Although the effects of arbuscular mycorrhizal fungi(AMF)on host plants have been well documented,whether the effects of AMF on parental generations affect offspring performance is not fully clear.We conducted a commo...Although the effects of arbuscular mycorrhizal fungi(AMF)on host plants have been well documented,whether the effects of AMF on parental generations affect offspring performance is not fully clear.We conducted a common garden experiment to determine whether AMF status of host plants(Medicago truncatula)affects phenotype and transcriptome expression of their offspring.Seeds from four type parental treatments(low-phosphorus(P)soil without AMF,low-P soil with AMF,high-P soil without AMF and high-P soil with AMF)were grown under low-P(LPS)and normal-P soil(OHS)conditions.The fowering pattern of LP offspring was similar to their parents,such that plants with AMF fowered earlier than those without AMF under OHS condition but were opposite under LPS condition.The transcriptome differential analysis showed that some differential transcripts(45 for parental plants growing under low-P condition and 3 for parental plants growing under high-P condition)expression patterns between offspring were comparable,and that only affected by parental AMF status regardless of the P environment that offspring was grown.Others(146 for parental plants growing under low-P condition and 2 for parental plants growing under high-P condition),however,were affected both by the parental AMF status and the offspring P environment.In addition,the number of differential transcripts between offspring whose parental plants grew under high-P condition was far less than under low-P condition.These results indicate that AMF may not only affect the current generation of host plants but also affect the offspring especially when their parents have experienced a stressful environment.展开更多
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...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.展开更多
基金supported by the National Natural Science Foundation of China(31470483,31570411)the Postdoctoral Science Foundation of China(2021M693732)the Postdoctoral Science Foundation of Chongqing,China(cstc2021jcyj-bshX0165)。
文摘Although the effects of arbuscular mycorrhizal fungi(AMF)on host plants have been well documented,whether the effects of AMF on parental generations affect offspring performance is not fully clear.We conducted a common garden experiment to determine whether AMF status of host plants(Medicago truncatula)affects phenotype and transcriptome expression of their offspring.Seeds from four type parental treatments(low-phosphorus(P)soil without AMF,low-P soil with AMF,high-P soil without AMF and high-P soil with AMF)were grown under low-P(LPS)and normal-P soil(OHS)conditions.The fowering pattern of LP offspring was similar to their parents,such that plants with AMF fowered earlier than those without AMF under OHS condition but were opposite under LPS condition.The transcriptome differential analysis showed that some differential transcripts(45 for parental plants growing under low-P condition and 3 for parental plants growing under high-P condition)expression patterns between offspring were comparable,and that only affected by parental AMF status regardless of the P environment that offspring was grown.Others(146 for parental plants growing under low-P condition and 2 for parental plants growing under high-P condition),however,were affected both by the parental AMF status and the offspring P environment.In addition,the number of differential transcripts between offspring whose parental plants grew under high-P condition was far less than under low-P condition.These results indicate that AMF may not only affect the current generation of host plants but also affect the offspring especially when their parents have experienced a stressful environment.
基金supported by the National Basic Research Program of China (Grant Nos. 2010CB945401, 2007CB108800)National Natural Science Foundation of China (Grant Nos. 30870575,31071162,31000590)Science and Technology Commission of Shanghai Municipality (Grant No. 11DZ2260300)
文摘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.
