Moses M. Muraya

Ecogeographical distribution of wild, weedy and cultivated Sorghum bicolor (L.) Moench in Kenya: implications for conservation and crop-to-wild gene flow

The potential gene flow between a crop and its wild relatives is largely determined by the overlaps in their ecological and geographical distributions. Ecogeographical databases are therefore indispensable tools for the sustainable management of genetic resources. In order to expand our knowledge of Sorghum bicolor distribution in Kenya, we conducted in situ collections of wild, weedy and cultivated sorghum. Qualitative and quantitative morphological traits were measured for each sampled wild sorghum plant. Farmers’ knowledge relating to the management of sorghum varieties and autecology of wild sorghum was also obtained. Cluster analysis supports the existence of several wild sorghum morphotypes that might correspond to at least three of the five ecotypes recognized in Africa. Intermediate forms between wild and cultivated sorghum belonging to the S. bicolor ssp. drummondii are frequently found in predominantly sorghum growing areas. Crop-wild gene flow in sorghum is likely to occur in many agroecosystems of Kenya.

Genetic structure and relationships within and between cultivated and wild sorghum (Sorghum bicolor (L.) Moench) in Kenya as revealed by microsatellite markers

Understanding the extent and partitioning of diversity within and among crop landraces and their wild/weedy relatives constitutes the first step in conserving and unlocking their genetic potential. This study aimed to characterize the genetic structure and relationships within and between cultivated and wild sorghum at country scale in Kenya, and to elucidate some of the underlying evolutionary mechanisms. We analyzed at total of 439 individuals comprising 329 cultivated and 110 wild sorghums using 24 microsatellite markers. We observed a total of 295 alleles across all loci and individuals, with 257 different alleles being detected in the cultivated sorghum gene pool and 238 alleles in the wild sorghum gene pool. We found that the wild sorghum gene pool harbored significantly more genetic diversity than its domesticated counterpart, a reflection that domestication of sorghum was accompanied by a genetic bottleneck. Overall, our study found close genetic proximity between cultivated sorghum and its wild progenitor, with the extent of crop-wild divergence varying among cultivation regions. The observed genetic proximity may have arisen primarily due to historical and/or contemporary gene flow between the two congeners, with differences in farmers’ practices explaining inter-regional gene flow differences. This suggests that deployment of transgenic sorghum in Kenya may lead to escape of transgenes into wild-weedy sorghum relatives. In both cultivated and wild sorghum, genetic diversity was found to be structured more along geographical level than agro-climatic level. This indicated that gene flow and genetic drift contributed to shaping the contemporary genetic structure in the two congeners. Spatial autocorrelation analysis revealed a strong spatial genetic structure in both cultivated and wild sorghums at the country scale, which could be explained by medium- to long-distance seed movement.

Wild sorghum from different eco-geographic regions of Kenya display a mixed mating system

Knowledge of mating systems is required in order to understand the genetic composition and evolutionary potential of plant populations. Outcrossing in a population may co-vary with the ecological and historical factors influencing it. However, literature on the outcrossing rate is limited in terms of wild sorghum species coverage and eco-geographic reference. This study investigated the outcrossing rates in wild sorghum populations from different ecological conditions of Kenya. Twelve wild sorghum populations were collected in four sorghum growing regions. Twenty-four individuals per population were genotyped using six polymorphic simple sequence repeat (SSR) markers to compute their indirect equilibrium estimates of outcrossing rate as well as population structure. In addition, the 12 populations were planted in a field in a randomised block design with five replications. Their progeny (250 individuals per population) were genotyped with the six SSR markers to estimate multi-locus outcrossing rates. Equilibrium estimates of outcrossing rates ranged from 7.0 to 75.0%, while multi-locus outcrossing rates (tm) ranged from 8.9 to 70.0% with a mean of 49.7%, indicating that wild sorghum exhibits a mixed mating system. The wide range of estimated outcrossing rates in wild sorghum populations indicate that environmental conditions may exist under which fitness is favoured by outcrossing and others under which selfing is more advantageous. The genetic structure of the populations studied is concordant with that expected for a species displaying mixed mating system.

Targeted Sequencing Reveals Large-Scale Sequence Polymorphism in Maize Candidate Genes for Biomass Production and Composition

A major goal of maize genomic research is to identify sequence polymorphisms responsible for phenotypic variation in traits of economic importance. Large-scale detection of sequence variation is critical for linking genes, or genomic regions, to phenotypes. However, due to its size and complexity, it remains expensive to generate whole genome sequences of sufficient coverage for divergent maize lines, even with access to next generation sequencing (NGS) technology. Because methods involving reduction of genome complexity, such as genotyping-by-sequencing (GBS), assess only a limited fraction of sequence variation, targeted sequencing of selected genomic loci offers an attractive alternative. We therefore designed a sequence capture assay to target 29 Mb genomic regions and surveyed a total of 4,648 genes possibly affecting biomass production in 21 diverse inbred maize lines (7 flints, 14 dents). Captured and enriched genomic DNA was sequenced using the 454 NGS platform to 19.6-fold average depth coverage, and a broad evaluation of read alignment and variant calling methods was performed to select optimal procedures for variant discovery. Sequence alignment with the B73 reference and de novo assembly identified 383,145 putative single nucleotide polymorphisms (SNPs), of which 42,685 were non-synonymous alterations and 7,139 caused frameshifts. Presence/absence variation (PAV) of genes was also detected. We found that substantial sequence variation exists among genomic regions targeted in this study, which was particularly evident within coding regions. This diversification has the potential to broaden functional diversity and generate phenotypic variation that may lead to new adaptations and the modification of important agronomic traits. Further, annotated SNPs identified here will serve as useful genetic tools and as candidates in searches for phenotype-altering DNA variation. In summary, we demonstrated that sequencing of captured DNA is a powerful approach for variant discovery in maize genes.

Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping

Summary Hitherto, most quantitative trait loci of maize growth and biomass yield have been identified for a single time point, usually the final harvest stage. Through this approach cumulative effects are detected, without considering genetic factors causing phase‐specific differences in growth rates. To assess the genetics of growth dynamics, we employed automated non‐invasive phenotyping to monitor the plant sizes of 252 diverse maize inbred lines at 11 different developmental time points; 50 k SNP array genotype data were used for genome‐wide association mapping and genomic selection. The heritability of biomass was estimated to be over 71%, and the average prediction accuracy amounted to 0.39. Using the individual time point data, 12 main effect marker‐trait associations (MTAs) and six pairs of epistatic interactions were detected that displayed different patterns of expression at various developmental time points. A subset of them also showed significant effects on relative growth rates in different intervals. The detected MTAs jointly explained up to 12% of the total phenotypic variation, decreasing with developmental progression. Using non‐parametric functional mapping and multivariate mapping approaches, four additional marker loci affecting growth dynamics were detected. Our results demonstrate that plant biomass accumulation is a complex trait governed by many small effect loci, most of which act at certain restricted developmental phases. This highlights the need for investigation of stage‐specific growth affecting genes to elucidate important processes operating at different developmental phases. Significance Statement Most genetic studies of biomass accumulation or yield in crops have focused on a single growth stage, but agronomic traits are complex and controlled by many genes, each with small effect. Here we use high‐throughput non‐invasive phenotyping to show that genetic effects on maize biomass accumulation differ across developmental phases, that there are complex interactions of loci with developmental progression, that allele effects and epistatic interaction patterns change over time, and that functional mapping can uncover additional genetic factors. Our results indicate that continuous assessment of growth dynamics coupled with transcript profiling will aid in detecting superior stage‐specific genes/alleles and thus provide a powerful tool for crop improvement.

Genetic structure and diversity of wild sorghum populations (Sorghum spp.) from different eco-geographical regions of Kenya

Wild sorghums are extremely diverse phenotypically, genetically and geographically. However, there is an apparent lack of knowledge on the genetic structure and diversity of wild sorghum populations within and between various eco-geographical regions. This is a major obstacle to both their effective conservation and potential use in breeding programs. The objective of this study was to assess the genetic diversity and structure of wild sorghum populations across a range of eco-geographical conditions in Kenya. Sixty-two wild sorghum populations collected from the 4 main sorghum growing regions in Kenya were genotyped using 18 simple sequence repeat markers. The study showed that wild sorghum is highly variable with the Coast region displaying the highest diversity. Analysis of molecular variance showed a significant variance component within and among wild sorghum populations within regions. The genetic structure of wild sorghum populations indicated that gene flow is not restricted to populations within the same geographic region. A weak regional differentiation was found among populations, reflecting human intervention in shaping wild sorghum genetic structure through seed-mediated gene flow. The sympatric occurrence of wild and cultivated sorghums coupled with extensive seed-mediated gene flow, suggests a potential crop-to-wild gene flow and vice versa across the regions. Wild sorghum displayed a mixed mating system. The wide range of estimated outcrossing rates indicate that some environmental conditions may exist where self-fertilisation is favoured while others cross-pollination is more advantageous.

Investigation of pollen competition between wild and cultivated sorghums (Sorghum bicolor (L.) Moench) using simple sequence repeats markers

In self-compatible plant species stigmata receive a mixture of self and outcrossed pollen and competition between them is expected to play a major role in determining the pollen-mediated gene flow. The use of male sterile bait plants in field trials to demonstrate the rate of gene flow is questionable due to lack of pollination competition. However, little direct evidence has been published. A field experiment of male sterile and male fertile sorghum pollen recipient bait plants was conducted to evaluate pollen competition between wild and cultivated sorghums and the effects of pollen competition on gene flow assessment. Pollen competition between wild and cultivated sorghums was estimated from two-component pollen mixtures of wild and cultivated sorghum (1:1 ratio) applied to wild, cultivated and male-sterile maternal bait plants. Paternity was determined in the progeny using two diagnostic Simple Sequence Repeat markers. The study found that self pollen has higher seed-siring success. Maternal genotype influences the siring ability of the pollen donor components which significantly deviated from the 1:1 pollen loads. The study showed that published estimates of gene flow derived from studies using male-sterile bait plants seriously overestimate gene flow and that pollen competition may be a significant factor influencing outcrossing rates. The results suggest that the predominant direction of gene flow is from cultivated to wild sorghum, potentially leading to introgression of crop genes into wild sorghum. Pollen competition should be taken into account in gene flow estimation, since presence of self-pollen can account for over half of seed produced irrespective of maternal genotype.

Investigation of recent population bottlenecks in Kenyan wild sorghum populations (#Sorghum bicolor# (L.) Moench ssp. #verticilliflorum# (Steud.) De Wet) based on microsatellite diversity and genetic disequilibria

Identifying populations that have recently suffered a severe reduction in size is particularly important for their conservation as they are likely to suffer an increased risk of genetic erosion. We investigated the presence of recent bottlenecks in two wild sorghum populations from different eco-geographical conditions in Kenya employing 18 microsatellite markers. Microsatellite analysis showed high allelic diversity in the two populations, with a mean of 4.11 and 6.94 alleles per locus in the North-West wild sorghum population (NWWSP) and the South-East wild sorghum population (SEWSP), respectively. The mean observed heterozygosity was 0.34 and 0.56 in NWWSP and SEWSP, respectively. A large long-term effective populations size for both populations was observed assuming either an infinite allele model or a stepwise mutation model. There was no apparent loss of genetic variability for either of the populations. Test of heterozygosity excess indicated that a recent bottleneck in the two populations is highly unlikely. Furthermore, analysis of the allele frequency distribution revealed an L-shaped distribution which would not have been observed in case a recent bottleneck had reduced genetic variability in the two populations. The fact that most loci displayed a significant heterozygosity deficiency could be explained by population subdivision and the mixed mating system exhibited by wild sorghum populations. Furthermore, the possibility of a historical expansion of wild sorghum populations and presence of null alleles could not be ruled out.

Phenomic prediction of maize hybrids

Phenomic experiments are carried out in large-scale plant phenotyping facilities that acquire a large number of pictures of hundreds of plants simultaneously. With the aid of automated image processing, the data are converted into genotype-feature matrices that cover many consecutive days of development. Here, we explore the possibility of predicting the biomass of the fully grown plant from early developmental stage image-derived features. We performed phenomic experiments on 195 inbred and 382 hybrid maizes varieties and followed their progress from 16 days after sowing (DAS) to 48 DAS with 129 image-derived features. By applying sparse regression methods, we show that 73% of the variance in hybrid fresh weight of fully-grown plants is explained by about 20 features at the three-leaf-stage or earlier. Dry weight prediction explained over 90% of the variance. When phenomic features of parental inbred lines were used as predictors of hybrid biomass, the proportion of variance explained was 42 and 45%, for fresh weight and dry weight models consisting of 35 and 36 features, respectively. These models were very robust, showing only a small amount of variation in performance over the time scale of the experiment. We also examined mid-parent heterosis in phenomic features. Feature heterosis displayed a large degree of variance which resulted in prediction performance that was less robust than models of either parental or hybrid predictors. Our results show that phenomic prediction is a viable alternative to genomic and metabolic prediction of hybrid performance. In particular, the utility of early-stage parental lines is very encouraging.

Towards a graph-theoretic approach to hybrid performance prediction from large-scale phenotypic data

High-throughput biological data analysis has received a large amount of interest in the last decade due to pioneering technologies that are able to automatically generate large-scale datasets by performing millions of analytical tests on a daily basis. Here we present a new network-based approach to analyze a high-throughput phenomic dataset that was collected on maize inbreds and hybrids by an automated phenotyping facility. Our dataset consists of 1600 biological samples from 600 different genotypes (200 inbred and 400 hybrid lines). On each sample, 141 phenotypic traits were observed for 33 days. We apply a graph-theoretic approach to address two important problems: (i) to discover meaningful patterns in the dataset and (ii) to predict hybrid performance in terms of biomass based on automatically collected phenotypic traits. We propose a modelling framework in which the prediction problem becomes transformed into finding the shortest path in a correlation-based network. Preliminary results show small but encouraging correlations between predicted and observed biomass. Extensions of the algorithm and applications of the modelling framework to other types of biological data are discussed.