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This Week in PNAS: Jan 24, 2017

In the early, online edition of the Proceedings of the National Academy of Sciences, a team from the US and the UK describe variation patterns in thousands of tetraploid or hexaploid wheat plant lines. Using a custom NimbleGen array designed to capture more than 82,500 wheat gene transcripts, the researchers sequenced nearly 287,000 protein-coding exon sequences from 1,535 mutagenized tetraploid wheat lines and 1,200 mutagenized versions of a hexaploid wheat variety. With these data, the researchers uncovered more than 10 million mutations, which cropped up between 35 and 40 times across each 1,000 bases of protein-coding sequence, on average. "This public collection of mutant seed stocks and sequence data enables rapid identification of mutation in the different copies of the wheat genes," they note, "which can be combined to uncover previously hidden variation."

A Massachusetts General Hospital-led group takes a look at the feasibility of using expression signature profiling and microfluidic methods to detect circulating tumor cells shed by hepatocellular carcinoma liver cancer tumors. The team did RNA-focused digital PCR on blood samples processed with a microfluidic chip known as CTC-iChip, designed to boost circulating tumor cell representation by weeding out hematopoietic cells. In the process, the authors narrowed in on 10-gene signature for finding circulating hepatocellular carcinoma cells, which they used to test samples from healthy individuals, individuals with hepatocellular carcinoma, and those with non-cancerous forms of liver disease. "[D]igital RNA quantification constitutes a sensitive and specific [circulating tumor cell] readout," they write, "enabling high-throughput clinical applications, such as non-invasive screening fro [hepatocellular carcinoma] in populations where viral hepatitis and cirrhosis are prevalent."

Finally, Swedish researchers explore regulatory variation in the Brassicaceae family plant Capsella grandiflora with the help of population genomic profiles, genome re-sequencing data, and allele-specific expression patterns teased out of transcriptome sequence data for flower bud and leaf tissues from a handful of C. grandiflora plants. Based on patterns at more than 1,000 genes with apparent allele-specific expression, coupled with whole-sequence data for almost three-dozen C. grandiflora plants, the team characterized cis-regulatory variation in relation to factors such as selection and gene body methylation.