Spatial structure and climatic adaptation in African maize revealed by surveying SNP diversity in relation to global breeding and landrace panels

Detection of the local adaptive and genome-wide associated loci in southeast Nigerian taro (Colocasia esculenta (L.) Schott) populations

BACKGROUND

Taro has a long history of being consumed and remains orphan and on the hand Nigeria farmers. The role of farmer-driven artificial selection is not negligible to fit landraces to a particular ecological condition. Limited study has been conducted on genome-wide association and no study has been conducted on genome-environment association for clinal adaptation for taro. Therefore, the objective of this study was to detect loci that are associated with environmental variables and phenotype traits and forward input to breeders. The study used 92 geographical referred taro landraces collected from Southeast (SE) Nigeria.

RESULTS

The result indicates that SE Nigerian taro has untapped phenotype and genetic variability with low admixture. Redundancy analysis indicated that collinear explained SNP variation more than single climatic variable. Overall, the results indicated that no single method exclusively was able to capture population confounding effects better than the others for all six traits. Nevertheless, based on overall model performance, Blink seemed to provide slight advantage over other models and was selected for all subsequent assessment of genome-environment association (GEA) and genome-wide association study (GWAS) models. Genome scan and GEA identified local adapted loci and co-located genes. A total of nine SNP markers associated with environmental variables. Some of the SNP markers (such as S_101024366) co-located with genes which previously reported for climatic adaptation such as astringency, diaminopimelate decarboxylase and MYB transcription factor. Genome-wide association also identified 45, 40 and 34 significant SNP markers associated with studied traits in combined, year 1 and year 2 data sets, respectively. Out of these, five SNP markers (S1_18891752 S3_100795476, S1_100584471 S1_100896936 and S2_10058799) were consistent in two different data sets.

CONCLUSIONS

The findings from this study improve our understanding of the genetic control of adaptive and phenotypic traits in Nigerian taro. However, the study suggests further study on identification of local adaptive loci and GWAS through collection of more landraces throughout the country, and across different agro-ecologies.

Modeling of Flowering Time in Vigna radiata with Artificial Image Objects, Convolutional Neural Network and Random Forest

Flowering time is an important target for breeders in developing new varieties adapted to changing conditions. In this work, a new approach is proposed in which the SNP markers influencing time to flowering in mung bean are selected as important features in a random forest model. The genotypic and weather data are encoded in artificial image objects, and a model for flowering time prediction is constructed as a convolutional neural network. The model uses weather data for only a limited time period of 5 days before and 20 days after planting and is capable of predicting the time to flowering with high accuracy. The most important factors for model solution were identified using saliency maps and a Score-CAM method. Our approach can help breeding programs harness genotypic and phenotypic diversity to more effectively produce varieties with a desired flowering time.

Climate Adaptation, Drought Susceptibility, and Genomic-Informed Predictions of Future Climate Refugia for the Australian Forest Tree Eucalyptus globulus

Understanding the capacity of forest tree species to adapt to climate change is of increasing importance for managing forest genetic resources. Through a genomics approach, we modelled spatial variation in climate adaptation within the Australian temperate forest tree Eucalyptus globulus, identified putative climate drivers of this genomic variation, and predicted locations of future climate refugia and populations at-risk of future maladaptation. Using 812,158 SNPs across 130 individuals from 30 populations (i.e., localities) spanning the species’ natural range, a gradientForest algorithm found 1177 SNPs associated with locality variation in home-site climate (climate-SNPs), putatively linking them to climate adaptation. Very few climate-SNPs were associated with population-level variation in drought susceptibility, signalling the multi-faceted nature and complexity of climate adaptation. Redundancy analysis (RDA) showed 24% of the climate-SNP variation could be explained by annual precipitation, isothermality, and maximum temperature of the warmest month. Spatial predictions of the RDA climate vectors associated with climate-SNPs allowed mapping of genomically informed climate selective surfaces across the species’ range under contemporary and projected future climates. These surfaces suggest over 50% of the current distribution of E. globulus will be outside the modelled adaptive range by 2070 and at risk of climate maladaptation. Such surfaces present a new integrated approach for natural resource managers to capture adaptive genetic variation and plan translocations in the face of climate change.

Dynamical climatic model for time to flowering in Vigna radiata

BACKGROUND

Phenology data collected recently for about 300 accessions of Vigna radiata (mungbean) is an invaluable resource for investigation of impacts of climatic factors on plant development.

RESULTS

We developed a new mathematical model that describes the dynamic control of time to flowering by daily values of maximal and minimal temperature, precipitation, day length and solar radiation. We obtained model parameters by adaptation to the available experimental data. The models were validated by cross-validation and used to demonstrate that the phenology of adaptive traits, like flowering time, is strongly predicted not only by local environmental factors but also by plant geographic origin and genotype.

CONCLUSIONS

Of local environmental factors maximal temperature appeared to be the most critical factor determining how faithfully the model describes the data. The models were applied to forecast time to flowering of accessions grown in Taiwan in future years 2020-2030.

Genomic Analysis of Selected Maize Landraces from Sahel and Coastal West Africa Reveals Their Variability and Potential for Genetic Enhancement

Genetic adaptation of maize to the increasingly unpredictable climatic conditions is an essential prerequisite for achievement of food security and sustainable development goals in sub-Saharan Africa. The landraces of maize; which have not served as sources of improved germplasm; are invaluable sources of novel genetic variability crucial for achieving this objective. The overall goal of this study was to assess the genetic diversity and population structure of a maize panel of 208 accessions; comprising landrace gene pools from Burkina Faso (58), Ghana (43), and Togo (89), together with reference populations (18) from the maize improvement program of the International Institute of Tropical Agriculture (IITA). Genotyping the maize panel with 5974 DArTseq-SNP markers revealed immense genetic diversity indicated by average expected heterozygosity (0.36), observed heterozygosity (0.5), and polymorphic information content (0.29). Model-based population structure; neighbor-joining tree; discriminant analysis of principal component; and principal coordinate analyses all separated the maize panel into three major sub-populations; each capable of providing a wide range of allelic variation. Analysis of molecular variance (AMOVA) showed that 86% of the variation was within individuals; while 14% was attributable to differences among gene pools. The Burkinabe gene pool was strongly differentiated from all the others (genetic differentiation values >0.20), with no gene flow (Nm) to the reference populations (Nm = 0.98). Thus; this gene pool could be a target for novel genetic variation for maize improvement. The results of the present study confirmed the potential of this maize panel as an invaluable genetic resource for future design of association mapping studies to speed-up the introgression of this novel variation into the existing breeding pipelines.

Transcriptional differentiation of UV-B protectant genes in maize landraces spanning an elevational gradient in Chiapas, Mexico

Globally, farmers cultivate and maintain crop landraces (i.e., traditional varieties). Landraces contain unique diversity shaped in part by natural and human-mediated selection and are an indispensable resource for farmers. Since environmental conditions change with elevation, crop landraces grown along elevational gradients have provided ideal locations to explore patterns of local adaptation. To further probe traits underlying this differentiation, transcriptome signatures can help provide a foundation for understanding the ways in which functional genetic diversity may be shaped by environment. In this study, we returned to an elevational gradient in Chiapas, Mexico, to assess transcriptional differentiation of genes underlying UV-B protection in locally adapted maize landraces from multiple elevations. We collected and planted landraces from three elevational zones (lowland, approximately 600 m; midland, approximately 1,550 m; highland approximately 2,100 m) in a common garden at 1,531 m. Using RNA-seq data derived from leaf tissue, we performed differential expression analysis between maize from these distinct elevations. Highland and lowland landraces displayed differential expression in phenylpropanoid and flavonoid biosynthesis genes involved in the production of UV-B protectants and did so at a rate greater than expected based on observed background transcriptional differentiation across the genome. These findings provide evidence for the differentiation of suites of genes involved in complex ecologically relevant pathways. Thus, while neutral evolutionary processes may have played a role in the observed patterns of differentiation, UV-B may have also acted as a selective pressure to differentiate maize landraces in the region. Studies of the distribution of functional crop genetic diversity across variable landscapes can aid us in understanding the response of diversity to abiotic/biotic change and, ultimately, may facilitate its conservation and utilization.

A Missense Mutation of the HSPB7 Gene Associated with Heat Tolerance in Chinese Indicine Cattle

Simple Summary

A missense mutation (NC_037329.1: g.136054902 C > G: p. Ala69Gly) was identified in the heat shock protein family B (small) member 7 (HSPB7) gene in indicine cattle, which might be a candidate mutation associated with the heat tolerance. Here, Polymerase Chain Reaction and DNA sequencing methods were used to detect this mutation in 774 individuals belonging to 32 Chinese indigenous cattle breeds. The distribution of alleles of NC_037329.1: g.136054902 C > G displays significant geographical difference across native Chinese cattle breeds and cattle carrying allele G distributed in regions with higher mean annual temperature, relative humidity, and temperature humidity index. Our results demonstrate that the mutation of the HSPB7 gene in Chinese indicine cattle might be a candidate gene associated with the heat tolerance.

Abstract

The small heat shock proteins (HSPB) are expressed in response to heat stress, and the heat shock protein family B (small) member 7 (HSPB7) gene has been reported to play an important role in heat tolerance pathways. Only a missense mutation (NC_037329.1: g.136054902 C > G: p.Ala69Gly) was identified in the HSPB7 gene in indicine cattle, which might be a candidate mutation associated with the heat tolerance. Here, we explore the allele frequency of this mutation in 774 individuals belonging to 32 Chinese indigenous cattle breeds using polymerase chain reaction (PCR) and DNA sequencing methods. The distribution of alleles of NC_037329.1: g.136054902 C > G displays significant geographical difference across native Chinese cattle breeds that the allele C was dominant in northern cattle groups, while allele G was dominant in southern indicine cattle groups. Additionally, the association analysis indicated that the G allele was significantly associated with mean annual temperature (T), relative humidity (RH), and temperature humidity index (THI) (p < 0.01), suggesting that cattle carrying allele G were distributed in regions with higher T, RH, and THI. Our results demonstrate that the mutation of the HSPB7 gene in Chinese indicine cattle might be a candidate gene associated with the heat tolerance.

Technological advances in maize breeding: past, present and future

Maize has for many decades been both one of the most important crops worldwide and one of the primary genetic model organisms. More recently, maize breeding has been impacted by rapid technological advances in sequencing and genotyping technology, transformation including genome editing, doubled haploid technology, parallelled by progress in data sciences and the development of novel breeding approaches utilizing genomic information. Herein, we report on past, current and future developments relevant for maize breeding with regard to (1) genome analysis, (2) germplasm diversity characterization and utilization, (3) manipulation of genetic diversity by transformation and genome editing, (4) inbred line development and hybrid seed production, (5) understanding and prediction of hybrid performance, (6) breeding methodology and (7) synthesis of opportunities and challenges for future maize breeding.

Towards the Genomic Basis of Local Adaptation in Landraces

Landraces are key elements of agricultural biodiversity that have long been considered a source of useful traits. Their importance goes beyond subsistence agriculture and the essential need to preserve genetic diversity, because landraces are farmer-developed populations that are often adapted to environmental conditions of significance to tackle environmental concerns. It is therefore increasingly important to identify adaptive traits in crop landraces and understand their molecular basis. This knowledge is potentially useful for promoting more sustainable agricultural techniques, reducing the environmental impact of high-input cropping systems, and diminishing the vulnerability of agriculture to global climate change. In this review, we present an overview of the opportunities and limitations offered by landraces’ genomics. We discuss how rapid advances in DNA sequencing techniques, plant phenotyping, and recombinant DNA-based biotechnology encourage both the identification and the validation of the genomic signature of local adaptation in crop landraces. The integration of ‘omics’ sciences, molecular population genetics, and field studies can provide information inaccessible with earlier technological tools. Although empirical knowledge on the genetic and genomic basis of local adaptation is still fragmented, it is predicted that genomic scans for adaptation will unlock an intraspecific molecular diversity that may be different from that of modern varieties.

Assessing and Exploiting Functional Diversity in Germplasm Pools to Enhance Abiotic Stress Adaptation and Yield in Cereals and Food Legumes

There is a need to accelerate crop improvement by introducing alleles conferring host plant resistance, abiotic stress adaptation, and high yield potential. Elite cultivars, landraces and wild relatives harbor useful genetic variation that needs to be more easily utilized in plant breeding. We review genome-wide approaches for assessing and identifying alleles associated with desirable agronomic traits in diverse germplasm pools of cereals and legumes. Major quantitative trait loci and single nucleotide polymorphisms (SNPs) associated with desirable agronomic traits have been deployed to enhance crop productivity and resilience. These include alleles associated with variation conferring enhanced photoperiod and flowering traits. Genetic variants in the florigen pathway can provide both environmental flexibility and improved yields. SNPs associated with length of growing season and tolerance to abiotic stresses (precipitation, high temperature) are valuable resources for accelerating breeding for drought-prone environments. Both genomic selection and genome editing can also harness allelic diversity and increase productivity by improving multiple traits, including phenology, plant architecture, yield potential and adaptation to abiotic stresses. Discovering rare alleles and useful haplotypes also provides opportunities to enhance abiotic stress adaptation, while epigenetic variation has potential to enhance abiotic stress adaptation and productivity in crops. By reviewing current knowledge on specific traits and their genetic basis, we highlight recent developments in the understanding of crop functional diversity and identify potential candidate genes for future use. The storage and integration of genetic, genomic and phenotypic information will play an important role in ensuring broad and rapid application of novel genetic discoveries by the plant breeding community. Exploiting alleles for yield-related traits would allow improvement of selection efficiency and overall genetic gain of multigenic traits. An integrated approach involving multiple stakeholders specializing in management and utilization of genetic resources, crop breeding, molecular biology and genomics, agronomy, stress tolerance, and reproductive/seed biology will help to address the global challenge of ensuring food security in the face of growing resource demands and climate change induced stresses.

Analysis of genetic differentiation and genomic variation to reveal potential regions of importance during maize improvement

BACKGROUND

Exploring genetic differentiation and genomic variation is important for both the utilization of heterosis and the dissection of the genetic bases of complex traits.

METHODS

We integrated 1857 diverse maize accessions from America, Africa, Europe and Asia to investigatetheir genetic differentiation, genomic variation using 43,252 high-quality single-nucleotide polymorphisms(SNPs),combing GWAS and linkage analysis strategy to exploring the function of relevant genetic segments.

RESULTS

We uncovered many more subpopulations that recently or historically formed during the breeding process. These patterns are represented by the following lines: Mo17, GB, E28, Ye8112, HZS, Shen137, PHG39, B73, 207, A634, Oh43, Reid Yellow Dent, and the Tropical/subtropical (TS) germplasm. A total of 85 highly differentiated regions with a DEST of more than 0.2 were identified between the TS and temperate subpopulations. These regions comprised 79% of the genetic variation, and most were significantly associated with adaptive traits. For example, the region containing the SNP tag PZE.108075114 was highly differentiated, and this region was significantly associated with flowering time (FT)-related traits, as supported by a genome-wide association study (GWAS) within the interval of FT-related quantitative trait loci (QTL). This region was also closely linked to zcn8 and vgt1, which were shown to be involved in maize adaptation. Most importantly, 197 highly differentiated regions between different subpopulation pairs were located within an FT- or plant architecture-related QTL.

CONCLUSIONS

Here we reported that 700-1000 SNPs were necessary needed to robustly estimate the genetic differentiation of a naturally diverse panel. In addition, 13 subpopulations were observed in maize germplasm, 85 genetic regions with higher differentiation between TS and temperate maize germplasm, 197 highly differentiated regions between different subpopulation pairs, which contained some FT- related QTNs/QTLs/genes supported by GWAS and linkage analysis, and these regions were expected to play important roles in maize adaptation.

Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities.

Modern maize varieties going local in the semi-arid zone in Tanzania

BACKGROUND

Maize is the most produced crop in Sub-Saharan Africa, but yields are low and climate change is projected to further constrain smallholder production. The current efforts to breed and disseminate new high yielding and climate ready maize varieties are implemented through the formal seed system; the chain of public and private sector activities and institutions that produce and release certified seeds. These efforts are taking place in contexts currently dominated by informal seed systems; local and informal seed management and exchange channels with a long history of adapting crops to local conditions. We here present a case study of the genetic effects of both formal and informal seed management from the semi-arid zone in Tanzania.

RESULTS

Two open pollinated varieties (OPVs), Staha and TMV1, first released by the formal seed system in the 1980s are cultivated on two-thirds of the maize fields among the surveyed households. Farmer-recycling of improved varieties and seed selection are common on-farm seed management practices. Drought tolerance and high yield are the most important characteristics reported as reason for cultivating the current varieties as well as the most important criteria for farmers' seed selection. Bayesian cluster analysis, PCA and FST analyses based on 131 SNPs clearly distinguish between the two OPVs, and despite considerable heterogeneity between and within seed lots, there is insignificant differentiation between breeder's seeds and commercial seeds in both OPVs. Genetic separation increases as the formal system varieties enter the informal system and both hybridization with unrelated varieties and directional selection probably play a role in the differentiation. Using a Bayesian association approach we identify three loci putatively under selection in the informal seed system.

CONCLUSIONS

Our results suggest that the formal seed system in the study area distributes seed lots that are true to type. We suggest that hybridization and directional selection differentiate farmer recycled seed lots from the original varieties and potentially lead to beneficial creolization. Access to drought tolerant OPVs in combination with farmer seed selection is likely to enhance seed system security and farmers' adaptive capacity in the face of climate change.