An approximate Bayesian approach for mapping paired-end DNA reads to a reference genome

Shrestha, Anish Man Singh; Frith, Martin C.

doi:10.1093/bioinformatics/btt073

Cited by 17 publications

(20 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1. Map reads to the allopolyploid reference genome (STAR (ver 2.5.2b) [20], LAST (ver 809) [21,22]).…”

Section: Standard Rna-seq Analysismentioning

confidence: 99%

See 1 more Smart Citation

Homeolog expression quantification methods for allopolyploids

Kuo¹,

Hatakeyama

Tameshige

et al. 2018

Preprint

View full text Add to dashboard Cite

Genome duplication with hybridization, or allopolyploidization, occurs in animals, fungi, and plants, and is especially common in crop plants. There is increasing interest in the study of allopolyploids due to advances in polyploid genome assembly, however the high level of sequence similarity in duplicated gene copies (homeologs) pose many challenges. Here we compared standard RNA-seq expression quantification approaches used currently for diploid species against subgenome-classification approaches which maps reads to each subgenome separately. We examined mapping error using our previous and new RNA-seq data in which a subgenome is experimentally added (synthetic allotetraploid Arabidopsis kamchatica) or reduced (allohexaploid wheat Triticum aestivum versus extracted allotetraploid) as ground truth. The error rates in the two species were very similar. The standard approaches showed higher error rates (> 10% using pseudo-alignment with Kallisto) while subgenome-classification approaches showed much lower error rates (< 1% using EAGLE-RC, < 2% using HomeoRoq). Although downstream analysis may partly mitigate mapping errors, the difference in methods was substantial in hexaploid wheat, where Kallisto appeared to have systematic differences relative to other methods. Only approximately half of the differentially expressed homeologs detected using Kallisto overlapped with those by any other method. In general, disagreement in low expression genes was responsible for most of the discordance between methods, which is consistent with known biases in Kallisto. We also observed that there exist uncertainties in genome sequences and annotation which can affect each method differently. Overall, subgenome-classification approaches tend to perform better than standard approaches with EAGLE-RC having the highest precision.

show abstract

“…1. Map reads to the allopolyploid reference genome (STAR (ver 2.5.2b) [20], LAST (ver 809) [21,22]).…”

Section: Standard Rna-seq Analysismentioning

confidence: 99%

“…We test, to the best of our knowledge, all known approaches to quantify expression in polyploids with four approaches: 1. A standard genome alignment based RNA-seq analysis on the full allopolyploid reference genome with two different alignment tools STAR [20] and LAST [21,22]. [23] on the full allopolyploid transcriptome.…”

Section: Introductionmentioning

confidence: 99%

Homeolog expression quantification methods for allopolyploids

Kuo¹,

Hatakeyama

Tameshige

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Despite the critical differences, the HLA gene sequences are highly similar resulting in very high multi-mapping of the reads. Thus, we implemented the strategy of assessing allele-specific expression by aligning reads, using last [38] only to selected reference sequences extracted from the IMGT/HLA HLA reference database.…”

Section: Discussionmentioning

confidence: 99%

HLA RNAseq reveals high allele-specific variability in mRNA expression

Johansson

Koskela

et al. 2018

Preprint

View full text Add to dashboard Cite

18The HLA gene complex is the most important, single genetic factor in susceptibility to most 19 diseases with autoimmune or autoinflammatory origin and in transplantation matching. The majority of 20 the studies have focused on the huge allelic variation in these genes; only a few studies have explored 21 differences in expression levels of HLA alleles. To study the expression levels of HLA alleles more 22 systematically we utilised two different RNA sequencing methods. Illumina RNAseq has a high 23 sequencing accuracy and depth but is limited by the short read length, whereas Oxford Nanopore's 24 technology can sequence long templates, but has a poor accuracy. We studied allelic mRNA levels of 25 HLA class I and II alleles from peripheral blood samples of 50 healthy individuals. The results 26 demonstrate large differences in mRNA expression levels between HLA alleles. The method can be 27 applied to quantitate the expression differences of HLA alleles in various tissues and to evaluate the role 28 of this type of variation in transplantation matching and susceptibility to autoimmune diseases. 29 3 30 Author Summary 31 32Even though HLA is widely studied less is known of its allele-specific expression. Due to the pivotal role 33 of HLA in infection response, autoimmunity, and transplantation biology its expression surely must play 34 a part as well. In hematopoietic stem cell transplantation the challenge often is to find a suitable HLA-35 matched donor due to the high allelic variation. Classical HLA typing methods do not take into account 36 HLA allele-specific expression. However, differential allelic expression levels could be crucial in finding 37 permissive mismatches in order to save a patient's life. Additionally, differential HLA expression levels 38 can lead into beneficial impact in viral clearance but also undesirable effects in autoimmune diseases. To 39 study HLA expression we developed a novel RNAseq-based method to systematically characterize allele-40 specific expression levels of classical HLA genes. We tested our method in a set of 50 healthy individuals 41 and found differential expression levels between HLA alleles as well as interindividual variability at the 42 gene level. Since NGS is already well adopted in HLA research the next step could be to determine HLA 43 allele-specific expression in addition to HLA allelic variation and HLA-disease association studies in 44 various cells, tissues, and diseases. 45 54 reaction (PCR) and the mean fluorescence intensity (MFI).[3-10] The differential expression of HLA 55 alleles has been associated with immunologically mediated diseases, such as Crohn's disease [11] and 56 HIV [6,12], follicular lymphoma[7], and the outcome of HSCT through the risk of graft versus host 57 disease (GvHD)[8,9]. In fact, incompatibilities between the donor and the recipient in HSCT have made 58 the expression differences of HLA molecules an interesting target for finding permissive mismatches. 59 Although currently only the qualitative HLA typing is considered in dono...

show abstract

“…The resulting partial alignments are filtered according to their specificity as given by an alignment posterior, in addition to the posterior probability the read is in fact concordant. We adopt a strategy for calculation of alignment posteriors similar to [12]. Let x (1) , x (2) be alignment locations of paired ends r (1) , r (2) respectively.…”

Section: Probabilistic Partial Alignment For Identification Of Potentmentioning

confidence: 99%

“…Calculate the prior probability of observing alignment pair x (1) , x (2) as given by Equation 8. Note that [12] use a prior that assumes pairs of discordant alignments are drawn independently from the genome length, resulting in an infinitesimally small prior for all discordant alignments. By contrast, we assume that discordant status and one alignment location in the pair is sufficient to fully specify a prior on the pair, since a true tumour genome will not contain all possible pairs of positions as breakpoints.…”

Section: Probabilistic Partial Alignment For Identification Of Potentmentioning

confidence: 99%