Thousands of induced germline mutations affecting immune cells identified by automated meiotic mapping coupled with machine learning.

Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the identification of mutations causing immune phenotypes in mice by creating Candidate Explorer (CE), a machine-learning software program that integrates 67 features of genetic mapping data into a single numeric score, mathematically convertible to the probability of verification of any putative mutation-phenotype association. At this time, CE has evaluated putative mutation-phenotype associations arising from screening damaging mutations in ∼55% of mouse genes for effects on flow cytometry measurements of immune cells in the blood. CE has therefore identified more than half of genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

GABAA receptors contribute more to rate than temporal coding in the IC of awake mice.

Speech is our most important form of communication, yet we have a poor understanding of how communication sounds are processed by the brain. Mice make great model organisms to study neural processing of communication sounds because of their rich repertoire of social vocalizations and because they have brain structures analogous to humans, such as the auditory midbrain nucleus inferior colliculus (IC). Although the combined roles of GABAergic and glycinergic inhibition on vocalization selectivity in the IC have been studied to a limited degree, the discrete contributions of GABAergic inhibition have only rarely been examined. In this study, we examined how GABAergic inhibition contributes to shaping responses to pure tones as well as selectivity to complex sounds in the IC of awake mice. In our set of long-latency neurons, we found that GABAergic inhibition extends the evoked firing rate range of IC neurons by lowering the baseline firing rate but maintaining the highest probability of firing rate. GABAergic inhibition also prevented IC neurons from bursting in a spontaneous state. Finally, we found that although GABAergic inhibition shaped the spectrotemporal response to vocalizations in a nonlinear fashion, it did not affect the neural code needed to discriminate vocalizations, based either on spiking patterns or on firing rate. Overall, our results emphasize that even if GABAergic inhibition generally decreases the firing rate, it does so while maintaining or extending the abilities of neurons in the IC to code the wide variety of sounds that mammals are exposed to in their daily lives.NEW & NOTEWORTHY GABAergic inhibition adds nonlinearity to neuronal response curves. This increases the neuronal range of evoked firing rate by reducing baseline firing. GABAergic inhibition prevents bursting responses from neurons in a spontaneous state, reducing noise in the temporal coding of the neuron. This could result in improved signal transmission to the cortex.

SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples.

Advances in single-cell RNA sequencing (scRNA-Seq) have allowed for comprehensive analyses of single cell data. However, current analyses of scRNA-Seq data usually start from unsupervised clustering or visualization. These methods ignore prior knowledge of transcriptomes and the probable structures of the data. Moreover, cell identification heavily relies on subjective and possibly inaccurate human inspection afterwards. To address these analytical challenges, we developed SCINA (Semi-supervised Category Identification and Assignment), a semi-supervised model that exploits previously established gene signatures using an expectation-maximization (EM) algorithm. SCINA is applicable to scRNA-Seq and flow cytometry/CyTOF data, as well as other data of similar format. We applied SCINA to a wide range of datasets, and showed its accuracy, stability and efficiency, which exceeded most popular unsupervised approaches. SCINA discovered an intermediate stage of oligodendrocytes from mouse brain scRNA-Seq data. SCINA also detected immune cell population changes in cytometry data in a genetically-engineered mouse model. Furthermore, SCINA performed well with bulk gene expression data. Specifically, we identified a new kidney tumor clade with similarity to FH-deficient tumors (FHD), which we refer to as FHD-like tumors (FHDL). Overall, SCINA provides both methodological advances and biological insights from perspectives different from traditional analytical methods.

Mice produce ultrasonic vocalizations by intra-laryngeal planar impinging jets.

Rodent ultrasonic vocalizations (USVs) are a vital tool for linking gene mutations to behavior in mouse models of communication disorders, such as autism [1]. However, we currently lack an understanding of how physiological and physical mechanisms combine to generate acoustic features of the vocalizations, and thus cannot meaningfully relate those features to experimental treatments. Here we test and provide evidence against the two leading hypotheses explaining USV production: superficial vocal fold vibrations [2], and a hole-tone whistle [3]. Instead, we propose and provide theoretical and experimental evidence for an alternative and novel vocal production mechanism: a glottal jet impinging onto the laryngeal inner planar wall. Our data provide a framework for future research on the neuromuscular control of mouse vocal production and for interpreting mouse vocal behavior phenotypes.

16p11.2 Deletion Syndrome Mice Display Sensory and Ultrasonic Vocalization Deficits During Social Interactions.

Recurrent deletions and duplications at chromosomal region 16p11.2 are variably associated with speech delay, autism spectrum disorder, developmental delay, schizophrenia, and cognitive impairments. Social communication deficits are a primary diagnostic symptom of autism. Here we investigated ultrasonic vocalizations (USVs) in young adult male 16p11.2 deletion mice during a novel three-phase male-female social interaction test that detects vocalizations emitted by a male in the presence of an estrous female, how the male changes its calling when the female is suddenly absent, and the extent to which calls resume when the female returns. Strikingly fewer vocalizations were detected in two independent cohorts of 16p11.2 heterozygous deletion males (+/-) during the first exposure to an unfamiliar estrous female, as compared to wildtype littermates (+/+). When the female was removed, +/+ emitted calls, but at a much lower level, whereas +/- males called minimally. Sensory and motor abnormalities were detected in +/-, including higher nociceptive thresholds, a complete absence of acoustic startle responses, and hearing loss in all +/- as confirmed by lack of auditory brainstem responses to frequencies between 8 and 100 kHz. Stereotyped circling and backflipping appeared in a small percentage of individuals, as previously reported. However, these sensory and motor phenotypes could not directly explain the low vocalizations in 16p11.2 deletion mice, since (a) +/- males displayed normal abilities to emit vocalizations when the female was subsequently reintroduced, and (b) +/- vocalized less than +/+ to social odor cues delivered on an inanimate cotton swab. Our findings support the concept that mouse USVs in social settings represent a response to social cues, and that 16p11.2 deletion mice are deficient in their initial USVs responses to novel social cues.

Engineered deafness reveals that mouse courtship vocalizations do not require auditory experience.

Auditory experience during development is necessary for normal language acquisition in humans. Although songbirds, some cetaceans, and maybe bats may also be vocal learners, vocal learning has yet to be well established for a laboratory mammal. Mice are potentially an excellent model organism for studying mechanisms underlying vocal communication. Mice vocalize in different social contexts, yet whether they learn their vocalizations remains unresolved. To address this question, we compared ultrasonic courtship vocalizations emitted by chronically deaf and normal hearing adult male mice. We deafened CBA/CaJ male mice, engineered to express diphtheria toxin (DT) receptors in hair cells, by systemic injection of DT at postnatal day 2 (P2). By P9, almost all inner hair cells were absent and by P16 all inner and outer hair cells were absent in DTR mice. These mice did not show any auditory brainstem responses as adults. Wild-type littermates, also treated with DT at P2, had normal hair cells and normal auditory brainstem responses. We compared the temporal structure of vocalization bouts, the types of vocalizations, the patterns of syllables, and the acoustic features of each syllable type emitted by hearing and deaf males in the presence of a female. We found that almost all of the vocalization features we examined were similar in hearing and deaf animals. These findings indicate that mice do not need auditory experience during development to produce normal ultrasonic vocalizations in adulthood. We conclude that mouse courtship vocalizations are not acquired through auditory feedback-dependent learning.