Cotton pedigree genome reveals restriction of cultivar-driven strategy in cotton breeding.

BACKGROUND: Many elite genes have been identified from the available cotton genomic data, providing various genetic resources for gene-driven breeding. However, backbone cultivar-driven breeding is the most widely applied strategy. Revealing the genetic basis of cultivar-driven strategy's restriction is crucial for transition of cotton breeding strategy. RESULT: CRI12 is a backbone cultivar in cultivar-driven breeding. Here we sequence the pedigree of CRI12 using Nanopore long-read sequencing. We construct a graphical pedigree genome using the high-quality CRI12 genome and 13,138 structural variations within 20 different pedigree members. We find that low hereditary stability of elite segments in backbone cultivars is a drawback of cultivar-driven strategy. We also identify 623 functional segments in CRI12 for multiple agronomic traits in presence and absence variation-based genome-wide association study on three cohorts. We demonstrate that 25 deleterious segments are responsible for the geographical divergence of cotton in pathogen resistance. We also characterize an elite pathogen-resistant gene (GhKHCP) utilized in modern cotton breeding. In addition, we identify 386 pedigree fingerprint segments by comparing the segments of the CRI12 pedigree with those of a large cotton population. CONCLUSION: We characterize the genetic patterns of functional segments in the pedigree of CRI12 using graphical genome method, revealing restrictions of cultivar-driven strategies in cotton breeding. These findings provide theoretical support for transitioning from cultivar-driven to gene-driven strategy in cotton breeding.

Substitution spectra of SARS-CoV-2 genome from Pakistan reveals insights into the evolution of variants across the pandemic.

Changing morbidity and mortality due to COVID-19 across the pandemic has been linked with factors such as the emergence of SARS-CoV-2 variants and vaccination. Mutations in the Spike glycoprotein enhanced viral transmission and virulence. We investigated whether SARS-CoV-2 mutation rates and entropy were associated COVID-19 in Pakistan, before and after the introduction of vaccinations. We analyzed 1,705 SARS-CoV-2 genomes using the Augur phylogenetic pipeline. Substitution rates and entropy across the genome, and in the Spike glycoprotein were compared between 2020, 2021 and 2022 (as periods A, B and C). Mortality was greatest in B whilst cases were highest during C. In period A, G clades were predominant, and substitution rate was 5.25 × 10-4 per site per year. In B, Delta variants dominated, and substitution rates increased to 9.74 × 10-4. In C, Omicron variants led to substitution rates of 5.02 × 10-4. Genome-wide entropy was the highest during B particularly, at Spike E484K and K417N. During C, genome-wide mutations increased whilst entropy was reduced. Enhanced SARS-CoV-2 genome substitution rates were associated with a period when more virulent SARS-CoV-2 variants were prevalent. Reduced substitution rates and stabilization of genome entropy was subsequently evident when vaccinations were introduced. Whole genome entropy analysis can help predict virus evolution to guide public health interventions.

Sequential viral introductions and spread of BA.1 across Pakistan provinces during the Omicron wave.

BACKGROUND: COVID-19 waves caused by specific SARS-CoV-2 variants have occurred globally at different times. We focused on Omicron variants to understand the genomic diversity and phylogenetic relatedness of SARS-CoV-2 strains in various regions of Pakistan. METHODS: We studied 276,525 COVID-19 cases and 1,031 genomes sequenced from December 2021 to August 2022. Sequences were analyzed and visualized using phylogenetic trees. RESULTS: The highest case numbers and deaths were recorded in Sindh and Punjab, the most populous provinces in Pakistan. Omicron variants comprised 93% of all genomes, with BA.2 (32.6%) and BA.5 (38.4%) predominating. The first Omicron wave was associated with the sequential identification of BA.1 in Sindh, then Islamabad Capital Territory, Punjab, Khyber Pakhtunkhwa (KP), Azad Jammu Kashmir (AJK), Gilgit-Baltistan (GB) and Balochistan. Phylogenetic analysis revealed Sindh to be the source of BA.1 and BA.2 introductions into Punjab and Balochistan during early 2022. BA.4 was first introduced in AJK and BA.5 in Punjab. Most recent common ancestor (MRCA) analysis revealed relatedness between the earliest BA.1 genome from Sindh with Balochistan, AJK, Punjab and ICT, and that of first BA.1 from Punjab with strains from KPK and GB. CONCLUSIONS: Phylogenetic analysis provides insights into the introduction and transmission dynamics of the Omicron variant in Pakistan, identifying Sindh as a hotspot for viral dissemination. Such data linked with public health efforts can help limit surges of new infections.

Functional characterization of the GhNRT2.1e gene reveals its significant role in improving nitrogen use efficiency in Gossypium hirsutum.

Background: Nitrate is the primary type of nitrogen available to plants, which is absorbed and transported by nitrate transporter 2 (NRT2) at low nitrate conditions. Methods: Genome-wide identification of NRT2 genes in G. hirsutum was performed. Gene expression patterns were revealed using RNA-seq and qRT-PCR. Gene functions were characterized using overexpression in A. thaliana and silencing in G. hirsutum. Protein interactions were verified by yeast two-hybrid and luciferase complementation imaging (LCI) assays. Results: We identified 14, 14, seven, and seven NRT2 proteins in G. hirsutum, G. barbadense, G. raimondii, and G. arboreum. Most NRT2 proteins were predicted in the plasma membrane. The NRT2 genes were classified into four distinct groups through evolutionary relationships, with members of the same group similar in conserved motifs and gene structure. The promoter regions of NRT2 genes included many elements related to growth regulation, phytohormones, and abiotic stresses. Tissue expression pattern results revealed that most GhNRT2 genes were specifically expressed in roots. Under low nitrate conditions, GhNRT2 genes exhibited different expression levels, with GhNRT2.1e being the most up-regulated. Arabidopsis plants overexpressing GhNRT2.1e exhibited increased biomass, nitrogen and nitrate accumulation, nitrogen uptake and utilization efficiency, nitrogen-metabolizing enzyme activity, and amino acid content under low nitrate conditions. In addition, GhNRT2.1e-silenced plants exhibited suppressed nitrate uptake and accumulation, hampered plant growth, affected nitrogen metabolism processes, and reduced tolerance to low nitrate. The results showed that GhNRT2.1e could promote nitrate uptake and transport under low nitrate conditions, thus effectively increasing nitrogen use efficiency (NUE). We found that GhNRT2.1e interacts with GhNAR2.1 by yeast two-hybrid and LCI assays. Discussion: Our research lays the foundation to increase NUE and cultivate new cotton varieties with efficient nitrogen use.

Ceftriaxone resistant Salmonella enterica serovar Paratyphi A identified in a case of enteric fever: first case report from Pakistan.

BACKGROUND: Enteric fever is an acute systemic infectious disease associated with substantial morbidity and mortality in low- and middle-income countries (LMIC), with a global burden of 14.3 million cases. Cases of enteric fever or paratyphoid fever, caused by Salmonella enterica serovar Paratyphi A (S. Para A) have been found to rise in many endemic and non-endemic countries. Drug resistance is relatively uncommon in S. Para A. Here we report a case of paratyphoid fever caused by ceftriaxone resistant S. Para A from Pakistan. CASE PRESENTATION: A 29-year-old female presented with a history of fever, headache, and shivering. Her blood culture revealed a S. Para A isolate (S7), which was resistant to ceftriaxone, cefixime, ampicillin and ciprofloxacin. She was prescribed oral Azithromycin for 10 days, which resulted in resolution of her symptoms. Two other isolates of S. Para A (S1 and S4), resistant to fluoroquinolone were also selected for comparison. DST and whole genome sequencing was performed for all three isolates. Sequence analysis was performed for identification of drug resistance and phylogeny. Whole Genome Sequencing (WGS) of S7 revealed the presence of plasmids, IncX4 and IncFIB(K). blaCTX-M-15 and qnrS1 genes were found on IncFIB(K). The gyrA S83F mutation conferring fluoroquinolone resistance was also found present. Multi-locus sequence typing (MLST) showed the S7 isolate to belong to ST129. S1 and S4 had the gyrA S83Y and S83F mutations respectively. CONCLUSIONS: We highlight the occurrence of plasmid-mediated ceftriaxone resistant strain of S. Para A. This is of significance as ceftriaxone is commonly used to treat paratyphoid fever and resistance in S. Para A is not known. Continuous epidemiological surveillance is required to monitor the transmission and spread of antimicrobial resistance (AMR) among Typhoidal Salmonellae. This will guide treatment options and preventive measures including the need for vaccination against S. Para A in the region.

Bedaquiline resistant Mycobacterium tuberculosis clinical isolates with and without rv0678 mutations have similar growth patterns under varying BDQ drug pressure.

Resistance associated mutations have been reported to alter the growth of Mycobacterium tuberculosis (MTB) isolates under drug pressure. However, there is little information on the growth characteristics of bedaquiline (BDQ) resistant isolates in the presence of BDQ. To further understand the role of rv0678, we aimed to study whether the presence of rv0678 variants in BDQ resistant isolates alters the killing effect of BDQ. We, therefore, selected BDQ resistant clinical MTB isolates with (n = 6) and without (n = 3) variants in rv0678 gene. Using time kill assays, growth inhibition; taken as the relative change in log average colony forming unit (CFU)/ml at selected time points (24-96 h), was studied at Minimum Inhibitory Concentrations (MICs): 0x, 1x, 2.5x, 5x, 7.5x, 10x for these isolates. Growth inhibition was then analyzed using Kruskal Wallis and Kolmogorov Smirnov tests in PRISM vr.9. During the 24-96 h lag phase isolates with and without variants in rv0678 showed a similar growth inhibition pattern. No difference was noted in growth inhibition between BDQ resistant isolates and H37Rv. These findings suggest that role of alternate mechanisms in contributing to BDQ tolerance needs to be explored.

Interpretation of convolutional neural networks reveals crucial sequence features involving in transcription during fiber development.

BACKGROUND: Upland cotton provides the most natural fiber in the world. During fiber development, the quality and yield of fiber were influenced by gene transcription. Revealing sequence features related to transcription has a profound impact on cotton molecular breeding. We applied convolutional neural networks to predict gene expression status based on the sequences of gene transcription start regions. After that, a gradient-based interpretation and an N-adjusted kernel transformation were implemented to extract sequence features contributing to transcription. RESULTS: Our models had approximate 80% accuracies, and the area under the receiver operating characteristic curve reached over 0.85. Gradient-based interpretation revealed 5' untranslated region contributed to gene transcription. Furthermore, 6 DOF binding motifs and 4 transcription activator binding motifs were obtained by N-adjusted kernel-motif transformation from models in three developmental stages. Apart from 10 general motifs, 3 DOF5.1 genes were also detected. In silico analysis about these motifs' binding proteins implied their potential functions in fiber formation. Besides, we also found some novel motifs in plants as important sequence features for transcription. CONCLUSIONS: In conclusion, the N-adjusted kernel transformation method could interpret convolutional neural networks and reveal important sequence features related to transcription during fiber development. Potential functions of motifs interpreted from convolutional neural networks could be validated by further wet-lab experiments and applied in cotton molecular breeding.

Higher entropy observed in SARS-CoV-2 genomes from the first COVID-19 wave in Pakistan.

BACKGROUND: We investigated the genome diversity of SARS-CoV-2 associated with the early COVID-19 period to investigate evolution of the virus in Pakistan. MATERIALS AND METHODS: We studied ninety SARS-CoV-2 strains isolated between March and October 2020. Whole genome sequences from our laboratory and available genomes were used to investigate phylogeny, genetic variantion and mutation rates of SARS-CoV-2 strains in Pakistan. Site specific entropy analysis compared mutation rates between strains isolated before and after June 2020. RESULTS: In March, strains belonging to L, S, V and GH clades were observed but by October, only L and GH strains were present. The highest diversity of clades was present in Sindh and Islamabad Capital Territory and the least in Punjab province. Initial introductions of SARS-CoV-2 GH (B.1.255, B.1) and S (A) clades were associated with overseas travelers. Additionally, GH (B.1.255, B.1, B.1.160, B.1.36), L (B, B.6, B.4), V (B.4) and S (A) clades were transmitted locally. SARS-CoV-2 genomes clustered with global strains except for ten which matched Pakistani isolates. RNA substitution rates were estimated at 5.86 x10-4. The most frequent mutations were 5' UTR 241C > T, Spike glycoprotein D614G, RNA dependent RNA polymerase (RdRp) P4715L and Orf3a Q57H. Strains up until June 2020 exhibited an overall higher mean and site-specific entropy as compared with sequences after June. Relative entropy was higher across GH as compared with GR and L clades. More sites were under selection pressure in GH strains but this was not significant for any particular site. CONCLUSIONS: The higher entropy and diversity observed in early pandemic as compared with later strains suggests increasing stability of the genomes in subsequent COVID-19 waves. This would likely lead to the selection of site-specific changes that are advantageous to the virus, as has been currently observed through the pandemic.

Improved reconstruction and comparative analysis of chromosome 12 to rectify Mis-assemblies in Gossypium arboreum.

BACKGROUND: Genome sequencing technologies have been improved at an exponential pace but precise chromosome-scale genome assembly still remains a great challenge. The draft genome of cultivated G. arboreum was sequenced and assembled with shotgun sequencing approach, however, it contains several misassemblies. To address this issue, we generated an improved reassembly of G. arboreum chromosome 12 using genetic mapping and reference-assisted approaches and evaluated this reconstruction by comparing with homologous chromosomes of G. raimondii and G. hirsutum. RESULTS: In this study, we generated a high quality assembly of the 94.64 Mb length of G. arboreum chromosome 12 (A_A12) which comprised of 144 scaffolds and contained 3361 protein coding genes. Evaluation of results using syntenic and collinear analysis of reconstructed G. arboreum chromosome A_A12 with its homologous chromosomes of G. raimondii (D_D08) and G. hirsutum (AD_A12 and AD_D12) confirmed the significant improved quality of current reassembly as compared to previous one. We found major misassemblies in previously assembled chromosome 12 (A_Ca9) of G. arboreum particularly in anchoring and orienting of scaffolds into a pseudo-chromosome. Further, homologous chromosomes 12 of G. raimondii (D_D08) and G. arboreum (A_A12) contained almost equal number of transcription factor (TF) related genes, and showed good collinear relationship with each other. As well, a higher rate of gene loss was found in corresponding homologous chromosomes of tetraploid (AD_A12 and AD_D12) than diploid (A_A12 and D_D08) cotton, signifying that gene loss is likely a continuing process in chromosomal evolution of tetraploid cotton. CONCLUSION: This study offers a more accurate strategy to correct misassemblies in sequenced draft genomes of cotton which will provide further insights towards its genome organization.

Glutathione S-transferases GhGSTF1 and GhGSTF2 involved in the anthocyanin accumulation in Gossypium hirsutum L.

The glutathione S-transferases (GSTs) are important enzymes of secondary metabolism in plants. In this study, two putative GSTs, GhGSTF1 and GhGSTF2, were identified as anthocyanin-related GSTs by the transcriptome data of the leaves of Gossypium hirsutum L. TM-1 and T586. The quantitative real-time PCR showed that GhGSTF1 and GhGSTF2 were highly expressed in red leaves and stems of Gossypium hirsutum L. T586. Orthologous genes of GhGSTF2 in two Gossypium barbadense L. 3-79 and Xinhai21 contain bases deletion in N-terminal (GbGSTF2a) and C-terminal (GbGSTF2b) respectively. Among which, GhGSTF1 and GhGSTF2 can restore pigmentation in hypocotyls of Arabidopsis thaliana mutant tt19-7 while GbGSTF2a and GbGSTF2b cannot. Furthermore, in vitro assays showed the recombinant GhGSTF1 and GhGSTF2 had Glutathione S-transferase activities. Fluorescence quenching assays showed that Cya could obviously quench the fluorescence of GhGSTF1, GhGSTF2, GbGSTF2a and GbGSTF2b to lower levels as compared to C3G. Moreover, the transient dual-luciferase assays showed that the promoters of GhGSTF1 and GhGSTF2 could be activated by GhPAP1D at different levels. GUS staining assays showed that their promoters have different activities to light. This study indicated that GhGSTF1 and GhGSTF2 play important roles in anthocyanin accumulation and the regulatory mechanism of anthocyanin accumulation in allotetraploid Gossypium are complicated.

Petri Net modelling approach for analysing the behaviour of Wnt/[inline-formula removed]-catenin and Wnt/Ca2+ signalling pathways in arrhythmogenic right ventricular cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that may result in arrhythmia, heart failure and sudden death. The hallmark pathological findings are progressive myocyte loss and fibro fatty replacement, with a predilection for the right ventricle. This study focuses on the adipose tissue formation in cardiomyocyte by considering the signal transduction pathways including Wnt/[inline-formula removed]-catenin and Wnt/Ca2+ regulation system. These pathways are modelled and analysed using stochastic petri nets (SPN) in order to increase our comprehension of ARVC and in turn its treatment regimen. The Wnt/[inline-formula removed]-catenin model predicts that the dysregulation or absence of Wnt signalling, inhibition of dishevelled and elevation of glycogen synthase kinase 3 along with casein kinase I are key cytotoxic events resulting in apoptosis. Moreover, the Wnt/Ca2+ SPN model demonstrates that the Bcl2 gene inhibited by c-Jun N-terminal kinase protein in the event of endoplasmic reticulum stress due to action potential and increased amount of intracellular Ca2+ which recovers the Ca2+ homeostasis by phospholipase C, this event positively regulates the Bcl2 to suppress the mitochondrial apoptosis which causes ARVC.

Correction to: Fine mapping and identification of the fuzzless gene GaFzl in DPL972 (Gossypium arboreum).

Unfortunately, Figs. 5 and 6 were interchanged in the results section. Figures should swap positions, whereas the legends should stay in the given order.

Fine mapping and identification of the fuzzless gene GaFzl in DPL972 (Gossypium arboreum).

KEY MESSAGE: The fuzzless gene GaFzl was fine mapped to a 70-kb region containing a GIR1 gene, Cotton_A_11941, responsible for the fuzzless trait in Gossypium arboreum DPL972. Cotton fiber is the most important natural textile resource. The fuzzless mutant DPL972 (Gossypium arboreum) provides a useful germplasm resource to explore the molecular mechanism underlying fiber and fuzz initiation and development. In our previous research, the fuzzless gene in DPL972 was identified as a single dominant gene and named GaFzl. In the present study, we fine mapped this gene using F2 and BC1 populations. By combining traditional map-based cloning and next-generation sequencing, we mapped GaFzl to a 70-kb region containing seven annotated genes. RNA-Sequencing and re-sequencing analysis narrowed these candidates to two differentially expressed genes, Cotton_A_11941 and Cotton_A_11942. Sequence alignment uncovered no variation in coding or promoter regions of Cotton_A_11942 between DPL971 and DPL972, whereas two single-base mutations in the promoter region and a TTG insertion in the coding region were detected in Cotton_A_11941 in DPL972. Cotton_A_11941 encoding a homologous gene of GIR1 (GLABRA2-interacting repressor) in Arabidopsis thaliana is thus the candidate gene most likely responsible for the fuzzless trait in DPL972. Our findings should lead to a better understanding of cotton fuzz formation, thereby accelerating marker-assisted selection during cotton breeding.

Analyzing the Behavior of Neuronal Pathways in Alzheimer's Disease Using Petri Net Modeling Approach.

Alzheimer's Disease (AD) is the most common neuro-degenerative disorder in the elderly that leads to dementia. The hallmark of AD is senile lesions made by abnormal aggregation of amyloid beta in extracellular space of brain. One of the challenges in AD treatment is to better understand the mechanism of action of key proteins and their related pathways involved in neuronal cell death in order to identify adequate therapeutic targets. This study focuses on the phenomenon of aggregation of amyloid beta into plaques by considering the signal transduction pathways of Calpain-Calpastatin (CAST) regulation system and Amyloid Precursor Protein (APP) processing pathways along with Ca2+ channels. These pathways are modeled and analyzed individually as well as collectively through Stochastic Petri Nets for comprehensive analysis and thorough understating of AD. The model predicts that the deregulation of Calpain activity, disruption of Calcium homeostasis, inhibition of CAST and elevation of abnormal APP processing are key cytotoxic events resulting in an early AD onset and progression. Interestingly, the model also reveals that plaques accumulation start early (at the age of 40) in life but symptoms appear late. These results suggest that the process of neuro-degeneration can be slowed down or paused by slowing down the degradation rate of Calpain-CAST Complex. In the light of this study, the suggestive therapeutic strategy might be the prevention of the degradation of Calpain-CAST complexes and the inhibition of Calpain for the treatment of neurodegenerative diseases such as AD.

Recent insights into cotton functional genomics: progress and future perspectives.

Functional genomics has transformed from futuristic concept to well-established scientific discipline during the last decade. Cotton functional genomics promise to enhance the understanding of fundamental plant biology to systematically exploit genetic resources for the improvement of cotton fibre quality and yield, as well as utilization of genetic information for germplasm improvement. However, determining the cotton gene functions is a much more challenging task, which has not progressed at a rapid pace. This article presents a comprehensive overview of the recent tools and resources available with the major advances in cotton functional genomics to develop elite cotton genotypes. This effort ultimately helps to filter a subset of genes that can be used to assemble a final list of candidate genes that could be employed in future novel cotton breeding programme. We argue that next stage of cotton functional genomics requires the draft genomes refinement, re-sequencing broad diversity panels with the development of high-throughput functional genomics tools and integrating multidisciplinary approaches in upcoming cotton improvement programmes.

Mode of inheritance for biochemical traits in genetically engineered cotton under water stress.

Drought is an abiotic environmental stress that can significantly reduce crop productivity. We examined the mode of inheritance for different biochemical traits including total soluble proteins, chlorophyll a, chlorophyll b, total chlorophyll, carotenoids, total phenolic contents and enzymatic antioxidants (superoxide dismutase, peroxidase and catalase), and their relationship with Bacillus thuringiensis (Bt) toxin under control and drought conditions. Eight genetically diverse cotton genotypes were selfed for two generations to ensure homozygosity. Fifteen F1 hybrids were developed by crossing five non-Bt female lines with three Bt male testers. The F1 hybrids and eight parents were finally evaluated under control (100 % field capacity (FC)) and drought (50 % FC) conditions in 2013. The biochemical traits appeared to be controlled by non-additive gene action with low narrow sense heritability estimates. The estimates of general combining ability and specific combining ability for all biochemical traits were significant under control and drought conditions. The genotype-by-trait biplot analysis showed the better performance of Bt cotton hybrids when compared with their parental genotypes for various biochemical traits under control and drought conditions. The biplot and path coefficient analyses revealed the prevalence of different relationships between Cry1Ac toxin and biochemical traits in the control and drought conditions. In conclusion, biochemical traits could serve as potential biochemical markers for breeding Bt cotton genotypes without compromising the optimal level of Bt toxin.

Molecular markers and cotton genetic improvement: current status and future prospects.

Narrow genetic base and complex allotetraploid genome of cotton (Gossypium hirsutum L.) is stimulating efforts to avail required polymorphism for marker based breeding. The availability of draft genome sequence of G. raimondii and G. arboreum and next generation sequencing (NGS) technologies facilitated the development of high-throughput marker technologies in cotton. The concepts of genetic diversity, QTL mapping, and marker assisted selection (MAS) are evolving into more efficient concepts of linkage disequilibrium, association mapping, and genomic selection, respectively. The objective of the current review is to analyze the pace of evolution in the molecular marker technologies in cotton during the last ten years into the following four areas: (i) comparative analysis of low- and high-throughput marker technologies available in cotton, (ii) genetic diversity in the available wild and improved gene pools of cotton, (iii) identification of the genomic regions within cotton genome underlying economic traits, and (iv) marker based selection methodologies. Moreover, the applications of marker technologies to enhance the breeding efficiency in cotton are also summarized. Aforementioned genomic technologies and the integration of several other omics resources are expected to enhance the cotton productivity and meet the global fiber quantity and quality demands.