Comparative Performance of the MGISEQ-2000 and Illumina X-Ten Sequencing Platforms for Paleogenomics

The MGISEQ-2000 sequencer is widely used in various omics studies, but the performance of this platform for paleogenomics has not been evaluated. We here compare the performance of MGISEQ-2000 with the Illumina X-Ten on ancient human DNA using four samples from 1750BCE to 60CE. We found there were only slight differences between the two platforms in most parameters (duplication rate, sequencing bias, θ, δS, and λ). MGISEQ-2000 performed well on endogenous rate and library complexity although X-Ten had a higher average base quality and lower error rate. Our results suggest that MGISEQ-2000 and X-Ten have comparable performance, and MGISEQ-2000 can be an alternative platform for paleogenomics sequencing.

DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction

Pacific BioScience (PacBio) circular consensus sequencing (CCS) generates long (10-25 kb), accurate "HiFi" reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation uses a hidden Markov model (pbccs). Here, we introduce DeepConsensus, which uses a unique alignment-based loss to train a gap-aware transformer-encoder (GATE) for sequence correction. Compared to pbccs, DeepConsensus reduces read errors in the same dataset by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27%, and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity (NG50 4.9Mb to 17.2Mb), increase gene completeness (94% to 97%), reduce false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45), and also reduce variant calling errors by 24%.

Domain-based Comparative Analysis of Bacterial Proteomes: Uniqueness, Interactions, and the Dark Matter

Background: Proteins may have none, single, double, or multiple domains, while a single domain may appear in multiple proteins. Their distribution patterns may have impacts on bacterial physiology and lifestyle. Objective: This study aims to understand how domains are distributed and duplicated in bacterial proteomes, in order to better understand bacterial physiology and lifestyles. Methods: In this study, we used 16712 Hidden Markov Models to screen 944 bacterial reference proteomes versus a threshold E-value<0.001. The number of non-redundant domains and duplication rates of redundant domains for each species were calculated. The unique domains, if any, were also identified for each species. In addition, the properties of no-domain proteins were investigated in terms of physicochemical properties. Results: The increasing number of non-redundant domains for a bacterial proteome follows the trend of an asymptotic function. The domain duplication rate is positively correlated with proteome size and increases more rapidly. The high percentage of single-domain proteins is more associated with small proteome size. For each proteome, unique domains were also obtained. Moreover, no-domain proteins show differences with the other three groups for several physicochemical properties analysed in this study. Conclusion: The study confirmed that a low domain duplication rate and a high percentage of singledomain proteins are more likely to be associated with bacterial host-dependent or restricted nicheadapted lifestyle. In addition, the unique lifestyle and physiology were revealed based on the analysis of species-specific domains and core domain interactions or co-occurrences.

Duplicate publications: A sample of redundancy in the Journal of

Purpose: Redundant publications occur when authors publish apartial or complete duplicate of data from an existing manuscript. The push for academic advancement in medicine may result in redundant publications that erode the quality of literature. We sampled the extent of redundancy within the Journal of Urology.Methods: Original articles published in the Journal of Urology in2006 were reviewed. MEDLINE was used to identify suspectedduplicate publications by combining the last names of the first,second and last authors with keywords provided by the article.Results were limited to 2004 to 2008. Two investigators reviewed the suspected duplicate publications and classified them as duplicate, probable duplicate and salami-slicing.Results: We screened 723 original articles. Of these originalarticles, 13 (1.8%) had some form of redundancy. One (0.1%)original article had a duplicate article, 5 (0.7%) original articleshad probable duplicates, and 7 (1%) original articles were salamisliced. The proportion of redundant articles published prior to, and following, their 2006 index article was 5/13 (38.5%) and 7/13 (53.8%), respectively. One duplicate (7.7%) was published in the same month as its index.Conclusion: Detection of redundant publications is a laboriousprocess for reviewers and editors. This sampling of the Journal of Urology revealed that the duplication rate in this journal is small, but significant. Further assessment of the urological literature is warranted.