Biology subjects

Sandhu, K. S.

Publications and source records attributed to Sandhu, K. S..

13 recordsLinked to original sources

bioRxiv2026

Evolutionary turnover of protein structural disorder drives aberrant proteome remodelling in naked mole rat

The naked mole rat is an evolutionary outlier among mammals, exhibiting extreme longevity, cancer resistance, hypoxia tolerance, pain insensitivity, eusociality, poikilothermy and other distinctive physiological traits, most of which likely resulted from its adaptation to highly adverse subterranean habitat. Despite accumulating data, the genetic and molecular basis underlying these traits remain poorly understood. Through analyses of 18 distinct protein attributes and allied datasets across hystricomorphs, myomorphs, carnivores, and primates, we observed lineage-specific evolutionary divergence in intrinsic protein disorder in the naked mole rat. The disorder turnover exhibited functional dichotomy. The gain of disorder preferentially associated with proteostasis, immune regulation, neurodevelopment, skeletal growth and tumour suppressive properties, while loss of disorder modulated mostly the cardiac development. The proteins that gained disorder in NMR exhibited lower degradation rates, consistent with stabilization through phase-separation, while the proteins losing disorder show pronounced divergence in gene expression. The disorder turnover was primarily driven by indels affecting functional regions including Pfam domains, ANCHOR-predicted binding sites, short linear motifs, stress induced modifications of Tyr, Met, and Cys residues. Notably, the gained disordered regions were inferred to be redox-sensitive, aligning to exceptional stress tolerance in naked mole rats. Collectively, our results highlight an unusual and previously overlooked large-scale proteome remodelling that drives the molecular evolution of extraordinary traits of naked mole rat. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=169 SRC="FIGDIR/small/720964v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@644d1dorg.highwire.dtl.DTLVardef@102c9e4org.highwire.dtl.DTLVardef@14c770org.highwire.dtl.DTLVardef@31bc5e_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2025

Restructured genomes may have shaped the evolution of clade-specific traits in mammals

Genomic rearrangements (GRs) are pervasive in mammalian evolution, yet their contribution to adaptive trait divergence remains poorly defined. By examining 71 mammalian genomes across eight major clades, we uncovered 206 clade-specific disruptions of ancestral synteny. These rearrangements consistently localize near genes underpinning clade-specific physiological, metabolic and behavioural traits and coincided with the accelerated expression rates in the affected lineage. The disruption of otherwise syntenic chromatin contacts and the fusion of domains with contrasting epigenetic states implied that the alteration in regulatory adjacency may underlie the expression divergence. Primate-specific rearrangements exhibited signatures of selective constraint, including fixation across species, reduced recombination, elevated linkage disequilibrium, and enhanced co-expression of genes flanking rearranged loci, indicating that these genomic architectures are selectively maintained. Our observations imply that the clade-specific genomic rearrangements repeatedly reconfigured the mammalian regulatory landscape and likely served as an evolutionary substrate for lineage-specific adaptation.

evolutionary biology↗

bioRxiv2024

Genomics and resistance assays inform the management of two tree species being devastated by the invasive myrtle rust pathogen

Myrtle rust is a plant disease caused by the invasive fungal pathogen Austropuccinia psidii (G. Winter) Beenken, which has a global host list of 480 species. It was detected in Australia in 2010 and has caused the rapid decline of native Myrtaceae species, including rainforest trees Rhodamnia rubescens (Benth.) Miq. (scrub turpentine) and Rhodomyrtus psidioides (G.Don) Benth. (native guava). Ex situ collections of these species have been established, with the goal of preserving remaining genetic variation. Analysis of reduced representation sequencing (DArTseq; n = 444 for R. rubescens and n = 301 for R. psidioides) showed genetic diversity is distributed along a latitudinal gradient across the range of each species. A panel of samples of each species (n = 27 for R. rubescens and n = 37 for R. psidioides) were resequenced at genome scale, revealing large historical e]ective population sizes, and little variation among individuals in inferred levels of deleterious load. In Rhodamnia rubescens, experimental assays (n = 297) identified individuals that are putatively resistant to myrtle rust. This highlights two important points: there are tangible pathways to recovery for species that are highly susceptible to rust via a genetically informed breeding program, and there is a critical need to act quickly before more standing diversity is lost.

genomics↗

bioRxiv2024

Loss of conserved noncoding elements likely shaped the evolution of regressed phenotypes in cavefish

The Mexican cavefish, Astyanax mexicanus, is a captivating model for probing cave adaptations, showcasing pronounced divergence in traits like vision, brain morphology, behaviour, pigmentation, and hypoxia tolerance compared to its surface-dwelling counterpart. Very few protein-coding variants are identified in cave-morphs, and the vast phenotypic gap between the two morphs remains inadequately explained. We investigated the noncoding genomes of teleosts and found that 3,343 conserved non-coding elements (CNEs) were independently lost in cave-morphs. These CNEs, confirmed in Zebrafish, displayed enhancer-associated histone modifications, possessed binding sites of neuronal transcription factors and interacted with cognate genes through chromatin loops. Genes crucial for eye and nervous system development were located adjacent to CNEs lost in cave morphs. Notably, these flanking genes were gradually downregulated during embryonic development of cave-morphs, contrasting with surface morphs. These insights underscore how compromised developmental pathways, stemming from the loss of distal regulatory elements, contribute to the regression of phenotypes in cave morphs. Article SummaryDespite availability of genome sequences and allied datasets, the genetic underpinning of regressed traits of cavefish remains enigmatic. By aligning the genome sequences of teleosts, we identified thousands of noncoding elements specifically lost in cavefish, exhibited enhancer-associated hallmarks, and were enriched with the binding sites of neuronal transcription factors. Their cognate genes were associated with eye and nervous system development, and exhibited developmental downregulation in cavefish. This study highlights how the loss of regulatory elements impacted the cavefish evolution and adaptation.

genomics↗

bioRxiv2024

Preferred left-handed conformations of glycyls with pathogenic variants protect against aggregation

Due to the lack of C{beta} atom, the glycyl residues can exhibit left-handed Ramachandran conformations that are mostly disallowed for L-amino acids. The structural and functional significance of distinct glycyl conformations remains under-appreciated. Through systematic analyses of various datasets, we show that: i) the left-handed glycyl residues are over-represented at disease-associated sites and are evolutionarily conserved. ii) The mutations of L-disallowed Gly tend to destabilize the native folding as assessed through the change in free energies. An independent analysis of folding nuclei further corroborates the findings. iii) L-disallowed Gly are enriched at the aggregation gatekeepers, more significantly so in thermophiles, and the mutations thereof reduce the protein solubility. (iv) The positive{Phi} dihedral angle of L-disallowed Gly disorients its C atom out of the phase of alternating pleats of {beta}-strand, conforming a crescent that is incompatible to further pair with other {beta}-strands, and thus discourages the inter-molecular aggregation of {beta}-strands during protein folding. v) L-disallowed conformation of Gly holds predictive power to identify sites having pathogenic variants. Altogether, our observations highlight that the L-disallowed conformations of glycyls are evolutionarily selected to endow protein stability and protection against aggregation. Apart from enhancing the existing knowledge, the findings have implications in prioritizing the genetic lesions implicated in diseases, and in designing proteins with greater stability and solubility.

biochemistry↗

bioRxiv2022

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

In wheat, a meta-analysis was performed using previously identified QTLs associated with drought stress, heat stress, salinity stress, water-logging stress, pre-harvest sprouting, and aluminium stress which predicted a total of 134 meta-QTLs (MQTLs) that involved at least 28 consistent and stable MQTLs conferring tolerance to five or all six abiotic stresses under study. Seventy-six MQTLs out of the 132 physically anchored MQTLs were also verified with genome-wide association studies. Around 43% of MQTLs had genetic and physical confidence intervals of less than 1 cM and 5 Mb, respectively. Consequently, 539 genes were identified in some selected MQTLs providing tolerance to 5 or all 6 abiotic stresses. Comparative analysis of genes underlying MQTLs with four RNA-seq based transcriptomic datasets unravelled a total of 191 differentially expressed genes which also included at least 11 most promising candidate genes common among different datasets. The promoter analysis showed that the promoters of these genes include many stress responsiveness cis-regulatory elements, such as ARE, MBS, TC-rich repeats, As-1 element, STRE, LTR, WRE3, and WUN-motif among others. Further, some MQTLs also overlapped with as many as 34 known abiotic stress tolerance genes. In addition, numerous ortho-MQTLs among the wheat, maize, and rice genomes were discovered. These findings could help with fine mapping and gene cloning, as well as marker-assisted breeding for multiple abiotic stress tolerances in wheat.

bioinformatics↗

bioRxiv2021

Genomic Selection for End-Use Quality and Processing Traits in Soft White Winter Wheat Breeding Program with Machine and Deep Learning Models

Breeding for grain yield, biotic and abiotic stress resistance, and end-use quality are important goals of wheat breeding programs. Screening for end-use quality traits is usually secondary to grain yield due to high labor needs, cost of testing, and large seed requirements for phenotyping. Hence, testing is delayed until later stages in the breeding program. Delayed phenotyping results in advancement of inferior end-use quality lines into the program. Genomic selection provides an alternative to predict performance using genome-wide markers. Due to large datasets in breeding programs, we explored the potential of the machine and deep learning models to predict fourteen end-use quality traits in a winter wheat breeding program. The population used consisted of 666 wheat genotypes screened for five years (2015-19) at two locations (Pullman and Lind, WA, USA). Nine different models, including two machine learning (random forest and support vector machine) and two deep learning models (convolutional neural network and multilayer perceptron), were explored for cross-validation, forward, and across locations predictions. The prediction accuracies for different traits varied from 0.45-0.81, 0.29-0.55, and 0.27-0.50 under cross-validation, forward, and across location predictions. In general, forward prediction accuracies kept increasing over time due to increments in training data size and was more evident for machine and deep learning models. Deep learning models performed superior over the traditional ridge regression best linear unbiased prediction (RRBLUP) and Bayesian models under all prediction scenarios. The high accuracy observed for end-use quality traits in this study support predicting them in early generations, leading to the advancement of superior genotypes to more extensive grain yield trailing. Furthermore, the superior performance of machine and deep learning models strengthen the idea to include them in large scale breeding programs for predicting complex traits.

genetics↗

bioRxiv2021

Genome-Wide Association Studies and Genomic Selection for Grain Protein Content Stability in a Nested Association Mapping Population of Spring Wheat

Grain protein content (GPC) is controlled by complex genetic systems and their interactions, and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, Berkut, was phenotyped over three years of field trials (2014-2016). Genomic selection models were developed and compared based on prediction of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from Finlay-Wilkinson regression. A genome-wide association study identified seven significant QTLs for GPC stability with a Bonferroni-adjusted P value <0.05. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

genomics↗

bioRxiv2021

Multi-Trait Machine and Deep Learning Models for Genomic Selection using Spectral Information in a Wheat Breeding Program

Prediction of breeding values and phenotypes is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine and deep learning algorithms applied to complex traits in plants can improve prediction accuracies in the context of GS. Spectral reflectance indices further provide information about various physiological parameters previously undetectable in plants. This research explores the potential of multi-trait (MT) machine and deep learning models for predicting grain yield and grain protein content in wheat using spectral information in GS models. This study compares the performance of four machine and deep learning-based uni-trait (UT) and MT models with traditional GBLUP and Bayesian models. The dataset consisted of 650 recombinant inbred lines from a spring wheat breeding program, grown for three years (2014-2016), and spectral data were collected at heading and grain filling stages. MT-GS models performed 0-28.5% and -0.04-15% superior to the UT-GS models for predicting grain yield and grain protein content. Random forest and multilayer perceptron were the best performing machine and deep learning models to predict both traits. These two models performed similarly under UT and MT-GS models. Four explored Bayesian models gave similar accuracies, which were less than machine and deep learning-based models, and required increased computational time. Green normalized difference vegetation index best predicted grain protein content in seven out of the nine MT-GS models. Overall, this study concluded that machine and deep learning-based MT-GS models increased prediction accuracy and should be employed in large-scale breeding programs. Core IdeasO_LIPotential for combining high throughput phenotyping, machine and deep learning in breeding. C_LIO_LIMulti-trait models exploit information from secondary correlated traits efficiently. C_LIO_LISpectral information improves genomic selection models. C_LIO_LIDeep learning can aid plant breeders owing to increased data generated in breeding programs C_LI

genetics↗

bioRxiv2020

Swi6/HP1 binding to RNA-DNA hybrids initiates heterochromatin assembly at the centromeric dg-dh repeats in Fission Yeast

Canonically, heterochromatin formation in fission yeast and metazoans is initiated by di/trimethylation of histone H3 at lysine 9 position by the histone methyltransferase Suv39H1/Clr4, followed by binding of Swi6/HP1 to H3-K9-me2/me3 via its chromodomain. Subsequent self-association of Swi6/HP1 on adjacent nucleosomes or a cooperative interaction between Clr4 and Swi6/HP1 leads to folded heterochromatin structure. HP1 binding to RNA is shown to facilitate its localization at and assembly of heterochromatin in metazoans. Likewise, recruitment of Swi6/HP1 to centromere depends on the RNAi pathway in fission yeast; paradoxically, Swi6/HP1 is also thought to play a role in RNA turnover. Here we provide evidence in support of RNAi-independent recruitment of Swi6. We show that, apart from the low affinity binding to RNAs through its hinge domain, as already reported, Swi6/HP1 displays a hierarchy of increasing binding affinity through its chromodomain to the siRNAs corresponding to specific dg-dh repeats and even stronger binding to the cognate siRNA-DNA hybrids than to the siRNA precursors or general RNAs. Our results support a mechanism of recruitment of Swi6, which is dependent on its specific and high affinity binding to siRNA-DNA hybrid at the dg-dh repeats. This binding, which is independent of, albeit augmented by binding to H3-K9-Me2, leads to heterochromatin formation and silencing. We suggest that the net role of Swi6 in RNA physiology may be regulated by a balance between abundance and affinity of Swi6 towards heterochromatic and euchromatic RNAs and siRNAs.

genetics↗

bioRxiv2018

Biased visibility in HiC datasets marks dynamically regulated condensed and decondensed chromatin states genome-wide.

Proximity ligation based techniques, like HiC, involve restriction digestion followed by ligation of formaldehyde cross-linked chromatin. We showed that the HiC datasets have significant bias due to differential accessibility of chromatin domains to restriction endonucleases. Through analysis of lamina-associated domains (LADs), inactive X-chromosome in mammals and polytene bands in fly, we established that the DNA in condensed chromatin had lesser accessibility to nucleases used in HiC as compared to that in decondensed chromatin. The observed bias was independent of known systematic biases attributed to length and GC content of the restriction fragments and was not appropriately corrected by computational methods. We identified novel condensed domains outside LADs, which were bordered by insulators and were dynamically associated with the developmentally regulated epigenetic and transcriptional states. Our observations suggested that the corrected read counts of existing HiC datasets can be reliably repurposed to study the dynamics of chromatin condensation and decondensation and that the existing HiC datasets should be interpreted with cautions.

genomics↗

bioRxiv2017

CTCF mediated genome architecture regulates the dosage of mitotically stable mono-allelic expression of autosomal genes

Mammalian genomes exhibit widespread mono-allelic expression of autosomal genes. However, the mechanistic insight that allows specific expression of one allele remains enigmatic. Here, we present evidence that the linear and the three dimensional architectures of the genome ascribe the appropriate framework that guides the mono-allelic expression of genes. We show that: 1) mono-allelically expressed genes are assorted into genomic domains that are insulated from domains of bi-allelically expressed genes through CTCF mediated chromatin loops; 2) evolutionary and cell-type specific gain and loss of mono-allelic expression coincide respectively with the gain and loss of chromatin insulator sites; 3) dosage of mono- allelically expressed genes is more sensitive to loss of chromatin insulationn associated with CTCF depletion as compared to bi-allelically expressed genes; 4) distinct susceptibility of mono- and bi-allelically expressed genes to CTCF depletion can be attributed to distinct functional roles of CTCF around these genes. Altogether, our observations highlight a general topological framework for the mono-allelic expression of genes, wherein the alleles are insulated from the spatial interference of chromatin and transcriptional states from neighbouring bi-allelic domains via CTCF mediated chromatin loops. The study also suggests that the three-dimensional genome organization might have evolved under the constraint to mitigate the fluctuations in the dosage of mono-allelically expressed genes, which otherwise are dosage sensitive.

genomics↗

bioRxiv2017

Evolutionary Dynamics Of Genome-Wide Position Effects In Mammals

Conserved noncoding elements (CNEs) have significant regulatory influence on their neighbouring genes. Loss of synteny to CNEs through genomic rearrangements can, therefore, impact the transcriptional states of the cognate genes. Yet, the evolutionary implications of such chromosomal position effects have not been studied. Through genome-wide analysis of CNEs and the cognate genes of representative species from 5 different mammalian orders, we observed significant loss of synteny to CNEs in rat lineage. The CNEs and genes losing synteny had significant association with the fetal, but not the post-natal, brain development as assessed through ontology terms, developmental gene expression, chromatin marks and genetic mutations. The loss of synteny correlated with the independent evolutionary loss of fetus-specific upregulation of genes in rat brain. DNA-breakpoints implicated in brain abnormalities of germ-line origin had significant representation between CNE and the gene that exhibited loss of synteny, signifying the underlying developmental tolerance of genomic rearrangements that had allowed the evolutionary splits of CNEs and the cognate genes in rodent lineage. These observations highlighted the non-trivial impact of chromosomal position-effect in shaping the evolutionary dynamics of mammalian brain development and might explain loss of brain traits, like cerebral folding of cortex, in rodent lineage.\n\nAuthor SummaryExpression of genes is regulated by proximally located non-coding regulatory elements. Loss of linear proximity between gene and its regulatory element thus can alter the expression of gene. Such a phenomenon can be tested at whole genome scale using evolutionary methods. We compared the positions of genes and regulatory elements in 5 different mammals and identified the significant loss of proximities between gene and their regulatory elements in rat during evolution. Brain development related function was selectively enriched among the genes and regulatory elements that had lost the proximity in rat. The observed separation of genes and their regulatory elements was strongly associated with the evolutionary loss of developmental gene expression pattern in rat brain, which coincided with the loss of brain traits in rodents. The study highlighted the importance of relative chromosomal positioning of genes and their gene regulatory elements in the evolution of phenotypes.

genomics↗