Identification of MITF Gene Mutation in Porcupines: A Novel Link to Congenital Deafness and Pigmentation Disorders

doi:10.21203/rs.3.rs-4679701/v1

Download PDF

Article

Identification of MITF Gene Mutation in Porcupines: A Novel Link to Congenital Deafness and Pigmentation Disorders

https://doi.org/10.21203/rs.3.rs-4679701/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Worldwide, congenital deafness and pigmentation disorders impact millions with their diverse manifestations, and among these genetic conditions, mutations in the Microphthalmia-associated transcription factor (MITF: OMIM#156845) gene are notable for their profound effects on melanocyte development and auditory functions. We first discovered congenital deafness in mutant porcupine individuals with abnormal pigmentation among artificially bred porcupines. Their phenotypic characteristics closely resemble those of human Waardenburg Syndrome Type 2 (WS2: OMIM#193510). This study aims to establish a mutant porcupine model family for identifying candidate pathogenic genes and mutation sites, offering insights into the molecular mechanisms of human hereditary deafness. By analyzing coat color, skin, and eyes, we distinguished between different porcupine phenotypes and utilized the auditory brainstem response (ABR) method to examine and identify hearing function. Then, we used Bulk Segregant Analysis (BSA) to identify and locate the target trait genes of porcupines with pigmentary aberrations. We collected auricle skin tissue from wild type porcupines for reference-free transcriptome sequencing, and then annotated and extracted the transcript sequences of candidate genes. Finally, primers based on the identified candidate genes were designed for PCR amplification, followed by verification through Sanger sequencing. Through BSA analysis, we identified a total of 88 SNP and 336 InDel candidate sites. By annotating the MITF gene, we obtained four unique transcript sequences. The SNP and InDel sites within the porcupine MITF gene sequence, identified through BSA screening, were analyzed in conjunction with the gene's annotation results. This analysis revealed a specific mutation site, MITF c.875_877delGAA p. (Arg217del), which was subsequently verified by Sanger sequencing. This study successfully identified a mutant in porcupine that reflects the genetic and phenotypic complexity of human congenital deafness and pigmentation disorders, specifically WS2.

Biological sciences/Computational biology and bioinformatics

Biological sciences/Genetics

Biological sciences/Molecular biology

Biological sciences/Zoology

Health sciences/Diseases

BSA-Seq

RNA-Seq

MITF

Deafness

Porcupines

Deafness, defined by a partial or complete inability to hear, poses a substantial global health issue and is a primary factor in contributing to years lived with disability, negatively impacting overall well-being ^1,2. According to projections by the World Health Organization (WHO), the number of individuals affected by disabling hearing impairment, which stood at 466 million in 2018, is expected to increase to 630 million by 2030 and surpass 900 million by 2050³. Hereditary deafness, often accompanied by pigmentary disorders, represents a unique yet significant group of genetic conditions where the causal connection intertwines pigmentation with auditory function. WS2 serves as a notable example of a human condition uniquely defined by its dual manifestation of hearing loss and distinctive pigmentation irregularities. These irregularities span from hypopigmentation to heterochromia affecting the skin, hair, and iris, presenting a heterogeneous visual profile. The incidence of this syndrome ranges between 1 in 42,000 to 1 in 50,000 individuals, signifying its rarity. Despite this, WS2 significantly contributes to the broader landscape of auditory disorders, accounting for an estimated 2–5% of all cases of congenital deafness in children⁴. Although the precise mechanisms linking pigmentary disorders to deafness remain to be fully clarified, research suggests a significant intersection of the pathways involved in both pigment production and auditory function.

WS2 exhibits a broad spectrum of genetic variability⁵, with most currently identified associated genes having a direct link to melanocyte migration, as well as to the development of neural crest and inner ear cells. Genetic factors underlying the conditions are manifold, with mutations in a cohort of genes including, but not limited to, PAX3, EDNRB, SOX10, and the MITF known to play pivotal roles^6–9. Among these, the gene known as MITF, a member of the MYC superfamily that is mutated in 10–15% of WS2, is renowned as a pivotal regulator that orchestrates the development, functionality, and preservation of melanocytes¹⁰. Given the MITF gene's importance and complexity, studying animal models with mutations in this gene is a crucial approach to elucidate its function and the pathogenesis of related diseases when mutations arise.

The BSA method, also known as population segregation analysis, is primarily employed in genetics for the identification of genes associated with extreme phenotypes. With the evolution of Next-Generation Sequencing (NGS) technologies, BSA is utilized to swiftly identify relevant markers and candidate genes, finding extensive application in the study of plant molecular breeding. For instance, the SLAF-seq and BSA strategy has been utilized for the localization of starch-related candidate genes¹¹, the selection of genes resistant to powdery mildew in wheat¹², and the identification of the main loci controlling leaf thickness in rice¹³.

Our research team discovered the first congenital deafness mutant in porcupines, characterized by abnormal pigmentation, with some mutant individuals displaying typical microphthalmia phenotype characteristics. These characteristics bear phenotypic similarities to human WS2. We speculate that MITF may be the gene causing the disease in this porcupine lineage. Based on the establishment of a mutant porcupine model family, this study first identified its phenotype through coat color, skin, eyes, and hearing. We then used the BSA method combined with transcriptome sequencing to finely locate the pathogenic gene and mutation site and confirmed the mutation using Sanger sequencing.

2.1. Ethical statement

All animal study protocols were conducted in strict adherence to the Ethical Management of Laboratory Animal Welfare standards established by Zunyi Medical University. The animal experiment was approved by the Animal Center of Zunyi Medical University (Approval number: [2016] 2-059) and was carried out in accordance with ARRIVE guidelines.

2.2. Breeding of the Porcupine Family Line

The porcupines used in the experiment were acquired from Muxinyuan Ecological Agriculture Development Co., Ltd., situated in Suiyang County, Zunyi City, Guizhou Province. The facility holds a wild animal breeding license numbered Suidong 2013 Xunfan (010). For the experiment, we utilized 4 heterozygous mutant male porcupines and 8 wild type female porcupines as the F0 generation. These porcupines were paired for breeding in a 1 male to 2 female ratio to establish the family lineage. The offspring, comprising the F1 generation, were initially screened for traits, and those partially showing albino phenotypes in coat, skin, and sclera color were identified as heterozygous mutants. By interbreeding the F1 generation's heterozygous mutant individuals. The offspring of F2 generation were preliminarily screened, and the offspring showing complete albinism in their coat, spines, skin, and sclera, as well as a microphthalmia phenotype were identified as homozygous mutant. A partial genetic pedigree of the porcupine family is shown in Figure 1.

2.3. Collection of Skin and Inner Ear Tissues

Specimens were collected from 3 wild type porcupines, 3 heterozygous mutant porcupines, and 3 homozygous mutant porcupines, which were anesthetized with intramuscular injections of "Su-Mian-Xin," a specialized anesthetic provided by Dunhua Shengda Animal Pharmaceutical Co., Ltd., Dunhua, China, at a dosage of 0.1 ml/kg. Following anesthesia, the subjects were promptly decapitated, and with ear notchers, we excised 2×2 cm sections of auricle skin tissue. We then removed the surface hair with a scalpel and submerged the tissue samples in 4% paraformaldehyde before placing them in a 4°C refrigerator overnight for fixation.

2.4. Histology

The fixed tissues were rinsed in running water for several hours to wash away fixative residues, followed by dehydration through a graded ethanol series (70%, 80% and 90%) to remove moisture. Subsequently, the tissues were cleared in xylene, rendering them transparent and ready for paraffin embedding. The tissue blocks were then sectioned at 4 μm thickness using a microtome. These paraffin sections, placed on glass slides, were deparaffinized in xylene and rehydrated through a descending ethanol series. The sections were sequentially stained with hematoxylin, to target the nuclei, and eosin, to stain the cytoplasm and extracellular components. Following staining, the slides were dehydrated using an ascending ethanol series, cleared in xylene, and then mounted with a xylene-based adhesive under a coverslip. Finally, pigment deposition was observed under a microscope.

2.5. Auditory Brainstem Response (ABR) Assessment

ABR assessments were performed on wild type, heterozygous mutant porcupines and homozygous mutant porcupines using an auditory function tester within a soundproof and shielded room. Silver needle electrodes were utilized where the recording electrode was positioned along the line connecting the vertex of the porcupine's skull to the anterior edge of both ears. The reference electrode was inserted into the earlobe, while the ground electrode was secured at the tip of the snout. Stimulus tones comprised of brief clicks and short pure tones (tone burst) at frequencies of 0.5 kHz, 1 kHz, 4 kHz, 8 kHz, 16 kHz, and 32 kHz. The sound was emitted at a distance of 2 cm from the porcupine's ear, with each acoustic stimulus lasting 4 ms and subjected to a band-pass filter range of 300-3000 Hz. The short-tone stimulus operated at 12.1 beats/s with a duration of 0.1 ms, followed by a 4 ms short tone burst with rise and fall times of 0.5 ms. The evoked response potentials were amplified by a factor of 10,000 across an average of 1024 superimpositions. The apex stimulus sound intensity reached 120 dB SPL and was methodically attenuated from 120 dB SPL in decrements of 10 dB SPL until a consistent ABR waveform could no longer be elicited. The intensity was then increased in increments of 5 dB SPL to determine the threshold, which was defined as the lowest stimulus intensity at which consistent ABR waveforms were perceptible. This process was repeated three times, and the mean value was recorded as the ABR threshold for the porcupine¹⁴.

2.6. DNA Mixing Pool Construction

We constructed two offspring DNA pools based on phenotypic traits, distinguishing them into a heterozygous mutant group and a wild type group, rather than on genetic relationships. The parental generation comprised only one male heterozygous mutant individual. For the mutant group, auricular skin tissue samples were collected from 13 heterozygous mutant porcupines; for the normal group, samples were taken from 18 wild type individuals. Additionally, a sample was collected from one male heterozygous mutant individual. Each sample was placed in an individually labeled, sealed sampling tube. Tissue DNA was extracted using the Genomic DNA Extraction and Detection Kit from Tiangen Biochemical Technology Co., Ltd. (Lot: U9022), following the provided instructions meticulously. The samples were then sent to Beijing Novogene Technology Co., Ltd. for sequencing.

2.7. BSA Library Construction and Sequencing

A total amount of 1.5μg DNA per sample was used as input material for the DNA sample preparations. Sequencing libraries were generated using Truseq Nano DNA HT Sample preparation Kit following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. Briefly, the DNA sample was fragmented by sonication to a size of 350bp, then DNA fragments were end polished, A-tailed, and ligated with the full-length adapter for Illumina sequencing with further PCR amplification. At last, PCR products were purified (AMPure XP system) and libraries were analyzed for size distribution by Agilent2100 Bioanalyzer and quantified using real-time PCR. These libraries constructed above were sequenced by Illumina HiSeq4000 platform and 150bp paired-end reads were generated with insert size around 350bp.

2.8. Mapping to reference genome

We first performed a quality assessment of the raw sequencing data, which included analyzing the error rate distribution and nucleotide content. Then, we removed the adapter sequences and filtered out reads of low quality and those with an N ratio (indicating bases that cannot be determined) greater than 10%. This process yielded clean reads suitable for subsequent analysis. The clean reads are mapped onto the reference genome (Mus musculus) employing the BWA software (Burrows-Wheeler Aligner)¹⁵. Furthermore, the command "rmdup" from SAMtools¹⁶ software is utilized to eliminate possible PCR duplicates. In scenarios where multiple read pairs share identical external coordinates, only the pair exhibiting the highest mapping quality is preserved. The basic information of the reference genome is shown in Table 1.

Table1. Basic information of reference genome.

Seq number	Total length	GC content(%)	Gap rate(%)	N50 length	N90 length
1136598	2,470,917,678	41.52	0.02	64,768	459

2.9. SNP and InDel Detection and Annotation

The variant identification process across all samples was performed using the Genome Analysis Toolkit (GATK) software's Unified Genotyper feature¹⁷. For SNPs, we applied the Variant Filtration parameter within GATK with the following configuration: --filter Expression set to "QD < 4.0 || FS > 60.0 || MQ < 40.0", -G_filter to "GQ<20", and –cluster WindowSize specified as 4.InDels were filtered using Variant Filtration parameters (settings: --filter Expression "QD < 4.0 || FS > 200.0 || Read PosRankSum < -20.0 || Inbreeding Coeff < -0.8"). ANNOVAR¹⁸, an effective software tool, annotated SNPs or InDels based on GFF3 files of the reference genome, given its powerful annotation capabilities and international recognition, so we used it to annotate the results of our assay.

2.10. SNP and InDel Calculations

We used one parent's genotype (1f1) as a reference to statistically analyze the number of reads corresponding to this genotype or others within the offspring pools. This method involves using sequencing reads to enumerate the nucleotides at each genomic position. It then compares these nucleotides to the reference genome. For a given site, we count the reads in the progeny pool that match or differ from the reference genome. The SNP-index is then calculated by dividing the number of differing reads by the total number of reads at that site, providing a measure of variation at that locus. In this context, a completely identical SNP-index equals 0, while a completely different SNP-index equals 1. The calculation of the InDel-index followed a similar methodology to that of the SNP-index.

To mitigate background noise, sequencing and alignment errors, and improve gene positioning efficiency, we meticulously screened and filtered SNP/InDel and SNP/InDel-index data. The screening and filtering process adhered to the following criteria:

1. Screening for markers indicating parental homozygosity within the parent population.

2. Excluding sites with an SNP/InDel-index less than 0.3 and SNP depth below 7 in both offspring groups.

3. Filtering out sites with a missing SNP-index in any offspring group.

2.11. Differential Analysis of SNP and InDel

To visualize the differences between the two offspring pools, the △(SNP-index) = SNP-index (S2)-SNP-index (S1) was calculated. We set the window to 1Mb and the step size to 1kb, calculating the mean value of △(SNP-index) to assess the △(SNP-index) distribution. Alongside the population type and the number of offspring mixing pools, a 1,000 permutation test was conducted¹⁹. The calculation of the △(InDel-index) followed a similar methodology to that of the SNP-index.

2.12. Identify candidate genes based on SNP and InDel

In order not to ignore the influence of micro-effective quantitative trait loci (QTLs), SNP and InDel loci with significant differences in their respective indices between two offspring were selected across the genome. That is, sites where the SNP index or InDel index of offspring 2 are close to 1.0 are selected, and sites where the SNP index or InDel index of offspring 1 are close to 0.0 are selected. For these candidate polymorphic loci, annotation results were extracted using ANNOVAR, prioritizing genes containing loci that resulted in termination loss, termination gain, nonsynonymous mutations, or alternative splicing as candidate genes.

2.13. Transcriptome Sequencing

The auricle skin tissue from adult wild type porcupines was sized, washed thrice with PBS, and then promptly cut, placed into a sampling tube, and stored in liquid nitrogen. This tissue was subsequently sent to Shanghai Zhongke New Life Biotechnology Co., Ltd. for transcriptome sequencing. Total RNA from the sample was extracted using the TRIzol method. After passing the quality test, mRNA was enriched with magnetic beads containing Oligo(dT), and Fragmentation Buffer was added to cleave the mRNA into short fragments of 200-300 bp. The RNA sample was then used as a template to synthesize the first strand of cDNA using 6-base random primers and reverse transcriptase. Subsequently, the second strand of cDNA was synthesized using the first strand as a template. The double-stranded cDNA was purified using AMPure XP beads. This purified double-stranded cDNA underwent end repair, A-tailing, and ligation with sequencing adapters. The fragment size was selected with AMPure XP beads, followed by PCR amplification to generate the final cDNA library. After the insert fragment length and the effective concentration of the library had been tested and met the qualifications, sequencing was performed using the Illumina HiSeq platform. Raw image data procured from Illumina's high-throughput sequencing undergoes base calling with CASAVA, transforming them into sequenced reads.

2.14. Transcript Splicing and MITF gene annotation

The sequencing data were then subjected to quality assessment, including error rate distribution and nucleotide content analysis. Adapter sequences were trimmed, and reads with low quality and undetermined bases (N) were filtered out to obtain clean reads for subsequent analyses²⁰. Using Trinity software, the gold standard for assembling Illumina short-read sequences, we constructed reference sequences from clean reads. This process, comprising the Inchworm, Chrysalis, and Butterfly stages²¹, resulted in the assembled transcript sequences being saved in the FASTA format. Since the porcupine genome sequence has not been annotated, we first annotated the candidate genes for porcupine pathogenicity. In this study, we found that the phenotypic characteristics of the mutant porcupine were very similar to those of human WS2, and the homozygous mutant individuals exhibited typical microphthalmia phenotypic characteristics. We speculate that the pathogenic gene in this porcupine family is likely to be MITF. So we selected MITF as the candidate gene for porcupine pathogenicity and annotated it. We searched for the human MITF gene sequence information on Genbank, then compared the spliced porcupine MITF transcript sequence with the human MITF gene sequence. The region on the porcupine MITF gene with the highest consistency with the human MITF gene exon sequence was defined as the porcupine MITF gene exon region, resulting in the annotation of the porcupine MITF gene.

2.15. Localization of Candidate Mutation Sites in MITF Gene

By comparing the annotation results of the porcupine MITF gene with the candidate mutation sites screened by the BSA method, the mutation site on the MITF gene was accurately located. For further analysis, 23 porcupines from the family were selected, comprising 17 heterozygous mutants and 6 wild types, all of whom provided ear skin tissue samples. After extracting DNA from these samples, we designed specific primers flanking the mutation sites previously identified in the MITF gene. Sanger sequencing, along with co-segregation analysis, confirmed the link between phenotype and genotype. The primer sequences used were as follows: Forward: 5'TTTTCCTGACCTGGGTAACGTTC3' and Reverse: 5'AATCTGTTTGCCAAGGAATCTC3'.

3.1. Animal Phenotype

Wild type porcupines possess a coat, skin, and sclera of a brownish-black color (Figure 2A). In contrast, heterozygous mutant porcupines display albinism in their spines and sclera, alongside large albino patches on their head skin (Figure 2B). Homozygous mutant porcupines exhibit comprehensive albinism encompassing their coat, spines, skin, and sclera, as well as microphthalmia (Figure 2C). Histological evaluation using hematoxylin and eosin (HE) staining of skin tissue sections revealed that the melanin granules in wild type porcupines were prominently located in the basal layer of the epidermis, demonstrating abundant distribution and fullness (Figure 2D). In contrast, the melanin granules in heterozygous mutant phenotype porcupines were sparsely distributed and considerably smaller in size (Figure 2E). Almost no melanin particles are found in homozygous porcupines (Figure 2F).

3.2. ABR Assessment Results

In auditory tests, wild type porcupines produced distinguishable and consistent ABR waveforms across a complete frequency range of 0.5 kHz to 32 kHz, with Wave I cochlear elicitation at an 80 dB threshold (Figure 3A). Conversely, heterozygous and homozygous mutant phenotype porcupines fail to generate recognizable ABR waveforms at any frequency, even at a maximum sound pressure of 120 dB (Figure 3B, Figure 3C).

3.3. Quality Of Sequencing Data

This BSA sequencing run generated a total of 157.524G of Raw data, and after filtering, 156.833G of clean data were obtained. The Raw data for each sample ranged between 49723.477 M and 56402.203 M, with high sequencing quality (Q20 ≥ 96.34%, Q30 ≥ 90.99%) and a GC content between 42.35% and 43.39% (Supplementary Table 1). By comparing the reads to the reference genome, the alignment rate for all samples is observed to range between 98.61% and 99.52%. The average coverage depth of the reference genome spans from 15.77X to 18.74X, with coverage at 1X exceeding 92.94% and coverage at 4X exceeding 88.55%. These alignment results are within normal parameters and are suitable for subsequent variant detection and related analyses (Table 2). The sequencing depth distribution is shown in Supplementary Figure 1.

Table 2. Sequencing depth and coverage statistics.

Sample	Mapped reads	Total reads	Mapping rate (%)	Average depth(X)	Coverage 1X (%)	Coverage 4X (%)
HW	338,556,232	340,194,094	99.52	16.84	93.17	88.98
1f1	369,318,600	374,511,424	98.61	18.74	93.37	89.29
HM	326,543,562	330,850,344	98.70	15.77	92.94	88.55

Note: 1f1: Parent pool; HM: Mutant pool; HW: Wild pool.

3.4. SNP and InDel site statistics

Samtools software was utilized to identify sample loci, yielding a total of 30,931,493 SNP and 3,357,842 InDel sites. ANNOVAR was employed for annotating the detection results, resulting in 22,901,283 conversion SNP sites, 8,030,156 transversion SNP sites, 1,498,425 insertion InDel sites, and 1,859,417 deletion InDel sites (Table 3).

Table 3. Statistics of SNP and InDel detection and annotation results.

Category	Number of SNP	Number of Indel
Transitions	22,901,283	/
Transversions	8,030,156	/
Transitions/ Transversions	2.851	/
Total	30,931,439	/
Insertion	/	1,498,425
Deletion	/	1,859,417
Total	/	3,357,842

3.5. SNP and InDel Index Distribution

To minimize background noise and sequencing errors, SNP-index and InDel-index filtering was applied, to yield 5,225,858 SNP and 433,134 InDel polymorphic marker sites. The distribution of these sites across chromosomes was mapped with a window size of 1Mb and step size of 1kb, calculating average SNP and InDel index values per window (Figure 4). This analysis provides a comprehensive overview of the distribution of SNP, InDel, and the combined all-index across the genome in offspring pools.

3.6. Differential Analysis of SNP/InDel Index

We also chose 1Mb as the window and 1kb as the step size, and calculated the average value of ∆(SNP/InDel-index) in each window to reflect the ∆(SNP/InDel-index) distribution. Differential chromosome indices illustrate the variance in SNP (Figure 5A), InDel indices (Figure 5B). A total of 3,797 SNP and 545 InDel sites were identified with a confidence level of 95% and 99% respectively after performing a permutation test.

3.7. Candidate Polymorphic Marker Sites

Based on ANNOVAR annotation results, we identified candidate genes at loci associated with stop loss, stop gain, non-synonymous mutations, or alternative splicing. A total of 424 polymorphic markers were identified, including 88 SNP candidates and 336 InDel candidates (Table 4).

Table 4. Candidate SNP and InDel polymorphic marker sites.

Category	Number of SNP	Number of Indel
transitions	73	/
transversions	15	/
Transitions/ Transversions	4.867	/
Total	88	/
Insertion	/	40
Deletion	/	296
Total	/	336

3.8. Illumina sequencing and de novo transcriptome assembly

We obtained approximately 6G of raw data through Illumina high-throughput sequencing, and the summary statistics are shown in Table 5. Using Trinity software to assemble high-quality reads de novo, the length of the obtained transcripts ranged from 180 to 27,668 bp, with an average length of 973 bp and an N50 of 2,186 bp. For intuitive representation, the results were displayed as bar charts, showcasing the length distribution of transcripts and unigene sequences (Supplementary Figure 2).

Table 5. Summary of data quality of each sample.

Sample	Raw reads	Clean reads	Clean bases	Q20(%)	Q30(%)	GC(%)
etw	43640370	43104906	6G	97.69	93.24	47.11

3.9. MITF mutation site screening

Based on the reference-free transcriptome sequencing library, we extracted a total of 4 non-repetitive porcupine MITF gene transcripts (uploaded to GenBank, accession numbers: MW840376, MW840377, MW840378, and MW840379). We analyzed the human MITF-M transcript isoform (NM_198158) included in the GenBank database, which contains a total of 9 exons, and compared the 4 porcupine transcripts with these exons. The comparison exhibited a similarity above 98% except for exons 2 and 6. Comparison of exon lengths between porcupine and human MITF-M transcript isoforms is shown in Supplementary Table 2. Through BLAST alignment, the porcupine MITF gene was located in the reference genome fragment PVJO010006423.1. Based on the experimental results of the BSA method, SNP and InDel sites on the PVJO010006423.1 fragment were searched, and 0 SNP and 7 InDel sites were screened. The MITF regions where these InDel sites are located were annotated (Table 6). As can be seen from Table 6, only the deletion mutation of three bases (TTC) at position 77566 on the PVJO010006423.1 fragment is in the exon region.

Table 6. InDel site information within the MITF gene region.

CHROM & POS	REF & ALT	INTRON or EXSON
PVJO010006423.1_66182	CAGTTAGT_CAGT	INTRON 4
PVJO010006423.1_67123	TAAAAA_TAAAA	INTRON 4
PVJO010006423.1_67869	TG_TGG	INTRON 4
PVJO010006423.1_68013	GCTTTCT_GCT	INTRON 5
PVJO010006423.1_68030	GTCTCTCTCTCTCTC_GTCTC	INTRON 5
PVJO010006423.1_77566	ATCTTCTTCTTC_ATCTTCTTC	EXSON 7
PVJO010006423.1_88250	TAAAAA_TAA	INTRON8

3.10. Sanger Sequencing Validation

Sanger sequencing of 23 individuals (17 heterozygous mutants and 6 wild types) confirmed this deletion, with mutant individuals lacking GAA at the locus and exhibiting a double peak, indicative of a heterozygous pattern (Figure 6). By querying the human deafness-related gene mutation database at http://grenada.lumc.nl/LOVD3/WS, we compared the mutation site of the MITF gene identified in the albino deaf porcupine in this study. The results showed that the mutation site of the MITF gene in the albino deaf porcupine was consistent with the arginine deletion at position 217 (MITF-M R217del) in the nuclear localization signal (NLS) region of the human MITF-M. The mutation base site was MITF c.875_877delGAA p. (Arg217del).

Congenital deafness and pigmentary abnormalities represent significant global health challenges, impacting the quality of life for millions ¹. The MITF gene, crucial for melanocyte development and auditory function, has become a key focus area in the scientific community. WS2, which is characterized by deafness and pigmentary abnormalities, is often caused by mutations in the MITF gene²². This study accurately identified the pathogenic gene and mutation site in the porcupine model of spontaneous dyschromatosis deafness as MITF c.875_877delGAA p. (Arg217del). This mutation, consistent with the arginine deletion at position 217 within the NLS region of the nuclear localization signal of human MITF-M (R217del).

Utilizing BSA-seq together with RNA-seq has been validated as an efficient approach for detailed gene mapping²³. In this effort, we generated 156.833G of clean data via BSA sequencing, achieving high sequencing quality as indicated by Q20 values over 96.34% and Q30 values exceeding 90.99%. This highlights the sequencing process's efficiency and quality. A maximum mapping rate of 99.52% alongside substantial average genome coverage underscores the comprehensive genomic coverage obtained, assuring the dependability of further variant identification and analyses. By conducting SNP/InDel analysis complemented with ANNOVAR annotation, we pinpointed 424 polymorphic markers at loci linked to termination loss, gain, non-synonymous mutations, or alternative splicing, comprising 88 SNP and 336 InDel candidate markers. Observing the similar phenotypic traits between homozygous mutant porcupines and humans afflicted with WS2, we honed in on the MITF gene as our targeted gene. Employing de novo transcriptome sequencing on wild type porcupines allowed for the extraction and successful annotation of the MITF gene transcript. Through Blast alignment, we positioned the porcupine’s MITF gene within the reference genome segment PVJO010006423.1. Leveraging BSA-seq outcomes, we filtered down to 7 InDel sites, with just a single InDel situated within an exon. Primers specific to this exon were designed, PCR amplified, and Sanger sequencing corroborated the absence of GAA at this site. At present, the genetic landscapes of certain experimental animals (such as tree shrews, gerbils, Eastern European voles) and specific breeds (such as foxes, sika deer, bamboo rats) remain opaque, presenting challenges to annotation efforts. Conventional methodologies aimed at pinpointing genes associated with specific traits in these entities may face hurdles. This investigation, through the integration of BSA-seq and RNA-seq approaches, successfully identified the disease-causing gene linked to autosomal dominant pigmentary dyschromatosis syndrome-type deafness in porcupines. This accomplishment provides a valuable reference for uncovering pathogenic genes within distinctive animal species.

The porcupine model of spontaneous dyschromatosis deafness represents a valuable addition to the current repertoire of animal models for WS2. Currently, more than 400 animal models of hereditary deafness have been reported, mainly including small rodents such as mice and guinea pigs. From Paula Hertwig's²⁴ discovery of the first MITF mutant mouse in 1942 to the construction of MITF+/− gene knockout mice by Shuxian Han²⁵ through genetic engineering, mice have made substantial contributions to the study of MITF gene function. However, employing mice for research into deafness-related diseases inevitably faces limitations. Although the auditory structure of mice shares a certain degree of similarity with humans, their auditory system requires postnatal development to reach full maturity, diverging significantly from that of humans²⁶. Consequently, certain diseases related to inner ear development cannot be replicated in mouse models²⁷. The current big animal models for hereditary deafness are quite lacking. Ning Li²⁸ has developed a porcine model of Vitiligo-deafness with MITF mutations, which holds considerable application potential for the development of otological techniques and clinical translational research. However, the model exhibits recessive inheritance, and the mutation sites have not been reported in human cases of WS. The MITF c.875_877delGAA p. (Arg217del) mutant deafness porcupine model family identified in this study provides important tools and materials for studying the pathogenic mechanism, clinical treatment and medical device evaluation of the corresponding human hereditary deafness.

This study successfully established a porcupine family with spontaneous pigmentary abnormality syndrome type deafness; phenotypic identification showed that the phenotypic characteristics of this model are very similar to the disease manifestations of human WS2; at the same time, the pathogenic gene and mutation site were accurately identified as MITF c.875_877delGAA p. (Arg217del). The research results can provide a theoretical basis and reference for studying the molecular pathogenic mechanism of the corresponding human hereditary deafness disease.

BSA: Bulked Sergeant Analysis

InDel: Insertion-Deletion

MITF: Microphthalmia-Associated Transcription Factor

SNP: Single Nucleotide Polymorphism

WS: Waardenburg Syndrome

Consent for publication: Not applicable.

Availability of data and material: The data that support the findings of this study are available on request from the corresponding author, [SZ], upon reasonable request.

Competing interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Funding: This study was supported by the National Natural Science Foundation of China (No. 81660176) for their support.

Authors' contributions: KL: Writing – review, editing; CH: Data accessibility; HL: Bioinformatics-related data analysis; KT: Experimental porcupine feeding management, animal experiment operation; SZ: Experimental design, data analysis.

Acknowledgments: We are grateful for the BSA sequencing services provided by Beijing Novogene Technology Co., Ltd. We also thank Shanghai Zhongke New Life Biotechnology Co., Ltd. for their transcriptome sequencing services.

Olusanya, B. O., Neumann, K. J. & Saunders, J. E. The global burden of disabling hearing impairment: a call to action. Bull World Health Organ 92, 367–373 (2014).
GBD 2017 Disease and Injury Incidence and Prevalence Collaborators. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet 392, 1789–1858 (2018).
Chadha, S. & Cieza, A. World Health Organization and Its Initiative for Ear and Hearing Care. Otolaryngol Clin North Am 51, 535–542 (2018).
Rawlani, S. M., Ramtake, R., Dhabarde, A. & Rawlani, S. S. Waardenburg syndrome: A rare case. Oman J Ophthalmol 11, 158–160 (2018).
Lee, C.-Y. et al. Identification of nine novel variants across PAX3, SOX10, EDNRB, and MITF genes in Waardenburg syndrome with next-generation sequencing. Mol Genet Genomic Med 10, e2082 (2022).
Boudjadi, S., Chatterjee, B., Sun, W., Vemu, P. & Barr, F. G. The expression and function of PAX3 in development and disease. Gene 666, 145–157 (2018).
Issa, S. et al. EDNRB mutations cause Waardenburg syndrome type II in the heterozygous state. Hum Mutat 38, 581–593 (2017).
Yu, Y. et al. Two novel mutations of PAX3 and SOX10 were characterized as genetic causes of Waardenburg Syndrome. Mol Genet Genomic Med 8, e1217 (2020).
Yang, T. et al. Double heterozygous mutations of MITF and PAX3 result in Waardenburg syndrome with increased penetrance in pigmentary defects. Clin Genet 83, 78–82 (2013).
Pogenberg, V. et al. Restricted leucine zipper dimerization and specificity of DNA recognition of the melanocyte master regulator MITF. Genes Dev 26, 2647–2658 (2012).
Geng, X. et al. Rapid Identification of Candidate Genes for Seed Weight Using the SLAF-Seq Method in Brassica napus. PLoS One 11, e0147580 (2016).
Tan, C., Li, G., Cowger, C., Carver, B. F. & Xu, X. Characterization of Pm59, a novel powdery mildew resistance gene in Afghanistan wheat landrace PI 181356. Theor Appl Genet 131, 1145–1152 (2018).
Chen, D.-G. et al. Fine-mapping and candidate gene analysis of a major locus controlling leaf thickness in rice (Oryza sativa L.). Mol Breed 42, 6 (2022).
Liberman, M. C. et al. Prestin is required for electromotility of the outer hair cell and for the cochlear amplifier. Nature 419, 300–304 (2002).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
The Sequence Alignment/Map format and SAMtools - PubMed. https://pubmed.ncbi.nlm.nih.gov/19505943/.
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 20, 1297–1303 (2010).
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res 38, e164 (2010).
Takagi, H. et al. QTL-seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations. Plant J 74, 174–183 (2013).
Kechin, A., Boyarskikh, U., Kel, A. & Filipenko, M. cutPrimers: A New Tool for Accurate Cutting of Primers from Reads of Targeted Next Generation Sequencing. J Comput Biol 24, 1138–1143 (2017).
Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc 8, 1494–1512 (2013).
Tassabehji, M., Newton, V. E. & Read, A. P. Waardenburg syndrome type 2 caused by mutations in the human microphthalmia (MITF) gene. Nat Genet 8, 251–255 (1994).
Ye, S. et al. Combined BSA-Seq Based Mapping and RNA-Seq Profiling Reveal Candidate Genes Associated with Plant Architecture in Brassica napus. Int J Mol Sci 23, 2472 (2022).
Vazquez, F. et al. PGC1α expression defines a subset of human melanoma tumors with increased mitochondrial capacity and resistance to oxidative stress. Cancer Cell 23, 287–301 (2013).
Ronai, Z. The masters talk: the PGC-1α-MITF axis as a melanoma energizer. Pigment Cell Melanoma Res (2013) doi:10.1111/pcmr.12090.
Ploper, D. & De Robertis, E. M. The MITF family of transcription factors: Role in endolysosomal biogenesis, Wnt signaling, and oncogenesis. Pharmacol Res 99, 36–43 (2015).
Ploper, D. et al. MITF drives endolysosomal biogenesis and potentiates Wnt signaling in melanoma cells. Proc Natl Acad Sci U S A 112, E420-429 (2015).
Wu, M. et al. c-Kit triggers dual phosphorylations, which couple activation and degradation of the essential melanocyte factor Mi. Genes Dev 14, 301–312 (2000).

No competing interests reported.

SupplementaryFigureandTable.zip

Download PDF

Reviewers agreed at journal
11 Sep, 2024
Reviews received at journal
04 Sep, 2024
Reviewers agreed at journal
15 Aug, 2024
Reviewers invited by journal
13 Aug, 2024
Editor assigned by journal
06 Aug, 2024
Editor invited by journal
05 Aug, 2024
Submission checks completed at journal
30 Jul, 2024
First submitted to journal
03 Jul, 2024

You are reading this latest preprint version

Identification of MITF Gene Mutation in Porcupines: A Novel Link to Congenital Deafness and Pigmentation Disorders

Status:

Version 1

Abstract

Figures

1. Introduction

2. Materials and Methods

3. Results

4. Discussion

5. Conclusions

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1