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Background Insertions/deletions (InDels) and more specifically presence/absence variations (PAVs) are pervasive in several species and have strong functional and phenotypic effect by removing or drastically modifying genes. Genotyping of such variants on large panels remains poorly addressed, while necessary for approaches such as association mapping or genomic selection. Results We have developed, as a proof of concept, a new high-throughput and affordable approach to genotype InDels. We first identified 141,000 InDels by aligning reads from the B73 line against the genome of three temperate maize inbred lines (F2, PH207, and C103) and reciprocally. Next, we designed an Affymetrix® Axiom® array to target these InDels, with a combination of probes selected at breakpoint sites (13%) or within the InDel sequence, either at polymorphic (25%) or non-polymorphic sites (63%) sites. The final array design is composed of 662,772 probes and targets 105,927 InDels, including PAVs ranging from 35 bp to 129kbp. After Affymetrix® quality control, we successfully genotyped 86,648 polymorphic InDels (82% of all InDels interrogated by the array) on 445 maize DNA samples with 422,369 probes. Genotyping InDels using this approach produced a highly reliable dataset, with low genotyping error (~ 3%), high call rate (~ 98%), and high reproducibility (> 95%). This reliability can be further increased by combining genotyping of several probes calling the same InDels (< 0.1% error rate and > 99.9% of call rate for 5 probes). This “proof of concept” tool was used to estimate the kinship matrix between 362 maize lines with 57,824 polymorphic InDels. This InDels kinship matrix was highly correlated with kinship estimated using SNPs from Illumina 50 K SNP arrays. Conclusions We efficiently genotyped thousands of small to large InDels on a sizeable number of individuals using a new Affymetrix® Axiom® array. This powerful approach opens the way to studying the contribution of InDels to trait variation and heterosis in maize. The approach is easily extendable to other species and should contribute to decipher the biological impact of InDels at a larger scale.

Soybean (Glycine max L.) is gaining in importance due to its many uses, including as a food crop and a source of industrial products, among others. Increasing efforts are made to accelerate soybean research and develop new soybean varieties to meet global demands. Soybean research, breeding, identification, and variety protection all rely on precise genomic information. While DNA markers are invaluable tools for these purposes, the older generations, especially those developed before the advent of genome sequencing, lack precision and specificity. Thankfully, advancements in genome sequencing technologies have generated vast amounts of sequence data over the past decade, allowing precise and high-resolution analyses. However, making sense of the genomic information requires a certain level of professional training and computational power, which are not universally available to researchers. To address this, we generated a set of PCR-based DNA markers out of the existing genomic data from 228 popular soybean varieties that offer precise, unambiguous genomic information and can be easily adapted in various applications. A standard operating procedure (SOP) was also designed for these markers and validated on diverse soybean varieties to ensure their reproducibility. This user-friendly universal panel of DNA markers, along with the SOP, will facilitate soybean research and breeding programs through simple applications.