Phosphorus uptake and utilization efficiency in West African pearl millet inbred lines

Pearl millet [Pennisetum glaucum (L.) R. Br] production on the acid sandy Sahelian soils in West Africa (WA) is severely limited by low plant-available phosphorus (P) in addition to erratic rainfall. We sought to examine the genetic variability for P uptake and P utilization efficiency in 180 WA pearl millet inbred lines or subsets thereof under low (LP) and high P (HP) conditions in one field and two pot experiments, determine the relationships among the measured traits and grain yield under field conditions at three other independent WA sites, and identify potential secondary selection traits for improving grain yield under LP. We observed genetic variation for P uptake and utilization in both seedling and mature plants. P utilization efficiency increased under LP conditions. Total P uptake was more important for grain production than P utilization under LP field conditions (r = 0.57*** vs r = 0.30***). The estimated response to indirect selection was positive for most of the measured morphological and P-efficiency parameters. We conclude that both seedling and mature plant traits are potentially useful as secondary traits in selection of pearl millet for low-P adaptation. These results should be validated using heterozygous pearl millet genetic materials. Ultimately, pearl millet breeding activities for low P tolerance in WA should be integrated with other system-oriented research such as nutrient cycling, intercropping or rotations with legumes, better crop-tree-livestock integration, and modest applications of locally available rock phosphate

Pearl Millet Inbred and Testcross Performance under Low Phosphorus in West Africa

Pearl millet [Pennisetum glaucum (L.) R. Br] is a food security crop for millions living in drylands of Africa and Asia. Its production on acid sandy soils of the Sahel is limited by erratic rainfall and poor soil fertility, especially low P soils. We sought to elucidate the genetic variation in West and Central African landrace-derived inbred lines for grain yield under low P conditions, to determine their performance as inbred lines per se and in hybrid combinations, and to determine quantitative-genetic parameters to derive an appropriate breeding strategy to enhance grain yield under low P conditions. We evaluated a total of 155 landrace-derived inbred lines as well as their testcrosses in four locations during two years under two treatments, high P (HP; with P fertilization) and low P (LP; without P fertilization). Results revealed significant effects for genotypes, P-level, genotype × P-level, as well as genotype × environment interactions. Grain yield reductions under LP treatment ranged from 7.9 to 35.5%, and 11.2 to 60.9% for inbred lines and testcrosses respectively, with positive midparent heterosis averaging 43.5% under LP. We conclude that direct selection of testcrosses under LP is more effective and that indirect selection for testross performance from inbred line performance is not desirable

Breeding schemes: what are they, how to formalize them, and how to improve them?

Open Access Journal; Published online: 21 Jan 2022Formalized breeding schemes are a key component of breeding program design and a gateway to conducting plant breeding as a quantitative process. Unfortunately, breeding schemes are rarely defined, expressed in a quantifiable format, or stored in a database. Furthermore, the continuous review and improvement of breeding schemes is not routinely conducted in many breeding programs. Given the rapid development of novel breeding methodologies, it is important to adopt a philosophy of continuous improvement regarding breeding scheme design. Here, we discuss terms and definitions that are relevant to formalizing breeding pipelines, market segments and breeding schemes, and we present a software tool, Breeding Pipeline Manager, that can be used to formalize and continuously improve breeding schemes. In addition, we detail the use of continuous improvement methods and tools such as genetic simulation through a case study in the International Institute of Tropical Agriculture (IITA) Cassava east-Africa pipeline. We successfully deploy these tools and methods to optimize the program size as well as allocation of resources to the number of parents used, number of crosses made, and number of progeny produced. We propose a structured approach to improve breeding schemes which will help to sustain the rates of response to selection and help to deliver better products to farmers and consumers

Towards understanding the traits contributing to performance of pearl millet open-pollinated varieties in phosphorus-limited environments of West Africa

Aims Pearl millet [Pennisetum glaucum (L.) R. Br.] open-pollinated varieties, which are the predominant cultivars, have never been systematically evaluated for adaptation to low-soil phosphorus (P), a major constraint on pearl millet production in West Africa (WA). Methods We evaluated grain yield (GY), flowering time (FLO), harvest index (HI), and residual grain yields (RGY) of 102 open-pollinated varieties from WA under low-P (−P) and high-P (+P) field conditions in six environments of WA. In addition, PE-related traits of the varieties were evaluated at early growth stage in a pot experiment. Results Significant genetic variation was observed for GY, FLO, HI and PE-related traits. P-efficient varieties had higher yield under −P conditions. Varietal performance under −P varied across environments depending on FLO, relative flowering delay under −P (FD) and RGY measured in the field. Low-P-susceptible varieties had higher FLO, lower HI than low-P-tolerant varieties. Response to direct selection under −P field conditions was 20.1 g m−2, whereas indirect selection response under +P was 16.3 g m−2. Conclusions Selection under −P field conditions while taking into account seasonal variations for FLO, FD and PE is expected to be important for improving GY specifically targeting −P environments in WA

Association analysis of low-phosphorus tolerance in West African pearl millet using DArT markers

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a food security crop in the harshest agricultural regions of the world. While low soil phosphorus (P) availability is a big constraint on its production, especially in West Africa (WA), information on genomic regions responsible for low-P tolerance in pearl millet is generally lacking. We present the first report on genetic polymorphisms underlying several plant P-related parameters, flowering time (FLO) and grain yield (GY) under P-limiting conditions based on 285 diversity array technology markers and 151 West African pearl millet inbred lines phenotyped in six environments in WA under both high-P and low-P conditions. Nine markers were significantly associated with P-related traits, nine markers were associated with FLO, whereas 13 markers were associated with GY each explaining between 5.5 and 15.9 % of the observed variation. Both constitutive and adaptive associations were observed for FLO and GY, with markers PgPb11603 and PgPb12954 being associated with the most stable effects on FLO and GY, respectively, across locations. There were a few shared polymorphisms between traits, especially P-efficiency-related traits and GY, implying possible colocation of genomic regions responsible for these traits. Our findings help bridge the gap between quantitative and molecular methods of studying complex traits like low-P tolerance in WA. However, validation of these markers is necessary to determine their potential applicability in marker-assisted selection programs targeting low-P environments, which are especially important in WA where resource-poor farmers are expected to be the hardest hit by the approaching global P crisis

Archetype for implementing Rapid Cycle Genomic Selection (RCGS) in CGIAR-NARES-SME breeding network pipelines: Examples for pure line crops; RTB crops and hybrid crops

Accelerated Breeding Initiative’s aim is to develop a continuous stream of climate-resilient, preferred, inclusive, high-yielding, and nutritious varieties, against the present-day global challenges such as climate change and environmental degradation. We are committed to increasing genetic gains in farmer’s fields by developing and availing to seed systems new varieties that perform well under farmer conditions and have clear advantages in essential traits that can be recognized by farmers and end-users in order to incentivise the farmers to adopt the new varieties in lieu of their familiar varieties, and to do so at a pace that matches the increasingly erratic growing conditions. The rapid cycle genomic selection (RCGS) archetype seeks to enable selection and recycling of new parents as fast as possible – preferably two-to-three-year cycles, using data that is accurately representing the target population of environments (TPE) in which the future potential varieties will grow. This will ensure that breeding populations are continuously improved to provide high-value alleles and haplotypes for adaptation to biotic and abiotic stresses, and high-value parents from which superior products are identified and released as new varieties. To achieve this we need to: i) Take advantage of the BRS-procured genotyping services with mid-density marker panels that can estimate genomic relationships and marker effects; ii) Deploy new testing strategies that sample the TPE better, using relatively similar resources, e.g. by use of sparse testing where alleles are replicated across locations in the TPE without physical replications or with partial replications, and using the family structure and genomic relationships to provide connectivity, as well as the additional use of managed stress trials to mimic different environments; iii) Build and leverage on efficient CGIAR-NARES-SME breeding networks to scale up testing sites at Early Testing 1 and develop innovative ways for resource reallocation between Early Testing and later stages of testing; iv) Recycle new parents for population improvement faster using the improved accuracy from better testing strategies. In this document we: • Articulate a value proposition for working as a breeding network to CGIAR-NARESSME partners. • Provide clear steps on how to redesign existing pipelines to optimally implement a rapid cycle genomic selection scheme, with example breeding schemes in pure line crops, roots, tubers and bananas (RTB), and hybrid crops. • We identify the support and services needed by the CGIAR-NARES-SME breeding networks to implement this archetype.27 page

Opportunities and challenges to implementing genomic selection in clonally propagated crops.

Clonal propagation of fruits, flowers, and forest trees leads to high levels of heterozygosity, fixes favorable combinations of traits, eliminates undesirable deleterious effects, allows easy identification, propagation of favorable mutations, and is an efficient method for in vitro and ex vitro maintenance and conservation. However, these same characteristics pose challenges to genetic improvement. Many clonal fruits and forest trees have a long juvenile phase, extensive outcrossing, widespread hybridization, limited population structure, multiple origins, and ongoing crop–wild gene flow, and have suffered from domestication bottlenecks, and are polyploid. Breeding clonal crops requires a crossing step involving two heterozygous parents, as a break to create genetic variation that can be exploited during selection in subsequent cycles, before reverting to clonal selection. The presence of several segregating alleles, overdominance and epistatic interactions, at each locus of highly heterozygous clonal crop decreases efficiency of phenotypic selection in breeding programs and genetic studies. Genomic selection (GS) that uses genome-wide genotypic data to predict the phenotypic performance of a genotype by estimating its breeding value has the potential to increase efficiency of clonal crop breeding. In this chapter, potential use and challenges of GS to expedite the breeding process in clonally propagated crops are discussed, with examples. We identify challenges associated with specific features of clonal crops to be addressed in GS models and highlight development of improved marker and bioinformatics platforms to distinguish between paralogous copies and to incorporate partial heterozygosity and allele dosage determination

FieldSimR: an R package for simulating plot data in multi-environment field trials

This paper presents a general framework for simulating plot data in multi-environment field trials with one or more traits. The framework is embedded within the R package FieldSimR, whose core function generates plot errors that capture global field trend, local plot variation, and extraneous variation at a user-defined ratio. FieldSimR's capacity to simulate realistic plot data makes it a flexible and powerful tool for a wide range of improvement processes in plant breeding, such as the optimisation of experimental designs and statistical analyses of multi-environment field trials. FieldSimR provides crucial functionality that is currently missing in other software for simulating plant breeding programmes and is available on CRAN. The paper includes an example simulation of field trials that evaluate 100 maize hybrids for two traits in three environments. To demonstrate FieldSimR's value as an optimisation tool, the simulated data set is then used to compare several popular spatial models for their ability to accurately predict the hybrids' genetic values and reliably estimate the variance parameters of interest. FieldSimR has broader applications to simulating data in other agricultural trials, such as glasshouse experiments

Genome-assisted breeding for drought resistance.

Drought stress caused by unpredictable precipitation poses a major threat to food production worldwide, and its impact is only expected to increase with the further onset of climate change. Understanding the effect of drought stress on crops and plants' response is critical for developing improved varieties with stable high yield to fill a growing food gap from an increasing population depending on decreasing land and water resources. When a plant encounters drought stress, it may use multiple response types, depending on environmental conditions, drought stress intensity and duration, and the physiological stage of the plant. Drought stress responses can be divided into four broad types: drought escape, drought avoidance, drought tolerance, and drought recovery, each characterized by interacting mechanisms, which may together be referred to as drought resistance mechanisms. The complex nature of drought resistance requires a multi-pronged approach to breed new varieties with stable and enhanced yield under drought stress conditions. High throughput genomics and phenomics allow marker-assisted selection (MAS) and genomic selection (GS), which offer rapid and targeted improvement of populations and identification of parents for rapid genetic gains and improved drought-resistant varieties. Using these approaches together with appropriate genetic diversity, databases, analytical tools, and well-characterized drought stress scenarios, weather and soil data, new varieties with improved drought resistance corresponding to grower preferences can be introduced into target regions rapidly

Reciprocal recurrent selection based on genetic complementation: An efficient way to build heterosis in diploids due to directional dominance

Depending on the trait architecture and reproduction system, selection strategies in plant breeding focus on the accumulation of additive, dominance effects, or both. Innovation in the exploitation of dominance-effect-based heterosis has been limited since the proposal of general combining ability (GCA)-based approaches. We propose the use of a new surrogate of genetic complementation between genetic pools to increase accumulation of dominance effects and heterosis. We simulated breeding programs to show how reciprocal recurrent selection (RRS) by genetic complementation would build the dominance-based heterosis cheaper than GCA-based approaches and used real phenotypic data from hybrid maize (Zea mays) to demonstrate the underlying concepts. We found RRS by genetic complementation to be an attractive and viable strategy to exploit dominance, build de novo heterotic pools, and enhance the current GCA-based approaches. If demonstrated in practice, we hypothesized that this approach would lower the cost of hybrid breeding drastically and contribute to food security.2205-221