GPA: A Microbial Genetic Polymorphisms Assignments Tool in Metagenomic Analysis by Bayesian Estimation

Identifying antimicrobial resistant(AMR) bacteria in metagenomics samples is essential for public health and food safety. Next-generation sequencing(NGS) technology has provided a powerful tool in identifying the genetic variation and constructing the correlations between genotype and phenotype in humans and other species. However, for complex bacterial samples, there lacks a powerful bioinformatic tool to identify genetic polymorphisms or copy number variations(CNVs) for given genes. Here we provide a Bayesian framework for genotype estimation for mixtures of multiple bacteria, named as Genetic Polymorphisms Assignments(GPA). Simulation results showed that GPA has reduced the false discovery rate(FDR) and mean absolute error(MAE) in CNV and single nucleotide variant(SNV) identification. This framework was validated by whole-genome sequencing and Pool-seq data from Klebsiella pneumoniae with multiple bacteria mixture models, and showed the high accuracy in the allele fraction detections of CNVs and SNVs in AMR genes between two populations. The quantitative study on the changes of AMR genes fraction between two samples showed a good consistency with the AMR pattern observed in the individual strains. Also, the framework together with the genome annotation and population comparison tools has been integrated into an application, which could provide a complete solution for AMR gene identification and quantification in unculturable clinical samples. The GPA package is available at https://github.com/IID-DTH/GPA-package.     

引进马铃薯种质资源抗旱性评价

马铃薯属于干旱敏感型作物,当前生产上的马铃薯品种多数不耐旱,中国马铃薯抗旱育种进程又受到遗传背景狭窄的制约。引进外来种质资源,拓宽我国马铃薯遗传背景,加快选育抗旱品种是马铃薯应对干旱的关键策略。2016年和2017年,在常规滴灌和雨养条件下,利用增广设计方法,以生产上常用的5个马铃薯品种为对照,对来自国际马铃薯中心的315份高代品系和中国已有的3个品种进行抗旱性评价。通过AMMI模型和GGE模型分析基因型、环境及二者互作对产量的影响,并结合抗旱指数筛选抗旱性稳定且产量高的材料。从整体上看,在雨养条件下,两年马铃薯平均产量差异较小,但是变异系数较大,常规滴灌条件下正好相反。马铃薯产量受基因型、环境及其交互作用的显著影响,其变异平方和分别占总处理平方和的43.39%、39.36%和17.26%;C93和YS902两年的抗旱指数均高于对照品种,稳产性好,C48虽然抗旱指数相对较低,但是高产和稳产性高于所有材料。筛选出来的材料不仅可以作为抗旱育种亲本,还可以通过进一步研究其抗旱机制,为抗旱育种提供理论支持。     

入侵害虫菊方翅网蝽在中国的潜在分布预测

菊方翅网蝽Corythucha marmorata(Uhler,1878)是我国新近发现的外来入侵害虫,研究明确菊方翅网蝽在我国的潜在分布范围对其监测预警及科学防控具有重要意义。本研究根据菊方翅网蝽的地理分布数据及相关环境变量,运用Maxent生态位模型与ArcGIS预测了菊方翅网蝽在中国的潜在地理分布范围。预测结果表明:菊方翅网蝽在我国的适生区主要分布于100°～125°E,20°～40°N的亚热带、暖温带区域,其中高适生区主要集中在长江中下游地区,包括浙江、江苏、湖南、上海大部分地区、安徽南部、湖北南部、江西西部及南部、贵州东部、福建东部、广西北部、山东中部、河南南部以及重庆、台湾局部;此外,极端气温、平均气温、最干月份降雨量对菊方翅网蝽的潜在分布影响较大。菊方翅网蝽已在我国成功入侵并迅速蔓延成灾,应在疫区边缘地带加强监测,并采取措施防止其进一步扩散。     

Genome sequencing and CRISPR/Cas9 gene editing of an early flowering Mini‐Citrus (Fortunella hindsii)

Hongkong kumquat (Fortunella hindsii) is a wild citrus species characterized by dwarf plant height and early flowering. Here, we identified the monoembryonic F. hindsii (designated as ‘Mini‐Citrus’) for the first time and constructed its selfing lines. This germplasm constitutes an ideal model for the genetic and functional genomics studies of citrus, which have been severely hindered by the long juvenility and inherent apomixes of citrus. F. hindsii showed a very short juvenile period (~8 months) and stable monoembryonic phenotype under cultivation. We report the first de novo assembled 373.6 Mb genome sequences (Contig‐N50 2.2 Mb and Scaffold‐N50 5.2 Mb) for F. hindsii. In total, 32 257 protein‐coding genes were annotated, 96.9% of which had homologues in other eight Citrinae species. The phylogenomic analysis revealed a close relationship of F. hindsii with cultivated citrus varieties, especially with mandarin. Furthermore, the CRISPR/Cas9 system was demonstrated to be an efficient strategy to generate target mutagenesis on F. hindsii. The modifications of target genes in the CRISPR‐modified F. hindsii were predominantly 1‐bp insertions or small deletions. This genetic transformation system based on F. hindsii could shorten the whole process from explant to T₁ mutant to about 15 months. Overall, due to its short juvenility, monoembryony, close genetic background to cultivated citrus and applicability of CRISPR, F. hindsii shows unprecedented potentials to be used as a model species for citrus research.     

Prediction of lymph node metastasis in oral squamous cell carcinoma based on protein profile

Objective: Lymph node metastasis leads to high mortality rates of oral squamous cell carcinoma (OSCC). However, it is still controversial to define clinically negative neck (cN0) and positive neck (cN1-3).

Methods: We retrieved candidate biomarkers identified by proteomic analysis in OSCC from published works of literature. In training stage, immunohistochemistry (IHC) analysis was used to determine the expression of proteins and logistic regression models with stepwise variable selection were used to identify potential factors that might affect lymph node metastasis and life status. Furthermore, the prediction model was validated in validating stage.

Results: We screened eight highly expressed proteins related to lymph node metastasis in OSCC and found that the expression levels of SOD2, BST2, CAD, ITGB6, and PRDX4 were significantly elevated in patients with lymph node metastasis compared to the patients without lymph node metastasis. Furthermore, in training and validating stages, the prediction model base on the combination of CAD, SOD2 expression levels, and histopathologic grade was developed and validated in patients with OSCC.

Conclusions: Our findings showed that the developed model well predicts the lymph node metastasis and life status in patients with OSCC, independent of TNM stage.     

RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: A case study in roe deer

Estimating the evolutionary potential of quantitative traits and reliably predicting responses to selection in wild populations are important challenges in evolutionary biology. The genomic revolution has opened up opportunities for measuring relatedness among individuals with precision, enabling pedigree‐free estimation of trait heritabilities in wild populations. However, until now, most quantitative genetic studies based on a genomic relatedness matrix (GRM) have focused on long‐term monitored populations for which traditional pedigrees were also available, and have often had access to knowledge of genome sequence and variability. Here, we investigated the potential of RAD‐sequencing for estimating heritability in a free‐ranging roe deer (Capreolous capreolus) population for which no prior genomic resources were available. We propose a step‐by‐step analytical framework to optimize the quality and quantity of the genomic data and explore the impact of the single nucleotide polymorphism (SNP) calling and filtering processes on the GRM structure and GRM‐based heritability estimates. As expected, our results show that sequence coverage strongly affects the number of recovered loci, the genotyping error rate and the amount of missing data. Ultimately, this had little effect on heritability estimates and their standard errors, provided that the GRM was built from a minimum number of loci (above 7,000). Genomic relatedness matrix‐based heritability estimates thus appear robust to a moderate level of genotyping errors in the SNP data set. We also showed that quality filters, such as the removal of low‐frequency variants, affect the relatedness structure of the GRM, generating lower h² estimates. Our work illustrates the huge potential of RAD‐sequencing for estimating GRM‐based heritability in virtually any natural population.