Rubio, A. — Page 2 | bioRxiv Science

bioRxiv2020

Community structure and seasonality of bees and flowering plants in a riparian corridor of the lower Rio Grande River in Webb County, Texas (USA)

The Rio Grande in Texas serves as the geo-political boundary between the United States and Mexico. It is considered one of the worlds most at-risk rivers and has been the subject of intensified management by the inhabitants of both countries lining its banks. Additionally, invasion by non-native Arundo donax (Linnaeus) (Cyperales: Poaceae), giant reed, has been extensive in the riparian corridor, with potential impacts to native wildlife. Locally, there remains a significant lack of ecological community data of riparian and upland habitats parallel to the river. We sampled bee and flowering plant communities monthly over two years, along a 3.22 km stretch of the lower Rio Grande in Webb County, TX. Data show that bee and plant richness and abundance was highest during March-April and September among both habitat types. Analysis of bee communities showed low spatial and temporal variation at the habitat level. Although common bee taxa (Halictidae and Apidae) were numerically dominant, NMS and ISA found key bee species driving community patterns. This included higher abundances of two species in the riparian habitat Anthophora occidentalis (Cresson) (Hymenoptera: Apidae) and Lasioglossum sp.L (Curtis) (Hymenoptera: Apidae) and one showing affinity for the upland habitat Halictus ligatus (Say) (Hymenoptera: Halictidae). Additionally, ISA analysis of plant data revealed that three species were significant indicator taxa in riparian habitats. Further analysis showed a positive correlation between bee generic richness and abundance with various climate attributes. Management of the riparian corridor and associated watershed could include significant areas for ecological restoration to assist pollinators.

ecology↗

bioRxiv2017

Comparison of RNA-seq and Microarray Platforms for Splice Event Detection using a Cross-Platform Algorithm

RNA-seq is a reference technology for determining alternative splicing at genome-wide level. Exon arrays remain widely used for the analysis of gene expression, but show poor validation rate with regard to splicing events. Commercial arrays that include probes within exon junctions have been developed in order to overcome this problem.\n\nWe compare the performance of RNA-seq (Illumina HiSeq) and junction arrays (Affymetrix Human Transcriptome array) for the analysis of transcript splicing events. Three different breast cancer cell lines were treated with CX-4945, a drug that severely affects splicing. To enable a direct comparison of the two platforms, we adapted EventPointer, an algorithm that detects and labels alternative splicing events using junction arrays, to work also on RNA-seq data. Common results and discrepancies between the technologies were validated and/or resolved by over 200 PCR experiments.\n\nAs might be expected, RNA-seq appears superior in cases where the technologies disagree, and is able to discover novel splicing events beyond the limitations of physical probe-sets. We observe a high degree of coherence between the two technologies, however, with correlation of EventPointer results over 0.90. Through decimation, the detection power of the junction arrays is equivalent to RNA-seq with up to 60 million reads. Our results suggest, therefore, that exon-junction arrays are a viable alternative to RNA-seq for detection of alternative splicing events when focusing on well-described transcriptional regions.

bioinformatics↗