Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.

Background: Hyperimmune anti-COVID-19 Intravenous Immunoglobulin (C-IVIG) is an unexplored therapy amidst the rapidly evolving spectrum of medical therapies for COVID-19 and is expected to counter the three most lifethreatening consequences of COVID-19 including lung injury by the virus, cytokine storm and sepsis. Methods: A single center, phase I/II, randomized controlled, single-blinded trial was conducted at Dow University of Health Sciences, Karachi, Pakistan. Participants were COVID-19 infected individuals, classified as either severely or critically ill with Acute Respiratory Distress Syndrome (ARDS). Participants were randomized through parallel-group design with sequential assignment in a 4:1 allocation to either intervention group with four C-IVIG dosage arms (0.15, 0.20, 0.25, 0.30 g/kg), or control group receiving standard of care only (n = 10). Primary outcomes were 28-day mortality, patient's clinical status on ordinal scale and Horowitz index (HI), and were analysed in all randomized participants that completed the follow-up period (intentionto-treat population). The trial was registered at clinicaltrials.gov (NCT04521309). Findings: Fifty participants were enrolled in the study from June 19, 2020 to February 3, 2021 with a mean age of 56.54 §13.2 years of which 22 patients (44%) had severe and 28 patients (56%) had critical COVID-19. Mortality occurred in ten of 40 participants (25%) in intervention group compared to six of ten (60%) in control group, with relative risk reduction in intervention arm I (RR, 0.333; 95% CI, 0.087À1.272), arm II (RR, 0.5; 95% CI, 0.171À1.463), arm III (RR, 0.167; 95% CI, 0.024À1.145), and arm IV (RR, 0.667; 95% CI, 0.268À1.660). In intervention group, median HI significantly improved to 359 mmHg [interquartile range (IQR) 127À400, P = 0.009)] by outcome day, while the clinical status of intervention group also improved as compared to control group, with around 15 patients (37.5%) being discharged by 7th day with complete recovery. Additionally, resolution of chest X-rays and restoration of biomarkers to normal levels were also seen in intervention groups. No drug-related adverse events were reported during the study. Interpretation: Administration of C-IVIG in severe and critical COVID-19 patients was safe, increased the chance of survival and reduced the risk of disease progression. Funding: Higher Education Commission (HEC), Pakistan (Ref no. 20-RRG-134/RGM/R&D/HEC/2020).

The North-Eastern region (NER) of India, comprising of Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland and Tripura, is a hot spot for genetic diversity and the most probable origin of rice. North-east rice collections are known to possess various agronomically important traits like biotic and abiotic stress tolerance, unique grain and cooking quality. The genetic diversity and associated population structure of 6,984 rice accessions, originating from NER, were assessed using 36 genome wide unlinked single nucleotide polymorphism (SNP) markers distributed across the 12 rice chromosomes. All of the 36 SNP loci were polymorphic and bi-allelic, contained five types of base substitutions and together produced nine types of alleles. The polymorphic information content (PIC) ranged from 0.004 for Tripura to 0.375 for Manipur and major allele frequency ranged from 0.50 for Assam to 0.99 for Tripura. Heterozygosity ranged from 0.002 in Nagaland to 0.42 in Mizoram and gene diversity ranged from 0.006 in Arunachal Pradesh to 0.50 in Manipur. The genetic relatedness among the rice accessions was evaluated using an unrooted phylogenetic tree analysis, which grouped all accessions into three major clusters. For determining population structure, populations K = 1 to K = 20 were tested and population K = 3 was present in all the states, with the exception of Meghalaya and Manipur where, K = 5 and K = 4 populations were present, respectively. Principal Coordinate Analysis (PCoA) showed that accessions were distributed according to their population structure. AMOVA analysis showed that, maximum diversity was partitioned at the individual accession level (73% for Nagaland, 58% for Arunachal Pradesh and 57% for Tripura). Using POWERCORE software, a core set of 701 accessions was obtained, which accounted for approximately 10% of the total NE India collections, representing 99.9% of the allelic diversity. The rice core set developed will be a valuable resource for future genomic studies and crop improvement strategies.

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Spot blotch disease caused by Bipolaris sorokiniana is a major constraint for wheat production in tropics and subtropics. The introgression of spot blotch resistance alleles to the disease susceptible lines is critical to securing the wheat production in these regions. Although genome-wide association studies (GWASs) for spot blotch were attempted earlier, the present study focused on identifying new quantitative trait loci (QTLs) for spot blotch under natural disease pressure in diverse field conditions. A total of 139 advanced spring wheat lines were evaluated in three environments (three years and two locations) in India and Bangladesh. The GWAS using 14,063 polymorphic genotyping-by-sequencing (GBS) markers identified eight QTLs associated with spot blotch disease resistance belonging to eight chromosomes across the wheat genome. Here, we report the identified marker–trait associations (MTAs), along with the allele effects associated with the disease. The functional annotation of the significant markers identified NBS-LRR, MADS-box transcription factor, and 34 other plant-related protein families across multiple chromosomal regions. The results indicate four promising new QTLs on chromosomes 1A (497.2 Mb), 1D (89.84 Mb), 2B (421.92 Mb), and 6D (6.84 Mb) associated with several disease resistance protein families. These results provide insights into new genomic regions associated with spot blotch disease, and with additional validation, could be utilized in disease resistance breeding efforts in wheat development.