Cryptosporidium species and subtypes in river water and riverbed sediment using next-generation sequencing

This study uncovered the prevalence, harboured species, and subtype diversity of Cryptosporidium species in river water and its sediment from the Apies River in South Africa. Cryptosporidium spp. concentrations in freshwater and its sediment were determined using Ziehl-Neelsen staining and quantitative Polymerase Chain Reaction (qPCR) techniques. Next-generation sequencing (NGS) targeting the 60 kDa glycoprotein (gp60) gene of Cryptosporidium spp. was performed to reveal the species, subtype families and subtypes harboured in freshwater and its sediment. Although the results revealed that water samples had a higher prevalence (30%) compared with sediment (28%), the number of observable Cryptosporidium spp. oocysts in sediment samples (ranging from 4.90 to 5.81 log₁₀ oocysts per 1 Liter) was higher than that of river water samples (ranging from 4.60 to 5.58 log₁₀ oocysts per 1 L) using Ziehl-Neelsen staining. The 18S ribosomal ribonucleic acid (rRNA) gene copy of Cryptosporidium in riverbed sediments ranged from 6.03 to 7.65 log₁₀, whereas in river water, it was found to be between 4.20 and 6.79 log₁₀. Subtyping results showed that in riverbed sediments, Cryptosporidium parvum accounted for 40.72% of sequences, followed by Cryptosporidium hominis with 23.64%, Cryptosporidium cuniculus with 7.10%, Cryptosporidium meleagridis with 4.44% and the least was Cryptosporidium wrairi with 2.59%. A considerable percentage of reads in riverbed sediment (21.25%) was not assigned to any subtype. River water samples had 45.63% of sequences assigned to C. parvum, followed by 30.32% to C. hominis, 17.99% to C. meleagridis and 5.88% to C. cuniculus. The data obtained are concerning, as Cryptosporidium spp. have intrinsic resistance to water treatment processes and low infectious doses, which can pose a risk to human health due to the various uses of water (for human consumption, leisure, and reuse).     

Comparative systems biology between human and animal models based on next-generation sequencing methods

Animal models provide myriad benefits to both experimental and clinical research. Unfortunately, in many situations, they fall short of expected results or provide contradictory results. In part, this can be the result of traditional molecular biological approaches that are relatively inefficient in elucidating underlying molecular mechanism. To improve the efficacy of animal models, a technological breakthrough is required. The growing availability and application of the high-throughput methods make systematic comparisons between human and animal models easier to perform. In the present study, we introduce the concept of the comparative systems biology, which we define as "comparisons of biological systems in different states or species used to achieve an integrated understanding of life forms with all their characteristic complexity of interactions at multiple levels". Furthermore, we discuss the applications of RNA-seq and ChIP-seq technologies to comparative systems biology between human and animal models and assess the potential applications for this approach in the future studies.     

QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

基于高通量测序数据构建斑马鱼隐性遗传突变筛选系统

目的:针对斑马鱼高通量测序数据,通过一系列质量控制和突变过滤,构建一套有效隐性遗传突变筛选系统。方法:A)经过与斑马鱼参考基因组比对,利用GATK获得初始的VCF格式突变信息。B)使用perl语言编写本地脚本,对突变信息进行过滤,注释等。C)通过绘制纯合突变点分布图,找出突变富集区域。整合以上步骤,构建出一套针对斑马鱼高通量测序数据的遗传性突变筛选系统。结果:对获得的突变位点进行了一系列的质量控制,定位到具体染色体上的特定区域,并且对获得的突变进行了功能上的注释。结论:本过滤筛选系统能有效控制检测的假阳性率,对斑马鱼致病性的隐性突变位点筛查提供有力参考。     

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.     

Fungal communities associated with acorn woodpeckers and their excavations

Wood-decay fungi soften wood, putatively providing opportunities for woodpeckers to excavate an otherwise hard substrate, yet the fungal community composition in tree cavities and the specificity of these relationships is largely unknown. We used high-throughput amplicon sequencing of the fungal ITS2 region to examine the fungal communities associated with acorn woodpeckers (Melanerpes formicivorus) and their cavities in mature valley oak (Quercus lobata) and blue oak (Q. douglasii) trees in an oak savannah of central coastal California, USA. Acorn woodpeckers and their excavations harbored over 1500 fungal taxa, including more than 100 putative wood-decay fungi. The fungal communities found on the birds were more similar to those found in excavated cavities than those found in trees without excavated holes. These results suggest that symbiotic associations between acorn woodpeckers and fungi are highly diverse, with low specificity. Symbiotic associations between cavity-excavators and fungi are likely more common and widespread than previously thought.     

Differential expression profiles of miRNA in the serum of sarcopenic rats

As the geriatric population and life expectancy increase, the interest in preventing geriatric diseases, such as sarcopenia, is increasing. However, the causes of sarcopenia are unclear, and current diagnostic methods for sarcopenia are unreliable. We hypothesized that the changes in the expression of certain miRNAs may be associated with the pathophysiology of sarcopenia. Herein, we analyzed the miRNA expression profiles in the blood of young (3-months-old) healthy rats, old sarcopenic (17-months-old) rats, and age-matched (17-months-old) control rats. The changes in miRNA expression levels were analyzed using Bowtie 2 software. A total of 523 miRNAs were detected in the rat serum. Using scatter plots and clustering heatmap data, we found 130 miRNAs that were differentially expressed in sarcopenic rats (>2-fold change) compared to the expression in young healthy and age-matched control rats. With a threshold of >5-fold change, we identified 14 upregulated miRNAs, including rno-miR-133b-3p, rno-miR-133a-3p, rno-miR-133c, rno-miR-208a-3p, and rno-miR434-5p among others in the serum of sarcopenic rats. A protein network map based on these 14 miRNAs identified the genes involved in skeletal muscle differentiation, among which Notch1, Egr2, and Myocd represented major nodes. The data obtained in this study are potentially useful for the early diagnosis of sarcopenia and for the identification of novel therapeutic targets for the treatment and/or prevention of sarcopenia.