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1.
BMC Genomics ; 21(1): 777, 2020 Nov 10.
Artículo en Inglés | MEDLINE | ID: mdl-33167854

RESUMEN

BACKGROUND: Pearl millet, a nutritious food for around 100 million people in Africa and India, displays extensive genetic diversity and a high degree of admixture with wild relatives. Two major morphotypes can be distinguished in Senegal: early-flowering Souna and late-flowering Sanio. Phenotypic variabilities related to flowering time play an important role in the adaptation of pearl millet to climate variability. A better understanding of the genetic makeup of these variabilities would make it possible to breed pearl millet to suit regions with different climates. The aim of this study was to characterize the genetic basis of these phenotypic differences. RESULTS: We defined a core collection that captures most of the diversity of cultivated pearl millets in Senegal and includes 60 early-flowering Souna and 31 late-flowering Sanio morphotypes. Sixteen agro-morphological traits were evaluated in the panel in the 2016 and 2017 rainy seasons. Phenological and phenotypic traits related with yield, flowering time, and biomass helped differentiate early- and late-flowering morphotypes. Further, using genotyping-by-sequencing (GBS), 21,663 single nucleotide polymorphisms (SNPs) markers with more than 5% of minor allele frequencies were discovered. Sparse non-negative matrix factorization (sNMF) analysis confirmed the genetic structure in two gene pools associated with differences in flowering time. Two chromosomal regions on linkage groups (LG 3) (~ 89.7 Mb) and (LG 6) (~ 68.1 Mb) differentiated two clusters among the early-flowering Souna. A genome-wide association study (GWAS) was used to link phenotypic variation to the SNPs, and 18 genes were linked to flowering time, plant height, tillering, and biomass (P-value < 2.3E-06). CONCLUSIONS: The diversity of early- and late-flowering pearl millet morphotypes in Senegal was captured using a heuristic approach. Key phenological and phenotypic traits, SNPs, and candidate genes underlying flowering time, tillering, biomass yield and plant height of pearl millet were identified. Chromosome rearrangements in LG3 and LG6 were inferred as a source of variation in early-flowering morphotypes. Using candidate genes underlying these features between pearl millet morphotypes will be of paramount importance in breeding for resilience to climatic variability.


Asunto(s)
Flores/fisiología , Pennisetum , Clima , Estudios de Asociación Genética , India , Pennisetum/genética , Pennisetum/fisiología , Fitomejoramiento , Senegal
2.
Front Plant Sci ; 8: 818, 2017.
Artículo en Inglés | MEDLINE | ID: mdl-28567050

RESUMEN

Pearl millet (Pennisetum glaucum (L.) R. Br.) is a staple food and a drought-tolerant cereal well adapted to Sub-Saharan Africa agro-ecosystems. An important diversity of pearl millet landraces has been widely conserved by farmers and therefore could help copping with climate changes and contribute to future food security. Hence, characterizing its genetic diversity and population structure can contribute to better assist breeding programs for a sustainable agricultural productivity enhancement. Toward this goal, a comprehensive panel of 404 accessions were used that correspond to 12 improved varieties, 306 early flowering and 86 late-flowering cultivated landraces from Senegal. Twelve highly polymorphic SSR markers were used to study diversity and population structure. Two genes, PgMADS11 and PgPHYC, were genotyped to assess their association to flowering phenotypic difference in landraces. Results indicate a large diversity and untapped potential of Senegalese pearl millet germplasm as well as a genetic differentiation between early- and late-flowering landraces. Further, a fine-scale genetic difference of PgPHYC and PgMADS11 (SNP and indel, respectively) and co-variation of their alleles with flowering time were found among landraces. These findings highlight new genetic insights of pearl millet useful to define heterotic populations for breeding, genomic association panel, or crosses for trait-specific mapping.

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