framework for differential HiChIP analysis with an option to utilize ChIP-seq data for further characterizing differential loops. Even though designed for HiChIP, FitHiChIP is also applicable to other conformation capture assays.

gapsplit: Efficient random sampling for non-convex constraint-based models

SummaryGapsplit generates random samples from convex and non-convex constraint-based models. Gapsplit targets under-sampled regions of the solution space for uniform coverage.Availability and ImplementationPython and Matlab source code are freely available at http://jensenlab.net/[email protected]

Polishing path generation for physical uniform coverage of the aspheric surface based on the Archimedes spiral in bonnet polishing

As a new polishing method, bonnet polishing is suitable for polishing the curved surface due to its advantages in flexibility and adaptability of the polishing tool. In the polishing process, the contact state between the bonnet and the curved surface always changes. The traditional polishing tool path with equal interval will inevitably lead to over-polished areas and unpolished areas. In this article, a new tool path for bonnet polishing, which is called the revised Archimedes spiral polishing path, is proposed to ensure the physical uniform coverage of the curved surface in bonnet polishing. The path generation method is based on the modified tool–workpiece contact model and the pointwise searching algorithm. To prove the effectiveness of the revised path, two aspheric workpieces were polished along the traditional Archimedes spiral polishing path and the revised path, respectively. The roughnesses of the two workpieces are 10.94 and 10 nm, and the profile tolerances are 0.4097 and 0.2037 μm, respectively. The experimental results show that the revised path achieves lower roughness and surface tolerance than the traditional Archimedes path, which indicates that the revised path can achieve uniform physical coverage on the surface.

FitHiChIP: Identification of significant chromatin contacts from HiChIP data

Here we describe FitHiChIP (github.com/ay-lab/FitHiChIP), a computational method for identifying chromatin contacts among regulatory regions such as en-hancers and promoters from HiChIP/PLAC-seq data. FitHiChIP jointly models the non-uniform coverage and genomic distance scaling of HiChIP data, captures previously validated enhancer interactions for several genes including MYC and TP53, and recovers contacts genome-wide that are supported by ChIA-PET, pro-moter capture Hi-C and Hi-C data. FitHiChIP also provides a framework for differential contact analysis as showcased in a comparison of HiChIP data we have generated for two distinct immune cell types.