Biology subjects

Anand, A.

Publications and source records attributed to Anand, A..

At least 91 records · Page 5Linked to original sources

bioRxiv2020

Quantifying the Brain Predictivity of Artificial Neural Networks with Nonlinear Response Mapping

Quantifying the similarity between artificial neural networks (ANNs) and their biological counterparts is an important step towards building more brain-like artificial intelligence systems. Recent efforts in this direction use neural predictivity, or the ability to predict the responses of a biological brain given the information in an ANN (such as its internal activations), when both are presented with the same stimulus. We propose a new approach to quantifying neural predictivity by explicitly mapping the activations of an ANN to brain responses with a nonlinear function, and measuring the error between the predicted and actual brain responses. Further, we propose to use a neural network to approximate this mapping function by training it on a set of neural recordings. The proposed method was implemented within the Tensorflow framework and evaluated on a suite of 8 state-of-the-art image recognition ANNs. Our experiments suggest that the use of a non-linear mapping function leads to higher neural predictivity. Our findings also reaffirm the observation that the latest advances in classification performance of image recognition ANNs are not matched by improvements in their neural predictivity. Finally, we examine the impact of pruning, a widely used ANN optimization, on neural predictivity, and demonstrate that network sparsity leads to higher neural predictivity.

neuroscience↗

bioRxiv2020

Hyaluronic Acid Fuels Pancreatic Cancer Growth

Rewired metabolism is a hallmark of pancreatic ductal adenocarcinomas (PDA). Previously, we demonstrated that PDA cells enhance glycosylation precursor biogenesis through the hexosamine biosynthetic pathway (HBP) via activation of the rate limiting enzyme, glutamine-fructose 6-phosphate amidotransferase 1 (GFAT1). Here, we genetically ablated GFAT1 in PDA cell lines, which completely blocked proliferation in vitro and led to cell death. In contrast, GFAT1 knockout did not impair tumor growth, suggesting that cancer cells can maintain fidelity of glycosylation precursor pools by scavenging nutrients from the tumor microenvironment. Here, we show that hyaluronic acid (HA), an abundant carbohydrate polymer in pancreatic tumors composed of repeating N-acetyl-glucosamine (GlcNAc) and glucuronic acid sugars, can bypass GFAT1 to refuel the HBP via the GlcNAc salvage pathway. Furthermore, HA facilitates proliferation in nutrient-starved wild-type PDA. Together, these data show HA can serve as a nutrient fueling PDA metabolism beyond its previously appreciated structural and signaling roles.

cancer biology↗

bioRxiv2020

Characterization of Onion Seedlots into Different Storability Groups with 4 Parameter Hill Function (4-PHF)

Onion varieties were classified into different storability groups by comparing two approaches (i)germination and vigor indices (conventional germination parameters) (ii)variables extracted from 4 Parameter Hill Function (4-PHF), after mimicking ageing conditions with accelerated ageing (42 {degrees}C and 100% RH). The study revealed that in comparison to evaluation using conventional germination parameters, the parameters extracted using 4-PHF provided realistic characterization of varieties as good, medium and poor storers. Time related parameters like time to maximum germination rate (TMGR), time to 50% germination (T50), difference between time at germination onset (lag) and 50% germination (Dlag-50), uniformity (U) along with germination percent (a) and area under curve (AUC) were decisive in identification of the varieties to a storage category which was misinterpreted with exclusive use of conventional approach. The distinction between good and medium storers was not of much significance but shift of varieties like Bhima Super, Pusa Red and Agrifound Light Red from poor to good performance cluster could be detected exclusively through 4-PHF analysis. Curve fittings highlighted AUC as the most crucial parameter contributing towards clustering of the varieties in different storability groups. Our study is the first reported research of using 4-PHF mathematical function for seedlot characterization into different storability groups.

plant biology↗

bioRxiv2020

Efficient Gene Targeting in Maize using Inducible CRISPR-Cas9 and Marker-Free Donor Template

CRISPR-Cas9 is a powerful tool for generating targeted mutations and genomic deletions. However, precise gene insertion or sequence replacement remains a major hurdle before application of CRISPR-Cas9 technology is fully realized in plant breeding. Here we report high frequency, selectable marker-free intra-genomic gene targeting (GT) in maize. Heat shock-inducible Cas9 was used for generating targeted double-strand breaks (DSBs) and simultaneous mobilization of the donor template from pre-integrated T-DNA. The construct was designed such that release of the donor template and subsequent DNA repair activated expression of the selectable marker gene within the donor locus. This approach generated up to 4.7% targeted insertion of the donor sequence into the target locus in T0 plants, with up to 86% detected donor template release and 99% mutation rate were observed at the donor loci and the genomic target site, respectively. Unlike previous in planta or intra-genomic homologous recombination reports, that required multiple generations and extensive screening, our method provides non-chimeric, heritable GT in the T0 generation.

plant biology↗

bioRxiv2020

Neuroimaging Correlates of Emotional Response-Inhibition Discriminate Between Young Depressed Adults With and Without Sub-threshold Bipolar Symptoms

BackgroundA significant number of subjects with major depression (MDD) exhibit subthreshold mania symptoms (MDD+). This study investigated, for the first time, using emotional inhibition tasks, whether the neurobiology of MDD+ subjects is more akin to bipolar disorder depression (BDD) or to MDD subjects without any subthreshold bipolar symptoms (MDD-). MethodThis study included 118 medication-free young adult subjects (16 - 30 yrs.): 20 BDD, 28 MDD+, 41 MDD-, and 29 HC subjects. Participants underwent fMRI during emotional and non-emotional Go/No-go tasks during which they responded for Go stimuli and inhibited response for happy, fear, emotional (happy + fear) and non-emotional (gender) faces No-go stimuli. Linear mixed effects (LME) analysis for group effects and Gaussian Process Classifier (GPC) analyses was conducted. ResultsMDD- group compared to both the BDD and MDD+ groups, exhibited significantly lower activation in parietal, temporal and frontal regions (cluster-wise corrected p <0.05) for emotional inhibition conditions vs. non-emotional condition. No significant differences were found between BDD and MDD+ groups. GPC classification of emotional vs non-emotional response-inhibition activation pattern showed good discrimination between BDD and MDD- subjects (AUC: 0.70; balanced accuracy: 70% (p = 0.006)) as well as MDD+ and MDD- subjects (AUC: 0.72; balanced accuracy: 67% (p = 0.015)) but less efficient discrimination between BDD and MDD+ groups (AUC: 0.68; balanced accuracy: 61% (p = 0.091)). Notably, classification of the MDD- group was weighted for left amygdala activation pattern. ConclusionUsing an fMRI emotional Go-Nogo task, MDD- subjects can be discriminated from BDD subjects and MDD+.

neuroscience↗

bioRxiv2020

Organ-on-a-chip model of vascularized human bone marrow niches

Animal models of bone marrow have limited spatial and temporal resolution to observe biological events (intravasation and cellular egress) and are inadequate to dissect dynamic events at the niche level (100 microns). Utilizing microfluidic and stem cell technology, we present a 3D in vitro model of human bone marrow that contains perivascular and endosteal niches complete with dynamic, perfusable vascular networks. We demonstrate that our model can perform in vivo functions including maintenance and differentiation of CD34+ hematopoietic stem/progenitor cells (HSPC) for up to fourteen days, egress of myeloid progenitors, and expression of markers consistent with in vivo human bone marrow. The platform design enables the addition of tissue niches at a later timepoint to probe mechanisms such as tumor cell migration. Overall, we present a novel organ-on-a-chip platform that is capable of recapitulating the human bone marrow microenvironment to observe hematopoietic phenomena at high spatial and temporal resolution.

bioengineering↗

bioRxiv2020

Reorganization of 3D genome structure in the Drosophila melanogaster species group

Topologically associating domains, or TADs, are functional units that organize chromosomes into 3D structures of interacting chromatin. TADs play an important role in regulating gene expression by constraining enhancer-promoter contacts; there is evidence that deletion of TAD boundaries leads to aberrant expression of neighboring genes. While the mechanisms of TAD formation have been well-studied, current knowledge on the extent of TAD conservation across species is inconclusive. Due to the integral role TADs play in gene regulation, their structure and organization is expected to be conserved during evolution. However, more recent research suggests that TAD structures diverge relatively rapidly. We use Hi-C chromosome conformation capture to measure evolutionary conservation of whole TADs and TAD boundary elements between D. melanogaster and D. triauraria, two early-branching species from the melanogaster species group which diverged ~15 million years ago. We find that 75% of TAD boundaries are orthologous while only 25% of TAD domains are conserved and these are enriched for Polycomb-repressed chromatin. Our results show that TADs have been reorganized since the common ancestor of D. melanogaster and D. triauraria, yet the sequence elements that specify TAD boundaries remain highly conserved. We propose that evolutionary divergence in 3D genome organization results from shuffling of conserved boundary elements across chromosomes, breaking old TADs and creating new TAD architectures. This result supports the existence of distinct TAD subtypes: some may be evolutionarily flexible while others remain highly conserved due to their importance in restricting gene-regulatory element interactions.

genomics↗

bioRxiv2020

Knowledge synthesis from 100 million biomedical documents augments the deep expression profiling of coronavirus receptors

The COVID-19 pandemic demands assimilation of all available biomedical knowledge to decode its mechanisms of pathogenicity and transmission. Despite the recent renaissance in unsupervised neural networks for decoding unstructured natural languages, a platform for the real-time synthesis of the exponentially growing biomedical literature and its comprehensive triangulation with deep omic insights is not available. Here, we present the nferX platform for dynamic inference from over 45 quadrillion possible conceptual associations extracted from unstructured biomedical text, and their triangulation with Single Cell RNA-sequencing based insights from over 25 tissues. Using this platform, we identify intersections between the pathologic manifestations of COVID-19 and the comprehensive expression profile of the SARS-CoV-2 receptor ACE2. We find that tongue keratinocytes, airway club cells, and ciliated cells are likely underappreciated targets of SARS-CoV-2 infection, in addition to type II pneumocytes and olfactory epithelial cells. We further identify mature small intestinal enterocytes as a possible hotspot of COVID-19 fecal-oral transmission, where an intriguing maturation-correlated transcriptional signature is shared between ACE2 and the other coronavirus receptors DPP4 (MERS-CoV) and ANPEP (-coronavirus). This study demonstrates how a holistic data science platform can leverage unprecedented quantities of structured and unstructured publicly available data to accelerate the generation of impactful biological insights and hypotheses. The nferX Platform Single-cell resource - https://academia.nferx.com/

genomics↗

bioRxiv2020

Revealing 29 sets of independently modulated genes in Staphylococcus aureus, their regulators and role in key physiological responses

The ability of Staphylococcus aureus to infect many different tissue sites is enabled, in part, by its Transcriptional Regulatory Network (TRN) that coordinates its gene expression to respond to different environments. We elucidated the organization and activity of this TRN by applying Independent Component Analysis (ICA) to a compendium of 108 RNAseq expression profiles from two S. aureus clinical strains (TCH1516 and LAC). ICA decomposed the S. aureus transcriptome into 29 independently modulated sets of genes (i-modulons) that revealed (1) high confidence associations between 21 i-modulons and known regulators; (2) an association between an i-modulon and {sigma}S, whose regulatory role was previously undefined; (3) the regulatory organization of 65 virulence factors in the form of three i-modulons associated with AgrR, SaeR and Vim-3, (4) the roles of three key transcription factors (codY, Fur and ccpA) in coordinating the metabolic and regulatory networks; and (5) a low dimensional representation, involving the function of few transcription factors, of changes in gene expression between two laboratory media (RPMI, CAMHB) and two physiological media (blood and serum). This representation of the TRN covers 842 genes representing 76% of the variance in gene expression that provides a quantitative reconstruction of transcriptional modules in S. aureus, and a platform enabling its full elucidation. Significance StatementStaphylococcus aureus infections impose an immense burden on the healthcare system. To establish a successful infection in a hostile host environment, S. aureus must coordinate its gene expression to respond to a wide array of challenges. This balancing act is largely orchestrated by the Transcriptional Regulatory Network (TRN). Here, we present a model of 29 independently modulated sets of genes that form the basis for a segment of the TRN in clinical USA300 strains of S. aureus. Using this model, we demonstrate the concerted role of various cellular systems (e.g. metabolism, virulence and stress response) underlying key physiological responses, including response during blood infection.

microbiology↗

bioRxiv2020

SpliceViNCI: Visualizing the splicing of non-canonical introns through recurrent neural networks

Most of the current computational models for splice junction prediction are based on the identification of canonical splice junctions. However, it is observed that the junctions lacking the consensus dimers GT and AG also undergo splicing. Identification of such splice junctions, called the non-canonical splice junctions, is also essentially important for a comprehensive understanding of the splicing phenomenon. This work focuses on the identification of non-canonical splice junctions through the application of a bidirectional long short-term memory (BLSTM) network. Furthermore, we apply a back-propagation based (integrated gradient) and a perturbation based (occlusion) visualization techniques to extract the non-canonical splicing features learned by the model. The features obtained are validated with the existing knowledge from the literature. Integrated gradient extracts features that comprise contiguous nucleotides, whereas occlusion extracts features that are individual nucleotides distributed across the sequence.

bioinformatics↗

bioRxiv2019

Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory

Reconstruction of time-varying gene regulatory networks underlying a time-series gene expression data is a fundamental challenge in the computational systems biology. The challenge increases multi-fold if the target networks need to be constructed for hundreds to thousands of genes. There have been constant efforts to design an algorithm that can perform the reconstruction task correctly as well as can scale efficiently (with respect to both time and memory) to such a large number of genes. However, the existing algorithms either do not offer time-efficiency, or they offer it at other costs - memory-inefficiency or imposition of a constraint, known as the smoothly time-varying assumption. In this paper, two novel algorithms - an algorithm for reconstructing Time-varying Gene regulatory networks with Shortlisted candidate regulators - which is Light on memory (TGS-Lite) and TGS-Lite Plus (TGS-Lite+) - are proposed that are time-efficient, memory-efficient and do not impose the smoothly time-varying assumption. Additionally, they offer state-of-the-art reconstruction correctness as demonstrated with three benchmark datasets.\n\nSource Codehttps://github.com/sap01/TGS-Lite-supplem/tree/master/sourcecode

bioinformatics↗

bioRxiv2019

Gene variants in ZGRF1 implicated for a rare sensory reflex epilepsy

Hot water epilepsy (HWE) is a sensory reflex epilepsy in which seizures are precipitated by a stimulus such as contact with hot water. While there is a genetic basis to its etiology, identity of the genes underlying this relatively uncommon disorder has remained unknown. Here, we present the results of our studies aimed at identifying a causative gene in a south Indian four-generation family with several affected members. We conducted whole-exome sequencing and examined a known locus that maps to 4q24-q28 (HWE2, MIM: 613340) that we had previously identified. We identified a sequence variant, c.1805C>T (p.Thr602Ile) in ZGRF1, located within the HWE2 locus, co-segregating with the disorder. The transcript structure of ZGRF1 was examined in 288 HWE patients, and five additional missense variants, Arg326Gln, Glu660Gly, Arg1862*, Phe1940Leu and Asp1984Gly, present exclusively or almost exclusively in the patients were found. Functional correlates of the six variants identified were examined in cultured mammalian cells. We observed spindle pole defects during cell division and partially disrupted localization of UPF1, a protein involved in cell cycle regulation, at the spindles. Our observations provide insights into the genetic basis of HWE and suggest the involvement of hitherto unanticipated molecular process in this disorder.

genetics↗

bioRxiv2018

A New Family of Similarity Measures for Scoring Confidence of Protein Interactions using Gene Ontology

The large-scale protein-protein interaction (PPI) data has the potential to play a significant role in the endeavor of understanding cellular processes. However, the presence of a considerable fraction of false positives is a bottleneck in realizing this potential. There have been continuous efforts to utilize complementary resources for scoring confidence of PPIs in a manner that false positive interactions get a low confidence score. Gene Ontology (GO), a taxonomy of biological terms to represent the properties of gene products and their relations, has been widely used for this purpose. We utilize GO to introduce a new set of specificity measures: Relative Depth Specificity (RDS), Relative Node-based Specificity (RNS), and Relative Edge-based Specificity (RES), leading to a new family of similarity measures. We use these similarity measures to obtain a confidence score for each PPI. We evaluate the new measures using four different benchmarks. We show that all the three measures are quite effective. Notably, RNS and RES more effectively distinguish true PPIs from false positives than the existing alternatives. RES also shows a robust set-discriminating power and can be useful for protein functional clustering as well.

bioinformatics↗

bioRxiv2018

Inference of splicing motifs through visualization of recurrent networks

Neural models have been able to obtain state-of-the-art performances on several genome sequence-based prediction tasks. Such models take only nucleotide sequences as input and learn relevant features on its own. However, extracting the interpretable motifs from the model remains a challenge. This work explores various existing visualization techniques in their ability to infer relevant sequence information learned by a recurrent neural network (RNN) on the task of splice junction identification. The visualization techniques have been modulated to suit the genome sequences as input. The visualizations inspect genomic regions at the level of a single nucleotide as well as a span of consecutive nucleotides. This inspection is performed based on modification of input sequences (perturbation-based) or the embedding space (back-propagation based). We infer features pertaining to both canonical and non-canonical splicing from a single neural model. Results indicate that the visualization techniques produce comparable performance for branchpoint detection. However, in case of canonical donor and acceptor junction motifs, perturbation based visualizations perform better than back-propagation based visualizations and vice-versa for non-canonical motifs.

bioinformatics↗

bioRxiv2018

Global Adoption of High-Sensitivity Cardiac Troponins and the Universal Definition of Myocardial Infarction

ImportanceThe third Universal Definition of Myocardial Infarction aimed to standardize the approach to the diagnosis and management of myocardial infarction. High-sensitivity cardiac troponin testing was recommended, as these assays have improved precision at low concentrations, but concerns over specificity may have limited implementation.\n\nObjectiveTo determine the global adoption of high-sensitivity cardiac troponin assays and key recommendations from the Universal Definition.\n\nDesign, Setting and ParticipantsGlobal survey of 1,902 medical centers across 23 countries evenly distributed across all five continents. Included respondents were involved in the diagnosis and management of patients with suspected acute coronary syndrome at their institutions.\n\nMain Outcomes and MeasuresStructured questionnaire detailing the primary biomarker used for myocardial infarction, diagnostic thresholds and critical elements of clinical pathways for comparison to the third Universal Definition recommendations.\n\nResultsCardiac troponin was the primary diagnostic biomarker for myocardial infarction at 96% of all sites surveyed. Only 41% of centers had adopted high-sensitivity cardiac troponin assays, with wide variation from 7% in North America to 60% in Europe. Sites using high-sensitivity assays more frequently employed serial sampling pathways (91% vs. 78%) and the 99th percentile diagnostic threshold (74% vs. 66%) when compared to sites using the previous generation of troponin assays. Furthermore, sites using high-sensitivity assays more often used earlier serial sampling ([≤]3 hours) and accelerated diagnostic pathways. However, fewer than 1 in 5 sites using high-sensitivity assays had adopted sex-specific thresholds (18%).\n\nConclusions and RelevanceProgress has been made in adopting the recommendations of the Universal Definition of Myocardial Infarction, particularly in the use of the 99th percentile diagnostic threshold and serial sampling. However, high-sensitivity assays are used in a minority of sites and sex-specific thresholds in even fewer. These findings highlight regions where additional efforts are required to improve the risk stratification and diagnosis of patients with myocardial infarction.

biochemistry↗

bioRxiv2018

Sequence variation of rare outer membrane protein β-barrel domains in clinical strains provides insights into the evolution of Treponema pallidum subsp. pallidum, the syphilis spirochete.

In recent years, considerable progress has been made in topologically and functionally characterizing integral outer membrane proteins (OMPs) of Treponema pallidum subspecies pallidum (TPA), the syphilis spirochete, and identifying its surface-exposed {beta}-barrel domains. Extracellular loops in OMPs of Gram-negative bacteria are known to be highly variable. We examined the sequence diversity of {beta}-barrel-encoding regions of tprC, tprD, and bamA, in 31 specimens from Cali, Colombia; San Francisco, California; and the Czech Republic and compared them to allelic variants in the 41 reference genomes in the NCBI database. To establish a phylogenetic framework, we used tp0548 genotyping and tp0558 sequences to assign strains to the Nichols or SS14 clades. We found that (i) {beta}-barrels in clinical strains could be grouped according to allelic variants in TPA reference genomes; (ii) for all three OMP loci, clinical strains within the Nichols or SS14 clades often harbored {beta}-barrel variants that differed from the Nichols and SS14 reference strains; and (iii) OMP variable regions often reside in predicted extracellular loops containing B-cell epitopes. Based upon structural models, non-conservative amino acid substitutions in predicted transmembrane {beta}-strands of TprC and TprD2 could give rise to functional differences in their porin channels. OMP profiles of some clinical strains were mosaics of different reference strains and did not correlate with results from enhanced molecular typing. Our observations suggest that human host selection pressures drive TPA OMP diversity and that genetic exchange contributes to the evolutionary biology of TPA. They also set the stage for topology-based analysis of antibody responses against OMPs and help frame strategies for syphilis vaccine development.\n\nIMPORTANCEDespite recent progress characterizing outer membrane proteins (OMPs) of Treponema pallidum (TPA), little is known about how their surface-exposed, {beta}-barrel-forming domains vary among strains circulating within high-risk populations. In this study, sequences for the {beta}-barrel-encoding regions of three OMP loci, tprC, tprD, and bamA, in TPA from a large number of patient specimens from geographically disparate sites were examined. Structural models predict that sequence variation within {beta}-barrel domains occurred predominantly within predicted extracellular loops. Amino acid substitutions in predicted transmembrane strands that could potentially affect porin channel function also were noted. Our findings suggest that selection pressures exerted by human populations drive TPA OMP diversity and that recombination at OMP loci contributes to the evolutionary biology of syphilis spirochetes. These results also set the stage for topology-based analysis of antibody responses that promote clearance of TPA and frame strategies for vaccine development based upon conserved OMP extracellular loops.

microbiology↗

bioRxiv2018

Rapid Reconstruction of Time-varying Gene Regulatory Networks

--Rapid advancements in high-throughput technologies has resulted in genome-scale time series datasets. Uncovering the temporal sequence of gene regulatory events, in the form of time-varying gene regulatory networks (GRNs), demands computationally fast, accurate and scalable algorithms. The existing algorithms can be divided into two categories: ones that are time-intensive and hence unscalable; others that impose structural constraints to become scalable. In this paper, a novel algorithm, namely an algorithm for reconstructing Time-varying Gene regulatory networks with Shortlisted candidate regulators (TGS), is proposed. TGS is time-efficient and does not impose any structural constraints. Moreover, it provides such flexibility and time-efficiency, without losing its accuracy. TGS consistently outperforms the state-of-the-art algorithms in true positive detection, on three benchmark synthetic datasets. However, TGS does not perform as well in false positive rejection. To mitigate this issue, TGS+ is proposed. TGS+ demonstrates competitive false positive rejection power, while maintaining the superior speed and true positive detection power of TGS. Nevertheless, main memory requirements of both TGS variants grow exponentially with the number of genes, which they tackle by restricting the maximum number of regulators for each gene. Relaxing this restriction remains a challenge as the actual number of regulators is not known a priori.\n\nReproducibilityThe datasets and results can be found at: https://github.com/aaiitg-grp/TGS. This manuscript is currently under review. As soon as it is accepted, the source code will be made available at the same link. There are mentions of a supplementary document throughout the text. The supplementary document will also be made available after acceptance of the manuscript. If you wish to be notified when the supplementary document and source code are available, kindly send an email to saptarshipyne01@gmail.com with subject line TGS Source Code: Request for Notification. The email body can be kept blank.

bioinformatics↗

bioRxiv2018

Heat shock factor 5 is conserved in vertebrates and essential forspermatogenesis in zebrafish

Heat shock factors (Hsfs) are transcription factors that regulate response to heat shock and to variety of other environmental and physiological stimuli. Four HSFs (HSF1-4) known in vertebrates till date, perform a wide variety of functions from mediating heat shock response to development and gametogenesis. Here, we describe a new yet conserved member of HSF family, Hsf5, which likely exclusively functions for spermatogenesis. The hsf5 is predominantly expressed in developing testicular tissues, in comparison to wider expression reported for other HSFs. HSF5 loss causes male sterility due to drastically reduced sperm count, and severe abnormalities in remaining few spermatozoa. While hsf5 mutant female did not show any abnormality. We show that Hsf5 is required for progression through meiotic prophase 1 during spermatogenesis. The hsf5 mutants indeed show misregulation of a substantial number of genes regulating cell cycle, DNA-damage repair, apoptosis and cytoskeleton proteins. We also show that Hsf5 physically binds to majority of these differentially expressed genes, suggesting its direct role in regulating the expression of many genes important for spermatogenesis.

developmental biology↗