PotatoMASH—A Low Cost, Genome-Scanning Marker System for Use in Potato Genomics and Genetics Applications
Round 1
Reviewer 1 Report
The authors were successful in implementing a low-cost GT-Seq platform for genotyping potato in combination with a haplotag approach. They have demonstrated it’s effectiveness through generating a genetic map of markers and doing a QTL analysis of fry quality. The description of the methods provided a lot of details and the figures providing an overview of the methods were well done.
The strategy for GT-Seq involved targeting euchromatic regions outside of the centromeric heterochromatin to enable a cost-reduction. The authors indicate publications by others that they used to guide decisions on which euchromatic regions to include in Potato-MASH platform. Lines 551-559 have some discussion on this approach to reducing genome representation. However, it would be good to get some additional discussion on the frequency of genetic variation in heterochromatic regions and the risk is of using a euchromatic approach. Are there situations where a euchromatic approach is not suitable?
Figure 7 showed that there is a QTL using analysis with multiallelic haplotypes, but not SNPs. Please explain further. Did the haplotypes carry any of the biallelic SNPs?
Line 4: Change “allows to genotype” to “allows genotyping of”
Line 8: Change “quantitative loci traits” to “quantitative trait loci”
Line 8 : Change “Genome-” to “genome-”
Line 146, 271: Why was DM_v4.04 used and not v6.1?
Line 232: Include a brief description of normalization strategy used in Sequal Prep. This is important as studies are done to compare normalized to non-normalized library preps.
Line 291: change “Excell” to “Excel” and include manufacturer information
Line 583: change “to follow” to “following”
Fig. 3: Suggestion to add steps for biallelic SNP calling and SMAP haplotyping.
Author Response
Please see the attached pdf file with our answers. You can either download author-coverletter-xxx.vx.pdf or click "report notes".
Our modifications in the manuscript are highlighted in the reviewed manuscript pdf in yellow. The lines modified in the reviewed version are also indicated in ours answers.
Author Response File: Author Response.pdf
Reviewer 2 Report
Leyva-Pérez described a low-cost, genome-scanning marker system, PotatoMASH, which could efficiently investigate variation in the potato genome. Authors have demonstrated that PotatoMASH could simultaneously diagnose the presence of target pest resistance markers and track haplotype variation for hundreds to a few thousands of samples. Overall, this manuscript is of high quality in terms of writing and presentation. I have several suggestions as follows:
Lines 86 123; the potato genome paper should be cited.
Line 146; I warmly suggest to to use the latest version of the potato reference genome.
Line 179 T=57C should be T=57°C
Line 180 3mM should be 3 mM
Line 181 2000bp should be 2000 bp
Line 188 100μM should be 100 μM
Figure 4 It is better to indicate the centromeric region.
Part of the information on the x-axis of Figure 6a is missing.
The authors would ideally provide sequence information for the different haplotypes identified in the Supplementary Data.
Author Response
Please see the attached pdf file with our answers. You can either download author-coverletter-xxx.vx.pdf or click "report notes".
Our modifications in the manuscript are highlighted in the reviewed manuscript pdf in yellow. The lines modified in the reviewed version are also indicated in ours answers.
Author Response File: Author Response.pdf
Reviewer 3 Report
This is a well-written manuscript that describes the development of a flexible and low-cost marker assay for assessing haplotypes (**and not just individual SNPs**) at several hundred well-distributed sites across the potato genome. I’m a potato breeder and have long wanted a haplotype-sensitive marker system for potato – a joy to see one finally developed! PotatoMASH markers will find widespread use.
A few editorial comments, and one scientific:
1. Abstract, line 2. evaluated 339 multi-allelic regions, not designed a panel of 339 multi-allelic regions
2. Abstract, line 7. locus, not loci
3. Abstract, line 8. quantitative trait loci, not quantitative loci traits
4. Line 291. Excel, not Excell.
5. In the discussion, I’d like to see a brief explanation of why LG5 (especially; also true for a few other LGs) has a large genetic distance gap, i.e., between 5 and 6 Mb, genetic map jumps almost 15 cM. Did markers in this region get filtered out during data processing? Or is this region especially recombinogenic? Anyone who cares about the short arm of chromosome 5 (and there are many of us) would like to understand what’s happening.
Author Response
Please see the attached pdf file with our answers. You can either download author-coverletter-xxx.vx.pdf or click "report notes".
Our modifications in the manuscript are highlighted in the reviewed manuscript pdf in yellow. The lines modified in the reviewed version are also indicated in ours answers.
Author Response File: Author Response.pdf