Peer review of: Comprehensive identification of mRNA isoforms reveals the diversity of neural cell-surface (2020)

Reviewers' comments: 

Reviewer #1 (Remarks to the Author): 

This is a very well written manuscript describing a comprehensive set of studies that identified an 
important Crb1 isoform that was not previously known. The manuscript is quite long however, and 
would benefit by some re-focussing. At 85 pages overall and some 20+ pages of text, it would be 
improved my moving some of the content to the supplemental data section. I as a reviewer appreciate 
the concept that the discovery of the new, clearly important disease causing isoform of Crb1 was the 
result of an unbiased screen - not looking for retina disease genes, nor retina specific genes, but as a 
result of a screen for neuronal cell surface molecules. However I believe that a major portion of the 
interest will come from retina disease research community, and moving the retinal disease component 
to a more prominent position in the abstract and perhaps the title as well will improve the focus. As it 
now reads, it begins with a strong focus on the screening techniques, and the validation of the 
identification of the important crb1 disease causing isoform by the KO mouse model is not apparent 
until the reader is well into it. Overall, the finding does turn on its head over a decade of work on the " 
other' isoform of Crb1 and many papers on knocking out and replacing this other isoform with mixed 
results, and this is a major finding of the work, which should be emphasized early in the text. 

Reviewer #2 (Remarks to the Author): 

This manuscript from Ray et al. addresses a glaring gap in our existing gene annotation, namely how 
poorly the current annotation catalogs the set of full-length mRNA transcript isoforms. This gap creates 
a whole lot of confusion and wasted time, as cogently laid out in the manuscript’s introduction. The gap 
reflects a glaring technological blind spot that the authors partially address by developing a capture 
approach that enables full-length sequencing of mRNAs on the PacBio platform. While this approach is 
not, by a long shot, a genome-wide approach (30 genes only here), it is very well executed. Moreover, 
the authors go to surprising lengths to demonstrate the full power of the information they are 
generating, including an in-depth study of a new CRB1 isoform, featuring an antibody and knockouts 
that enable the new isoform to be detected and studied functionally in the retina. They show that the 
newly identified isoform is important for the integrity of junctions in the outer limiting membrane. 

This manuscript is a vivid reminder of the limitations of our existing annotation, and it goes all the long 
way from discovery of thousands of new isoforms to demonstration of the functional importance of one 
of them. Although I have never before recommended publication of a manuscript without any suggested 
revisions, in this case it seems most appropriate to do so. 

Other comments: 

This manuscript is not just refreshingly well-written, it is one of the more lucid manuscripts I have ever 
read. 

The treeplot (e.g., Figure 2D) is a fantastic way to show frequency of transcript isoforms -- I wish this had 
been used in some of the early RNA-seq studies on alternative splicing, where it was so hard to 
understand the significance of the diversity that was reported in the absence of this kind of 
transparency. 

Reviewer #3 (Remarks to the Author): 

In the ms by Ray et.al, the authors developed a new strategy to characterize the full-length sequence of 
various mRNA isoforms derived from a target set of genes. The so-termed long-read capture sequencing 
(lrCaptureSeq) used biotinylated probes to enrich cDNAs from target transcripts, which were then 
sequenced by using PacBio long read technology. They applied it on 30 genes encoding cell-surface 
proteins expressed across development in mouse retina and brain, and identified a total of 4116 
different isoforms, with a median 50 isoforms per gene. This dataset largely expanded the current 
isoform annotation and a major fraction of newly discovered isoforms could encode novel protein 
isoforms, many of which could be supported with MS-based proteomics data. Finally, they focused on 
one gene CRB1, for which they discovered a novel isoform expressed in photoreceptors. By isoform-
specific genetic perturbation, the authors demonstrated the important function of this novel isoforms 
and explained the previous inconsistent phenotypes between different mouse mutants affecting 
different isoforms. Overall, by presenting a new strategy (although not the first one) of applications to 
many different systems, the manuscript should be of interest to broad audience. However, a few points 
listed below should be addressed before accepted for publication. 

1) How can the authors be sure of the completeness of their isoform sequences, particularly the 5’end 
(strand switch is not necessarily happening only at the intact 5’end)? They should use independent 
approach, such as CAGE and 3’end sequencing to validate both ends of their isoforms. 
2) As I understood, the authors estimated the cellular abundance of different isoforms based on the 
number of corresponding pacbio reads. Given the potential biases introduced during capture and pacbio 
sequencing, such estimation might be inaccurate and this should be addressed. 
3) The authors selected the cDNA size between 4.5 and 10kb for library preparation. Will this introduce 
false negatives, i.e. how can they assure no. isoform beyond the size range? They should collect 5’/3’ 
end RNA-sequencing data (see 1)) to estimate false negatives. 
4) In the part of MS-based proteomics validation, out of 686 peptides, only 35 were not matched to 
Uniprot, but to their references. This corresponded to a 5% gain, instead of 25% as they claimed (Page 
12, line 252). The authors should state clearly what fraction of novel protein isoform as well as 
annotated isoforms were supported by peptide findings and what are the factors affecting it, e.g. the 
isoform abundance. 
5) IN page 19, the authors suggested that the isoform diversity they described is likely to be typical for 
the upper 10-15% of the isoform diversity distribution. In addition to the fact that 30 genes studied in 
this ms is of specific function (the authors discussed this point), the neuronal tissues used here is also 

special. Likely, the different isoforms identified here are present in different cell types and brain, which 
consists of more diversified types of cells, would potentially manifest higher isoform diversity. 
Moreover, when discussing the diversity, not only the number of isoforms, but also the evenness of 
their abundance distribution are important metrics. Therefore, they should be cautious to generalize 
their speculation and use also Shannon index as the measurement of isoform diversity. 
6) In page 18, the authors suggested that their full-length mRNA data could be integrated with single-cell 
RNA sequencing (scRNA-seq) data to study the temporal and spatial isoform-specific expression pattern. 
Given the majority of current scRNA-seq technologies could only capture 3’ or 5’ end sequences. The 
potential usage of such integration would be rather limited to those with distinct 5’/3’ end, as the case 
for CRB1 gene.