Genome resources for three modern cotton lines guide future breeding efforts.

Cotton (Gossypium hirsutum L.) is the key renewable fibre crop worldwide, yet its yield and fibre quality show high variability due to genotype-specific traits and complex interactions among cultivars, management practices and environmental factors. Modern breeding practices may limit future yield gains due to a narrow founding gene pool. Precision breeding and biotechnological approaches offer potential solutions, contingent on accurate cultivar-specific data. Here we address this need by generating high-quality reference genomes for three modern cotton cultivars ('UGA230', 'UA48' and 'CSX8308') and updating the 'TM-1' cotton genetic standard reference. Despite hypothesized genetic uniformity, considerable sequence and structural variation was observed among the four genomes, which overlap with ancient and ongoing genomic introgressions from 'Pima' cotton, gene regulatory mechanisms and phenotypic trait divergence. Differentially expressed genes across fibre development correlate with fibre production, potentially contributing to the distinctive fibre quality traits observed in modern cotton cultivars. These genomes and comparative analyses provide a valuable foundation for future genetic endeavours to enhance global cotton yield and sustainability.

Genomic diversifications of five Gossypium allopolyploid species and their impact on cotton improvement.

Polyploidy is an evolutionary innovation for many animals and all flowering plants, but its impact on selection and domestication remains elusive. Here we analyze genome evolution and diversification for all five allopolyploid cotton species, including economically important Upland and Pima cottons. Although these polyploid genomes are conserved in gene content and synteny, they have diversified by subgenomic transposon exchanges that equilibrate genome size, evolutionary rate heterogeneities and positive selection between homoeologs within and among lineages. These differential evolutionary trajectories are accompanied by gene-family diversification and homoeolog expression divergence among polyploid lineages. Selection and domestication drive parallel gene expression similarities in fibers of two cultivated cottons, involving coexpression networks and N6-methyladenosine RNA modifications. Furthermore, polyploidy induces recombination suppression, which correlates with altered epigenetic landscapes and can be overcome by wild introgression. These genomic insights will empower efforts to manipulate genetic recombination and modify epigenetic landscapes and target genes for crop improvement.

Induced Gamma-Band Activity during Actual and Imaginary Movements: EEG Analysis.

The purpose of this paper is to record and analyze induced gamma-band activity (GBA) (30-60 Hz) in cerebral motor areas during imaginary movement and to compare it quantitatively with activity recorded in the same areas during actual movement using a simplified electroencephalogram (EEG). Brain activity (basal activity, imaginary motor task and actual motor task) is obtained from 12 healthy volunteer subjects using an EEG (Cz channel). GBA is analyzed using the mean power spectral density (PSD) value. Event-related synchronization (ERS) is calculated from the PSD values of the basal GBA (GBAb), the GBA of the imaginary movement (GBAim) and the GBA of the actual movement (GBAac). The mean GBAim and GBAac values for the right and left hands are significantly higher than the GBAb value (p = 0.007). No significant difference is detected between mean GBA values during the imaginary and actual movement (p = 0.242). The mean ERS values for the imaginary movement (ERSimM (%) = 23.52) and for the actual movement (ERSacM = 27.47) do not present any significant difference (p = 0.117). We demonstrated that ERS could provide a useful way of indirectly checking the function of neuronal motor circuits activated by voluntary movement, both imaginary and actual. These results, as a proof of concept, could be applied to physiology studies, brain-computer interfaces, and diagnosis of cognitive or motor pathologies.

Enhancing Upland cotton for drought resilience, productivity, and fiber quality: comparative evaluation and genetic dissection.

To provision the world sustainably, modern society must increase overall crop production, while conserving and preserving natural resources. Producing more with diminishing water resources is an especially daunting endeavor. Toward the goal of genetically improving drought resilience of cultivated Upland cotton (Gossypium hirsutum L.), this study addresses the genetics of differential yield components referred to as productivity and fiber quality traits under regular-water versus low-water (LW) field conditions. We used ten traits to assess water stress deficit, which included six productivity and four fiber quality traits on two recombinant inbred line (RIL) populations from reciprocally crossed cultivars, Phytogen 72 and Stoneville 474. To facilitate genetic inferences, we genotyped RILs with the CottonSNP63K array, assembled high-density linkage maps of over 7000 SNPs and then analyzed quantitative trait variations. Analysis of variance revealed significant differences for all traits (p < 0.05) in these RIL populations. Although the LW irrigation regime significantly reduced all traits, except lint percent, the RILs exhibited a broad phenotypic spectrum of heritable differences across the water regimes. Transgressive segregation occurred among the RILs, suggesting the possibility of genetic gain through phenotypic selection for drought resilience and perhaps through marker-based selection. Analyses revealed more than 150 quantitative trait loci (QTLs) associated with productivity and fiber quality traits (p < 0.005) on different genomic regions of the cotton genome. The multiple-QTL models analysis with LOD > 3.0 detected 21 QTLs associated with productivity and 22 QTLs associated with fiber quality. For fiber traits, strong clustering and QTL associations occurred in c08 and its homolog c24 as well as c10, c14, and c21. Using contemporary genome sequence assemblies and bioinformatically related information, the identification of genomic regions associated with responses to plant stress/drought elevates the possibility of using marker-assisted and omics-based selection to enhance breeding for drought resilient cultivars and identifying candidate genes and networks. RILs with different responses to drought indicated that it is possible to maintain high fiber quality under LW conditions or reduce the of LW impact on quality. The heritable variation among elite bi-parental RILs for productivity and quality under field drought conditions, and their association of QTLs, and thus specific genomic regions, indicate opportunities for breeding-based gains in water resource conservation, i.e., enhancing cotton's agricultural sustainability.

Empirical Mode Decomposition-Based Filter Applied to Multifocal Electroretinograms in Multiple Sclerosis Diagnosis.

As multiple sclerosis (MS) usually affects the visual pathway, visual electrophysiological tests can be used to diagnose it. The objective of this paper is to research methods for processing multifocal electroretinogram (mfERG) recordings to improve the capacity to diagnose MS. MfERG recordings from 15 early-stage MS patients without a history of optic neuritis and from 6 control subjects were examined. A normative database was built from the control subject signals. The mfERG recordings were filtered using empirical mode decomposition (EMD). The correlation with the signals in a normative database was used as the classification feature. Using EMD-based filtering and performance correlation, the mean area under the curve (AUC) value was 0.90. The greatest discriminant capacity was obtained in ring 4 and in the inferior nasal quadrant (AUC values of 0.96 and 0.94, respectively). Our results suggest that the combination of filtering mfERG recordings using EMD and calculating the correlation with a normative database would make mfERG waveform analysis applicable to assessment of multiple sclerosis in early-stage patients.

A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings.

INTRODUCTION: The aim of this study is to develop a computer-aided diagnosis system to identify subjects at differing stages of development of multiple sclerosis (MS) using multifocal visual-evoked potentials (mfVEPs). Using an automatic classifier, diagnosis is performed first on the eyes and then on the subjects. PATIENTS: MfVEP signals were obtained from patients with Radiologically Isolated Syndrome (RIS) (n = 30 eyes), patients with Clinically Isolated Syndrome (CIS) (n = 62 eyes), patients with definite MS (n = 56 eyes) and 22 control subjects (n = 44 eyes). The CIS and MS groups were divided into two subgroups: those with eyes affected by optic neuritis (ON) and those without (non-ON). METHODS: For individual eye diagnosis, a feature vector was formed with information about the intensity, latency and singular values of the mfVEP signals. A flat multiclass classifier (FMC) and a hierarchical classifier (HC) were tested and both were implemented using the k-Nearest Neighbour (k-NN) algorithm. The output of the best eye classifier was used to classify the subjects. In the event of divergence, the eye with the best mfVEP recording was selected. RESULTS: In the eye classifier, the HC performed better than the FMC (accuracy = 0.74 and extended Matthew Correlation Coefficient (MCC) = 0.68). In the subject classification, accuracy = 0.95 and MCC = 0.93, confirming that it may be a promising tool for MS diagnosis. CONCLUSION: In addition to amplitude (axonal loss) and latency (demyelination), it has shown that the singular values of the mfVEP signals provide discriminatory information that may be used to identify subjects with differing degrees of the disease.

Empirical mode decomposition processing to improve multifocal-visual-evoked-potential signal analysis in multiple sclerosis.

OBJECTIVE: To study the performance of multifocal-visual-evoked-potential (mfVEP) signals filtered using empirical mode decomposition (EMD) in discriminating, based on amplitude, between control and multiple sclerosis (MS) patient groups, and to reduce variability in interocular latency in control subjects. METHODS: MfVEP signals were obtained from controls, clinically definitive MS and MS-risk progression patients (radiologically isolated syndrome (RIS) and clinically isolated syndrome (CIS)). The conventional method of processing mfVEPs consists of using a 1-35 Hz bandpass frequency filter (XDFT). The EMD algorithm was used to decompose the XDFT signals into several intrinsic mode functions (IMFs). This signal processing was assessed by computing the amplitudes and latencies of the XDFT and IMF signals (XEMD). The amplitudes from the full visual field and from ring 5 (9.8-15° eccentricity) were studied. The discrimination index was calculated between controls and patients. Interocular latency values were computed from the XDFT and XEMD signals in a control database to study variability. RESULTS: Using the amplitude of the mfVEP signals filtered with EMD (XEMD) obtains higher discrimination index values than the conventional method when control, MS-risk progression (RIS and CIS) and MS subjects are studied. The lowest variability in interocular latency computations from the control patient database was obtained by comparing the XEMD signals with the XDFT signals. Even better results (amplitude discrimination and latency variability) were obtained in ring 5 (9.8-15° eccentricity of the visual field). CONCLUSIONS: Filtering mfVEP signals using the EMD algorithm will result in better identification of subjects at risk of developing MS and better accuracy in latency studies. This could be applied to assess visual cortex activity in MS diagnosis and evolution studies.

Induced gamma band activity from EEG as a possible index of training-related brain plasticity in motor tasks.

The aim of this study was proposing gamma band activity (GBA) as an index of training-related brain plasticity in the motor cortex. Sixteen controls underwent an experimental session where electroencephalography (EEG) activity was recorded at baseline (resting) and during a motor task (hand movements). GBA was obtained from the EEG data at baseline and during the task. Index of plasticity (IP) was defined as the relationship between GBA at the end of the motor task (GBAM_FIN), divided by GBA at the beginning of the task (GBAM_INI) for movements of both hands. There was a significant increase in GBA at the end of the task, compared to the initial GBA for the motor task (GBAM_FIN > GBAM_INI). No differences were found at baseline (GBAB_FIN ≈ GBAB_INI). Individual IP values had a positive (r = 0.624) and significant correlation with subject's handedness. Due to plastic changes, GBA could indirectly but objectively reveal changes in cerebral activity related to physical training. This method could be used as a future diagnostic test in the follow-up of patients undergoing rehabilitation. It could also have potential applications in the fields of sports medicine.

Analysis of Gamma-Band Activity from Human EEG Using Empirical Mode Decomposition.

The purpose of this paper is to determine whether gamma-band activity detection is improved when a filter, based on empirical mode decomposition (EMD), is added to the pre-processing block of single-channel electroencephalography (EEG) signals. EMD decomposes the original signal into a finite number of intrinsic mode functions (IMFs). EEGs from 25 control subjects were registered in basal and motor activity (hand movements) using only one EEG channel. Over the basic signal, IMF signals are computed. Gamma-band activity is computed using power spectrum density in the 30-60 Hz range. Event-related synchronization (ERS) was defined as the ratio of motor and basal activity. To evaluate the performance of the new EMD based method, ERS was computed from the basic and IMF signals. The ERS obtained using IMFs improves, from 31.00% to 73.86%, on the original ERS for the right hand, and from 22.17% to 47.69% for the left hand. As EEG processing is improved, the clinical applications of gamma-band activity will expand.

Multifocal visual evoked potentials for quantifying optic nerve dysfunction in patients with optic disc drusen.

PURPOSE: To explore the applicability of multifocal visual evoked potentials (mfVEPs) for research and clinical diagnosis in patients with optic disc drusen (ODD). This is the first assessment of mfVEP amplitude in patients with ODD. METHODS: MfVEP amplitude and latency from 33 patients with ODD and 22 control subjects were examined. Mean amplitude, mean inner ring (IR) amplitude (0.87-5.67° of visual field) and mean outer ring amplitude (5.68-24° of visual field) were calculated using signal-to-noise ratio (SNR) and peak-to-peak analysis. Monocular latency was calculated using second peak analysis, while latency asymmetry was calculated using cross-correlation analysis. RESULTS: Compared to normals, significantly decreased mean overall amplitude (p < 0.001), IR amplitude (p < 0.001) and outer ring amplitude (p < 0.001) were found in ODD patients when using SNR. An overall monocular latency delay of 7 ms was seen in ODD patients (p = 0.001). A significant correlation between amplitude and automated perimetric mean deviation as well as retinal nerve fibre layer thickness was found (respectively, p < 0.001 and p = 0.003). The overall highest correlation was found in this order: outer ring, full eye and IR. In the control group, SNR intersubject variability was 17.6% and second peak latency intersubject variability was 2.8%. CONCLUSION: Decreased mfVEP amplitude in patients with ODD suggests a direct mechanical compression of the optic nerve axons. Our results suggest that mfVEP amplitude is applicable for the assessment of optic nerve dysfunction in patients with ODD.

Insights Into Upland Cotton (Gossypium hirsutum L.) Genetic Recombination Based on 3 High-Density Single-Nucleotide Polymorphism and a Consensus Map Developed Independently With Common Parents.

High-density linkage maps are vital to supporting the correct placement of scaffolds and gene sequences on chromosomes and fundamental to contemporary organismal research and scientific approaches to genetic improvement, especially in paleopolyploids with exceptionally complex genomes, eg, upland cotton (Gossypium hirsutum L., "2n = 52"). Three independently developed intraspecific upland mapping populations were analyzed to generate 3 high-density genetic linkage single-nucleotide polymorphism (SNP) maps and a consensus map using the CottonSNP63K array. The populations consisted of a previously reported F2, a recombinant inbred line (RIL), and reciprocal RIL population, from "Phytogen 72" and "Stoneville 474" cultivars. The cluster file provided 7417 genotyped SNP markers, resulting in 26 linkage groups corresponding to the 26 chromosomes (c) of the allotetraploid upland cotton (AD)1 arisen from the merging of 2 genomes ("A" Old World and "D" New World). Patterns of chromosome-specific recombination were largely consistent across mapping populations. The high-density genetic consensus map included 7244 SNP markers that spanned 3538 cM and comprised 3824 SNP bins, of which 1783 and 2041 were in the At and Dt subgenomes with 1825 and 1713 cM map lengths, respectively. Subgenome average distances were nearly identical, indicating that subgenomic differences in bin number arose due to the high numbers of SNPs on the Dt subgenome. Examination of expected recombination frequency or crossovers (COs) on the chromosomes within each population of the 2 subgenomes revealed that COs were also not affected by the SNPs or SNP bin number in these subgenomes. Comparative alignment analyses identified historical ancestral At-subgenomic translocations of c02 and c03, as well as of c04 and c05. The consensus map SNP sequences aligned with high congruency to the NBI assembly of Gossypium hirsutum. However, the genomic comparisons revealed evidence of additional unconfirmed possible duplications, inversions and translocations, and unbalance SNP sequence homology or SNP sequence/loci genomic dominance, or homeolog loci bias of the upland tetraploid At and Dt subgenomes. The alignments indicated that 364 SNP-associated previously unintegrated scaffolds can be placed in pseudochromosomes of the NBI G hirsutum assembly. This is the first intraspecific SNP genetic linkage consensus map assembled in G hirsutum with a core of reproducible mendelian SNP markers assayed on different populations and it provides further knowledge of chromosome arrangement of genic and nongenic SNPs. Together, the consensus map and RIL populations provide a synergistically useful platform for localizing and identifying agronomically important loci for improvement of the cotton crop.

Induced Gamma-Band Activity During Voluntary Movement: EEG Analysis for Clinical Purposes.

OBJECTIVE: Propose a simplified method applicable in routine clinical practice that uses EEG to assess induced gamma-band activity (GBA) in the 30-90 Hz frequency range in cerebral motor areas. DESIGN: EEG recordings (25 healthy subjects) of cerebral activity (at rest, motor task). GBA was obtained as power spectral density (PSD). GBA - defined as the gamma index (Iγ) - was calculated using the basal GBA (γB) and motor GBA (γMOV) PSD values. RESULTS: The mean values of Iγ were (IγR (right hand) = 1.30, IγL (left hand) = 1.22). Manual laterality showed a correlation with Iγ. CONCLUSIONS: Iγ may provide a useful way of indirectly assessing operation of activated motor neuronal circuits. It could be applied to diagnosis of motor area pathologies and as follow up in rehabilitation processes. Likewise, Iγ could enable the assessment of motor capacity, physical training and manual laterality in sport medicine.