CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning

Recent progress in cryo-EM research has ignited a revolution in biological macromolecule structure determination. Resolution is an essential parameter for quality assessment of a cryo-EM density map, and it is known that resolution varies in different regions of a map. Currently available methods for local resolution estimation require manual adjustment of parameters and in some cases necessitate acquisition or de novo generation of so-called “half maps”. Here, we developed CryoRes, a deep-learning algorithm to estimate local resolution directly from a single final cryo-EM density map, specifically by learning resolution-aware patterns of density map voxels through supervised training on a large dataset comprising 1,174 experimental cryo-EM density maps. CryoRes significantly outperforms all of the state-of-the-art competing resolution estimation methods, achieving an average RMSE of 2.26 Å for local resolution estimation relative to the currently most reliable FSC-based method blocres, yet requiring only the single final map as input. Further, CryoRes is able to generate a molecular mask for each map, with accuracy 12.12% higher than the masks generated by ResMap. CryoRes is ultra-fast, fully automatic, parameter-free, applicable to cryo-EM subtomogram data, and freely available at https://cryores.zhanglab.net.     

不同预处理对小鼠粪样菌群高通量测序分析结果的影响

应用高通量测序技术比较不同预处理对小鼠粪样菌群结构的影响,以期为后续相关研究提供参考依据。采集昆明小鼠新鲜粪样,分为原始粪样组、生理盐水处理组和PBS处理组,提取粪样DNA,采用Illumina MiSeq平台进行测序对3组样本的16S rRNA V3~V4区基因文库进行生物信息学分析。结果显示,3组样本拥有共同的OTUs 188个,不同预处理对粪样微生物多样性和丰度产生影响,生理盐水处理组、PBS处理组和原始粪样组分别检出14、11、12个门,3组样本共有门11个;分别检出24、21、21个纲,3组样本共有纲20个;分别检出62、55、59个科,3组样本共有科26个;分别检出147、126、137个属,3组样本共有属117个。总体来看,生理盐水处理组微生物多样性和丰度相对最高,原始粪样组次之,PBS处理组最低。粪样经生理盐水处理后,能在一定程度上提高肠道菌群检测的准确性。     

A transformer architecture for retention time prediction in liquid chromatography mass spectrometry-based proteomics

Accurate retention time (RT) prediction is important for spectral library-based analysis in data-independent acquisition mass spectrometry-based proteomics. The deep learning approach has demonstrated superior performance over traditional machine learning methods for this purpose. The transformer architecture is a recent development in deep learning that delivers state-of-the-art performance in many fields such as natural language processing, computer vision, and biology. We assess the performance of the transformer architecture for RT prediction using datasets from five deep learning models Prosit, DeepDIA, AutoRT, DeepPhospho, and AlphaPeptDeep. The experimental results on holdout datasets and independent datasets exhibit state-of-the-art performance of the transformer architecture. The software and evaluation datasets are publicly available for future development in the field.     

DNA barcoding of Cymbidium by genome skimming: Call for next-generation nuclear barcodes

Cymbidium is an orchid genus that has undergone rapid radiation and has high ornamental, economic, ecological and cultural importance, but its classification based on morphology is controversial. The plastid genome (plastome), as an extension of plant standard DNA barcodes, has been widely used as a potential molecular marker for identifying recently diverged species or complicated plant groups. In this study, we newly generated 237 plastomes of 50 species (at least two individuals per species) by genome skimming, covering 71.4% of members of the genus Cymbidium. Sequence-based analyses (barcoding gaps and automatic barcode gap discovery) and tree-based analyses (maximum likelihood, Bayesian inference and multirate Poisson tree processes model) were conducted for species identification of Cymbidium. Our work provides a comprehensive DNA barcode reference library for Cymbidium species identification. The results show that compared with standard DNA barcodes (rbcL + matK) as well as the plastid trnH-psbA, the species identification rate of the plastome increased moderately from 58% to 68%. At the same time, we propose an optimized identification strategy for Cymbidium species. The plastome cannot completely resolve the species identification of Cymbidium, the main reasons being incomplete lineage sorting, artificial cultivation, natural hybridization and chloroplast capture. To further explore the potential use of nuclear data in identifying species, the Skmer method was adopted and the identification rate increased to 72%. It appears that nuclear genome data have a vital role in species identification and are expected to be used as next-generation nuclear barcodes.     

ploidyfrost: Reference-free estimation of ploidy level from whole genome sequencing data based on de Bruijn graphs

Polyploidy is ubiquitous and its consequences are complex and variable. A change of ploidy level generally influences genetic diversity and results in morphological, physiological and ecological differences between cells or organisms with different ploidy levels. To avoid cumbersome experiments and take advantage of the less biased information provided by the vast amounts of genome sequencing data, computational tools for ploidy estimation are urgently needed. Until now, although a few such tools have been developed, many aspects of this estimation, such as the requirement of a reference genome, the lack of informative results and objective inferences, and the influence of false positives from errors and repeats, need further improvement. We have developed ploidyfrost , a de Bruijn graph-based method, to estimate ploidy levels from whole genome sequencing data sets without a reference genome. ploidyfrost provides a visual representation of allele frequency distribution generated using the ggplot2 package as well as quantitative results using the Gaussian mixture model. In addition, it takes advantage of colouring information encoded in coloured de Bruijn graphs to analyse multiple samples simultaneously and to flexibly filter putative false positives. We evaluated the performance of ploidyfrost by analysing highly heterozygous or repetitive samples of Cyclocarya paliurus and a complex allooctoploid sample of Fragaria × ananassa. Moreover, we demonstrated that the accuracy of analysis results can be improved by constraining a threshold such as Cramér's V coefficient on variant features, which may significantly reduce the side effects of sequencing errors and annoying repeats on the graphical structure constructed.     

A chromosome-level genome assembly enables the identification of the follicule stimulating hormone receptor as the master sex-determining gene in the flatfish Solea senegalensis

Sex determination (SD) shows huge variation among fish and a high evolutionary rate, as illustrated by the Pleuronectiformes (flatfishes). This order is characterized by its adaptation to demersal life, compact genomes and diversity of SD mechanisms. Here, we assembled the Solea senegalensis genome, a flatfish of great commercial value, into 82 contigs (614 Mb) combining long- and short-read sequencing, which were next scaffolded using a highly dense genetic map (28,838 markers, 21 linkage groups), representing 98.9% of the assembly. Further, we established the correspondence between the assembly and the 21 chromosomes by using BAC-FISH. Whole genome resequencing of six males and six females enabled the identification of 41 single nucleotide polymorphism variants in the follicle stimulating hormone receptor (fshr) consistent with an XX/XY SD system. The observed sex association was validated in a broader independent sample, providing a novel molecular sexing tool. The fshr gene displayed differential expression between male and female gonads from 86 days post-fertilization, when the gonad is still an undifferentiated primordium, concomitant with the activation of amh and cyp19a1a, testis and ovary marker genes, respectively, in males and females. The Y-linked fshr allele, which included 24 nonsynonymous variants and showed a highly divergent 3D protein structure, was overexpressed in males compared to the X-linked allele at all stages of gonadal differentiation. We hypothesize a mechanism hampering the action of the follicle stimulating hormone driving the undifferentiated gonad toward testis.     

Contemporary issues,current best practice and ways forward in soil protist ecology

Soil protists are increasingly studied due to a release from previous methodological constraints and the acknowledgement of their immense diversity and functional importance in ecosystems. However, these studies often lack sufficient depth in knowledge, which is visible in the form of falsely used terms and false- or over-interpreted data with conclusions that cannot be drawn from the data obtained. As we welcome that also non-experts include protists in their still mostly bacterial and/or fungal-focused studies, our aim here is to help avoid some common errors. We provide suggestions for current terms to use when working on soil protists, like protist instead of protozoa, predator instead of grazer, microorganisms rather than microflora and other terms to be used to describe the prey spectrum of protists. We then highlight some dos and don'ts in soil protist ecology including challenges related to interpreting 18S rRNA gene amplicon sequencing data. We caution against the use of standard bioinformatic settings optimized for bacteria and the uncritical reliance on incomplete and partly erroneous reference databases. We also show why causal inferences cannot be drawn from sequence-based correlation analyses or any sampling/monitoring, study in the field without thorough experimental confirmation and sound understanding of the biology of taxa. Together, we envision this work to help non-experts to more easily include protists in their soil ecology analyses and obtain more reliable interpretations from their protist data and other biodiversity data that, in the end, will contribute to a better understanding of soil ecology.     

PHYLOGENY OF THE ULVOPHYCEAE (CHLOROPHYTA): CLADISTIC ANALYSIS OF NUCLEAR-ENCODED rRNA SEQUENCE DATA1

Cladistic analysis of nuclear-encoded rRNA sequence data provided us with the basis for some new hypotheses of relationships within the green algal class Ulvophyceae. The orders Ulotrichales and Ulvales are separated from the clade formed by the remaining orders of siphonous and siphonocladous Ulvophyceae (Caulerpales, Siphonocladales /Cladophorales [S/C] complex, and the Dasycladales), by the Chlorophyceae and Pleurastrophyceae. Our results suggest that the Ulvophyceae is not a monophyletic group. Examination of inter- and intra-ordinal relationships within the siphonous and siphonocladous ulvophycean algae revealed that Cladophora, Chaetomorpha, Anadyomene, Microdictyon, Cladophoropsis and Dictyosphaeria form a clade. Thus the hypothesis, based on ultrastructural features, that the Siphonocladales and Cladophorales are closely related is supported. Also, the Caulerpales is a monophyletic group with two lineages; Caulerpa, Halimeda, and Udotea comprise one, and Bryopsis and Codium comprise the other. The Dasycladales (Cymopolia and Batophora) also forms a clade, but this clade is not inferred to be the sister group to the S/C complex as has been proposed. Instead, it is either the sister taxon to the Caulerpales or basal to the Caulerpales and S/C clade The Trentepohliales is also included at the base of the siphonous and siphonocladous ulvophycean clade. The Pleurastrophyceae, which, like the Ulvophyceae, posses a counter-clockwise arrangement of flagellar basal bodies, are more closely related to the Chlorophyceae than to the Ulvophyceae based on rRNA sequences. Thus, the arrangement of basal bodies does not diagnose a monophyletic group. Previously reported hypotheses of phylogenetic relationships of ulvophycean algae were tested. In each case, additional evolutionary steps were required to obtain the proposed relationships. Relationships of ulvophycean algae to other classes of green algae are discussed.