# Transcriptome Landscape Variation in the Genus _Thymus_
## 3 Results and Discussion
### RNA Sequencing and De Novo Transcriptome Assembly  
To obtain _Thymus_ transcriptome data, paired-end RNA-Seq libraries were constructed for _T. daenensis_ (Tdae, from Lorestan), _T. vulgaris_ (Tvul), _T. lancifolius_ (Tlan, from Kordestan), _T. persicus_ (Tper, from West Azerbaijan), and _T. pubescens_ (Tpub, from West Azerbaijan). The five libraries described above were represented by 60.98, 64.99, 65.85, 61.81, and 62.20 million reads on Illumina HiSeq 4000, respectively. To facilitate and improve quality and efficiency of assembly, a fraction of reads (28.59% on average, ranging from 22.59% to 32.41%) were removed by filtering adapter sequences and low-quality and short reads (shorter than 50 base pairs). After filtering, a total of 43.38, 43.92, 47.10, 47.62, and 43.38 million high-quality clean reads from the cDNA libraries of Tdae, Tvul, Tian, Tper, and Tpub were obtained, respectively. Clean reads obtained from samples were independently assembled de novo using Trinity, Bridger, BinPacker, and Velvet/Oases as described in Section 2, and the resultant assemblies were analyzed to evaluate quality. There are different criteria used to evaluate de novo transcriptome assembly quality, each of which has its advantages and disadvantages. As the first assembly quality metrics, assemblies were evaluated through the number of predicted transcripts and assembly size with different k-mer lengths. Among Trinity and BinPacker with k-mer 25 and Bridger with two k-mers (25 and 27 bp), Trinity produced the highest number of transcripts in all samples (ranging from 85,084 to 123,698) whilst BinPacker and Bridger with k-mer 27 perched on the opposite side. With Velvet/Oases, the total number of transcripts dropped off with an increment in k-mer size, similar to previous studies [54; 55], but increased slightly between k-mer 51 and k-mer 57. BinPacker produced a larger assembly size for all samples (ranging from 68.45 to 98.79 Mb) compared to the other programs. Results for the assembly size in Velvet/Oases showed a reversed trend as k-mer size increased. K-mer size plays an important role in increasing or decreasing the number of predicted transcripts and assembly size [55; 56]. In theory, large k-mer sizes lead to a decrease in the total number of transcripts, because high k-mer values have a tendency to produce a more contiguous assembly consisting of high-coverage transcripts [56]. This may be due to the capturing of only highly represented reads, or the better assembly of highly expressed transcripts. In contrast, low k-mer values produce a highly fragmented assembly due to sequencing errors and lack of overlap. Short k-mers can lead to the generation of multiple paths in the assembly graph. Therefore, the graph structure can be ambiguous, and the represented isoforms can be challenging to resolve. Because of ambiguous regions, a single path is almost impossible to find in the assembly [22; 56]. The results in the present study show that assembly size and the total number of contigs depend on k-mer length, which is highly linked to how the assembler handles the ambiguous paths. Bridger and BinPacker yielded N50 values ranging from 819 to 1553 bp in Tdae, 732 to 1603 bp in Tvul, 767 to 1634 bp in Tian, 999 to 1665 bp in Tper, and 818 to 1574 bp in Tpub. BinPacker produced the longest N50 value and had the highest average contig length, while Trinity performed the worst for the N50 length and average contig length in all samples. Bridger had slightly better N50 values in comparison to Trinity, similar to the results from previous research [56]. In Velvet/Oases, the N50 and average contig length slightly increased with a simultaneous increase of k-mer size to k = 29 or k = 31 before deteriorating. However, a longer N50 does not necessarily produce a better assembly, as it may indicate a high level of chimerism [55; 57], and previous research indicates that the largest N50 can artificially infer a higher quality of assembly [58; 59]. A summary of statistics for all assemblies in all species is shown in Tables S1 and S2.