Genome scan reveals selection acting on genes linked to stress response in wild pearl millet

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Crop adaptation to climate change: An evolutionary perspective

The disciplines of evolutionary biology and plant and animal breeding have been intertwined throughout their development, with responses to artificial selection yielding insights into the action of natural selection and evolutionary biology providing statistical and conceptual guidance for modern breeding. Here we offer an evolutionary perspective on a grand challenge of the 21st century: feeding humanity in the face of climate change. We first highlight promising strategies currently under way to adapt crops to current and future climate change. These include methods to match crop varieties with current and predicted environments and to optimize breeding goals, management practices, and crop microbiomes to enhance yield and sustainable production. We also describe the promise of crop wild relatives and recent technological innovations such as speed breeding, genomic selection, and genome editing for improving environmental resilience of existing crop varieties or for developing new crops. Next, we discuss how methods and theory from evolutionary biology can enhance these existing strategies and suggest novel approaches. We focus initially on methods for reconstructing the evolutionary history of crops and their pests and symbionts, because such historical information provides an overall framework for crop-improvement efforts. We then describe how evolutionary approaches can be used to detect and mitigate the accumulation of deleterious mutations in crop genomes, identify alleles and mutations that underlie adaptation (and maladaptation) to agricultural environments, mitigate evolutionary trade-offs, and improve critical proteins. Continuing feedback between the evolution and crop biology communities will ensure optimal design of strategies for adapting crops to climate change.

Genome Scan of Rice Landrace Populations Collected Across Time Revealed Climate Changes' Selective Footprints in the Genes Network Regulating Flowering Time

Analyses of the genetic bases of plant adaptation to climate changes, using genome-scan approaches, are often conducted on natural populations, under hypothesis of out-crossing reproductive regime. We report here on a study based on diachronic sampling (1980 and 2011) of the autogamous crop species, Oryza sativa and Oryza glaberrima, in the tropical forest and the Sudanian savannah of West Africa. First, using historical meteorological data we confirmed changes in temperatures (+ 1 °C on average) and rainfall regime (less predictable and reduced amount) in the target areas. Second, phenotyping the populations for phenology, we observed significantly earlier heading time in the 2010 samples. Third, implementing two genome-scan methods (one of which specially developed for selfing species) on genotyping by sequencing genotypic data of the two populations, we detected 31 independent selection footprints. Gene ontology analysis detected significant enrichment of these selection footprints in genes involved in reproductive processes. Some of them bore known heading time QTLs and genes, including OsGI, Hd1 and OsphyB. This rapid adaptive evolution, originated from subtle changes in the standing variation in genetic network regulating heading time, did not translate into predominance of multilocus genotypes, as it is often the case in selfing plants, and into notable selective sweeps. The high adaptive potential observed results from the multiline genetic structure of the rice landraces, and the rather large and imbricated genetic diversity of the rice meta-population at the farm, the village and the region levels, that hosted the adaptive variants in multiple genetic backgrounds before the advent of the environmental selective pressure. Our results illustrate the evolution of in situ diversity through processes of human and natural selection, and provide a model for rice breeding and cultivars deployment strategies aiming resilience to climate changes. It also calls for further development of population genetic models for adaptation of plant populations to environmental changes. To our best knowledge, this is the first study dealing with climate-changes' selective footprint in crops.

Genome-Environment Associations, an Innovative Tool for Studying Heritable Evolutionary Adaptation in Orphan Crops and Wild Relatives

Leveraging innovative tools to speed up prebreeding and discovery of genotypic sources of adaptation from landraces, crop wild relatives, and orphan crops is a key prerequisite to accelerate genetic gain of abiotic stress tolerance in annual crops such as legumes and cereals, many of which are still orphan species despite advances in major row crops. Here, we review a novel, interdisciplinary approach to combine ecological climate data with evolutionary genomics under the paradigm of a new field of study: genome-environment associations (GEAs). We first exemplify how GEA utilizes in situ georeferencing from genotypically characterized, gene bank accessions to pinpoint genomic signatures of natural selection. We later discuss the necessity to update the current GEA models to predict both regional- and local- or micro-habitat-based adaptation with mechanistic ecophysiological climate indices and cutting-edge GWAS-type genetic association models. Furthermore, to account for polygenic evolutionary adaptation, we encourage the community to start gathering genomic estimated adaptive values (GEAVs) for genomic prediction (GP) and multi-dimensional machine learning (ML) models. The latter two should ideally be weighted by de novo GWAS-based GEA estimates and optimized for a scalable marker subset. We end the review by envisioning avenues to make adaptation inferences more robust through the merging of high-resolution data sources, such as environmental remote sensing and summary statistics of the genomic site frequency spectrum, with the epigenetic molecular functionality responsible for plastic inheritance in the wild. Ultimately, we believe that coupling evolutionary adaptive predictions with innovations in ecological genomics such as GEA will help capture hidden genetic adaptations to abiotic stresses based on crop germplasm resources to assist responses to climate change. "I shall endeavor to find out how nature's forces act upon one another, and in what manner the geographic environment exerts its influence on animals and plants. In short, I must find out about the harmony in nature" Alexander von Humboldt-Letter to Karl Freiesleben, June 1799.

Transcriptome Analysis of Pennisetum glaucum (L.) R. Br. Provides Insight Into Heat Stress Responses

Pennisetum glaucum (L.) R. Br., being widely grown in dry and hot weather, frequently encounters heat stress at various stages of growth. The crop, due to its inherent capacity, efficiently overcomes such stress during vegetative stages. However, the same is not always the case with the terminal (flowering through grain filling) stages of growth, where recovery from stress is more challenging. However, certain pearl millet genotypes such as 841-B are known to overcome heat stress even at the terminal growth stages. Therefore, we performed RNA sequencing of two contrasting genotypes of pearl millet (841-B and PPMI-69) subjected to heat stress (42°C for 6 h) at flowering stages. Over 274 million high quality reads with an average length of 150 nt were generated, which were assembled into 47,310 unigenes having an average length of 1,254 nucleotides, N50 length of 1853 nucleotides, and GC content of 53.11%. Blastx resulted in the annotation of 35,628 unigenes, and functional classification showed 15,950 unigenes designated to 51 Gene Ontology terms. A total of 13,786 unigenes were allocated to 23 Clusters of Orthologous Groups, and 4,255 unigenes were distributed to 132 functional Kyoto Encyclopedia of Genes and Genomes database pathways. A total of 12,976 simple sequence repeats and 305,759 SNPs were identified in the transcriptome data. Out of 2,301 differentially expressed genes, 10 potential candidate genes were selected based on log2 fold change and adjusted p value parameters for their differential gene expression by qRT-PCR. We were able to identify differentially expressed genes unique to either of the two genotypes, and also, some DEGs common to both the genotypes were enriched. The differential expression patterns suggested that 841-B 6 h has better ability to maintain homeostasis during heat stress as compared to PPMI-69 6 h. The sequencing data generated in this study, like the SSRs and SNPs, shall serve as an important resource for the development of genetic markers, and the differentially expressed heat responsive genes shall be used for the development of transgenic crops.

Breeding Drought-Tolerant Pearl Millet Using Conventional and Genomic Approaches: Achievements and Prospects

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a C4 crop cultivated for its grain and stover in crop-livestock-based rain-fed farming systems of tropics and subtropics in the Indian subcontinent and sub-Saharan Africa. The intensity of drought is predicted to further exacerbate because of looming climate change, necessitating greater focus on pearl millet breeding for drought tolerance. The nature of drought in different target populations of pearl millet-growing environments (TPEs) is highly variable in its timing, intensity, and duration. Pearl millet response to drought in various growth stages has been studied comprehensively. Dissection of drought tolerance physiology and phenology has helped in understanding the yield formation process under drought conditions. The overall understanding of TPEs and differential sensitivity of various growth stages to water stress helped to identify target traits for manipulation through breeding for drought tolerance. Recent advancement in high-throughput phenotyping platforms has made it more realistic to screen large populations/germplasm for drought-adaptive traits. The role of adapted germplasm has been emphasized for drought breeding, as the measured performance under drought stress is largely an outcome of adaptation to stress environments. Hybridization of adapted landraces with selected elite genetic material has been stated to amalgamate adaptation and productivity. Substantial progress has been made in the development of genomic resources that have been used to explore genetic diversity, linkage mapping (QTLs), marker-trait association (MTA), and genomic selection (GS) in pearl millet. High-throughput genotyping (HTPG) platforms are now available at a low cost, offering enormous opportunities to apply markers assisted selection (MAS) in conventional breeding programs targeting drought tolerance. Next-generation sequencing (NGS) technology, micro-environmental modeling, and pearl millet whole genome re-sequence information covering circa 1,000 wild and cultivated accessions have helped to greater understand germplasm, genomes, candidate genes, and markers. Their application in molecular breeding would lead to the development of high-yielding and drought-tolerant pearl millet cultivars. This review examines how the strategic use of genetic resources, modern genomics, molecular biology, and shuttle breeding can further enhance the development and delivery of drought-tolerant cultivars.

Rewilding crops for climate resilience: economic analysis and de novo domestication strategies

To match predicted population growth, annual food production should be doubled by 2050. This is not achievable by current agronomical and breeding practices, due to the impact of climate changes and associated abiotic stresses on agricultural production systems. Here, we analyze the impact of global climate trends on crop productivity and show that the overall loss in crop production from climate-driven abiotic stresses may exceed US$170 billion year-1 and represents a major threat to global food security. We also show that abiotic stress tolerance had been present in wild progenitors of modern crops but was lost during their domestication. We argue for a major shift in our paradigm of crop breeding, focusing on climate resilience, and call for a broader use of wild relatives as a major tool in this process. We argue that, while molecular tools are currently in place to harness the potential of climate-resilient genes present in wild relatives, the complex polygenic nature of tolerance traits remains a major bottleneck in this process. Future research efforts should be focused not only on finding appropriate wild relatives but also on development of efficient cell-based high-throughput phenotyping platforms allowing assessment of the in planta operation of key genes.

Abandonment of pearl millet cropping and homogenization of its diversity over a 40 year period in Senegal

Cultivated diversity is considered an insurance against major climatic variability. However, since the 1980s, several studies have shown that climate variability and agricultural changes may already have locally eroded crop genetic diversity. We studied pearl millet diversity in Senegal through a comparison of pearl millet landraces collected 40 years apart. We found that more than 20% of villages visited in 1976 had stopped growing pearl millet. Despite this, its overall genetic diversity has been maintained but differentiation between early- and late-flowering accessions has been reduced. We also found stronger crop-to-wild gene flow than wild-to-crop gene flow and that wild-to-crop gene flow was weaker in 2016 than in 1976. In conclusion, our results highlight genetic homogenization in Senegal. This homogenization within cultivated pearl millet and between wild and cultivated forms is a key factor in genetic erosion and it is often overlooked. Improved assessment and conservation strategies are needed to promote and conserve both wild and cultivated pearl millet diversity.

Exploring the application of wild species for crop improvement in a changing climate

Modern agriculture is currently facing challenges from a burgeoning population and changing climate, which requires improved crops with adaptation to climate and elite yield and quality traits. While there is a breeding bottleneck caused by intensive selection, gene banks containing conserved wild relatives and landraces can be used as breeding resources. However, with limited genetic information available on these wild relatives, the application has been hindered. With the development of both genomics and bioinformatics techniques, it is now easier to identify the genetic variation in wild species, which can be utilized for the introgression of elite traits. These wild species can therefore play an important role in food security and breeding sustainability.

Transcriptome analysis of heat stress and drought stress in pearl millet based on Pacbio full-length transcriptome sequencing

BACKGROUND

Heat and drought are serious threats for crop growth and development. As the sixth largest cereal crop in the world, pearl millet can not only be used for food and forage but also as a source of bioenergy. Pearl millet is highly tolerant to heat and drought. Given this, it is considered an ideal crop to study plant stress tolerance and can be used to identify heat-resistant genes.

RESULTS

In this study, we used Pacbio sequencing data as a reference sequence to analyze the Illumina data of pearl millet that had been subjected to heat and drought stress for 48 h. By summarizing previous studies, we found 26,299 new genes and 63,090 new transcripts, and the number of gene annotations increased by 20.18%. We identified 2792 transcription factors and 1223 transcriptional regulators. There were 318 TFs and 149 TRs differentially expressed under heat stress, and 315 TFs and 128 TRs were differentially expressed under drought stress. We used RNA sequencing to identify 6920 genes and 6484 genes differentially expressed under heat stress and drought stress, respectively.

CONCLUSIONS

Through Pacbio sequencing, we have identified more new genes and new transcripts. On the other hand, comparing the differentially expressed genes under heat tolerance with the DEGs under drought stress, we found that even in the same pathway, pearl millet responds with a different protein.

Landscape genetics reveals that adaptive genetic divergence in Pinus bungeana (Pinaceae) is driven by environmental variables relating to ecological habitats

Background

Understanding the genetic basis of local adaptation has long been the concern of biologists. Identifying these adaptive genetic variabilities is crucial not only to improve our knowledge of the genetic mechanism of local adaptation but also to explore the adaptation potential of species.

Results

Using 10 natural populations and 12 start codon targeted (SCoT) markers, a total of 430 unambiguous loci were yielded. The Bayesian analysis of population structure clearly demonstrated that the 10 populations of P. bungeana could be subdivided into three groups. Redundancy analysis showed that this genetic divergence was caused by divergence selection from environmental variables related to the ecological habitats of “avoidance of flooding” and “avoidance of high temperature and humidity.” LFMM results indicated that Bio1, Bio5, Bio8, Bio12, Bio14, and Bio16, which are related to the ecological habitat of P. bungeana, were correlated with the highest numbers of environment-associated loci (EAL).

Conclusions

The results of EAL characterization in P. bungeana clearly supported the hypothesis that environmental variations related to the ecological habitat of species are the key drivers of species adaptive divergence. Moreover, a method to calculate the species landscape adaptation index and quantify the adaptation potential of species was proposed and verified using ecological niche modeling. This model could estimate climatically suitable areas of species spatial distribution. Taking the results together, this study improves the current understanding on the genetic basis of local adaptation.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1489-x) contains supplementary material, which is available to authorized users.

Adaptive Introgression: An Untapped Evolutionary Mechanism for Crop Adaptation

Global environmental changes strongly impact wild and domesticated species biology and their associated ecosystem services. For crops, global warming has led to significant changes in terms of phenology and/or yield. To respond to the agricultural challenges of this century, there is a strong need for harnessing the genetic variability of crops and adapting them to new conditions. Gene flow, from either the same species or a different species, may be an immediate primary source to widen genetic diversity and adaptions to various environments. When the incorporation of a foreign variant leads to an increase of the fitness of the recipient pool, it is referred to as "adaptive introgression". Crop species are excellent case studies of this phenomenon since their genetic variability has been considerably reduced over space and time but most of them continue exchanging genetic material with their wild relatives. In this paper, we review studies of adaptive introgression, presenting methodological approaches and challenges to detecting it. We pay particular attention to the potential of this evolutionary mechanism for the adaptation of crops. Furthermore, we discuss the importance of farmers' knowledge and practices in shaping wild-to-crop gene flow. Finally, we argue that screening the wild introgression already existing in the cultivated gene pool may be an effective strategy for uncovering wild diversity relevant for crop adaptation to current environmental changes and for informing new breeding directions.

Accuracy of RNAseq based SNP discovery and genotyping in Populusnigra

Backgroud

Populus nigra is a major tree species of ecological and economic importance for which several initiatives have been set up to create genomic resources. In order to access the large number of Single Nucleotide Polymorphisms (SNPs) typically needed to carry out a genome scan, the present study aimed at evaluating RNA sequencing as a tool to discover and type SNPs in genes within natural populations of P. nigra.

Results

We have devised a bioinformatics pipeline to call and type SNPs from RNAseq reads and applied it to P. nigra transcriptomic data. The accuracy of the resulting RNAseq-based SNP calling and typing has been evaluated by (i) comparing their position and alleles to those previously reported in candidate genes, (ii) assessing their genotyping accuracy with respect to a previously available SNP chip and (iii) evaluating their inter-annual repeatability. We found that a combination of several callers yields a good compromise between the number of variants type and the accuracy of genotyping. We further used the resulting genotypic data to carry out basic genetic analyses whose results confirm the quality of the RNAseq-based SNP dataset.

Conclusions

We demonstrated the potential and accuracy of RNAseq as an efficient way to genotype SNPs in P. nigra. These results open prospects towards the use of this technology for quantitative and population genomics studies.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5239-z) contains supplementary material, which is available to authorized users.

The search for loci under selection: trends, biases and progress

Detecting genetic variants under selection using F_ST outlier analysis (OA) and environmental association analyses (EAAs) are popular approaches that provide insight into the genetic basis of local adaptation. Despite the frequent use of OA and EAA approaches and their increasing attractiveness for detecting signatures of selection, their application to field-based empirical data have not been synthesized. Here, we review 66 empirical studies that use Single Nucleotide Polymorphisms (SNPs) in OA and EAA. We report trends and biases across biological systems, sequencing methods, approaches, parameters, environmental variables and their influence on detecting signatures of selection. We found striking variability in both the use and reporting of environmental data and statistical parameters. For example, linkage disequilibrium among SNPs and numbers of unique SNP associations identified with EAA were rarely reported. The proportion of putatively adaptive SNPs detected varied widely among studies, and decreased with the number of SNPs analysed. We found that genomic sampling effort had a greater impact than biological sampling effort on the proportion of identified SNPs under selection. OA identified a higher proportion of outliers when more individuals were sampled, but this was not the case for EAA. To facilitate repeatability, interpretation and synthesis of studies detecting selection, we recommend that future studies consistently report geographical coordinates, environmental data, model parameters, linkage disequilibrium, and measures of genetic structure. Identifying standards for how OA and EAA studies are designed and reported will aid future transparency and comparability of SNP-based selection studies and help to progress landscape and evolutionary genomics.

Genotyping by Sequencing and Genome-Environment Associations in Wild Common Bean Predict Widespread Divergent Adaptation to Drought

Drought will reduce global crop production by >10% in 2050 substantially worsening global malnutrition. Breeding for resistance to drought will require accessing crop genetic diversity found in the wild accessions from the driest high stress ecosystems. Genome-environment associations (GEA) in crop wild relatives reveal natural adaptation, and therefore can be used to identify adaptive variation. We explored this approach in the food crop Phaseolus vulgaris L., characterizing 86 geo-referenced wild accessions using genotyping by sequencing (GBS) to discover single nucleotide polymorphisms (SNPs). The wild beans represented Mesoamerica, Guatemala, Colombia, Ecuador/Northern Peru and Andean groupings. We found high polymorphism with a total of 22,845 SNPs across the 86 accessions that confirmed genetic relationships for the groups. As a second objective, we quantified allelic associations with a bioclimatic-based drought index using 10 different statistical models that accounted for population structure. Based on the optimum model, 115 SNPs in 90 regions, widespread in all 11 common bean chromosomes, were associated with the bioclimatic-based drought index. A gene coding for an ankyrin repeat-containing protein and a phototropic-responsive NPH3 gene were identified as potential candidates. Genomic windows of 1 Mb containing associated SNPs had more positive Tajima's D scores than windows without associated markers. This indicates that adaptation to drought, as estimated by bioclimatic variables, has been under natural divergent selection, suggesting that drought tolerance may be favorable under dry conditions but harmful in humid conditions. Our work exemplifies that genomic signatures of adaptation are useful for germplasm characterization, potentially enhancing future marker-assisted selection and crop improvement.

No Excess of Cis-Regulatory Variation Associated with Intraspecific Selection in Wild Pearl Millet (Cenchrus americanus)

Several studies suggest that cis-regulatory mutations are the favorite target of evolutionary changes, one reason being that cis-regulatory mutations might have fewer deleterious pleiotropic effects than protein-coding mutations. A review of the process also suggests that this bias towards adaptive cis-regulatory variation might be less pronounced at the intraspecific level compared with the interspecific level. In this study, we assessed the contribution of cis-regulatory variation to adaptation at the intraspecific level using populations of wild pearl millet (Cenchrus americanus ssp. monodii) sampled along an environmental gradient in Niger. From RNA sequencing of hybrids to assess allele-specific expression, we identified genes with cis-regulatory divergence between two parental accessions collected in contrasted environmental conditions. This revealed that ∼15% of transcribed genes showed cis-regulatory variation. Intersecting the gene set exhibiting cis-regulatory variation with the gene set identified as targets of selection revealed no excess of cis-acting mutations among the selected genes. We additionally found no excess of cis-regulatory variation among genes associated with adaptive traits. As our approach relied on methods identifying mainly genes submitted to strong selection pressure or with high phenotypic effect, the contribution of cis-regulatory changes to soft selection or polygenic adaptive traits remains to be tested. However our results favor the hypothesis that enrichment of adaptive cis-regulatory divergence builds up over time. For short evolutionary time-scales, cis-acting mutations are not predominantly involved in adaptive evolution associated with strong selective signal.

Myosin XI is associated with fitness and adaptation to aridity in wild pearl millet

Phenotypic changes in plants can be observed along many environmental gradients and are determined by both environmental and genetic factors. The identification of alleles associated with phenotypic variations is a rapidly developing area of research. We studied the genetic basis of phenotypic variations in 11 populations of wild pearl millet (Pennisetum glaucum) on two North-South aridity gradients, one in Niger and one in Mali. Most of the 11 phenotypic traits assessed in a common garden experiment varied between the populations studied. Moreover, the size of the inflorescence, the number of flowers and aboveground dry mass co-varied positively with a decrease in rainfall. To decipher the genetic basis of these phenotypes, we used an association mapping strategy with a mixed model. We found two SNPs on the same myosin XI contig significantly associated with variations in the average number of flowers. Both the allele frequency of the two SNPs and the average number of flowers co-varied with the rainfall gradient on the two gradients. Interestingly, this gene was also a target of selection during domestication. The Myosin XI gene is thus a good candidate for fitness-related adaptation in wild populations.