Genomic Rearrangements in Arabidopsis Considered as Quantitative Traits

Exploring the role of polymorphic interspecies structural variants in reproductive isolation and adaptive divergence in Eucalyptus

Structural variations (SVs) play a significant role in speciation and adaptation in many species, yet few studies have explored the prevalence and impact of different categories of SVs. We conducted a comparative analysis of long-read assembled reference genomes of closely related Eucalyptus species to identify candidate SVs potentially influencing speciation and adaptation. Interspecies SVs can be either fixed differences or polymorphic in one or both species. To describe SV patterns, we employed short-read whole-genome sequencing on over 600 individuals of Eucalyptus melliodora and Eucalyptus sideroxylon, along with recent high-quality genome assemblies. We aligned reads and genotyped interspecies SVs predicted between species reference genomes. Our results revealed that 49,756 of 58,025 and 39,536 of 47,064 interspecies SVs could be typed with short reads in E. melliodora and E. sideroxylon, respectively. Focusing on inversions and translocations, symmetric SVs that are readily genotyped within both populations, 24 were found to be structural divergences, 2,623 structural polymorphisms, and 928 shared structural polymorphisms. We assessed the functional significance of fixed interspecies SVs by examining differences in estimated recombination rates and genetic differentiation between species, revealing a complex history of natural selection. Shared structural polymorphisms displayed enrichment of potentially adaptive genes. Understanding how different classes of genetic mutations contribute to genetic diversity and reproductive barriers is essential for understanding how organisms enhance fitness, adapt to changing environments, and diversify. Our findings reveal the prevalence of interspecies SVs and elucidate their role in genetic differentiation, adaptive evolution, and species divergence within and between populations.

Genetic Mapping of Multiple Traits Identifies Novel Genes for Adiposity, Lipids, and Insulin Secretory Capacity in Outbred Rats

Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.

Does divergence from normal patterns of integration increase as chromosomal fusions increase in number? A test on a house mouse hybrid zone

Chromosomal evolution is widely considered an important driver of speciation because it can promote the establishment of reproductive barriers. Karyotypic reorganization is also expected to affect the mean phenotype, as well as its development and patterns of phenotypic integration, through processes such as variation in genetic linkage between quantitative trait loci or between regulatory regions and their targets. Here we explore the relationship between chromosomal evolution and phenotypic integration by analyzing a well-known house mouse parapatric contact zone between a highly derived Robertsonian (Rb) race (2n = 22) and populations with standard karyotype (2n = 40). Populations with hybrid karyotypes are scattered throughout the hybrid zone connecting the two parental races. Using mandible shape data and geometric morphometrics, we test the hypothesis that patterns of integration progressively diverge from the “normal” integration pattern observed in the standard race as they accumulate Rb fusions. We find that the main pattern of integration observed between the posterior and anterior part of the mandible can be largely attributed to allometry. We find no support for a gradual increase in divergence from normal patterns of integration as fusions accumulate. Surprisingly, however, we find that the derived Rb race (2n = 22) has a distinct allometric trajectory compared with the standard race. Our results suggest that either individual fusions disproportionately affect patterns of integration or that there are mechanisms which “purge” extreme variants in hybrids (e.g. reduced fitness of hybrid shape).

Multi-parent populations in crops: a toolbox integrating genomics and genetic mapping with breeding

Crop populations derived from experimental crosses enable the genetic dissection of complex traits and support modern plant breeding. Among these, multi-parent populations now play a central role. By mixing and recombining the genomes of multiple founders, multi-parent populations combine many commonly sought beneficial properties of genetic mapping populations. For example, they have high power and resolution for mapping quantitative trait loci, high genetic diversity and minimal population structure. Many multi-parent populations have been constructed in crop species, and their inbred germplasm and associated phenotypic and genotypic data serve as enduring resources. Their utility has grown from being a tool for mapping quantitative trait loci to a means of providing germplasm for breeding programmes. Genomics approaches, including de novo genome assemblies and gene annotations for the population founders, have allowed the imputation of rich sequence information into the descendent population, expanding the breadth of research and breeding applications of multi-parent populations. Here, we report recent successes from crop multi-parent populations in crops. We also propose an ideal genotypic, phenotypic and germplasm 'package' that multi-parent populations should feature to optimise their use as powerful community resources for crop research, development and breeding.

Evaluating Structural Variation Detection Tools for Long-Read Sequencing Datasets in Saccharomyces cerevisiae

Structural variation (SV) represents a major form of genetic variations that contribute to polymorphic variations, human diseases, and phenotypes in many organisms. Long-read sequencing has been successfully used to identify novel and complex SVs. However, comparison of SV detection tools for long-read sequencing datasets has not been reported. Therefore, we developed an analysis workflow that combined two alignment tools (NGMLR and minimap2) and five callers (Sniffles, Picky, smartie-sv, PBHoney, and NanoSV) to evaluate the SV detection in six datasets of Saccharomyces cerevisiae. The accuracy of SV regions was validated by re-aligning raw reads in diverse alignment tools, SV callers, experimental conditions, and sequencing platforms. The results showed that SV detection between NGMLR and minimap2 was not significant when using the same caller. The PBHoney was with the highest average accuracy (89.04%) and Picky has the lowest average accuracy (35.85%). The accuracy of NanoSV, Sniffles, and smartie-sv was 68.67%, 60.47%, and 57.67%, respectively. In addition, smartie-sv and NanoSV detected the most and least number of SVs, and SV detection from the PacBio sequencing platform was significantly more than that from ONT (p = 0.000173).

SyRI: finding genomic rearrangements and local sequence differences from whole-genome assemblies

Genomic differences range from single nucleotide differences to complex structural variations. Current methods typically annotate sequence differences ranging from SNPs to large indels accurately but do not unravel the full complexity of structural rearrangements, including inversions, translocations, and duplications, where highly similar sequence changes in location, orientation, or copy number. Here, we present SyRI, a pairwise whole-genome comparison tool for chromosome-level assemblies. SyRI starts by finding rearranged regions and then searches for differences in the sequences, which are distinguished for residing in syntenic or rearranged regions. This distinction is important as rearranged regions are inherited differently compared to syntenic regions.

Components of the ribosome biogenesis pathway underlie establishment of telomere length set point in Arabidopsis

Telomeres cap the physical ends of eukaryotic chromosomes to ensure complete DNA replication and genome stability. Heritable natural variation in telomere length exists in yeast, mice, plants and humans at birth; however, major effect loci underlying such polymorphism remain elusive. Here, we employ quantitative trait locus (QTL) mapping and transgenic manipulations to identify genes controlling telomere length set point in a multi-parent Arabidopsis thaliana mapping population. We detect several QTL explaining 63.7% of the total telomere length variation in the Arabidopsis MAGIC population. Loss-of-function mutants of the NOP2A candidate gene located inside the largest effect QTL and of two other ribosomal genes RPL5A and RPL5B establish a shorter telomere length set point than wild type. These findings indicate that evolutionarily conserved components of ribosome biogenesis and cell proliferation pathways promote telomere elongation.

Major effect loci controlling natural, heritable variation in telomere length are not known. Here, the authors use QTL mapping and transgenic manipulations in Arabidopsis to implicate the rRNA-processing genes NOP2A and RPL5 in telomere length set point regulation in this model species.

Modeling copy number variation in the genomic prediction of maize hybrids

Our study indicates that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids. Moreover, predicting hybrid phenotypes by combining additive-dominance effects with copy variants has the potential to be a viable predictive model. Non-additive effects resulting from the actions of multiple loci may influence trait variation in single-cross hybrids. In addition, complementation of allelic variation could be a valuable contributor to hybrid genetic variation, especially when crossing inbred lines with higher contents of copy gains. With this in mind, we aimed (1) to study the association between copy number variation (CNV) and hybrid phenotype, and (2) to compare the predictive ability (PA) of additive and additive-dominance genomic best linear unbiased prediction model when combined with the effects of CNV in two datasets of maize hybrids (USP and HELIX). In the USP dataset, we observed a significant negative phenotypic correlation of low magnitude between copy number loss and plant height, revealing a tendency that more copy losses lead to lower plants. In the same set, when CNV was combined with the additive plus dominance effects, the PA significantly increased only for plant height under low nitrogen. In this case, CNV effects explicitly capture relatedness between individuals and add extra information to the model. In the HELIX dataset, we observed a pronounced difference in PA between additive (0.50) and additive-dominance (0.71) models for predicting grain yield, suggesting a significant contribution of dominance. We conclude that copy variants may play an essential role in the phenotypic variation of complex traits in maize hybrids, although the inclusion of CNVs into datasets does not return significant gains concerning PA.

Natural variation in acyl editing is a determinant of seed storage oil composition

Seeds exhibit wide variation in the fatty acid composition of their storage oil. However, the genetic basis of this variation is only partially understood. Here we have used a multi-parent advanced generation inter-cross (MAGIC) population to study the genetic control of fatty acid chain length in Arabidopsis thaliana seed oil. We mapped four quantitative trait loci (QTL) for the quantity of the major very long chain fatty acid species 11-eicosenoic acid (20:1), using multiple QTL modelling. Surprisingly, the main-effect QTL does not coincide with FATTY ACID ELONGASE 1 and a parallel genome wide association study suggested that LYSOPHOSPHATIDYLCHOLINE ACYLTRANSFERASE 2 (LPCAT2) is a candidate for this QTL. Regression analysis also suggested that LPCAT2 expression and 20:1 content in seeds of the 19 MAGIC founder accessions are related. LPCAT is a key component of the Lands cycle; an acyl editing pathway that enables acyl-exchange between the acyl-Coenzyme A and phosphatidylcholine precursor pools used for microsomal fatty acid elongation and desaturation, respectively. We Mendelianised the main-effect QTL using biparental chromosome segment substitution lines and carried out complementation tests to show that a single cis-acting polymorphism in the LPCAT2 promoter causes the variation in seed 20:1 content, by altering the LPCAT2 expression level and total LPCAT activity in developing siliques. Our work establishes that oilseed species exhibit natural variation in the enzymic capacity for acyl editing and this contributes to the genetic control of storage oil composition.

A genome-wide scan for correlated mutations detects macromolecular and chromatin interactions in Arabidopsis thaliana

The concept of exploiting correlated mutations has been introduced and applied successfully to identify interactions within and between biological macromolecules. Its rationale lies in the preservation of physical interactions via compensatory mutations. With the massive increase of available sequence information, approaches based on correlated mutations have regained considerable attention. We analyzed a set of 10 707 430 single nucleotide polymorphisms detected in 1135 accessions of the plant Arabidopsis thaliana. To measure their covariance and to reveal the global genome-wide sequence correlation structure of the Arabidopsis genome, the adjusted mutual information has been estimated for each possible pair of polymorphic sites. We developed a series of filtering steps to account for genetic linkage and lineage relations between Arabidopsis accessions, as well as transitive covariance as possible confounding factors. We show that upon appropriate filtering, correlated mutations prove indeed informative with regard to molecular interactions, and furthermore, appear to reflect on chromosomal interactions. Our study demonstrates that the concept of correlated mutations can also be applied successfully to within-species sequence variation and establishes a promising approach to help unravel the complex molecular interactions in A. thaliana and other species with broad sequence information.

Accurate detection of complex structural variations using single-molecule sequencing

Structural variations are the greatest source of genetic variation, but they remain poorly understood because of technological limitations. Single-molecule long-read sequencing has the potential to dramatically advance the field, although high error rates are a challenge with existing methods. Addressing this need, we introduce open-source methods for long-read alignment (NGMLR; https://github.com/philres/ngmlr ) and structural variant identification (Sniffles; https://github.com/fritzsedlazeck/Sniffles ) that provide unprecedented sensitivity and precision for variant detection, even in repeat-rich regions and for complex nested events that can have substantial effects on human health. In several long-read datasets, including healthy and cancerous human genomes, we discovered thousands of novel variants and categorized systematic errors in short-read approaches. NGMLR and Sniffles can automatically filter false events and operate on low-coverage data, thereby reducing the high costs that have hindered the application of long reads in clinical and research settings.

Epistatic and allelic interactions control expression of ribosomal RNA gene clusters in Arabidopsis thaliana

BACKGROUND

Ribosomal RNA (rRNA) accounts for the majority of the RNA in eukaryotic cells, and is encoded by hundreds to thousands of nearly identical gene copies, only a subset of which are active at any given time. In Arabidopsis thaliana, 45S rRNA genes are found in two large ribosomal DNA (rDNA) clusters and little is known about the contribution of each to the overall transcription pattern in the species.

RESULTS

By taking advantage of genome sequencing data from the 1001 Genomes Consortium, we characterize rRNA gene sequence variation within and among accessions. Notably, variation is not restricted to the pre-rRNA sequences removed during processing, but it is also present within the highly conserved ribosomal subunits. Through linkage mapping we assign these variants to a particular rDNA cluster unambiguously and use them as reporters of rDNA cluster-specific expression. We demonstrate that rDNA cluster-usage varies greatly among accessions and that rDNA cluster-specific expression and silencing is controlled via genetic interactions between entire rDNA cluster haplotypes (alleles).

CONCLUSIONS

We show that rRNA gene cluster expression is controlled via complex epistatic and allelic interactions between rDNA haplotypes that apparently regulate the entire rRNA gene cluster. Furthermore, the sequence polymorphism we discovered implies that the pool of rRNA in a cell may be heterogeneous, which could have functional consequences.

Unstable Inheritance of 45S rRNA Genes in Arabidopsis thaliana

The considerable genome size variation in Arabidopsis thaliana has been shown largely to be due to copy number variation (CNV) in 45S ribosomal RNA (rRNA) genes. Surprisingly, attempts to map this variation by means of genome-wide association studies (GWAS) failed to identify either of the two likely sources, namely the nucleolus organizer regions (NORs). Instead, GWAS implicated a trans-acting locus, as if rRNA gene CNV was a phenotype rather than a genotype. To explain these results, we investigated the inheritance and stability of rRNA gene copy number using the variety of genetic resources available in A. thaliana - F2 crosses, recombinant inbred lines, the multiparent advanced-generation inter-cross population, and mutation accumulation lines. Our results clearly show that rRNA gene CNV can be mapped to the NORs themselves, with both loci contributing equally to the variation. However, NOR size is unstably inherited, and dramatic copy number changes are visible already within tens of generations, which explains why it is not possible to map the NORs using GWAS. We did not find any evidence of trans-acting loci in crosses, which is also expected since changes due to such loci would take very many generations to manifest themselves. rRNA gene copy number is thus an interesting example of "missing heritability"-a trait that is heritable in pedigrees, but not in the general population.

Genome Wide Analysis of Fatty Acid Desaturation and Its Response to Temperature

Plants modify the polyunsaturated fatty acid content of their membrane and storage lipids in order to adapt to changes in temperature. In developing seeds, this response is largely controlled by the activities of the microsomal ω-6 and ω-3 fatty acid desaturases, FAD2 and FAD3. Although temperature regulation of desaturation has been studied at the molecular and biochemical levels, the genetic control of this trait is poorly understood. Here, we have characterized the response of Arabidopsis (Arabidopsis thaliana) seed lipids to variation in ambient temperature and found that heat inhibits both ω-6 and ω-3 desaturation in phosphatidylcholine, leading to a proportional change in triacylglycerol composition. Analysis of the 19 parental accessions of the multiparent advanced generation intercross (MAGIC) population showed that significant natural variation exists in the temperature responsiveness of ω-6 desaturation. A combination of quantitative trait locus (QTL) analysis and genome-wide association studies (GWAS) using the MAGIC population suggests that ω-6 desaturation is largely controlled by cis-acting sequence variants in the FAD2 5' untranslated region intron that determine the expression level of the gene. However, the temperature responsiveness of ω-6 desaturation is controlled by a separate QTL on chromosome 2. The identity of this locus is unknown, but genome-wide association studies identified potentially causal sequence variants within ∼40 genes in an ∼450-kb region of the QTL.