Francesca Cordero | Search bioRxiv

bioRxiv2015

Sequencing of 15,622 gene-bearing BACs reveals new features of the barley genome

Barley (Hordeum vulgare L.) possesses a large and highly repetitive genome of 5.1 Gb that has hindered the development of a complete sequence. In 2012, the International Barley Sequencing Consortium released a resource integrating whole-genome shotgun sequences with a physical and genetic framework. However, since only 6,278 BACs in the physical map were sequenced, detailed fine structure was limited. To gain access to the gene-containing portion of the barley genome at high resolution, we identified and sequenced 15,622 BACs representing the minimal tiling path of 72,052 physical mapped gene-bearing BACs. This generated about 1.7 Gb of genomic sequence containing 17,386 annotated barley genes. Exploration of the sequenced BACs revealed that although distal ends of chromosomes contain most of the gene-enriched BACs and are characterized by high rates of recombination, there are also gene-dense regions with suppressed recombination. Knowledge of these deviant regions is relevant to trait introgression, genome-wide association studies, genomic selection model development and map-based cloning strategies. Sequences and their gene and SNP annotations can be accessed and exported via http://harvest-web.org/hweb/utilmenu.wc or through the software HarvEST:Barley (download from harvest.ucr.edu). In the latter, we have implemented a synteny viewer between barley and Aegilops tauschii to aid in comparative genome analysis.

Genomics↗

bioRxiv2014

Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis

BackgroundRNAseq provides remarkable power in the area of biomarkers discovery and disease stratification. The main technical steps affecting the results of RNAseq experiments are Library Sample Preparation (LSP) and Bioinformatics Analysis (BA). At the best of our knowledge, a comparative evaluation of the combined effect of LSP and BA was never considered and it might represent a valuable knowledge to optimize alternative splicing detection, which is a challenging task due to moderate fold change differences to be detected within a complex isoforms background.\n\nResultsDifferent LSPs (TruSeq unstranded/stranded, ScriptSeq, NuGEN) allow the detection of a large common set of isoforms. However, each LSP also detects a smaller set of isoforms, which are characterized both by lower coverage and lower FPKM than that observed for the common ones among LSPs. This characteristic is particularly critical in case of low input RNA NuGEN v2 LSP.\n\nThe effect on statistical detection of alternative splicing considering low input LSP (NuGEN v2) with respect to high input LSP (TruSeq) on statistical detection of alternative splicing was studied using a benchmark dataset, in which both synthetic reads and reads generated from high (TruSeq) and low input (NuGEN) LSPs were spiked-in. Statistical detection of alternative splicing (AltDE) was done using prototypes of BA for isoform-reconstruction (Cuffdiff) and exon-level analysis (DEXSeq). Exon-level analysis performs slightly better than isoform-reconstruction approach although at most only 50% of the spiked-in transcripts are detected. Both isoform-reconstruction and exon-level analysis performances improve by rising the number of input reads.\n\nConclusionData, derived from NuGEN v2, are not the ideal input for AltDE, specifically when exon-level approach is used. It is notable that ribosomal depletion, with respect to polyA+ selection, reduces the amount of coding mappable reads resulting detrimental in the case of AltDE. Furthermore, we observed that both isoform-reconstruction and exon-level analysis performances are strongly dependent on the number of input reads.

Genomics↗