The population genomics of adaptive loss of function.

Discoveries of adaptive gene knockouts and widespread losses of complete genes have in recent years led to a major rethink of the early view that loss-of-function alleles are almost always deleterious. Today, surveys of population genomic diversity are revealing extensive loss-of-function and gene content variation, yet the adaptive significance of much of this variation remains unknown. Here we examine the evolutionary dynamics of adaptive loss of function through the lens of population genomics and consider the challenges and opportunities of studying adaptive loss-of-function alleles using population genetics models. We discuss how the theoretically expected existence of allelic heterogeneity, defined as multiple functionally analogous mutations at the same locus, has proven consistent with empirical evidence and why this impedes both the detection of selection and causal relationships with phenotypes. We then review technical progress towards new functionally explicit population genomic tools and genotype-phenotype methods to overcome these limitations. More broadly, we discuss how the challenges of studying adaptive loss of function highlight the value of classifying genomic variation in a way consistent with the functional concept of an allele from classical population genetics.

African genomes illuminate the early history and transition to selfing in Arabidopsis thaliana.

Over the past 20 y, many studies have examined the history of the plant ecological and molecular model, Arabidopsis thaliana, in Europe and North America. Although these studies informed us about the recent history of the species, the early history has remained elusive. In a large-scale genomic analysis of African A. thaliana, we sequenced the genomes of 78 modern and herbarium samples from Africa and analyzed these together with over 1,000 previously sequenced Eurasian samples. In striking contrast to expectations, we find that all African individuals sampled are native to this continent, including those from sub-Saharan Africa. Moreover, we show that Africa harbors the greatest variation and represents the deepest history in the A. thaliana lineage. Our results also reveal evidence that selfing, a major defining characteristic of the species, evolved in a single geographic region, best represented today within Africa. Demographic inference supports a model in which the ancestral A. thaliana population began to split by 120-90 kya, during the last interglacial and Abbassia pluvial, and Eurasian populations subsequently separated from one another at around 40 kya. This bears striking similarities to the patterns observed for diverse species, including humans, implying a key role for climatic events during interglacial and pluvial periods in shaping the histories and current distributions of a wide range of species.

Measuring the dynamic photosynthome.

Background: Photosynthesis underpins plant productivity and yet is notoriously sensitive to small changes in environmental conditions, meaning that quantitation in nature across different time scales is not straightforward. The 'dynamic' changes in photosynthesis (i.e. the kinetics of the various reactions of photosynthesis in response to environmental shifts) are now known to be important in driving crop yield. Scope: It is known that photosynthesis does not respond in a timely manner, and even a small temporal 'mismatch' between a change in the environment and the appropriate response of photosynthesis toward optimality can result in a fall in productivity. Yet the most commonly measured parameters are still made at steady state or a temporary steady state (including those for crop breeding purposes), meaning that new photosynthetic traits remain undiscovered. Conclusions: There is a great need to understand photosynthesis dynamics from a mechanistic and biological viewpoint especially when applied to the field of 'phenomics' which typically uses large genetically diverse populations of plants. Despite huge advances in measurement technology in recent years, it is still unclear whether we possess the capability of capturing and describing the physiologically relevant dynamic features of field photosynthesis in sufficient detail. Such traits are highly complex, hence we dub this the 'photosynthome'. This review sets out the state of play and describes some approaches that could be made to address this challenge with reference to the relevant biological processes involved.

Draft genome of the aardaker (Lathyrus tuberosus L.), a tuberous legume.

OBJECTIVES: Lathyrus tuberosus is a nitrogen-fixing member of the Fabaceae which forms protein-rich tubers. To aid future domestication programs for this legume plant and facilitate evolutionary studies of tuber formation, we have generated a draft genome assembly based on Pacific Biosciences sequence reads. DATA DESCRIPTION: Genomic DNA from L. tuberosus was sequenced with PacBio's HiFi sequencing chemistry generating 12.8 million sequence reads with an average read length of 14 kb (approximately 180 Gb of sequence data). The reads were assembled to give a draft genome of 6.8 Gb in 1353 contigs with an N50 contig length of 11.1 Mb. The GC content of the genome assembly was 38.3%. BUSCO analysis of the genome assembly indicated a genome completeness of at least 96%. The genome sequence will be a valuable resource, for example, in assessing genomic consequences of domestication efforts and developing marker sets for breeding programs. The L. tuberosus genome will also aid in the analysis of the evolutionary history of plants within the nitrogen-fixing Fabaceae family and in understanding the molecular basis of tuber evolution.

A two-step adaptive walk rewires nutrient transport in a challenging edaphic environment.

Most well-characterized cases of adaptation involve single genetic loci. Theory suggests that multilocus adaptive walks should be common, but these are challenging to identify in natural populations. Here, we combine trait mapping with population genetic modeling to show that a two-step process rewired nutrient homeostasis in a population of Arabidopsis as it colonized the base of an active stratovolcano characterized by extremely low soil manganese (Mn). First, a variant that disrupted the primary iron (Fe) uptake transporter gene (IRT1) swept quickly to fixation in a hard selective sweep, increasing Mn but limiting Fe in the leaves. Second, multiple independent tandem duplications occurred at NRAMP1 and together rose to near fixation in the island population, compensating the loss of IRT1 by improving Fe homeostasis. This study provides a clear case of a multilocus adaptive walk and reveals how genetic variants reshaped a phenotype and spread over space and time.

Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages.

Understanding how populations adapt to abrupt environmental change is necessary to predict responses to future challenges, but identifying specific adaptive variants, quantifying their responses to selection and reconstructing their detailed histories is challenging in natural populations. Here, we use Arabidopsis from the Cape Verde Islands as a model to investigate the mechanisms of adaptation after a sudden shift to a more arid climate. We find genome-wide evidence of adaptation after a multivariate change in selection pressures. In particular, time to flowering is reduced in parallel across islands, substantially increasing fitness. This change is mediated by convergent de novo loss of function of two core flowering time genes: FRI on one island and FLC on the other. Evolutionary reconstructions reveal a case where expansion of the new populations coincided with the emergence and proliferation of these variants, consistent with models of rapid adaptation and evolutionary rescue.

Reciprocal cybrids reveal how organellar genomes affect plant phenotypes.

Assessment of the impact of variation in chloroplast and mitochondrial DNA (collectively termed the plasmotype) on plant phenotypes is challenging due to the difficulty in separating their effect from nuclear-derived variation (the nucleotype). Haploid-inducer lines can be used as efficient plasmotype donors to generate new plasmotype-nucleotype combinations (cybrids)1. We generated a panel comprising all possible cybrids of seven Arabidopsis thaliana accessions and extensively phenotyped these lines for 1,859 phenotypes under both stable and fluctuating conditions. We show that natural variation in the plasmotype results in both additive and epistatic effects across all phenotypic categories. Plasmotypes that induce more additive phenotypic changes also cause more epistatic effects, suggesting a possible common basis for both additive and epistatic effects. On average, epistatic interactions explained twice as much of the variance in phenotypes as additive plasmotype effects. The impact of plasmotypic variation was also more pronounced under fluctuating and stressful environmental conditions. Thus, the phenotypic impact of variation in plasmotypes is the outcome of multi-level nucleotype-plasmotype-environment interactions and, as such, the plasmotype is likely to serve as a reservoir of variation that is predominantly exposed under certain conditions. The production of cybrids using haploid inducers is a rapid and precise method for assessment of the phenotypic effects of natural variation in organellar genomes. It will facilitate efficient screening of unique nucleotype-plasmotype combinations to both improve our understanding of natural variation in these combinations and identify favourable combinations to enhance plant performance.

Using natural variation to understand the evolutionary pressures on plant photosynthesis.

Photosynthesis is the gateway of the Sun's energy into the biosphere and the source of the ozone layer; thus it is both provider and protector of life as we know it. Despite its pivotal role we know surprisingly little about the genetic basis of variation in photosynthesis and the selective pressures giving rise to or maintaining this variation. In this review, I will briefly summarise our current knowledge of intraspecific and interspecific variation in photosynthesis to understand the main selective constraints on photosynthesis and what this means for the future of nature and agriculture in a changing world.

Linked-read sequencing of gametes allows efficient genome-wide analysis of meiotic recombination.

Meiotic crossovers (COs) ensure proper chromosome segregation and redistribute the genetic variation that is transmitted to the next generation. Large populations and the demand for genome-wide, fine-scale resolution challenge existing methods for CO identification. Taking advantage of linked-read sequencing, we develop a highly efficient method for genome-wide identification of COs at kilobase resolution in pooled recombinants. We first test this method using a pool of Arabidopsis F2 recombinants, and recapitulate results obtained from the same plants using individual whole-genome sequencing. By applying this method to a pool of pollen DNA from an F1 plant, we establish a highly accurate CO landscape without generating or sequencing a single recombinant plant. The simplicity of this approach enables the simultaneous generation and analysis of multiple CO landscapes, accelerating the pace at which mechanisms for the regulation of recombination can be elucidated through efficient comparisons of genotypic and environmental effects on recombination.

The genomic basis of adaptation in plants.

Plants are powerful models for the study of adaptive evolution. Since they are rooted in place, they must directly face environmental insults, making adaptation to local conditions vital. In addition to adaptation to natural conditions, some plant species have held a central role in human subsistence over the past several thousand years. In these species, humans exerted strong selective pressures on traits of agricultural importance. Recently, an increasing number of studies have aimed to identify the genomic basis of adaptation. These studies have provided insights into the mechanisms through which the raw materials of adaptation were introduced as well as the modes of adaptation in wild and domesticated species.

Phenomics for photosynthesis, growth and reflectance in Arabidopsis thaliana reveals circadian and long-term fluctuations in heritability.

BACKGROUND: Recent advances in genome sequencing technologies have shifted the research bottleneck in plant sciences from genotyping to phenotyping. This shift has driven the development of phenomics, high-throughput non-invasive phenotyping technologies. RESULTS: We describe an automated high-throughput phenotyping platform, the Phenovator, capable of screening 1440 Arabidopsis plants multiple times per day for photosynthesis, growth and spectral reflectance at eight wavelengths. Using this unprecedented phenotyping capacity, we have been able to detect significant genetic differences between Arabidopsis accessions for all traits measured, across both temporal and environmental scales. The high frequency of measurement allowed us to observe that heritability was not only trait specific, but for some traits was also time specific. CONCLUSIONS: Such continuous real-time non-destructive phenotyping will allow detailed genetic and physiological investigations of the kinetics of plant homeostasis and development. The success and ultimate outcome of a breeding program will depend greatly on the genetic variance which is sampled. Our observation of temporal fluctuations in trait heritability shows that the moment of measurement can have lasting consequences. Ultimately such phenomic level technologies will provide more dynamic insights into plant physiology, and the necessary data for the omics revolution to reach its full potential.

Whole-Genome Hitchhiking on an Organelle Mutation.

Strong selection on a beneficial mutation can cause a selective sweep, which fixes the mutation in the population and reduces the genetic variation in the region flanking the mutation [1-3]. These flanking regions have increased in frequency due to their physical association with the selected loci, a phenomenon called "genetic hitchhiking" [4]. Theoretically, selection could extend the hitchhiking to unlinked parts of the genome, to the point that selection on organelles affects nuclear genome diversity. Such indirect selective sweeps have never been observed in nature. Here we show that strong selection on a chloroplast gene in the wild plant species Arabidopsis thaliana has caused widespread and lasting hitchhiking of the whole nuclear genome. The selected allele spread more than 400 km along the British railway network, reshaping the genetic composition of local populations. This demonstrates that selection on organelle genomes can significantly reduce nuclear genetic diversity in natural populations. We expect that organelle-mediated genetic draft is a more common occurrence than previously realized and needs to be considered when studying genome evolution.

Improved batch correction in untargeted MS-based metabolomics.

INTRODUCTION: Batch effects in large untargeted metabolomics experiments are almost unavoidable, especially when sensitive detection techniques like mass spectrometry (MS) are employed. In order to obtain peak intensities that are comparable across all batches, corrections need to be performed. Since non-detects, i.e., signals with an intensity too low to be detected with certainty, are common in metabolomics studies, the batch correction methods need to take these into account. OBJECTIVES: This paper aims to compare several batch correction methods, and investigates the effect of different strategies for handling non-detects. METHODS: Batch correction methods usually consist of regression models, possibly also accounting for trends within batches. To fit these models quality control samples (QCs), injected at regular intervals, can be used. Also study samples can be used, provided that the injection order is properly randomized. Normalization methods, not using information on batch labels or injection order, can correct for batch effects as well. Introducing two easy-to-use quality criteria, we assess the merits of these batch correction strategies using three large LC-MS and GC-MS data sets of samples from Arabidopsis thaliana. RESULTS: The three data sets have very different characteristics, leading to clearly distinct behaviour of the batch correction strategies studied. Explicit inclusion of information on batch and injection order in general leads to very good corrections; when enough QCs are available, also general normalization approaches perform well. Several approaches are shown to be able to handle non-detects-replacing them with very small numbers such as zero seems the worst of the approaches considered. CONCLUSION: The use of quality control samples for batch correction leads to good results when enough QCs are available. If an experiment is properly set up, batch correction using the study samples usually leads to a similar high-quality correction, but has the advantage that more metabolites are corrected. The strategy for handling non-detects is important: choosing small values like zero can lead to suboptimal batch corrections.

Marker-based estimation of heritability in immortal populations.

Heritability is a central parameter in quantitative genetics, from both an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within- and between-genotype variability. This approach estimates broad-sense heritability and does not account for different genetic relatedness. With the availability of high-density markers there is growing interest in marker-based estimates of narrow-sense heritability, using mixed models in which genetic relatedness is estimated from genetic markers. Such estimates have received much attention in human genetics but are rarely reported for plant traits. A major obstacle is that current methodology and software assume a single phenotypic value per genotype, hence requiring genotypic means. An alternative that we propose here is to use mixed models at the individual plant or plot level. Using statistical arguments, simulations, and real data we investigate the feasibility of both approaches and how these affect genomic prediction with the best linear unbiased predictor and genome-wide association studies. Heritability estimates obtained from genotypic means had very large standard errors and were sometimes biologically unrealistic. Mixed models at the individual plant or plot level produced more realistic estimates, and for simulated traits standard errors were up to 13 times smaller. Genomic prediction was also improved by using these mixed models, with up to a 49% increase in accuracy. For genome-wide association studies on simulated traits, the use of individual plant data gave almost no increase in power. The new methodology is applicable to any complex trait where multiple replicates of individual genotypes can be scored. This includes important agronomic crops, as well as bacteria and fungi.

Natural variation in phosphorylation of photosystem II proteins in Arabidopsis thaliana: is it caused by genetic variation in the STN kinases?

Reversible phosphorylation of photosystem II (PSII) proteins is an important regulatory mechanism that can protect plants from changes in ambient light intensity and quality. We hypothesized that there is natural variation in this process in Arabidopsis (Arabidopsis thaliana), and that this results from genetic variation in the STN7 and STN8 kinase genes. To test this, Arabidopsis accessions of diverse geographical origins were exposed to two light regimes, and the levels of phospho-D1 and phospho-light harvesting complex II (LHCII) proteins were quantified by western blotting with anti-phosphothreonine antibodies. Accessions were classified as having high, moderate or low phosphorylation relative to Col-0. This variation could not be explained by the abundance of the substrates in thylakoid membranes. In genotypes with atrazine-resistant forms of the D1 protein, low D1 and LHCII protein phosphorylation was observed, which may be due to low PSII efficiency, resulting in reduced activation of the STN kinases. In the remaining genotypes, phospho-D1 levels correlated with STN8 protein abundance in high-light conditions. In growth light, D1 and LHCII phosphorylation correlated with longitude and in the case of LHCII phosphorylation also with temperature variability. This suggests a possible role of natural variation in PSII protein phosphorylation in the adaptation of Arabidopsis to diverse environments.

Natural genetic variation in plant photosynthesis.

Natural genetic variation in plant photosynthesis is a largely unexplored and as a result an underused genetic resource for crop improvement. Numerous studies show genetic variation in photosynthetic traits in both crop and wild species, and there is an increasingly detailed knowledge base concerning the interaction of photosynthetic phenotypes with their environment. The genetic factors that cause this variation remain largely unknown. Investigations into natural genetic variation in photosynthesis will provide insights into the genetic regulation of this complex trait. Such insights can be used to understand evolutionary processes that affect primary production, allow greater understanding of the genetic regulation of photosynthesis and ultimately increase the productivity of our crops.