Detection of genomic variations and DNA polymorphisms and impact on analysis of meiotic recombination and genetic mapping

Abstract

DNA polymorphisms are important markers in genetic analyses and are increasingly detected by using genome resequencing. However, the presence of repetitive sequences and structural variants can lead to false positives in the identification of polymorphic alleles. Here, we describe an analysis strategy that minimizes false positives in allelic detection and present analyses of recently published resequencing data from Arabidopsis meiotic products and individual humans. Our analysis enables the accurate detection of sequencing errors, small insertions and deletions (indels), and structural variants, including large reciprocal indels and copy number variants, from comparisons between the resequenced and reference genomes. We offer an alternative interpretation of the sequencing data of meiotic products, including the number and type of recombination events, to illustrate the potential for mistakes in single-nucleotide polymorphism calling. Using these examples, we propose that the detection of DNA polymorphisms using resequencing data needs to account for nonallelic homologous sequences. Fig. 1 A and B). They can have phenotypic consequences and also serve as molecular markers for genetic analyses, facilitating linkage and association studies of genetic diseases, and other traits in humans (4-6), animals, plants, (7)(8)(9)(10) and other organisms. Using DNA polymorphisms for modern genetic applications requires low-error, high-throughput analytical strategies. Here, we illustrate the use of short-read nextgeneration sequencing (NGS) data to detect DNA polymorphisms in the context of whole-genome analysis of meiotic products.There are many methods for detecting SNPs (11-14) and structural variants (SVs) (15-25), including NGS, which can capture nearly all DNA polymorphisms (26-28). This approach has been widely used to analyze markers in crop species such as rice (29), genes associated with diseases (6, 26), and meiotic recombination in yeast and plants (30,31). However, accurate identification of DNA polymorphisms can be challenging, in part because short-read sequencing data have limited information for inferring chromosomal context.Genomes usually contain repetitive sequences that can differ in copy number between individuals (26-28, 31); therefore, resequencing analyses must account for chromosomal context to avoid mistaking highly similar paralogous sequences for polymorphisms. Here, we use recently published datasets to describe several DNA sequence features that can be mistaken as allelic (32, 33) and describe a strategy for differentiating between repetitive sequences and polymorphic alleles. We illustrate the effectiveness of these analyses by examining the reported polymorphisms from the published datasets.Meiotic recombination is initiated by DNA double-strand breaks (DSBs) catalyzed by the topoisomerase-like SPORULATION 11 (SPO11). DSBs are repaired as either crossovers (COs) between chromosomes (Fig. 1C), or noncrossovers (NCOs). Both COs and NCOs can be accompanied by gene conversion (GC) events, whic...

DNA Crossover Motifs Associated with Epigenetic Modifications Delineate Open Chromatin Regions in Arabidopsis

“…To generate a large data set of CO sites, the 201 CO events from this analysis were combined with previously published raw data (Lu et al, 2012a;Yang et al, 2012) and with the CO events listed in the Wijnker et al (2013) study. Although the frequency of gene conversion events in the data of Yang et al (2012) was not supported by other studies (Qi et al, 2014), the quality of the sequence data for CO detection was not challenged (Qi et al, 2014) and was supported by our quality control analysis. The combined data set included 737 CO events with fine resolution (median: 1534 bp).…”

Distribution, position and genomic characteristics of crossovers in tomato recombinant inbred lines derived from an interspecific cross between Solanum lycopersicum and Solanum pimpinellifolium

“…Furthermore, we identified seven significantly CO‐dense regions, so‐called ‘hot regions’, in tomato chromosome arms 1L, 3S, 3L, 6S, 6L, 9L and 12L (Figures and S2) of which, for example, a region of 100 kb in chromosome 6L comprised six CO events. These hot regions could potentially arise from erroneous SNP calling, for example caused by transposable elements, resulting in structural variation (Qi et al ., ). However, we did not find DNA transposon footprints at the hot regions.…”

Chromosome-level assembly ofArabidopsis thalianaLerreveals the extent of translocation and inversion polymorphisms

“…In contrast, de novo assemblies based only on long reads are easier to perform and start to become a powerful alternative (17,42), although they do not assemble entire chromosomes yet. Independent of the assembly type, the amount of rearranged sequence that was revealed by comparing two assemblies underlines the general importance of chromosomelevel assemblies, in particular because rearrangements have been recognized as confounding factors in genome-wide screens (11,43) and are essential to fully understand the segregation and evolution of natural haplotypes.…”