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Abstract Sunflower (Helianthus annuus L.) plays an essential role in meeting the demand for edible oil worldwide. The yield of sunflower seeds encompasses several component traits, including the disc diameter. Over three consecutive years, 2019, 2020, and 2022, we assessed phenotypic variation in disc diameter across a diverse set of sunflower accessions (N = 342) in replicated field trials. Upon aggregating the phenotypic data from multiple years, we estimated the broad sense heritability (H2) of the disc diameter trait to be 0.88. A subset of N = 274 accessions was genotyped by using the tunable genotyping‐by‐sequencing (tGBS) method, resulting in 226,779 high‐quality SNPs. Using these SNPs and the disc diameter phenotype, we conducted a genome‐wide association study (GWAS) employing two statistical approaches: the mixed linear model (MLM) and the fixed and random model circulating probability unification (farmCPU). The MLM and farmCPU GWAS approaches identified 106 and 8 significant SNPs located close to 53 and 21 genes, respectively. The MLM analysis identified two significant peaks: a prominent signal on chromosome 10 and a relatively weaker signal on chromosome 16, both of which were also detected by farmCPU. The genetic loci associated with disc diameter, as well as the related candidate genes, present promising avenues for further functional validation and serve as a basis for sunflower oil yield improvement.

Abstract Background Transcription bridges genetic information and phenotypes. Here, we evaluated how changes in transcriptional regulation enable maize (Zea mays), a crop originally domesticated in the tropics, to adapt to temperate environments. Result We generated 572 unique RNA-seq datasets from the roots of 340 maize genotypes. Genes involved in core processes such as cell division, chromosome organization and cytoskeleton organization showed lower heritability of gene expression, while genes involved in anti-oxidation activity exhibited higher expression heritability. An expression genome-wide association study (eGWAS) identified 19,602 expression quantitative trait loci (eQTLs) associated with the expression of 11,444 genes. A GWAS for alternative splicing identified 49,897 splicing QTLs (sQTLs) for 7614 genes. Genes harboring both cis-eQTLs and cis-sQTLs in linkage disequilibrium were disproportionately likely to encode transcription factors or were annotated as responding to one or more stresses. Independent component analysis of gene expression data identified loci regulating co-expression modules involved in oxidation reduction, response to water deprivation, plastid biogenesis, protein biogenesis, and plant-pathogen interaction. Several genes involved in cell proliferation, flower development, DNA replication, and gene silencing showed lower gene expression variation explained by genetic factors between temperate and tropical maize lines. A GWAS of 27 previously published phenotypes identified several candidate genes overlapping with genomic intervals showing signatures of selection during adaptation to temperate environments. Conclusion Our results illustrate how maize transcriptional regulatory networks enable changes in transcriptional regulation to adapt to temperate regions.

Abstract Domesticated ~10,000 years ago in northern China, Proso millet (Panicum miliaceum L.) is a climate‐resilient and human health‐promoting cereal crop. The genome size of this self‐pollinated allotetraploid is 923 Mb. Proso millet seeds are an important part of the human diet in many countries. In the USA, its use is restricted to the birdseed and pet food market. Proso millet is witnessing gradual demand in the global human health and wellness food market owing to its health‐promoting properties such as low glycemic index and gluten‐free. The breeding efforts for developing improved proso millet cultivars are hindered by the dearth of genomic resources available to researchers. The publication of the reference genome and availability of cost‐effective NGS methodologies could lead to the identification of high‐quality genetic variants, which can be incorporated into breeding pipelines. Here, we report the identification of single‐nucleotide polymorphisms (SNPs) by low‐pass (1×) genome sequencing of 85 diverse proso millet accessions from 23 different countries. The 2 × 150 bp Illumina paired‐end reads generated after sequencing were aligned to the proso millet reference genome. The resulting sequence alignment information was used to call SNPs. We obtained 972,863 bi‐allelic SNPs after quality filtering of the raw SNPs. These SNPs were used to assess the population structure and phylogenetic relationships among the accessions. Most of the accessions were found to be highly inbred with heterozygosity ranging between .05 and .20. Principal component analysis (PCA) showed that PC1 (principal component) and PC2 explained 19% of the variability in the population. PCA also clustered all the genotypes into three groups. A neighbor‐joining tree clustered the genotypes into four distinct groups exhibiting diverse representation within the population. The SNPs identified in our study could be used for molecular breeding and genetics research (e.g., genetic and association mapping, and population genetics) in proso millet after proper validation.

A study was undertaken to estimate combining ability effects in maize for different characters in a line × tester programme comprising 70 hybrids produced by crossing 14 lines and 5 testers. The interaction of line × tester was highly significant for twelve traits studied except for protein content. Significant general and specific combining ability variance were observed for all characters except protein content. The variance due to SCA was higher than GCA indicating the predominance of non-additive type of gene action. The ratio of GCA:SCA variance was lower than unity for all characters indicating predominance of non -additive gene action over additive gene action. Among the lines, genotype QPM 3 was found to be the best general combiner with better mean performance for most yield contributing traits followed by QPM 1 and QPM 187. Among the testers, T 323-8 was found to be the best general combiner with better mean performance for most of the yield contributing traits followed by T 209 and T 295 genotypes. Among the crosses, QPM 35 × T 295 was superior with positive significant SCA effects and better mean performance for grain yield and plant height. Similar superior positive significant SCA effects with better mean performance were also observed in QPM 6 × T 295 (ear length, test weight and grain yield per plant) and QPM 43 × T 193-2 (ear length and grain yield per plant).

Seventy Quality Protein Maize (QPM) (Zea mays L.) hybrids were grown in duplicate randomized complete block design forcharacter association study to assess the relationship among total grain protein content, grain yield and its components. Totalgrain protein showed significant correlation with plant height and ear height. Character association analysis revealed strongpositive association of Grain yield per plant with plant height, ear height, ear length, ear diameter, kernel rows per cob, kernelsper row, test weight and shelling per cent. Total grain protein showed strong negative association with days to 50 % flowering,days to anthesis and days to 50% silking. Hence, simultaneous selection of plant height and ear height would contribute for theimprovement of the grain yield per plant and total protein content in the grains at the same time.