Transcriptomic analysis of Raphidocelis subcapitata exposed to erythromycin: The role of DNA replication in hormesis and growth inhibition

HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.

Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability and implementation: HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. Contact: sanders@fs.tum.de

Antibiotics are widely used in humans and animals, but there is a big concern about their negative impacts on ecosystem and human health after use. So far there is a lack of information on emission inventory and environmental fate of antibiotics in China. We studied national consumption, emissions, and multimedia fate of 36 frequently detected antibiotics in China by market survey, data analysis, and level III fugacity modeling tools. Based on our survey, the total usage for the 36 chemicals was 92700 tons in 2013, an estimated 54000 tons of the antibiotics was excreted by human and animals, and eventually 53800 tons of them entered into the receiving environment following various wastewater treatments. The fugacity model successfully predicted environmental concentrations (PECs) in all 58 river basins of China, which are comparable to the reported measured environmental concentrations (MECs) available in some basins. The bacterial resistance rates in the hospitals and aquatic environments were found to be related to the PECs and antibiotic usages, especially for those antibiotics used in the most recent period. This is the first comprehensive study which demonstrates an alarming usage and emission of various antibiotics in China.