-
Pavel Mazin,
Jieyi Xiong,
Xiling Liu,
Zheng Yan,
Xiaoyu Zhang,
Mingshuang Li,
Liu He,
Mehmet Somel, Yuan Yuan,
Yi-Ping Phoebe Chen,
Na Li,
Yuhui Hu,
Ning Fu,
Zhibin Ning,
Rong Zeng,
Hongyi Yang,
Wei Chen,
Mikhail Gelfand,
Philipp Khaitovich
[show abstract]
[hide abstract]
ABSTRACT: While splicing differences between tissues, sexes and species are well documented, little is known about the extent and the nature of splicing changes that take place during human or mammalian development and aging. Here, using high-throughput transcriptome sequencing, we have characterized splicing changes that take place during whole human lifespan in two brain regions: prefrontal cortex and cerebellum. Identified changes were confirmed using independent human and rhesus macaque RNA-seq data sets, exon arrays and PCR, and were detected at the protein level using mass spectrometry. Splicing changes across lifespan were abundant in both of the brain regions studied, affecting more than a third of the genes expressed in the human brain. Approximately 15% of these changes differed between the two brain regions. Across lifespan, splicing changes followed discrete patterns that could be linked to neural functions, and associated with the expression profiles of the corresponding splicing factors. More than 60% of all splicing changes represented a single splicing pattern reflecting preferential inclusion of gene segments potentially targeting transcripts for nonsense-mediated decay in infants and elderly.
Molecular Systems Biology 01/2013; 9:633. · 8.63 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Human female life expectancy is higher than that of males. Intriguingly, it has been reported that women display faster rates of age-related cognitive decline and a higher prevalence of Alzheimer's disease (AD). To assess the molecular bases of these contradictory trends, we analyzed differences in expression changes with age between adult males and females, in four brain regions. In the superior frontal gyrus (SFG), a part of the prefrontal cortex, we observed manifest differences between the two sexes in the timing of age-related changes, that is, sexual heterochrony. Intriguingly, age-related expression changes predominantly occurred earlier, or at a faster pace, in females compared to men. These changes included decreased energy production and neural function and up-regulation of the immune response, all major features of brain aging. Furthermore, we found that accelerated expression changes in the female SFG correlated with expression changes observed in AD, as well as stress effects in the frontal cortex. Accelerated aging-related changes in the female SFG transcriptome may provide a link between a higher stress exposure or sensitivity in women and the higher prevalence of AD.
Aging cell 07/2012; 11(5):894-901. · 7.55 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements.
Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation.
The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.
BMC Bioinformatics 08/2011; 12:347. · 2.75 Impact Factor
-
Mehmet Somel,
Song Guo,
Ning Fu,
Zheng Yan,
Hai Yang Hu,
Ying Xu, Yuan Yuan,
Zhibin Ning,
Yuhui Hu,
Corinna Menzel,
Hao Hu,
Michael Lachmann,
Rong Zeng,
Wei Chen,
Philipp Khaitovich
[show abstract]
[hide abstract]
ABSTRACT: Changes in gene expression levels determine differentiation of tissues involved in development and are associated with functional decline in aging. Although development is tightly regulated, the transition between development and aging, as well as regulation of post-developmental changes, are not well understood. Here, we measured messenger RNA (mRNA), microRNA (miRNA), and protein expression in the prefrontal cortex of humans and rhesus macaques over the species' life spans. We find that few gene expression changes are unique to aging. Instead, the vast majority of miRNA and gene expression changes that occur in aging represent reversals or extensions of developmental patterns. Surprisingly, many gene expression changes previously attributed to aging, such as down-regulation of neural genes, initiate in early childhood. Our results indicate that miRNA and transcription factors regulate not only developmental but also post-developmental expression changes, with a number of regulatory processes continuing throughout the entire life span. Differential evolutionary conservation of the corresponding genomic regions implies that these regulatory processes, although beneficial in development, might be detrimental in aging. These results suggest a direct link between developmental regulation and expression changes taking place in aging.
Genome Research 09/2010; 20(9):1207-18. · 13.61 Impact Factor
-
Augix Guohua Xu,
Liu He,
Zhongshan Li,
Ying Xu,
Mingfeng Li,
Xing Fu,
Zheng Yan, Yuan Yuan,
Corinna Menzel,
Na Li,
Mehmet Somel,
Hao Hu,
Wei Chen,
Svante Pääbo,
Philipp Khaitovich
[show abstract]
[hide abstract]
ABSTRACT: Transcription is the first step connecting genetic information with an organism's phenotype. While expression of annotated genes in the human brain has been characterized extensively, our knowledge about the scope and the conservation of transcripts located outside of the known genes' boundaries is limited. Here, we use high-throughput transcriptome sequencing (RNA-Seq) to characterize the total non-ribosomal transcriptome of human, chimpanzee, and rhesus macaque brain. In all species, only 20-28% of non-ribosomal transcripts correspond to annotated exons and 20-23% to introns. By contrast, transcripts originating within intronic and intergenic repetitive sequences constitute 40-48% of the total brain transcriptome. Notably, some repeat families show elevated transcription. In non-repetitive intergenic regions, we identify and characterize 1,093 distinct regions highly expressed in the human brain. These regions are conserved at the RNA expression level across primates studied and at the DNA sequence level across mammals. A large proportion of these transcripts (20%) represents 3'UTR extensions of known genes and may play roles in alternative microRNA-directed regulation. Finally, we show that while transcriptome divergence between species increases with evolutionary time, intergenic transcripts show more expression differences among species and exons show less. Our results show that many yet uncharacterized evolutionary conserved transcripts exist in the human brain. Some of these transcripts may play roles in transcriptional regulation and contribute to evolution of human-specific phenotypic traits.
PLoS Computational Biology 01/2010; 6:e1000843. · 5.22 Impact Factor
