Xian Adiconis

Full-length transcriptome assembly from RNA-Seq data without a reference genome

Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.

Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs

Massively parallel cDNA sequencing (RNA-Seq) provides an unbiased way to study a transcriptome, including both coding and noncoding genes. Until now, most RNA-Seq studies have depended crucially on existing annotations and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We applied it to mouse embryonic stem cells, neuronal precursor cells and lung fibroblasts to accurately reconstruct the full-length gene structures for most known expressed genes. We identified substantial variation in protein coding genes, including thousands of novel 5′ start sites, 3′ ends and internal coding exons. We then determined the gene structures of more than a thousand large intergenic noncoding RNA (lincRNA) and antisense loci. Our results open the way to direct experimental manipulation of thousands of noncoding RNAs and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.RNA-Seq provides an unbiased way to study a transcriptome, including both coding and non-coding genes. To date, most RNA-Seq studies have critically depended on existing annotations, and thus focused on expression levels and variation in known transcripts. Here, we present Scripture, a method to reconstruct the transcriptome of a mammalian cell using only RNA-Seq reads and the genome sequence. We apply it to mouse embryonic stem cells, neuronal precursor cells, and lung fibroblasts to accurately reconstruct the full-length gene structures for the vast majority of known expressed genes. We identify substantial variation in protein-coding genes, including thousands of novel 5′-start sites, 3′-ends, and internal coding exons. We then determine the gene structures of over a thousand lincRNA and antisense loci. Our results open the way to direct experimental manipulation of thousands of non-coding RNAs, and demonstrate the power of ab initio reconstruction to render a comprehensive picture of mammalian transcriptomes.

Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells

Recent molecular studies have shown that, even when derived from a seemingly homogenous population, individual cells can exhibit substantial differences in gene expression, protein levels and phenotypic output, with important functional consequences. Existing studies of cellular heterogeneity, however, have typically measured only a few pre-selected RNAs or proteins simultaneously, because genomic profiling methods could not be applied to single cells until very recently. Here we use single-cell RNA sequencing to investigate heterogeneity in the response of mouse bone-marrow-derived dendritic cells (BMDCs) to lipopolysaccharide. We find extensive, and previously unobserved, bimodal variation in messenger RNA abundance and splicing patterns, which we validate by RNA-fluorescence in situ hybridization for select transcripts. In particular, hundreds of key immune genes are bimodally expressed across cells, surprisingly even for genes that are very highly expressed at the population average. Moreover, splicing patterns demonstrate previously unobserved levels of heterogeneity between cells. Some of the observed bimodality can be attributed to closely related, yet distinct, known maturity states of BMDCs; other portions reflect differences in the usage of key regulatory circuits. For example, we identify a module of 137 highly variable, yet co-regulated, antiviral response genes. Using cells from knockout mice, we show that variability in this module may be propagated through an interferon feedback circuit, involving the transcriptional regulators Stat2 and Irf7. Our study demonstrates the power and promise of single-cell genomics in uncovering functional diversity between cells and in deciphering cell states and circuits.

Integrative analysis of the melanoma transcriptome

Global studies of transcript structure and abundance in cancer cells enable the systematic discovery of aberrations that contribute to carcinogenesis, including gene fusions, alternative splice isoforms, and somatic mutations. We developed a systematic approach to characterize the spectrum of cancer-associated mRNA alterations through integration of transcriptomic and structural genomic data, and we applied this approach to generate new insights into melanoma biology. Using paired-end massively parallel sequencing of cDNA (RNA-seq) together with analyses of high-resolution chromosomal copy number data, we identified 11 novel melanoma gene fusions produced by underlying genomic rearrangements, as well as 12 novel readthrough transcripts. We mapped these chimeric transcripts to base-pair resolution and traced them to their genomic origins using matched chromosomal copy number information. We also used these data to discover and validate base-pair mutations that accumulated in these melanomas, revealing a surprisingly high rate of somatic mutation and lending support to the notion that point mutations constitute the major driver of melanoma progression. Taken together, these results may indicate new avenues for target discovery in melanoma, while also providing a template for large-scale transcriptome studies across many tumor types.

Ab initio construction of a eukaryotic transcriptome by massively parallel mRNA sequencing

Defining the transcriptome, the repertoire of transcribed regions encoded in the genome, is a challenging experimental task. Current approaches, relying on sequencing of ESTs or cDNA libraries, are expensive and labor-intensive. Here, we present a general approach for ab initio discovery of the complete transcriptome of the budding yeast, based only on the unannotated genome sequence and millions of short reads from a single massively parallel sequencing run. Using novel algorithms, we automatically construct a highly accurate transcript catalog. Our approach automatically and fully defines 86% of the genes expressed under the given conditions, and discovers 160 previously undescribed transcription units of 250 bp or longer. It correctly demarcates the 5′ and 3′ UTR boundaries of 86 and 77% of expressed genes, respectively. The method further identifies 83% of known splice junctions in expressed genes, and discovers 25 previously uncharacterized introns, including 2 cases of condition-dependent intron retention. Our framework is applicable to poorly understood organisms, and can lead to greater understanding of the transcribed elements in an explored genome.

Fenofibrate Effect on Triglyceride and Postprandial Response of Apolipoprotein A5 Variants The GOLDN Study

Objective—Apolipoprotein A5 (APOA5) is a key determinant of plasma triglyceride (TG) concentrations. Genetic variation at the APOA5 locus could be responsible for some of the observed differences in response to fenofibrate therapy. Methods and Results—We examined the association between tag SNPs (−1131T>C and 56C>G) at APOA5 and TG and HDL-C response to fenofibrate and a postprandial lipid challenge in 791 men and women participating in the GOLDN study. After 3-week drug treatment, APOA5 56G carriers displayed significant decrease in TG (P=0.006), and increase in HDL-C (P=0.002) levels relative to their basal values in the fasting state when compared with noncarriers (a TG reduction of −35.8±2.8% versus −27.9±0.9% and a HDL-C increase of 11.8±1.3% versus 6.9±0.5%, respectively). In the postprandial lipemia after a fat load, the 56G carriers showed a significant decrease in the area under curve for TG and increase for HDL-C than the noncarriers. These diverse beneficial responses of 56G carriers to fenofibrate were further characterized by a higher increase in large LDL-C concentrations and LDL size. On the other hand, subjects with different APOA5-1131T>C genotypes showed no significant response to fenofibrate intervention. Conclusion—This study suggests that the APOA5 56G carriers benefited more from the fenofibrate treatment than noncarriers in lowering plasma TG and increasing HDL-C levels.

Differential effects of the C1431T and Pro12Ala PPARγ gene variants on plasma lipids and diabetes risk in an Asian population

We investigated the association of C1431T and Pro12Ala polymorphisms at the peroxisome proliferator-activated receptor γ (PPARγ) locus with plasma lipids and insulin resistance-related variables, according to diabetes status, in a large and representative Asian population from Singapore consisting of 2,730 Chinese, 740 Malays, and 568 Indians. Moreover, we estimated the diabetes risk and examined gene-nutrient interactions between these variants and the ratio of polyunsaturated fatty acid to saturated fat (SFA) in determining body mass index (BMI) and fasting insulin. We found differential effects of these gene variants. The Pro12Ala polymorphism was more associated with plasma lipids and fasting glucose concentrations, whereas the C1431T polymorphism was related to the risk of diabetes. Carriers of the 12Ala allele had higher HDL-cholesterol than did Pro12Pro homozygotes (P < 0.05), and the effect of the 12Ala allele on fasting glucose was modified by diabetes status (P < 0.001). After controlling for confounders, carriers of the T allele had decreased risk of diabetes compared with CC homozygotes [odds ratio (OR) 0.73, 95% confidence interval (CI) 0.58–0.93; P = 0.011]; this effect was stronger in Indians (OR 0.38, 95% CI 0.15–0.92; P = 0.032). For both polymorphisms, normal subjects carrying the less prevalent allele had higher BMI (P < 0.05). The PUFA/SFA did not modify the effect of these polymorphisms on BMI or insulin.

Dietary intake of n-6 fatty acids modulates effect of apolipoprotein A5 gene on plasma fasting triglycerides, remnant lipoprotein concentrations, and lipoprotein particle size : The framingham heart study

Background— Apolipoprotein A5 gene (APOA5) variation is associated with plasma triglycerides (TGs). However, little is known about whether dietary fat modulates this association. Methods and Results— We investigated the interaction between APOA5 gene variation and dietary fat in determining plasma fasting TGs, remnant-like particle (RLP) concentrations, and lipoprotein particle size in 1001 men and 1147 women who were Framingham Heart Study participants. Polymorphisms −1131T>C and 56C>G, representing 2 independent haplotypes, were analyzed. Significant gene–diet interactions between the −1131T>C polymorphism and polyunsaturated fatty acid (PUFA) intake were found (P<0.001) in determining fasting TGs, RLP concentrations, and particle size, but these interactions were not found for the 56C>G polymorphism. The −1131C allele was associated with higher fasting TGs and RLP concentrations (P<0.01) in only the subjects consuming a high-PUFA diet (>6% of total energy). No heterogeneity by sex was found. These interactions showed a dose-response effect when PUFA intake was considered as a continuous variable (P<0.01). Similar interactions were found for the sizes of VLDL and LDL particles. Only in carriers of the −1131C allele did the size of these particles increase (VLDL) or decrease (LDL) as PUFA intake increased (P<0.01). We further analyzed the effects of n-6 and n-3 fatty acids and found that the PUFA–APOA5 interactions were specific for dietary n-6 fatty acids. Conclusions— Higher n-6 (but not n-3) PUFA intake increased fasting TGs, RLP concentrations, and VLDL size and decreased LDL size in APOA5 −1131C carriers, suggesting that n-6 PUFA–rich diets are related to a more atherogenic lipid profile in these subjects.

PPARGC1A variation associated with DNA damage, diabetes, and cardiovascular diseases: the Boston Puerto Rican Health Study.

OBJECTIVE—Individuals with type 2 diabetes exhibit higher DNA damage and increased risk of cardiovascular disease (CVD). However, mechanisms underlying the association between DNA damage and development of type 2 diabetes and CVD are not understood. We sought to link peroxisome proliferator–activated receptor-γ coactivator-1 α (PPARGC1A), a master transcriptional regulator of mitochondrial oxidative phosphorylation and cellular energy metabolism, with DNA damage, type 2 diabetes, and CVD. RESEARCH DESIGN AND METHODS—We measured DNA damage as urinary 8-hydroxydeoxyguanosine (8-OHdG) concentration and examined the relationship between nine PPARGC1A genetic variants, DNA damage, type 2 diabetes, and self-reported CVD in 959 participants of the Boston Puerto Rican Health Study. RESULTS—With respect to urinary 8-OHdG, PPARGC1A variants showed significant association, and PPARGC1A haplotypes exhibited significant association after correction for multiple testing. Two independent PPARGC1A variants associated significantly with type 2 diabetes (odds ratios [ORs] 1.35 and 2.46; P = 0.045 and <0.001). Carriers of minor alleles of two other PPARGC1A variants, both in strong linkage disequilibrium and associated with lower DNA damage, showed lower prevalence of CVD (ORs 0.53 and 0.65; P = 0.030 and 0.175). Moreover, we found that physical activity correlated negatively with DNA damage. CONCLUSIONS—It is plausible that low physical activity combined with risk haplotyes contribute to the high prevalence of type 2 diabetes in this population. We propose that PPARGC1A influences development of type 2 diabetes and CVD via DNA damage. Increasing physical activity, which induces PPARGC1A expression, is a potential strategy to slow DNA damage, thereby decreasing the risk of CVD for individuals with type 2 diabetes.

The TaqIB and −629C>A polymorphisms at the cholesteryl ester transfer protein locus: associations with lipid levels in a multiethnic population. The 1998 Singapore National Health Survey

The Singapore population comprises Chinese, Malays and Asian Indians. Within this population, Asian Indians have the highest rates of coronary heart disease, whereas Chinese have the lowest. Conversely, Indians have the lowest high‐density lipoprotein cholesterol (HDL‐C) concentrations, followed by Malays and Chinese. We studied the TaqIB and −629C>A polymorphisms at the CETP locus in 1300 Chinese, 364 Malay and 282 Asian Indian men, and in 1558 Chinese, 397 Malay and 306 Asian Indian women, to determine whether these polymorphisms are responsible for the ethnic difference in HDL‐C concentration. The frequency of the B2 allele in Chinese, Malays and Indians was 0.384, 0.339 and 0.449 in men, and 0.379, 0.329 and 0.415 in women, respectively (p < 0.001). For the A‐629 allele, the relative frequencies were 0.477, 0.423 and 0.592 in men and 0.486, 0.416 and 0.575 in women (p < 0.001). The two polymorphisms were in linkage disequilibrium (D / Dmax= 0.9772, p < 0.00001). The B2 and the A‐629 alleles were associated with increased HDL‐C concentrations in a dose‐dependent manner. The B2 allele continued to show an association with HDL‐C concentration, even after controlling for the genotype at position −629. Dietary cholesterol showed a significant interaction with the TaqIB polymorphism in determining HDL‐C concentrations in Indians and Malays, but not in Chinese. In conclusion, the high frequencies of these polymorphisms in Asian Indians could not explain the observed ethnic differences in HDL‐C concentration. Moreover, we observed an ethnic‐specific interaction among dietary cholesterol, the TaqIB polymorphism and HDL‐C concentrations.