Whole-genome variation of transposable element insertions in a maize diversity panel

Abstract

Intact transposable elements (TEs) account for 65% of the maize genome and can impact gene function and regulation. Although TEs comprise the majority of the maize genome and affect important phenotypes, genome wide patterns of TE polymorphisms in maize have only been studied in a handful of maize genotypes, due to the challenging nature of assessing highly repetitive sequences. We implemented a method to use short read sequencing data from 509 diverse inbred lines to classify the presence/absence of 445,418 non-redundant TEs that were previously annotated in four genome assemblies including B73, Mo17, PH207, and W22. Different orders of TEs (i.e. LTRs, Helitrons, TIRs) had different frequency distributions within the population. LTRs with lower LTR similarity were generally more frequent in the population than LTRs with higher LTR similarity, though high frequency insertions with very high LTR similarity were observed. LTR similarity and frequency estimates of nested elements and the outer elements in which they insert revealed that most nesting events occurred very near the timing of the outer element insertion. TEs within genes were at higher frequency than those that were outside of genes and this is particularly true for those not inserted into introns. Many TE insertional polymorphisms observed in this population were tagged by SNP markers. However, there were also 19.9% of the TE polymorphisms that were not well tagged by SNPs (R2 < 0.5) that potentially represent information that has not been well captured in previous SNP based marker-trait association studies. This study provides a population scale genome-wide assessment of TE variation in maize, and provides valuable insight on variation in TEs in maize and factors that contribute to this variation.

Association mapping across a multitude of traits collected in diverse environments in maize

“…We speculate that this difference may result from the inclusion of local checks or lines of interest or changes in naming convention or transcription errors that we were unable to resolve. For the 1,014 unique genotypes named as part of the SAM population [ 3 ] or WiDiv population [ 8 ], raw whole-genome sequencing or RNA-seq sequence data were aggregated from a number of sources ( Supplementary Table S2 ) [ 8 , 9 , 18 ] as described in Sun et al. [ 13 ].…”

Mapping Responsive Genomic Elements to Heat Stress in a Maize Diversity Panel

“…A subpanel of 102 diverse maize genotypes including stiff stalk, non-stiff stalk and iodent sub-populations representing the Wisconsin Diversity Panel (WiDiv) in maize 30,31 were selected for characterizing genotype responses to heat stress (Figure 1a). A set of 1,132,322 variants (1,032,834 SNPs + 99,488 InDels) was employed for this population (see methods for filtering details).…”

“…The SNP set of 509 inbreds from the WiDiv (Wisconsin Diversity) Panel was retrieved from a previous publication 31 for genotype subtraction. Biallelic SNPs were retained upon multiple thresholdings (no missing data across 509 inbreds; MAF > 0.05; heterozygosity <= 0.2).…”

Association Mapping Across a Multitude of Traits Collected in Diverse Environments Identifies Pleiotropic Loci in Maize

“…Phenotypic values for all trait datasets employed in this study for all maize accessions evaluated are provided in Table S2 and S3. The sources of sequence data used to call genetic marker genotypes for each maize accession were NCBI BioProjects PR-JNA661271, PRJNA189400 & PRJNA437324 5,6,8 . The specific SRA IDs for individual maize accessions are indicated in Table S2.…”

“…The original MAP population which shares many genotypes with both the SAM and WiDiv panels was resequenced as part of the Maize HapMap3 project increasing the number of segregating genetic markers to 83M 7 . A subset of lines from the WiDiv panel were resequenced, resulting in a set of 3.1M SNPs scored across 511 genotypes 8 .…”