Molecular Breeding最新文献

Panicle length is a crucial trait tightly associated with spikelets per panicle and grain yield in rice. To dissect the genetic basis of panicle length, a population of 161 recombinant inbred lines (RILs) was developed from the cross between an aus variety Chuan 7 (C7) and a tropical Geng variety Haoboka (HBK). C7 has a panicle length of 30 cm, 7 cm longer than that of HBK, and the panicle length was normally distributed in the RIL population. A total of six quantitative trait loci (QTLs) for panicle length were identified, and single QTLs explained the phenotypic variance from 4.9 to 18.1%. Among them, three QTLs were mapped to the regions harbored sd1, DLT, and Ehd1, respectively. To validate the genetic effect of a minor QTL qPL5, a near-isogenic F₂ (NIF₂) population segregated at qPL5 was developed. Interestingly, panicle length displayed bimodal distribution, and heading date also exhibited significant variation in the NIF₂ population. qPL5 accounted for 66.5% of the panicle length variance. The C7 allele at qPL5 increased panicle length by 2.4 cm and promoted heading date by 5 days. Finally, qPL5 was narrowed down to an 80-kb region flanked by markers M2197 and M2205 using a large NIF₂ population of 7600 plants. LOC_Os05g37540, encoding a phytochrome signal protein whose homolog in Arabidopsis enlarges panicle length, is regarded as the candidate gene because a single-nucleotide mutation (C1099T) caused a premature stop codon in HBK. The characterization of qPL5 with enlarging panicle length but promoting heading date makes its great value in breeding early mature varieties without yield penalty in rice.

With abundant available genomic data, genomic selection has become routine in many plant breeding programs. Multispectral data captured by UAVs showed potential for grain yield (GY) prediction in many plant species using machine learning; however, the possibilities of utilizing this data to augment genomic prediction models still need to be explored. We collected high-throughput phenotyping (HTP) multispectral data in a genotyped multi-environment large-scale field trial using two cost-effective cameras to fill this gap. We tested back to back the prediction ability of GY prediction models, including genomic (G matrix), multispectral-derived (M matrix), and environmental (E matrix) relationships using best linear unbiased predictor (BLUP) methodology in single and multi-environment scenarios. We discovered that M allows for GY prediction comparable to the G matrix and that models using both G and M matrices show superior accuracies and errors compared with G or M alone, both in single and multi-environment scenarios. We showed that the M matrix is not entirely environment-specific, and the genotypic relationships become more robust with more data capture sessions over the season. We discovered that the optimal time for data capture occurs during grain filling and that camera bands with the highest heritability are important for GY prediction using the M matrix. We showcased that GY prediction can be performed using only an RGB camera, and even a single data capture session can yield valuable data for GY prediction. This study contributes to a better understanding of multispectral data and its relationships. It provides a flexible framework for improving GS protocols without significant investments or software customization.

Improving quality is an essential goal of rice breeding and production. However, rice quality is not solely determined by genotype, but is also influenced by the environment. Phenotype plasticity refers to the ability of a given genotype to produce different phenotypes under different environmental conditions, which can be a representation of the stability of traits. Seven quality traits of 141 hybrid combinations, deriving from the test-crossing of 7 thermosensitive genic male sterile (TGMS) and 25 restorer lines, were evaluated at 5 trial sites with intermittent sowing of three to five in Southern China. In the Yangtze River Basin, it was observed that delaying the sowing time of hybrid rice combinations leads to an improvement in their overall quality. Twelve parents were identified to have lower plasticity general combing ability (GCA) values with increased ability to produce hybrids with a more stable quality. The parents with superior quality tend to exhibit lower GCA values for plasticity. The genome-wide association study (GWAS) identified 13 and 15 quantitative trait loci (QTLs) associated with phenotype plasticity and BLUP measurement, respectively. Notably, seven QTLs simultaneously affected both phenotype plasticity and BLUP measurement. Two cloned rice quality genes, ALK and GL7, may be involved in controlling the plasticity of quality traits in hybrid rice. The direction of the genetic effect of the QTL6 (ALK) on alkali spreading value (ASV) plasticity varies in different cropping environments. This study provides novel insights into the dynamic genetic basis of quality traits in response to different cropping regions, cultivation practices, and changing climates. These findings establish a foundation for precise breeding and production of stable and high-quality rice.

Starch is a major component of cereals, comprising over 70% of dry weight. It serves as a primary carbon source for humans and animals. In addition, starch is an indispensable industrial raw material. While maize (Zea mays) is a key crop and the primary source of starch, the genetic basis for starch content in maize kernels remains poorly understood. In this study, using an enlarged panel, we conducted a genome-wide association study (GWAS) based on best linear unbiased prediction (BLUP) value for starch content of 261 inbred lines across three environments. Compared with previous study, we identified 14 additional significant quantitative trait loci (QTL), encompassed a total of 42 genes, and indicated that increased marker density contributes to improved statistical power. By integrating gene expression profiling, Gene Ontology (GO) enrichment and haplotype analysis, several potential target genes that may play a role in regulating starch content in maize kernels have been identified. Notably, we found that ZmAPC4, associated with the significant SNP chr4.S_175584318, which encodes a WD40 repeat-like superfamily protein and is highly expressed in maize endosperm, might be a crucial regulator of maize kernel starch synthesis. Out of the 261 inbred lines analyzed, they were categorized into four haplotypes. Remarkably, it was observed that the inbred lines harboring hap4 demonstrated the highest starch content compared to the other haplotypes. Additionally, as a significant achievement, we have developed molecular markers that effectively differentiate maize inbred lines based on their starch content. Overall, our study provides valuable insights into the genetic basis of starch content and the molecular markers can be useful in breeding programs aimed at developing maize varieties with high starch content, thereby improving breeding efficiency.

We investigated the potential of markers associated with floral traits for parental selection in a cut rose breeding program. We analysed six Kompetitive Allele Specific PCR (KASP) markers for three important floral traits, petal length, petal number and scent, derived from experiments in a garden rose population. The six markers were applied to genotype a collection of 384 parental genotypes used for commercial cut rose breeding. We phenotyped a selection of progeny derived from pairs of parents having either high or low dosages of (contrasting) marker alleles associated with these traits. Significant differences were found between the contrasting progeny groups for each of the traits, although parents with the optimal allele dosage combinations could not always be used for the crosses. This not only supports the robustness of these marker‒trait associations but also demonstrates their potential for commercial rose breeding. It also demonstrates the use of marker information generated in garden rose populations for cut rose breeding.

Rice grain quality is a multifarious attribute mainly governed by multiple nutritional factors. Grain protein is the central component of rice grain nutrition dominantly affecting eating-cooking qualities. Grain protein content is quantitatively influenced by its protein fractions. Genetic quantification of five protein fractions-albumins, globulins, prolamins, glutelin, and grain protein content-were evaluated by exploiting two BC₃F₂ mapping populations, derived from Kongyu131/TKM9 (population-I) and Kongyu131/Bg94-1 (population-II), which were grown in a single environment. Correlation studies among protein fractions and grain protein content were thoroughly investigated. A genetic linkage map was developed by using 146 single sequence repeat (SSR) markers in population-I and 167 markers in population-II. In total, 40 QTLs were delineated for five traits in both populations. Approximately 22 QTLs were dissected in population-I, derived from Kongyu131/TKM9, seven QTLs for albumin content, four QTLs for globulin content, three QTLs for prolamin content, four QTLs for glutelin content, and four QTLs for grain protein content. In total, 18 QTLs were detected in population-II, derived from Kongyu131/Bg94-1, five QTLs for albumin content, three QTLs for globulin content, four QTLs for prolamin content, two QTLs for glutelin content, and four QTLs for grain protein content. Three QTLs, qAlb7.1, Alb7.2, and qGPC7.2, derived from population-II (Kongyu131/Bg94-1) for albumin and grain protein content were successfully validated in the near isogenic line (NIL) populations. The localized chromosomal locus of the validated QTLs could be helpful for fine mapping via map-based cloning to discover underlying candidate genes. The functional insights of the underlying candidate gene would furnish novel perceptivity for the foundation of rice grain protein content and trigger the development of nutritionally important rice cultivars by combining marker-assisted selection (MAS) breeding.

Supplementary information: The online version contains supplementary material available at 10.1007/s11032-023-01436-7.

Certain congenital craniofacial malformations can cause upper airway obstruction. Due to neurological involvement, these craniofacial deformities with upper airway blockage frequently require tracheostomy. Children who need weeks or months of continuous ventilator assistance require tracheostomies, which improve pulmonary toilet and decrease laryngotracheal lesions such subglottic stenosis and tracheomalacia. In this case report we will be discussing about two patients who underwent Pediatric tracheostomy for Pierre Robin sequence and supraglottic stenosis in our institute. This paper emphasizes on some of the rare causes of pediatric upper airway obstruction - Pierre Robin sequence and supraglottic stenosis. Also the importance of tracheostomy procedure, which is the gold standard for management of upper airway obstruction in patients who are not responding to conservative management is emphasized.

Supplementary information: The online version contains supplementary material available at 10.1007/s12070-023-03892-1.