Pearl millet [Cenchrus americanus (L.) Morrone] is a staple food for more than 90 million farmers in arid and semi-arid regions of sub-Saharan Africa, India and South Asia. We report the ∼1.79 Gb draft whole genome sequence of reference genotype Tift 23D₂B₁-P1-P5, which contains an estimated 38,579 genes. We highlight the substantial enrichment for wax biosynthesis genes, which may contribute to heat and drought tolerance in this crop. We resequenced and analyzed 994 pearl millet lines, enabling insights into population structure, genetic diversity and domestication. We use these resequencing data to establish marker trait associations for genomic selection, to define heterotic pools, and to predict hybrid performance. We believe that these resources should empower researchers and breeders to improve this important staple crop.

Zero hunger and good health could be realized by 2030 through effective conservation, characterization and utilization of germplasm resources¹. So far, few chickpea (Cicerarietinum) germplasm accessions have been characterized at the genome sequence level². Here we present a detailed map of variation in 3,171 cultivated and 195 wild accessions to provide publicly available resources for chickpea genomics research and breeding. We constructed a chickpea pan-genome to describe genomic diversity across cultivated chickpea and its wild progenitor accessions. A divergence tree using genes present in around 80% of individuals in one species allowed us to estimate the divergence of Cicer over the last 21 million years. Our analysis found chromosomal segments and genes that show signatures of selection during domestication, migration and improvement. The chromosomal locations of deleterious mutations responsible for limited genetic diversity and decreased fitness were identified in elite germplasm. We identified superior haplotypes for improvement-related traits in landraces that can be introgressed into elite breeding lines through haplotype-based breeding, and found targets for purging deleterious alleles through genomics-assisted breeding and/or gene editing. Finally, we propose three crop breeding strategies based on genomic prediction to enhance crop productivity for 16 traits while avoiding the erosion of genetic diversity through optimal contribution selection (OCS)-based pre-breeding. The predicted performance for 100-seed weight, an important yield-related trait, increased by up to 23% and 12% with OCS- and haplotype-based genomic approaches, respectively.

Large ex situ germplasm collections generally harbor a wide range of crop diversity. AVRDC – The World Vegetable Center is holding in trust the world’s second largest mungbean (Vigna radiata) germplasm collection with more than 6,700 accessions. Screening large collections for traits of interest is laborious and expensive. To enhance the access of breeders to the diversity of the crop, mungbean core and mini core collections have been established. The core collection of 1,481 entries has been built by random selection of 20% of the accessions after geographical stratification and subsequent cluster analysis of eight phenotypic descriptors in the whole collection. Summary statistics, especially the low differences of means, equal variance of the traits in both the whole and core collection and the visual inspection of quantile-quantile plots comparing the variation of phenotypic traits present in both collections indicated that the core collection well represented the pattern of diversity of the whole collection. The core collection was genotyped with 20 simple sequence repeat markers and a mini core set of 289 accessions was selected, which depicted the allele and genotype diversity of the core collection. The mungbean core and mini core collections plus their phenotypic and genotypic data are available for distribution to breeders. It is expected that these collections will enhance the access to biodiverse mungbean germplasm for breeding.

Motivation: Modern genomic breeding methods rely heavily on very large amounts of phenotyping and genotyping data, presenting new challenges in effective data management and integration. Recently, the size and complexity of datasets have increased significantly, with the result that data are often stored on multiple systems. As analyses of interest increasingly require aggregation of datasets from diverse sources, data exchange between disparate systems becomes a challenge. Results: To facilitate interoperability among breeding applications, we present the public plant Breeding Application Programming Interface (BrAPI). BrAPI is a standardized web service API specification. The development of BrAPI is a collaborative, community-based initiative involving a growing global community of over a hundred participants representing several dozen institutions and companies. Development of such a standard is recognized as critical to a number of important large breeding system initiatives as a foundational technology. The focus of the first version of the API is on providing services for connecting systems and retrieving basic breeding data including germplasm, study, observation, and marker data. A number of BrAPI-enabled applications, termed BrAPPs, have been written, that take advantage of the emerging support of BrAPI by many databases. Availability and implementation: More information on BrAPI, including links to the specification, test suites, BrAPPs, and sample implementations is available at https://brapi.org/. The BrAPI specification and the developer tools are provided as free and open source.

With an aim of enhancing drought tolerance using a marker‐assisted backcrossing (MABC) approach, we introgressed the “ QTL‐hotspot ” region from ICC 4958 accession that harbors quantitative trait loci (QTLs) for several drought‐tolerance related traits into three elite Indian chickpea ( Cicer arietinum L.) cultivars: Pusa 372, Pusa 362, and DCP 92‐3. Of eight simple sequence repeat (SSR) markers in the QTL‐hotspot region, two to three polymorphic markers were used for foreground selection with respective cross‐combinations. A total of 47, 53, and 46 SSRs were used for background selection in case of introgression lines (ILs) developed in genetic backgrounds of Pusa 372, Pusa 362, and DCP 92‐3, respectively. In total, 61 ILs (20 BC ₃ F ₃ in Pusa 372; 20 BC ₂ F ₃ in Pusa 362, and 21 BC ₃ F ₃ in DCP 92‐3), with >90% recurrent parent genome recovery were developed. Six improved lines in different genetic backgrounds (e.g. BGM 10216 in Pusa 372; BG 3097 and BG 4005 in Pusa 362; IPC(L4‐14), IPC(L4‐16), and IPC(L19‐1) in DCP 92‐3) showed better performance than their respective recurrent parents. BGM 10216, with 16% yield gain over Pusa 372, has been released as Pusa Chickpea 10216 by the Central Sub‐Committees on Crop Standards, Notification and Release of Varieties of Agricultural Crops, Ministry of Agriculture and Farmers Welfare, Government of India, for commercial cultivation in India. In summary, this study reports introgression of the QTL‐hotspot for enhancing yield under rainfed conditions, development of several introgression lines, and release of Pusa Chickpea 10216 developed through molecular breeding in India.