Recent studies utilizing transcriptome sequences generated by next-generation sequencing (NGS) technologies have demonstrated the ability to rapidly detect and characterize thousands of gene-based microsatellites from different plants. However, these simple sequence repeats (SSRs) were seldom used directly to test interspecific transferability in the populations of closely related species. Aspidistra Ker-Gawl. is a monocot genus with high species richness and diversity in flower structure, but its fresh floral materials are not easy to obtain. Until now, little is known about genetic background in the species of Aspidistra, quite apart from the fearful reduction of their natural habitats. In this study, the floral transcriptome of Aspidistra saxicola was obtained using NGS. Based on these data, a total of 5527 SSRs were identified in the unigenes. Among these SSRs, the proportions of di- and tri-nucleotide repeats were quite close (49.6% verse 46.8%), and the most tri-nucleotide repeats were AGG/CCT followed by AAG/CTT and AGC/GCT in A. saxicola, showing distinct differences with other angiosperm species. To assess genetic diversity in the species of Aspidistra, 48 SSR loci were tested in four available populations of A. elatior. The results revealed that more than a third of the loci were polymorphic. The majority of these primers could be amplified in 24 species representing the main clades of Aspidistra. The primer subsets from transcriptome data proved highly useful for detecting polymorphisms in the related species, supporting the finding that NGS is an efficient approach to molecular marker development at both intra- and interspecies levels, especially in endangered nonmodel species.

Microbiome studies continue to provide tremendous insight into the importance of microorganism populations to the macroscopic world. High-throughput DNA sequencing technology (i.e., Next-generation Sequencing) has enabled the costeffective, rapid assessment of microbial populations when combined with bioinformatic tools capable of identifying microbial taxa and calculating the diversity and composition of biological and environmental samples. Ribosomal RNA gene sequencing, where 16S and 18S rRNA gene sequences are used to identify prokaryotic and eukaryotic species, respectively, is one of the most widely-used techniques currently employed in microbiome analysis. Prior to bioinformatic analysis of these sequences, trimming parameters must be set so that post-trimming sequence information is maximized while expected errors in the sequences themselves are minimized. In this application note, we present FIGARO: a Python-based application designed to maximize read retention after trimming and filtering for quality. FIGARO was designed specifically to increase reproducibility and minimize trial-and-error in trimming parameter selection for a DADA2-based pipeline and will likely be useful for optimizing trimming parameters and minimizing sequence errors in other pipelines as well where paired-end overlap is required. Availability and implementation:The FIGARO application is freely available as source code at https://github.com/Zymo-Research/figaro.

Aging represents the most important risk factor for many chronic diseases including cardiovascular diseases, diabetes, and cancer, therefore understanding the mechanisms of aging is a fundamental step for designing new treatments for chronic diseases. DNA methylation is the most reliable and accurate molecular marker for aging quantification, however, genome‐wide DNA methylation profiling techniques, such as reduced representative bisulfite sequencing and Illumina Bead Array that are widely used in aging research are prohibitively expensive and have poor data quality at low‐read coverage sites. Here we report a robust targeted bisulfite sequencing approach, called SWARM™ (Simplified Whole‐panel Amplification Reaction Method), for the accurate biological age determination. SWARM™ is flexible and low cost, requires relatively low DNA input, allows the simultaneous amplification and sequencing of hundreds of loci, and has shown to increase sample throughput. Using the SWARM™ approach, we were able to analyze the methylation level of several hundreds of age‐associated loci including the published Horvath Clock sites. An age‐predictive model was built using the elastic net regression of DNA methylation levels of the loci and chronological age of blood DNA samples of over 300 healthy subjects of 18 to 89 years old. Our epigenetic age (DNAge™) predictor achieved a small median age error, and the DNAge™ of samples that were processed on both sequencing and array platforms highly correlated (r > 0.9). In brief, our versatile SWARM™ technology‐based DNAge™ platform is a very fast and accurate tool for the precise biological aging quantification and aging interventions monitoring. Dedicated DNAge™ platforms are compatible with various sample types, and can be applied for aging studies in human, and in other species including mice.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

No abstract

Aging represents the most important risk factor for many chronic diseases including cardiovascular diseases, diabetes, and cancer, therefore understanding the mechanisms of aging is a fundamental step for designing new treatments for chronic diseases. DNA methylation is the most reliable and accurate molecular marker for aging quantification, however, genome-wide DNA methylation profiling techniques, such as reduced representative bisulfite sequencing and Illumina Bead Array that are widely used in aging research are prohibitively expensive and have poor data quality at low-read coverage sites. Here we report a robust targeted bisulfite sequencing approach, called SWARM® (Simplified Whole-panel Amplification Reaction Method), for the accurate biological age determination. SWARM™ is flexible and low cost, requires relatively low DNA starting material, allows the simultaneous amplification and sequencing of hundreds of loci, and has shown to increase sample throughput. Using the SWARM® approach, we were able to analyze the methylation level of several hundreds of age-associated loci including the published Horvath Clock sites. Gender-specific age-predictive models were built using the elastic net regression of DNA methylation levels of the loci and chronological age of urine DNA samples of over 300 healthy subjects of 18 to 88 years old. Urine samples from bladder cancer patients exhibit significant age acceleration, with an average of >10 years. In brief, our gender-specific urine DNAge® analysis is a tool for the precise biological aging quantification and can be used to address questions in aging and urinary track cancers. Citation Format: Yap Ching Chew, Wei Guo, Xiaojing Yang, Paolo Piatti, Mingda Jin, Keith Booher, Benjamin Jara, Xi-Yu Jia. Accelerated epigenetic aging in bladder cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 828.