＜正＞Many sweet potato cultivars could accumulate high amount of anthocyanins in their storage roots[1], showing...
HongxiaWang, Peng Zhang* SIBS-ETH Shanghai Center for Cassava Biotechnology, National Laboratory of Plant Molecular Genetics, Institute of Plant Physiology & Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 300 Fenglin Road, Shanghai 200032, China
RNA-Seq technology is becoming widely used in various transcriptomics studies;however,analyzing and interpreting the RNA-Seq data face serious challenges.With the development of high-throughput sequencing technologies,the sequencing cost is dropping dramatically with the sequencing output increasing sharply.However,the sequencing reads are still short in length and contain various sequencing errors.Moreover,the intricate transcriptome is always more complicated than we expect.These challenges proffer the urgent need of efficient bioinformatics algorithms to effectively handle the large amount of transcriptome sequencing data and carry out diverse related studies.This review summarizes a number of frequently-used applications of transcriptome sequencing and their related analyzing strategies,including short read mapping,exon-exon splice junction detection,gene or isoform expression quantification,differential expression analysis and transcriptome reconstruction.
De novo transcriptome assembly is an important approach in RNA-Seq data analysis and it can help us to reconstruct the transcriptome and investigate gene expression profiles without reference genome sequences.We carried out transcriptome assemblies with two RNA-Seq datasets generated from human brain and cell line,respectively.We then determined an efficient way to yield an optimal overall assembly using three different strategies.We first assembled brain and cell line transcriptome using a single k-mer length.Next we tested a range of values of k-mer length and coverage cutoff in assembling.Lastly,we combined the assembled contigs from a range of k values to generate a final assembly.By comparing these assembly results,we found that using only one k-mer value for assembly is not enough to generate good assembly results,but combining the contigs from different k-mer values could yield longer contigs and greatly improve the overall assembly.
Leaf variegation resulting from nuclear gene mutations has been used as a model system to elucidate the molecular mechanisms of chloroplast development. Since most variegation genes also function in photosynthesis, it remains unknown whether their roles in photosynthesis and chloroplast development are distinct. Here, using the variegation mutant thylakoid formation1 （thfl） we show that variegation formation is light independent. It was found that slow and uneven chloroplast development in thfl can be attributed to defects in etioplast development in darkness. Ultrastructural analysis showed the coexistence of plastids with or without prolamellar bodies （PLB） in cells of thfl, but not of WT. Although THF1 mutation leads to significant decreases in the levels of Pchlide and Pchliide oxidoreductase （POR） expression, genetic and 5-aminolevulinic acid （ALA）-feeding analysis did not reveal Pchlide or POR to be critical factors for etioplast formation in thfl. Northern blot analysis showed that plastid gene expression is dramatically reduced in thfl compared with that in WT, particularly in the dark. Our results also indicate that chlorophyll biosynthesis and expression of plastidic genes are coordinately suppressed in thfl. Based on these results, we propose a model to explain leaf variegation formation from the plastid development perspective.
The discovery of RNA interference(RNAi) has augmented our knowledge of gene regulation and presents a fascinating technology that has a great potential for application in genetic analysis,disease therapy,plant protection,and many other areas.In this review,we will focus on the biological functions of RNAi and its application in agriculture with a brief introduction to the history of its discovery and molecular mechanism.
MAO YingBo,XUE XueYi & CHEN XiaoYa National Key Laboratory of Plant Molecular Genetics,Institute of Plant Physiology and Ecology,Shanghai Institutes for Biological Sciences,Chinese Academy of Sciences,Shanghai 200032,China
