GWAS Mediated Elucidation of Heterosis for Metric Traits in Cotton (Gossypium hirsutum L.) Across Multiple Environments.

For about a century, plant breeding has widely exploited the heterosis phenomenon-often considered as hybrid vigor-to increase agricultural productivity. The ensuing F1 hybrids can substantially outperform their progenitors due to heterozygous combinations that mitigate deleterious mutations occurring in each genome. However, only fragmented knowledge is available concerning the underlying genes and processes that foster heterosis. Although cotton is among the highly valued crops, its improvement programs that involve the exploitation of heterosis are still limited in terms of significant accomplishments to make it broadly applicable in different agro-ecological zones. Here, F1 hybrids were derived from mating a diverse Upland Cotton germplasm with commercially valuable cultivars in the Line × Tester fashion and evaluated across multiple environments for 10 measurable traits. These traits were dissected into five different heterosis types and specific combining ability (SCA). Subsequent genome-wide predictions along-with association analyses uncovered a set of 298 highly significant key single nucleotide polymorphisms (SNPs)/Quantitative Trait Nucleotides (QTNs) and 271 heterotic Quantitative Trait Nucleotides (hQTNs) related to agronomic and fiber quality traits. The integration of a genome wide association study with RNA-sequence analysis yielded 275 candidate genes in the vicinity of key SNPs/QTNs. Fiber micronaire (MIC) and lint percentage (LP) had the maximum number of associated genes, i.e., each with 45 related to QTNs/hQTNs. A total of 54 putative candidate genes were identified in association with HETEROSIS of quoted traits. The novel players in the heterosis mechanism highlighted in this study may prove to be scientifically and biologically important for cotton biologists, and for those breeders engaged in cotton fiber and yield improvement programs.

Comparing the prognostic significance of nutritional screening tools and ESPEN-DCM on 3-month and 12-month outcomes in stroke patients.

BACKGROUND AND AIMS: Malnutrition is prevalent among individuals with acute ischaemic stroke (AIS) and may worsen clinical outcomes. There is no consensus on the best tool for nutritional screening in this population. The present study compared four screening tools and one diagnostic tool in terms of their prognostic significance in predicting short-term and long-term outcomes in AIS patients. METHODS: We included patients admitted to five major hospitals in Wenzhou and diagnosed with a primary diagnosis of AIS from October 1 to December 31, 2018. The Controlling Nutritional Status (CONUT) score, the Geriatric Nutritional Risk Index (GNRI), the Malnutrition Universal Screening Tool (MUST), the Nutritional Risk Screening Tool 2002 (NRS-2002) and the European Society for Clinical Nutrition and Metabolism diagnostic criteria for malnutrition (ESPEN-DCM) were assessed at admission. The clinical outcomes were evaluated by the modified Rankin Scale (mRS) and mortality at 3 months and 12 months after discharge. RESULTS: Five hundred and ninety-three patients were included in our prospective study. The mean age was 67.3 ± 12.0 years. Based on the mRS score, 125 patients exhibited poor functional recovery (an mRS ≥3) at 3 months after discharge. Seventeen patients died during the 3-month follow-up period, and the other 25 did not survive 12 months. Multivariate binary logistic regression revealed that inadequate nutritional status at admission, as determined by the CONUT, GNRI, MUST, NRS-2002 and ESPEN-DCM, were independently associated with poor outcomes in AIS patients 3 months after discharge. Both MUST ≥2 and NRS-2002 ≥ 3 showed significant associations with poor outcomes at 12-month post-discharge. Further analysis with the receiver operator characteristic (ROC) curve showed similar results, where all the tools predicted the poor outcomes at 3 months while only the NRS-2002 and MUST scores were significantly associated with the mRS at 12 months post-discharge. Moreover, the area under the curve (AUC) of MUST and NRS-2002 were significantly larger than those for the other tools. The optimal cut-off values of the MUST and NRS-2002 to predict poor outcomes were scores of ≥2 and ≥ 3 points, respectively. CONCLUSIONS: Our data supported a deleterious effect of inadequate nutrition, as evidenced by the nutrition screening tools or ESPEN-DCM, on clinical outcomes during and beyond the acute phase of AIS. We recommended the use of the MUST and NRS-2002 in guiding nutritional support in AIS patients, as they have higher predictive power and can predict both short-term and long-term outcomes.

Genome-wide dissection of hybridization for fiber quality- and yield-related traits in upland cotton.

An evaluation of combining ability can facilitate the selection of suitable parents and superior F1 hybrids for hybrid cotton breeding, although the molecular genetic basis of combining ability has not been fully characterized. In the present study, 282 female parents were crossed with four male parents in accordance with the North Carolina II mating scheme to generate 1128 hybrids. The parental lines were genotyped based on restriction site-associated DNA sequencing and 306 814 filtered single nucleotide polymorphisms were used for genome-wide association analysis involving the phenotypes, general combining ability (GCA) values, and specific combining ability values of eight fiber quality- and yield-related traits. The main results were: (i) all parents could be clustered into five subgroups based on population structure analyses and the GCA performance of the female parents had significant differences between subgroups; (ii) 20 accessions with a top 5% GCA value for more than one trait were identified as elite parents for hybrid cotton breeding; (iii) 120 significant single nucleotide polymorphisms, clustered into 66 quantitative trait loci, such as the previously reported Gh_A07G1769 and GhHOX3 genes, were found to be significantly associated with GCA; and (iv) identified quantitative trait loci for GCA had a cumulative effect on GCA of the accessions. Overall, our results suggest that pyramiding the favorable loci for GCA may improve the efficiency of hybrid cotton breeding.

Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton.

BACKGROUND: Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. RESULTS: In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. CONCLUSIONS: Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice.

Association mapping analysis of fiber yield and quality traits in Upland cotton (Gossypium hirsutum L.).

Fiber yield and quality are the most important traits for Upland cotton (Gossypium hirsutum L.). Identifying high yield and good fiber quality genes are the prime concern of researchers in cotton breeding. Association mapping offers an alternative and powerful method for detecting those complex agronomic traits. In this study, 198 simple sequence repeats (SSRs) were used to screen markers associated with fiber yield and quality traits with 302 elite Upland cotton accessions that were evaluated in 12 locations representing the Yellow River and Yangtze River cotton growing regions of China. Three subpopulations were found after the estimation of population structure. The pair-wise kinship values varied from 0 to 0.867. Only 1.59% of the total marker locus pairs showed significant linkage disequilibrium (LD, p < 0.001). The genome-wide LD decayed within the genetic distance of ~30 to 32 cM at r 2 = 0.1, and decreased to ~1 to 2 cM at r 2 = 0.2, indicating the potential for association mapping. Analysis based on a mixed linear model detected 57 significant (p < 0.01) marker-trait associations, including seven associations for fiber length, ten for fiber micronaire, nine for fiber strength, eight for fiber elongation, five for fiber uniformity index, five for fiber uniformity ratio, six for boll weight and seven for lint percent, for a total of 35 SSR markers, of which 11 markers were associated with more than one trait. Among marker-trait associations, 24 associations coincided with the previously reported quantitative trait loci (QTLs), the remainder were newly identified QTLs/genes. The QTLs identified in this study will potentially facilitate improvement of fiber yield and quality in the future cotton molecular breeding programs.