Ciona

Reads from each library were trimmed using a procedure described in Shi et al. [4 (link)] to globally optimize read quality over all start and stop positions using quality parameters computed with ELAND. The reads were then aligned to the Ciona genome (JGI version 1.0) using BLAST with an E-value of 10, a word size of 7, and a gap penalty of 10,000. Hits to the genome were then filtered to only include those with an E-value ≤ 0.01.
After the reads have been aligned to the genome, read regions are defined. A read region is defined as a contiguous span of overlapping reads. Only reads with fewer than five hits to the genome are considered for the purposes of defining the read regions. Read regions shorter than 160 nucleotides and that do not overlap a repeat region or a tRNA are then used as candidate loci to be tested as a possible miR.
Our approach for the identification of microRNAs using high-throughput sequencing reads is to compute a set of quantities for each candidate locus, and by using thresholds for each quantity we define a space of values that contain the microRNA loci.
A key challenge to the program is to designate all read products on a potential hairpin as corresponding to miR/miR*, moR/moR* and/or loops because our program relies on this information to test whether the products are consistent with miRNA biogenesis. Once candidate loci are folded, all reads that overlap the locus are grouped to define 'products', and these products are then identified as miR, moR, or loop products according to Figure S1 in Additional file 1.
Many quantities we consider pertain to the structure of the hairpin and positions of reads. The distance between a miR and moR on the same arm of the hairpin, the offset of the 5' positions of products that overlap at least 2 nucleotides on the same arm of the hairpin, and the offset of overlapping products on opposite arms of the hairpin are used to evaluate the spacing and distribution of products. The 5' heterogeneity, defined as the fraction of reads within the miR product with the same 5' position as the predominant splice variant of this product, is evaluated for the most abundant miR product. Furthermore, we define the AAPD as the average distance between sense and antisense products that overlap, and apply this measure across all sense products that overlap antisense products. Additionally, the minimum number of base pairs per nucleotide for either a miR or miR* product is used to evaluate the locus.
Two additional quantities take into account information from the sequencing data outside the candidate locus under consideration. The average number of hits to the genome for reads within the most abundant miR product is evaluated as an additional level of repeat filtering. Finally, after producing a list of predicted positive loci using the above measures, we define the non-miR-neighbor-count as the number of read regions that do not overlap a predicted positive locus within a ± 1-kb window surrounding the locus in question. All read regions, including those overlapping repeat regions, tRNAs, and those longer than 160 nucleotides, are considered for this calculation.
Each of these quantities has user-defined thresholds that can be adjusted to meet the desired level of stringency of the predictions. The default values used in this analysis are summarized in Table S1 in Additional file 1. The software for miRTRAP and other resources are available on our website [49 ].

Each node of each tree was classified in comparison to the known evolutionary relationships of the animals. For example, if the gene cluster tree contains exactly four members, and one from each animal, then the parsimonious inference is that no gene duplication occurred. In the case of a similar cluster, but where one member is missing, this is a gene loss in a single group. Gene cluster trees can show duplications specific to individual lineages by having two genes clustered together for the same animal. A gene duplication that occurred before the split of fish from tetrapods is seen as a duplicated tree of the animal relationships after their splitting from Ciona and, similarly, a gene duplication that occurred in tetrapods but before the split of the mouse and human lineages is seen as a duplication of the mouse–human group. Combinations of these, such as a duplication for tetrapods followed by a loss in one of the tetrapod lineages, are also seen and scored (see Figure 3).
The sorting of orthologous and paralogous relationships for each gene cluster provides an effective tool for improving the inferences of gene function by allowing annotations from well studied genomes to be transferred to the orthologous genes of other species. Inferring function from orthology is expected to be more accurate than using sequence similarity alone, since the latter tends to incorrectly associate slowly evolving paralogs. We provide a web based resource for this sorting at http://phigs.org/.

Transcriptome data of C. robusta organs were obtained from a published dataset [24 (link)], from which a gene expression matrix of 67,716 transcriptional features were used for the next step of analysis. The public ID of the published dataset was PRJNA731286 in the NCBI bio-project. Cross-species homolog gene alignment was conducted with localized BLASTP, in which the longest transcript for each gene in Styela was aligned against the transcript dataset of C. robusta and the max_target_seqs was set to 1. The expression matrix of C. robusta in reads per kilobase per million mapped reads (RPKM) format was merged with Styela endostyle expression profile in fragments per kilobase per million mapped reads (FPKM) version. Homolog gene pairs with an expression value larger than 0.5 in Ciona organs (except endostyle) were eliminated. Genes with expression values larger than 1 in Styela endostyle were defined as OSGs of S. clava endostyle. A total of 104 OSGs were obtained (Supplementary Table S1).

The density of sperm in the undiluted semen was calculated by counting the number of diluted sperm with a hemocytometer. Since Phallusia sperm are almost quiescent even if suspended in ASW (pH 8.2) [25 (link)], sperm motility was pre-activated by suspension of semen into 100× the volume of the medium (pH 9.5 ASW) for 10–15 min. Then, the pH was re-adjusted to experimental conditions by diluting the activated sperm more than 100-fold in the measuring medium before insemination. Pre-activation of Ciona sperm was induced by 1 mM theophylline, as described elsewhere [40 (link)].

To examine the release of the sperm attractant from the eggs, the egg-conditioned seawater was used [25 (link)]. One volume of eggs was suspended in 15 volumes of ASW with different pH and incubated for 16–20 h at 4 °C. The egg suspensions were centrifuged at 20,000× g for 15 min at 4 °C and the obtained supernatant was designated as the egg-conditioned seawater.
Sperm motility and chemotaxis were examined, as previously described [40 (link)]. Pre-activation of sperm motility was performed, as described above. The pre-activated sperm suspension was mounted on the observation chamber pretreated with bovine serum albumin, and sperm movements around a micropipette tip containing the egg-conditioned seawater or 1 µM SAAF were recorded with a digital camera (Nikon1, Nikon, Tokyo, Japan) attached to a BX51 microscope (Olympus, Tokyo, Japan) under darkfield illumination. To analyze sperm chemotaxis around the egg, the dechorionated egg was placed directly in the observation chamber. For the chemotaxis assay, forced punctuation of the eggs was performed using a glass needle. The velocities and trajectories of spermatozoa were analyzed using the Bohboh software (BohbohSoft, Tokyo, Japan) [41 ]. The linear equation-based chemotaxis index (LECI) was calculated, as described previously [42 (link)].
The motility parameters, including curvilinear velocity (VCL) of the Ciona sperm, were observed by a microscope (BX 51, Olympus) equipped with the CCD camera (acA1300-200uc, Basler, Ahrensburg, Germany), and analyzed using the CASA system (SCA, Microptic, Barcelona, Spain) with sperm counting chamber slides (SC20-01-04-B, Leja, Nieuw-Vennep, The Netherlands). Spermatozoa with STR > 80 (%) and VCL > 10 (µm/s) were classed as motile. For precise information on the individual movement parameters, please see [43 (link)].