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Rapeseed is the most important oil crop used in the food and biodiesel industries. In this study, based on single nucleotide polymorphism (SNP) identified from genotyping-by-sequencing (GBS), and an association study of flowering time, crude fat and fatty acid contents were investigated in 46 rapeseed mutant lines derived from gamma rays. A total of 623,026,394 clean data reads were generated with 6.6 million reads on average. A set of 37,721 filtered SNPs was used to perform gene ontology and phylogenetic analysis. Hierarchical cluster analysis of the rapeseed mutant lines gave eight groups based on flowering time and fatty acid compositions. Gene ontological analysis of the mutant lines showed that many genes displaying SNPs are involved in cellular processes, cellular anatomy, and binding. A total of 40 SNPs were significantly associated with flowering time (1 SNP), crude fat content (2 SNPs), and fatty acid content (37 SNPs). A total of 21 genes were annotated from fatty acid content SNPs, among them, nine genes were significantly enriched in reproductive processes, such as embryonic development, fruit development, and seed development. This study demonstrated that SNPs are efficient tools for mutant screening and it provides a basis that the improving the oil qualities of rapeseed.

The use of Unmanned Aerial Vehicle (UAV) has been increasingly diverse. In Wireless Sensor Networks (WSNs), UAVs are used for sensor data collection. However, the path planning for the UAV is not practical for a large number of sensors, and is not effective for the battery consumption. In this paper, we propose the UAV path planning for data collection in WSNs using Polynomial Regression. With this algorithm, the UAV is able to save the battery and the mission time.

The unicellular green alga Chlamydomonas reinhardtti is a promising source of bioenergy and understanding its carbon metabolism is important. In this organism, carbon accumulation can be manipulated with nitrogen supply. Chlamydomonas reinhardtii is a mixotroph that can act as an autotroph or heterotroph, depending on conditions. Fructose-1,6-bisphosphate aldolases (FBAs) are important enzymes in energy pathways of algae; they convert fructose-1,6-bisphosphate to glyceraldehyde 3-phosphate and dihydroxyacetone phosphate. Expression of both CrFBA1 and CrFBA2 was less under nitrogen-deplete conditions than under nitrogen-replete conditions in Chlamydomonas cells. To explore CrFBA1 function, CrFBA1-overexpressing Chlamydomonas lines were generated. Compared to wild-type, transformed cells grew more slowly in photoautotrophic conditions, but at the same rate in mixotrophic condition. We suggest that overexpression of CrFBA1 affected photosynthetic carbon fixation in the Calvin-Benson cycle. The CrFBA1-overexpressing lines had less starch than the wild-type under mixotrophic, low-nitrogen conditions, but more fatty acids. In the transgenic cells, expression of granule bound starch synthase 1 (GBSS1) determined by quantitative reverse transcription-polymerase chain reaction was down-regulated, but acetyl-CoA synthetases (ACS1 and ACS2) and phosphoglucomutase (PGM) were up-regulated compared to wild-type. We propose three possible explanations for the observed low starch and high fatty acid content of the transgenic cells. Firstly, abnormal carbon flux by CrFBA1 overexpression leads to GBSS1 down-regulation in a feed-forward regulation, which resulted in the low starch accumulation. Secondly, increase of exogenous acetate assimilation by ACS1 and ACS2 up-regulation results in high accumulation of total fatty acid in transformants, perhaps due to compensation for reduced-carbon fixation. Lastly, activation of glycolytic pathway by CrFBA1 overexpression enhances conversion of starch to fatty acid. We conclude that overexpression of CrFBA1 deregulates carbon metabolism in Chlamydomonas reinhardtii.