WO2016201272A1

WO2016201272A1 - Method of diagnosing patients with conditions caused by mendelian mutations

Info

Publication number: WO2016201272A1
Application number: PCT/US2016/036953
Authority: WO
Inventors: Sultan Turki AL-SEDAIRY
Original assignee: King Abdulaziz City For Science And Technology
Priority date: 2015-06-12
Filing date: 2016-06-10
Publication date: 2016-12-15

Abstract

The method of diagnosing patients with conditions caused by Mendelian mutations is a genetic panel-based diagnostic method for determining if a patient has a condition (or a proclivity for a condition) based on detection of one or more specific genetic markers. A sample is first obtained from a patient and the sample is assayed to determine the presence of at least one genetic marker. The assay is a sequencing-based multiplexing assay designed for the detection of specific Mendelian mutations. The patient is then diagnosed with a particular condition (or with a proclivity for that condition) if the at least one genetic marker is detected.

Description

METHOD OF DIAGNOSING PATIENTS WITH CONDITIONS CAUSED

BY MENDELIAN MUTATIONS

SEQUENCE LISTING

This application hereby incorporates by reference the Sequence Listing submitted herewith in the file titled "32550_10_Sequence_Listing_Final_ST25.txt" created on June 12, 2015 and having a file size of 67,043 KB.

TECHNICAL FIELD

The present invention relates to genetic detection of conditions, and particularly to a method for diagnosing patients with conditions caused by Mendelian mutations, or diagnosing such patients as having a proclivity towards developing such conditions.

BACKGROUND ART

Genomics have ushered in a new era for clinical medicine. The ability to scan the entire genome (or its coding part) for disease causing mutations relatively free of clinical bias has uncovered the limited sensitivity and specificity of making diagnoses on clinical grounds only. This was first apparent with the advent of array-CGH that specifically targets large genomic mutations. Subsequently, whole genome sequencing (WGS) and whole exome sequencing (WES) confirmed the same pattern. This raises the interesting question of whether all patients with a suspected genetic diagnosis should have WGS/WES as the initial diagnostic test. Pending data on the validity of this approach, one has to consider some practical challenges. Cost remains a significant hurdle that prevents most patients, especially in less wealthy countries, from accessing WGS/WES. While the running cost will continue to decrease, the challenge of identifying a single causal variant from among tens of thousands will remain formidable for the foreseeable future. In addition, debate still rages over the issue of incidental findings with changing guidelines reflective of the strong and sound argument made by camps on either side of the debate, especially in pediatrics. Gene panels that specifically target a disease relevant to the patient' s presentation appear to address some of these limitations but suffer from lack of uniformity in design and are typically too focused on a particular phenotype that they may miss atypical presentation. This is a particular issue when it comes to Mendelian mutations, which are single-gene mutations which may result in a wide variety of disorders. It would obviously be desirable to be able to develop an assay that addresses these limitations. Thus, a method of diagnosing patients with conditions caused by Mendelian mutations solving the aforementioned problems is desired.

DISCLOSURE OF INVENTION

The method of diagnosing patients with conditions caused by Mendelian mutations (Mendelian disease) is a genetic panel-based diagnostic method for determining if a patient has a condition (or a proclivity for a condition) based on detection of one or more specific genetic markers. A sample is first obtained from a patient and the sample is assayed to determine the presence of at least one genetic marker. The assay is a sequencing-based multiplexing assay designed for the detection of specific Mendelian mutations (the set of which are referred to herein as the "Mendeliome"). The patient is then diagnosed with a particular condition (or with a proclivity for that condition) if the at least one genetic marker is detected.

For detection of cardiovascular disease (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of TTR, MYPN, TTN, COL4A3, KCNH2, SMAD4, NOTCH1, ANK2, PKP2, LDB3, MYH6, MYBPC3, SCN5A, MYL3,

CACNA1C, DMD, BAG3, EHMT1, DSG2, ABCC9, KCNE2, RYR2, TTN, TTN-AS1,

VCL, SOS1, ANKRD1, ACTN2, DSP, FBN1, CHD7, and combinations thereof.

For detection of deafness (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of UBIAD1, LARS2, GJB2, HGF, MY06, PCDH15, TMCl, MARVELD2, CDH23, OTOF, LRTOMT, LOXHDl, EDN3, MY015A, SLC26A4,

CLDN14, MARVELD2, WFSl, POU4F3, PTPRQ, SCARF2, COL4A4, USH2A, MY07A, and combinations thereof.

For detection of dermatological conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of XPC, COL7A1, ALDH3A2, SLC39A4, CTSC, ITGB4, TGM1, HPS1, TYR, LAMB 3, EOGT, DOCK6, LAMC2,

GORAB, KRT5, KRT83, COL18A1, ALDH18A1, FERMT1, EOGT, DCAF17, DSP, NF1, and combinations thereof.

For detection of dysmorphia-dysplasia (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of LIFR, TCOF1, LARP7, EVC, POC1A, HGSNAT, COL2A1, CRTAP, COL11A2, DYM, COL1A1, CREBBP, COL11A1,

PYCR1, NIPBL, ROR2, EXT1, ACTB, ADAMTSL2, NEK1, DYNC2H1, IRF6, NSD1,

UBE3B, DLL3, EP300, SGSH, EZH2, CHRNG, GALNS, MGAT2, TNFRSF11B, LMNA, ERCC8, CANT1, MMP2, FKBP10, CUL7, GNPAT, FGFR2, FGFR3, MASP1, FREM1, HSPG2, MEOX1, OBSL1, WNT1, COL1A2, COL1A1, ANTXR2, PEX13, ECEL1, KMT2A, KMT2D, PCNT, EBP, UBRl, WISP3, DLX5, IFT122, HRAS, SERPINFl, RIPK4, LEPRE1, BRAF, NFIX, FBN1, NF1, TMEM67, COLEC11, SCARF2, and combinations thereof.

For detection of endocrine conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of TBCE, GHR, GHRHR, BBS5, SHOX and combinations thereof.

For detection of gastrointestinal conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of UGT1A1, UGT1A10, UGT1A3,

UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, JAGl, BAAT, ATP7B, TJP2, EPCAM, ABCB4, ABCC2, LRBA, SLC10A2, ABCB11, VIPAS39, FAH, G6PC and combinations thereof.

For detection of hematological conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of BLM, FANCA, FANCM, BRCA2, ASXL1 and combinations thereof.

For detection of inborn errors of metabolism (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of L2HGDH, MCCC2, SLC37A4, ARSB, HSD3B7, DBT, PHKG2, BTD, MUT, ASL, DPAGT1, ASAH1, AMT, BCKDHB, BCKDHA, CBS, PAH, CLN8, GBA, ACADM, SLC3A1, MMACHC, PTS, GNS, GCDH, SLC22A5, GAA, MMADHC, PYGL, ASS1, CPS1, H6PD, PTS, PGM1, IVD, ARG1, ASAH1, GLB1, OXCT1, OPLAH, FAH, G6PC, PEX1 and combinations thereof.

For detection of neurological disorders (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of L1CAM, ABCD1, DYSF, GBA2, TRAPPC9, CYP2U1, PANK2, ARL13B, KIF7, ERLIN2, PSAP, VAPB, FKTN, PLP1, GDAP1, ASPM, LAMA2, MECP2, CDK5RAP2, WDR81, ABAT, NDE1, WDR45B, HSD17B4, HEXA, SPG11, PDGFRB, HUWE1, SLC25A19, ARHGEF6, ADRA2B, RELN, CENPJ, ARL14EP, PHGDH, ARID IB, WNK1, SEPN1, RNASEH2C, RNASEH2B, CYP27A1, ATN1, AHI1, STXBP1, CDKL5, MED23, ISPD, CEP57, AGRN, FKRP, ADCK3, SCN2A, MFSD8, TYMP, FLVCR2, SPG20, CACNA1G, PLA2G6, CLN6,

WDR62, PEX26, KIF1A, PNPO, LARGE, YARS, KIAA0196, CCDC88C, OPTN, OCLN, ATRX, ATL1, GNE, PEX12, SPTBN2, PEX16, COL6A1, COL6A3, COL6A2, HEPACAM, LRPPRC, RYR1, NTRK1, CAPN3, SOD1, COG6, ATP2B3, DPYD, TUBA1A, TCTN1, CPA6, ABHD12, NPC2, MPDZ, SYNGAP1, PEX5, PEX6, POMT1, POMT2, MCPH1, CASC5, SGCB, SGCA, POMGNT2, TRMTl, ARFGEF2, SYNE2, ADK, ZNF526, FOXGl, ALS2, C5orf42, TMEM237, C12orf57, TMEM67, PEX1 and combinations thereof.

For detection of pelvic inflammatory disease (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of IL7R, JAK3, CD40LG, AK2, DCLREIC, CD40, AICDA, MLPH, NHEJl, RAB27A, RAG2, RAGl, BTK, ATM, LYST, CYBB, AIRE, DOCK8, SLC17A5, STAT3, WAS, CD247, DNMT3B, FLG, NCF2, ADA, RFXANK, PTPRC, COLEC11 and combinations thereof.

For detection of pulmonary conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of SFTPB, CFTR and combinations thereof.

For detection of renal conditions (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of IQCB1, COL4A6, NPHP3, SLC4A4, DDX39A, SMARCALl, PKHDl, LAMB2, NEK8, NPHP4, FRASl, XDH, MKSl, FANl, TCTN2, NPHS1, CC2D2A, TMEM231, UPK3A, CEP290, NPHP4, COL4A4, TMEM67, C5orf42, TMEM237 and combinations thereof.

For detection of vision disorders (or the proclivity therefor), the at least one genetic marker is selected from the group consisting of ALMS1, CRB1, CHST6, CRYBA1, PRSS56, GUCY2D, SNRNP200, PDE6C, CNGA3, C8orf37, ABCA4, BBS 10, CERKL, GPR125, NHS, LTBP2, GCNT2, RLBP1, MIP, RP1L1, CHM, EYS, TULP1, IGFBP7, CYP1B1, LRAT, MERTK, CNNM4, RP1, RP2, LCA5, MFRP, CNGB1, CACNA1F,

KCNV2, CRX, PROM1, TRPM1, PAX6, IMPG2, CDHR1, GPR179, CRYGC, CRYGD, NMNATl, GALT, ARL6, LRP5, WDR19, SLC4A11, GDF3, SLC16A12, RGS9, RDH12, ADAM9, AIPL1, FAM161A, RPGRIP1, RAB3GAP2, RAB3GAP1, EFEMP1, BEST1, RPE65, EPHA2, FZD4, PRPH2, CRYAA, KCNJ13, NR2E3, BBS9, BBS1, BBS2, BBS5, BBS4, BBS7, SPATA7, CHD7, USH2A, MY07A, C12orf57, CEP290, NPHP4 and combinations thereof.

These and other features of the present invention will become readily apparent upon further review of the following specification.

BEST MODES FOR CARRYING OUT THE INVENTION

The method of diagnosing patients with conditions caused by Mendelian mutations is a genetic panel-based diagnostic method for determining if a patient has a condition (or a proclivity for a condition) based on detection of one or more specific genetic markers. A sample is first obtained from a patient and the sample is assayed to determine the presence of at least one genetic marker. The assay is a sequencing-based multiplexing assay designed for the detection of specific Mendelian mutations (the set of which are referred to herein as the "Mendeliome"). The patient is then diagnosed with a particular condition (or with a proclivity for that condition) if the at least one genetic marker is detected.

For detection of cardiovascular disease (or the proclivity therefor), the at least one genetic marker can be at least one of TTR, MYPN, TTN, COL4A3, KCNH2, SMAD4, NOTCH1, ANK2, PKP2, LDB3, MYH6, MYBPC3, SCN5A, MYL3, CACNA1C, DMD, BAG3, EHMTl, DSG2, ABCC9, KCNE2, RYR2, TTN, TTN-ASl, VCL, SOSl, ANKRDl, ACTN2, DSP, FBN1, CHD7. The details of the cardiovascular panel are given below in Table 1.

Table 1 : Cardiovascular Panel

Number

Gene Chr Start End Transcript of Exons MIM

TTR chrl8 29171729 29178986 NM_000371 4 176300

MYPN chr 10 69869189 69971773 NM_001256268 24 608517

TTN chr2 179390716 179672150 NM_001267550 363 188840

COL4A3 chr2 228029280 228179508 NM_000091 52 120070

KCNH2 chr7 150642043 150675402 NM_000238 15 152427

SMAD4 chrl8 48556582 48611411 NM_005359 12 600993

NOTCH 1 chr9 139388895 139440238 NM_017617 34 190198

ANK2 chr4 113970784 114304896 NM_001148 46 106410

PKP2 chr 12 32943679 33049780 NM_004572 14 602861

LDB3 chr 10 88428205 88495824 NM_001171610 14 605906

MYH6 chr 14 23851198 23877486 NM_002471 39 160710

MYBPC3 chrll 47352956 47374253 NM_000256 34 600958

SCN5A chr3 38589552 38691163 NM_198056 28 600163

MYL3 chr3 46899356 46904973 NM_000258 7 160790

CACNA1C chr 12 2162415 2807115 NM_199460 50 114205

DMD chrX 31137344 33038317 NM_004007 78 300377

BAG3 chr 10 121410881 121437329 NM_004281 4 603883

EHMTl chr9 140513443 140730578 NM_024757 27 607001

DSG2 chrl8 29078026 29128814 NM_001943 15 125671

ABCC9 chr 12 21958107 22089628 NM_005691 38 601439

KCNE2 chr21 35736322 35743440 NM_172201 2 603796

RYR2 chrl 237205701 237997288 NM_001035 105 180902

TTN chr2 179390716 179672150 NM_001267550 363 188840

TTN-ASl chr2 179385910 179644690 NR_038271 7 NA

VCL chrlO 75757871 75879914 NM_014000 22 193065

SOSl chr2 39208689 39347604 NM_005633 23 182530

ANKRDl chrlO 92671856 92681032 NM_014391 9 609599 ACTN2 chrl 236849753 236927927 NM_001278344 23 102573

For detection of deafness (or the proclivity therefor), the at least one genetic marker can be at least one of UBIAD1, LARS2, GJB2, HGF, MY06, PCDH15, TMC1,

MARVELD2, CDH23, OTOF, LRTOMT, LOXHD1, EDN3, MY015A, SLC26A4, CLDN14, MARVELD2, WFSl, POU4F3, PTPRQ, SCARF2, COL4A4, USH2A, MY07A. The details of the deafness panel are given below in Table 2.

Table 2: Deafness Panel

For detection of dermatological conditions (or the proclivity therefor), the at least one genetic marker can be at least one of XPC, COL7A1, ALDH3A2, SLC39A4, CTSC, ITGB4, TGM1, HPS1, TYR, LAMB 3, EOGT, DOCK6, LAMC2, GORAB, KRT5, KRT83, COL18A1, ALDH18A1, FERMT1, EOGT, DCAF17, DSP, NFL The details of the dermatological panel are given below in Table 3. Table 3: Dermatological Panel

For detection of dysmorphia-dysplasia (DD) (or the proclivity therefor), the at least one genetic marker can be at least one of LIFR, TCOF1, LARP7, EVC, POC1A, HGSNAT, COL2A1, CRTAP, COL11A2, DYM, COLlAl, CREBBP, COL11A1, PYCR1, NIPBL, ROR2, EXT1, ACTB, ADAMTSL2, NEK1, DYNC2H1, IRF6, NSD1, UBE3B, DLL3, EP300, SGSH, EZH2, CHRNG, GALNS, MGAT2, TNFRSFllB, LMNA, ERCC8, CANTl, MMP2, FKBP10, CUL7, GNPAT, FGFR2, FGFR3, MASP1, FREMl, HSPG2, MEOX1, OBSLl, WNTl, COL1A2, COLlAl, ANTXR2, PEX13, ECELl, KMT2A, KMT2D, PCNT, EBP, UBR1, WISP3, DLX5, IFT122, HRAS, SERPINF1, RIPK4, LEPRE1, BRAF, NFIX, FBNl, NFl, TMEM67, COLECll, SCARF2. The details of the dysmorphia-dysplasia panel are given below in Table 4.

Table 4: Dysmorphia-Dysplasia (DD) Panel

Number

of

Gene Chr Start End Transcript Exons MIM LIFR chr5 38475064 38595507 NM_002310 20 151443

TCOF1 chr5 149737201 149779871 NM_001135243 27 606847

LARP7 chr4 113558119 113578748 NM_001267039 15 612026

EVC chr4 5712923 5816031 NM_153717 21 604831

POC1A chr3 52109248 52188706 NM_015426 11 614783

HGSNAT chr8 42995591 43057970 NM_152419 18 610453

COL2A1 chrl2 48366747 48398285 NM_001844 54 120140

CRTAP chr3 33155449 33189265 NM_006371 7 605497

COL11A2 chr6 4610635 4637414 NM_080680 65 120290

DYM chrl8 46570171 46987079 NM_017653 17 607461

COL1A1 chrl7 48261456 48279000 NM_000088 51 120150

CREBBP chrl6 3775055 3930121 NM_004380 31 600140

COL11A1 chrl 103342022 103574052 NM_080629 67 120280

PYCR1 chrl7 79890266 79894968 NM_153824 8 179035

NIPBL chr5 36876860 37065921 NM_133433 47 608667

ROR2 chr9 94484877 94712444 NM_004560 9 602337

EXT1 chr8 118811601 119124058 NM_000127 11 608177

ACTB chr7 5566778 5570232 NM_001101 6 102630

ADAMTSL2 chr9 136399974 136440641 NM_014694 19 612277

NEK1 chr4 170314420 170533778 NM_001199397 36 604588

DYNC2H1 chrll 102980159 103350591 NM_001080463 90 603297

IRF6 chrl 209958967 209979520 NM_006147 9 607199

NSD1 chr5 176560832 176727214 NM_022455 23 606681

UBE3B chrl2 109915427 109974510 NM_183415 28 608047

DLL3 chrl9 39989556 39999121 NM_203486 9 602768

EP300 chr22 41488613 41576081 NM_001429 31 602700

SGSH chrl7 78183078 78194199 NM_000199 8 605270

EZH2 chr7 148504463 148581441 NM_001203247 20 601573

CHRNG chr2 233404436 233411038 NM_005199 12 100730

GALNS chrl6 88880141 88923374 NM_000512 14 612222

MGAT2 chrl4 50087488 50090199 NM_002408 1 602616

TNFRSF11B chr8 119935795 119964383 NM_002546 5 602643

LMNA chrl 156095950 156109880 NM_001257374 13 150330

ERCC8 chr5 60169658 60240905 NM_000082 12 609412

CANT1 chrl7 76987797 77005899 NM_001159773 5 613165

MMP2 chrl6 55513080 55540586 NM_004530 13 120360

FKBP10 chrl7 39968961 39979469 NM_021939 10 607063

CUL7 chr6 43005354 43021683 NM_001168370 26 609577

GNPAT chrl 231376918 231413719 NM_014236 16 602744

FGFR2 chrlO 123241366 123353481 NM_001144913 17 176943

FGFR3 chr4 1795038 1810599 NM_001163213 18 134934

MASP1 chr3 186933872 187009810 NM_001879 16 600521

FREM1 chr9 14734663 14910993 NM_144966 38 608944

HSPG2 chrl 22148736 22263750 NM_005529 97 142461

MEOX1 chrl7 41717757 41738931 NM_004527 3 600147

OBSL1 chr2 220415449 220436268 NM_015311 21 610991

WNT1 chrl2 49372235 49376396 NM_005430 4 164820 COL1A2 chr7 94023872 94060544 NM_000089 52 120160

COL1A1 chrl7 48261456 48279000 NM_000088 51 120150

ANTXR2 chr4 80898661 80994477 NM_001145794 16 608041

PEX13 chr2 61244811 61279125 NM_002618 4 601789

ECEL1 chr2 233344536 233352532 NM_004826 18 605896

KMT2A 11 118307205 118397539 NM_001197104 36 159555

KMT2D chrl2 49412758 49453557 NM_003482 54 602113

PCNT chr21 47744035 47865682 NM_006031 47 605925

EBP chrX 48380163 48387104 NM_006579 5 300205

UBR1 chrl5 43235097 43398286 NM_174916 47 605981

WISP3 chr6 112375277 112390887 NM_003880 6 603400

DLX5 chr7 96649701 96654143 NM_005221 3 600028

IFT122 chr3 129158967 129239191 NM_052985 31 606045

HRAS chrll 532241 535550 NM_005343 6 190020

SERPINF1 chrl7 1665258 1680859 NM_002615 8 172860

RIPK4 chr21 43159528 43187249 NM_020639 8 605706

LEPRE1 chrl 43212005 43232755 NM_022356 15 610339

BRAF chr7 140433812 140624564 NM_004333 18 164757

NFIX chrl9 13135394 13209610 NM_001271043 11 164005

FBN1 chrl5 48700502 48937985 NM_000138 66 134797

NF1 chrl7 29421944 29704695 NM_001042492 58 613113

TMEM67 chr8 94767071 94831460 NR_024522 29 609884

COLEC11 chr2 3642421 3692234 NM_199235 8 612502

For detection of endocrine conditions (or the proclivity therefor), the at least one genetic marker can be at least one of TBCE, GHR, GHRHR, BBS5, SHOX. The details of the endocrine panel are given below in Table 5.

Table 5: Endocrine Panel

For detection of gastrointestinal (GI) conditions (or the proclivity therefor), the at least one genetic marker can be at least one of UGT1A1, UGT1A10, UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, JAGl, BAAT, ATP7B, TJP2, EPCAM, ABCB4, ABCC2, LRBA, SLC10A2, ABCBll, VIPAS39, FAH, G6PC. The details of the gastrointestinal panel are given below in Table 6. Table 6: Gastrointestinal (GI) Panel

For detection of hematological conditions (or the proclivity therefor), the at least one genetic marker can be at least one of BLM, FANCA, FANCM, BRCA2, ASXLl. The details of the hematology panel are given below in Table 7.

Table 7: Hematology Panel

For detection of inborn errors of metabolism (IEM) (or the proclivity therefor), the at least one genetic marker can be at least one of L2HGDH, MCCC2, SLC37A4, ARSB, HSD3B7, DBT, PHKG2, BTD, MUT, ASL, DPAGT1, ASAH1, AMT, BCKDHB,

BCKDHA, CBS, PAH, CLN8, GBA, ACADM, SLC3A1, MMACHC, PTS, GNS, GCDH, SLC22A5, GAA, MMADHC, PYGL, ASSl, CPSl, H6PD, PTS, PGMl, IVD, ARGl, ASAHl, GLBl, OXCTl, OPLAH, FAH, G6PC, PEXl. The details of the inborn errors of metabolism panel are given below in Table 8.

Table 8: Inborn Errors of Metabolism (IEM) Panel

Number

of

Gene Chr Start End Transcript Exons MIM

L2HGDH chrl4 50709151 50778947 NM_024884 10 609584

MCCC2 chr5 70883114 70954530 NM_022132 17 609014

SLC37A4 chrll 118895060 118901616 NM_001164279 11 602671

ARSB chr5 78111333 78281766 NM_198709 8 611542

HSD3B7 chrl6 30996518 31000473 NM_025193 7 607764

DBT chrl 100652477 100715409 NM_001918 11 248610

PHKG2 chrl6 30759619 30772497 NM_001172432 11 172471

BTD chr3 15643254 15687325 NM_000060 4 609019

MUT chr6 49398072 49431041 NM_000255 13 609058

ASL chr7 65540775 65558329 NM_000048 17 608310

DPAGT1 chrll 118967212 118972785 NM_001382 9 191350

ASAHl chr8 17913924 17942507 NM_004315 14 613468

AMT chr3 49454210 49460111 NM_001164712 10 238310

BCKDHB chr6 80816343 81055987 NM_000056 11 248611

BCKDHA chrl 9 41937222 41945843 NM_018035 6 608348

CBS chr21 44473300 44496472 NM_001178009 18 613381

PAH chrl 2 103232103 103311381 NM_000277 13 612349

CLN8 chr8 1711869 1734736 NM_018941 3 607837

GBA chrl 155204238 155214653 NM_001005742 12 606463

ACADM chrl 76190042 76229355 NM_001127328 12 607008

SLC3A1 chr2 44502596 44547962 NM_000341 10 104614

MMACHC chrl 45965855 45976739 NM_015506 4 609831

PTS chrll 112097087 112104695 NM_000317 6 612719

GNS chrl 2 65107221 65153226 NM_002076 14 607664

GCDH chrl 9 13001942 13010813 NM_013976 12 608801

SLC22A5 chr5 131705400 131731306 NM_003060 10 603377

GAA chrl 7 78075354 78093679 NM_001079804 20 606800

MMADHC chr2 150426146 150444330 NM_015702 8 611935

PYGL chrl 4 51371934 51411248 NM_002863 20 613741

ASSl chr9 133320093 133376661 NM_000050 16 603470

CPSl chr2 211342405 211543831 NM_001122633 39 608307

H6PD chrl 9294862 9331394 NM_004285 5 138090

PTS chrll 112097087 112104695 NM_000317 6 612719

PGMl chrl 64088886 64125916 NM_001172818 11 171900

IVD chrl 5 40697685 40713512 NM_002225 12 607036

ARGl chr6 131894343 131905472 NM_001244438 8 608313

ASAHl chr8 17913924 17942507 NM_004315 14 613468

GLBl chr3 33038099 33138314 NM_001079811 16 611458 OXCT1 chr5 41730166 41870791 NM_000436 17 601424

OPLAH chr8 145106166 145115584 NM_017570 28 614243

FAH chr 15 80445232 80478924 NM_000137 14 613871

G6PC chr 17 41052813 41066450 NM_000151 5 613742

PEX1 chr7 92116336 92157845 NM_000466 24 602136

For detection of neurological disorders (or the proclivity therefor), the at least one genetic marker can be at least one of LICAM, ABCDl, DYSF, GBA2, TRAPPC9, CYP2U1, PANK2, ARL13B, KIF7, ERLIN2, PSAP, VAPB, FKTN, PLPl, GDAPl, ASPM, LAMA2, MECP2, CDK5RAP2, WDR81, ABAT, NDE1, WDR45B, HSD17B4, HEXA, SPG11, PDGFRB, HUWE1, SLC25A19, ARHGEF6, ADRA2B, RELN, CENPJ, ARL14EP, PHGDH, ARID IB, WNK1, SEPN1, RNASEH2C, RNASEH2B, CYP27A1, ATN1, AHI1, STXBP1, CDKL5, MED23, ISPD, CEP57, AGRN, FKRP, ADCK3, SCN2A, MFSD8, TYMP, FLVCR2, SPG20, CACNAIG, PLA2G6, CLN6, WDR62, PEX26, KIFIA, PNPO, LARGE, YARS, KIAA0196, CCDC88C, OPTN, OCLN, ATRX, ATL1, GNE, PEX12, SPTBN2, PEX16, COL6A1, COL6A3, COL6A2, HEPACAM, LRPPRC, RYR1, NTRK1, CAPN3, SOD1, COG6, ATP2B3, DPYD, TUBA1A, TCTN1, CPA6, ABHD12, NPC2, MPDZ, SYNGAP1, PEX5, PEX6, POMT1, POMT2, MCPH1, CASC5, SGCB, SGCA, POMGNT2, TRMT1, ARFGEF2, SYNE2, ADK, ZNF526, FOXG1, ALS2, C5orf42, TMEM237, C12orf57, TMEM67, PEX1. The details of the neurological panel are given below in Table 9.

Table 9: Neurological Panel

Number

of

Gene Chr Start End Transcript Exons MIM

LICAM chrX 153126968 153151628 NM_001278116 29 308840

ABCDl chrX 152990322 153010216 NM_000033 10 300371

DYSF chr2 71693831 71913893 NM_001130983 56 603009

GBA2 chr9 35736862 35749225 NM_020944 17 609471

TRAPPC9 chr8 140742585 141468678 NM_031466 23 611966

CYP2U1 chr4 108852716 108874613 NM_183075 5 610670

PANK2 chr20 3869741 3904502 NM_153638 7 606157

ARL13B chr3 93698982 93774522 NM_182896 11 608922

KIF7 chrl5 90171200 90198682 NM_198525 19 611254

ERLIN2 chr8 37594096 37615319 NM_007175 12 611605

PSAP chrlO 73576054 73611082 NM_001042465 15 176801

VAPB chr20 56964174 57026156 NM_004738 6 605704

FKTN chr9 108320410 108403399 NM_001198963 12 607440

PLPl chrX 103031753 103047547 NM_000533 7 300401 GDAP1 chr8 75262617 75279335 NM_018972 6 606598

ASPM chrl 197053256 197115824 NM_018136 28 605481

LAMA2 chr6 129204285 129837710 NM_000426 65 156225

MECP2 chrX 153295685 153363188 NM_001110792 3 300005

CDK5RAP2 chr9 123151146 123342448 NR_073556 39 608201

WDR81 chrl7 1628124 1641893 NM_001163809 10 614218

ABAT chrl6 8768443 8878432 NM_020686 16 137150

NDE1 chrl6 15737124 15820210 NM_017668 9 609449

WDR45B chrl7 80572438 80606429 NM_019613 10 609226

HSD17B4 chr5 118788201 118878030 NM_001199291 25 601860

HEXA chrl5 72635777 72668520 NM_000520 14 606869

SPG11 chrl5 44854893 44955876 NM_025137 40 610844

PDGFRB chr5 149493401 149535422 NM_002609 23 173410

HUWE1 chrX 53559056 53713697 NM_031407 84 300697

SLC25A19 chrl7 73269060 73285530 NM_001126122 7 606521

ARHGEF6 chrX 135747711 135863503 NM_004840 22 300267

ADRA2B chr2 96778622 96781888 NM_000682 1 104260

RELN chr7 103112230 103629963 NM_005045 65 600514

CENPJ chrl3 25456411 25497027 NR_047594 18 609279

ARL14EP chrll 30344598 30359774 NM_152316 4 612295

PHGDH chrl 120254418 120286849 NM_006623 12 606879

ARID IB chr6 157099063 157531913 NM_020732 20 614556

WNK1 chrl2 862088 1020618 NM_018979 28 605232

SEPN1 chrl 26126666 26144713 NM_020451 13 606210

RNASEH2C chrll 65485143 65488409 NM_032193 4 610330

RNASEH2B chrl3 51483813 51530901 NM_024570 11 610326

CYP27A1 chr2 219646471 219680016 NM_000784 9 606530

ATN1 chrl2 7033625 7051484 NM_001007026 10 607462

AHI1 chr6 135708921 135818903 NM_001134832 23 608894

STXBP1 chr9 130374485 130454995 NM_001032221 19 602926

CDKL5 chrX 18460343 18671749 NM_001037343 22 300203

MED23 chr6 131907877 131949379 NM_001270522 30 605042

ISPD chr7 16127151 16460947 NM_001101426 10 614631

CEP57 chrll 95523624 95565857 NM_001243776 12 607951

AGRN chrl 955502 991499 NM_198576 36 103320

FKRP chrl9 47249302 47261832 NM_001039885 4 606596

ADCK3 chrl 227127937 227175246 NM_020247 15 606980

SCN2A chr2 166095911 166248820 NM_001040142 27 182390

MFSD8 chr4 128838959 128887139 NM_152778 13 611124

TYMP chr22 50964180 50968514 NM_001257989 10 131222

FLVCR2 chrl4 76044939 76114512 NM_017791 10 610865

SPG20 chrl3 36875774 36944317 NM_001142294 9 607111

CACNA1G chrl7 48638428 48704832 NM_018896 38 604065

PLA2G6 chr22 38507501 38577761 NM_003560 17 603604

CLN6 chrl5 68499329 68522080 NM_017882 7 606725

WDR62 chrl9 36545782 36596012 NM_173636 32 613583

PEX26 chr22 18560759 18573797 NM_001127649 5 608666 KIF1A chr2 241653180 241759725 NM_001244008 49 601255

PNPO chrl7 46018888 46026674 NM_018129 7 603287

LARGE chr22 33669061 34316416 NM_133642 15 603590

YARS chrl 33240839 33283633 NM_003680 13 603623

KIAA0196 chr8 126036502 126104061 NM_014846 29 610657

CCDC88C chrl4 91737666 91884188 NM_001080414 30 611204

OPTN chrlO 13142081 13180276 NM_001008213 16 602432

OCLN chr5 68788589 68853931 NM_001205254 9 602876

ATRX chrX 76760355 77041719 NM_000489 35 300032

ATL1 chrl4 50999799 51099784 NM_001127713 14 606439

GNE chr9 36214438 36277053 NM_001128227 12 603824

PEX12 chrl7 33901813 33905656 NM_000286 3 601758

SPTBN2 chrll 66452719 66488870 NM_006946 37 604985

PEX16 chrll 45931219 45939674 NM_057174 11 603360

COL6A1 chr21 47401662 47424963 NM_001848 35 120220

COL6A3 chr2 238232654 238322850 NM_004369 44 120250

COL6A2 chr21 47518032 47552763 NM_001849 28 120240

HEPACAM chrll 124789145 124806308 NM_152722 7 611642

LRPPRC chr2 44113362 44223144 NM_133259 38 607544

RYR1 chrl9 38924339 39078204 NM_000540 106 180901

NTRK1 chrl 156830670 156851642 NM_002529 17 191315

CAPN3 chrl5 42651697 42704515 NM_000070 24 114240

SOD1 chr21 33031934 33041243 NM_000454 5 147450

COG6 chrl3 40229763 40326765 NR_026745 20 606977

ATP2B3 chrX 152801579 152848387 NM_021949 21 300014

DPYD chrl 97543299 98386615 NM_000110 23 612779

TUBA1A chrl2 49578577 49583107 NM_006009 4 602529

TCTN1 chrl2 111051911 111086935 NM_001173975 15 609863

CPA6 chr8 68334404 68658620 NM_020361 11 609562

ABHD12 chr20 25275378 25371618 NM_015600 13 613599

NPC2 chrl4 74946642 74960084 NM_006432 5 601015

MPDZ chr9 13105702 13279563 NM_001261406 46 603785

SYNGAP1 chr6 4868092 4901710 NM_006772 19 603384

PEX5 chrl2 7341758 7371169 NM_001131026 18 600414

PEX6 chr6 42931610 42946981 NM_000287 17 601498

POMT1 chr9 134378288 134399193 NM_001077365 20 607423

POMT2 chrl4 77741298 77787225 NM_013382 21 607439

MCPH1 chr8 6264112 6501140 NM_024596 14 607117

CASC5 chrl5 40886446 40954881 NM_170589 27 609173

SGCB chr4 52886860 52904485 NM_000232 6 600900

SGCA chrl7 48243365 48253293 NM_000023 10 600119

POMGNT2 chr3 43120724 43147568 NM_032806 2 614828

TRMT1 chrl9 13215713 13227563 NM_001136035 17 611669

ARFGEF2 chr20 47538274 47653230 NM_006420 39 605371

SYNE2 chrl4 64319682 64693167 NM_182914 116 608442

ADK chrlO 75910942 76469061 NM_006721 11 102750

ZNF526 chrl9 42724491 42732353 NM_133444 3 614387 FOXG1 chrl4 29236277 29239483 NM_005249 1 164874

ALS2 chr2 202564985 202645895 NM_020919 34 606352

C5orf42 chr5 37106329 37249530 NM_023073 52 614571

TMEM237 chr2 202484906 202508252 NM_001044385 12 614423

C12orf57 chrl2 7053202 7055165 NM_138425 3 615140

For detection of pelvic inflammatory disease (PID) (or the proclivity therefor), the at least one genetic marker can be at least one of IL7R, JAK3, CD40LG, AK2, DCLREIC, CD40, AICDA, MLPH, NHEJl, RAB27A, RAG2, RAGl, BTK, ATM, LYST, CYBB, AIRE, DOCK8, SLC17A5, STAT3, WAS, CD247, DNMT3B, FLG, NCF2, ADA,

RFXANK, PTPRC, COLEC11. The details of the pelvic inflammatory disease panel are given below in Table 10.

Table 10: Pelvic Inflammatory Disease (PID) Panel

Number

of

Gene Chr Start End Transcript Exons MIM

IL7R chr5 35856976 35879705 NM_002185 8 146661

JAK3 chrl9 17935592 17958841 NM_000215 24 600173

CD40LG chrX 135730335 135742549 NM_000074 5 300386

AK2 chrl 33473540 33502512 NR_037591 8 103020

DCLREIC chrlO 14948870 14996094 NM_001033858 16 605988

CD40 chr20 44746905 44758384 NM_001250 9 109535

AICDA chrl 2 8754761 8765442 NM_020661 5 605257

MLPH chr2 238395877 238463961 NM_024101 16 606526

NHEJl chr2 219940045 220025587 NM_024782 8 611290

RAB27A chrl 5 55495163 55582013 NM_183235 7 603868

RAG2 chrll 36613492 36619829 NM_000536 2 179616

RAGl chrll 36589562 36601310 NM_000448 2 179615

BTK chrX 100604434 100641212 NM_000061 19 300300

ATM chrll 108093558 108239826 NM_000051 63 607585

LYST chrl 235824330 236030227 NM_000081 53 606897

CYBB chrX 37639269 37672714 NM_000397 13 300481

AIRE chr21 45705720 45718102 NM_000383 14 607358

DOCK8 chr9 214864 465259 NM_203447 48 611432

SLC17A5 chr6 74303101 74363737 NM_012434 11 604322

STAT3 chrl 7 40465342 40540405 NM_213662 24 102582

WAS chrX 48542185 48549817 NM_000377 12 300392

CD247 chrl 167399876 167487847 NM_198053 8 186780

DNMT3B chr20 31350190 31397162 NM_006892 23 602900

FLG chrl 152274650 152297679 NM_002016 3 135940

NCF2 chrl 183524696 183560056 NM_001127651 16 608515

ADA chr20 43248162 43280376 NM_000022 12 608958

RFXANK chrl 9 19303007 19312678 NM_003721 10 603200

PTPRC chrl 198608097 198726605 NM_002838 33 151460 For detection of pulmonary conditions (or the proclivity therefor), the at least one genetic marker can be at least one of SFTPB, CFTR. The details of the pulmonary panel are given below in Table 11.

Table 11 : Pulmonary Panel

For detection of renal conditions (or the proclivity therefor), the at least one genetic marker can be at least one of IQCBl, COL4A6, NPHP3, SLC4A4, DDX39A, SMARCALl, PKHDl, LAMB2, NEK8, NPHP4, FRASl, XDH, MKSl, FANl, TCTN2, NPHSl, CC2D2A, TMEM231, UPK3A, CEP290, NPHP4, COL4A4, TMEM67, C5orf42,

TMEM237. The details of the renal panel are given below in Table 12.

Table 12: Renal Panel

Number

of

Gene Chr Start End Transcript Exons MIM

IQCBl chr3 121488609 121553926 NM_001023570 15 609237

COL4A6 chrX 107398836 107682704 NM_001847 45 303631

NPHP3 chr3 132399452 132441303 NM_153240 27 608002

SLC4A4 chr4 72053002 72437804 NM_001098484 26 603345

DDX39A chrl9 14519609 14529906 NR_038336 12 NA

SMARCALl chr2 217277472 217347774 NM_001127207 18 606622

PKHDl chr6 51585646 51952423 NM_170724 61 606702

LAMB2 chr3 49158546 49170599 NM_002292 32 150325

NEK8 chrl7 27055831 27069784 NM_178170 15 609799

NPHP4 chrl 5922869 6052533 NM_015102 30 607215

FRASl chr4 78978723 79465423 NM_025074 74 607830

XDH chr2 31557187 31637611 NM_000379 36 607633

MKSl chrl7 56282796 56296966 NM_001165927 18 609883

FANl chrl5 31196075 31203991 NM_001146096 4 613534

TCTN2 chrl2 124155659 124192950 NM_001143850 18 613846

NPHSl chrl9 36316273 36342895 NM_004646 29 602716

CC2D2A chr4 15471488 15603180 NM_001080522 38 612013

TMEM231 chrl6 75572014 75590184 NM_001077416 6 614949

UPK3A chr22 45680867 45691755 NM_006953 6 611559

CEP290 chrl2 88442789 88535993 NM_025114 54 610142

NPHP4 chrl 5922869 6052533 NM_015102 30 607215 For detection of vision disorders (or the proclivity therefor), the at least one genetic marker can be at least one of ALMS1, CRB1, CHST6, CRYBA1, PRSS56, GUCY2D, SNRNP200, PDE6C, CNGA3, C8orf37, ABCA4, BBS10, CERKL, GPR125, NHS, LTBP2, GCNT2, RLBPl, MIP, RP1L1, CHM, EYS, TULPl, IGFBP7, CYPIBI, LRAT, MERTK, CNNM4, RPl, RP2, LCA5, MFRP, CNGBl, CACNAIF, KCNV2, CRX, PROMl, TRPMl, PAX6, IMPG2, CDHR1, GPR179, CRYGC, CRYGD, NMNAT1, GALT, ARL6, LRP5, WDR19, SLC4A11, GDF3, SLC16A12, RGS9, RDH12, ADAM9, AIPL1, FAM161A, RPGRIPl, RAB3GAP2, RAB3GAP1, EFEMPl, BESTl, RPE65, EPHA2, FZD4, PRPH2, CRYAA, KCNJ13, NR2E3, BBS9, BBS1, BBS2, BBS5, BBS4, BBS7, SPATA7, CHD7, USH2A, MY07A, C12orf57, CEP290, NPHP4. The details of the vision panel are given below in Table 13.

Table 13: Vision Panel

Number

of

Gene Chr Start End Transcript Exons MIM

ALMS1 chr2 73612885 73837046 NM_015120 23 606844

CRB1 chrl 197170591 197447585 NM_001257965 15 604210

CHST6 chrl 6 75505950 75529282 NM_021615 3 605294

CRYBA1 chrl 7 27573874 27581502 NM_005208 6 123610

PRSS56 chr2 233385172 233390425 NM_001195129 13 613858

GUCY2D chrl 7 7905987 7923658 NM_000180 20 600179

SNRNP200 chr2 96940073 96971307 NM_014014 45 601664

PDE6C chrlO 95372344 95425429 NM_006204 22 600827

CNGA3 chr2 98962617 99015064 NM_001298 8 600053

C8orf37 chr8 96257140 96281462 NM_177965 6 614477

ABCA4 chrl 94458393 94586705 NM_000350 50 601691

BBS10 chrl 2 76738265 76742222 NM_024685 2 610148

CERKL chr2 182401400 182521834 NM_001030311 14 608381

GPR125 chr4 22388996 22517677 NM_145290 19 612303

NHS chrX 17653412 17754113 NM_001136024 9 300457

LTBP2 chrl 4 74964885 75079034 NM_000428 36 602091

GCNT2 chr6 10585992 10629601 NM_145655 3 600429

RLBPl chrl 5 89753097 89764922 NM_000326 9 180090

MIP chrl 2 56843285 56848435 NM_012064 4 154050

RP1L1 chr8 10463859 10512617 NM_178857 4 608581

CHM chrX 85116184 85302566 NM_000390 15 300390

EYS chr6 64429875 66417118 NM_001142800 43 612424

TULPl chr6 35465650 35480647 NM_003322 15 602280

IGFBP7 chr4 57897236 57976551 NM_001553 5 602867

CYPIBI chr2 38294745 38303323 NM_000104 3 601771 LRAT chr4 155665162 155674270 NM_004744 3 604863

MERTK chr2 112656190 112786945 NM_006343 19 604705

CNNM4 chr2 97426638 97477628 NM_020184 7 607805

RP1 chr8 55528626 55543394 NM_006269 4 603937

RP2 chrX 46696346 46741791 NM_006915 5 300757

LCA5 chr6 80194707 80247147 NM_001122769 8 611408

MFRP chrll 119209643 119217383 NM_015645 15 606227

CNGB1 chrl6 57916243 58005020 NM_001297 33 600724

CACNA1F chrX 49061522 49089771 NM_001256790 48 300110

KCNV2 chr9 2717525 2730037 NM_133497 2 607604

CRX chrl9 48325098 48346586 NM_000554 4 602225

PROM1 chr4 15969848 16077741 NM_006017 27 604365

TRPM1 chrl5 31293263 31393929 NM_001252024 28 603576

PAX6 chrll 31806339 31833731 NM_001258463 14 607108

IMPG2 chr3 100941389 101039419 NM_016247 19 607056

CDHR1 chrlO 85954390 85979376 NM_001171971 17 609502

GPR179 chrl7 36481492 36499693 NM_001004334 11 614515

CRYGC chr2 208992860 208994554 NM_020989 3 123680

CRYGD chr2 208986330 208989313 NM_006891 3 123690

NMNAT1 chrl 10003485 10045556 NM_022787 5 608700

GALT chr9 34646585 34650595 NM_000155 11 606999

ARL6 chr3 97483364 97520086 NR_103511 10 608845

LRP5 chrll 68080107 68216743 NM_002335 23 603506

WDR19 chr4 39184023 39287430 NM_025132 37 608151

SLC4A11 chr20 3208062 3219887 NM_001174089 20 610206

GDF3 chrl 2 7842380 7848360 NM_020634 2 606522

SLC16A12 chrlO 91190050 91295313 NM_213606 8 611910

RGS9 chrl 7 63133455 63223821 NM_001081955 19 604067

RDH12 chrl 4 68168602 68201168 NM_152443 9 608830

ADAM9 chr8 38854504 38962779 NM_003816 22 602713

AIPL1 chrl 7 6327058 6338519 NM_014336 6 604392

FAM161A chr2 62051982 62081278 NM_001201543 7 613596

RPGRIP1 chrl 4 21756135 21819460 NM_020366 24 605446

RAB3GAP2 chrl 220321609 220445843 NM_012414 35 609275

RAB3GAP1 chr2 135809834 135928279 NM_001172435 25 602536

EFEMP1 chr2 56093096 56151298 NM_001039349 11 601548

BEST1 chrll 61717355 61731935 NM_004183 11 607854

RPE65 chrl 68894506 68915642 NM_000329 14 180069

EPHA2 chrl 16450831 16482582 NM_004431 17 176946

FZD4 chrll 86656716 86666440 NM_012193 2 604579

PRPH2 chr6 42664332 42690358 NM_000322 3 179605

CRYAA chr21 44589140 44592913 NM_000394 3 123580

KCNJ13 chr2 233631174 233641278 NM_002242 3 603208

NR2E3 chrl 5 72102893 72110597 NM_014249 9 604485

BBS9 chr7 33169151 33645680 NM_198428 23 607968

BBS1 chrll 66278077 66301098 NM_024649 17 209901

BBS2 chrl 6 56518258 56554008 NM_031885 17 606151 BBS5 chr2 170336005 170363165 NM_152384 12 603650

BBS4 chrl5 72978519 73030817 NR_045565 17 600374

BBS7 chr4 122748881 122791652 NM_018190 18 607590

SPATA7 chrl4 88851987 88904804 NM_018418 12 609868

CHD7 chr8 61591323 61780586 NM_017780 38 608892

Each of the genetic markers was screened using one or more custom designed primer pairs. All of the primer pairs used to sequence genetic markers from a given Disease Panel make up a Mendelian Disease Panel. These primers are organized such that SEQ ID 1 and SEQ ID 10,518 are a pair, SEQ ID 31,552 and SEQ ID 34,959 are a pair, and so on. The primer pairs and their amplicons for each Disease Panel are given below in Table 14.

Table 14: Mendelian Disease Panels

642 samples with known mutations were used to calculate the analytical sensitivity of the Mendeliome assay. Overall analytical sensitivity was 79% (507/642). One hundred and thirty-five known mutations were missed by the Mendeliome assay, 46% (62/135) of which were due to a design flaw; i.e., the disease gene was not included in the panel appropriate for the disease presentation. If these 62 cases were to be excluded, the overall analytical sensitivity would increase to 87% (507/580). Based on these positive controls (580), sensitivity for single nucleotide variants was found to be 93% (398/428). However, sensitivity for indels was lower at 72% (109/152). As expected for semiconductor-based Ion Torrent sequencing, the bias against indels was not uniform but was largely sequence context-dependent, especially around homopolymer region.

In addition to these positive controls, single nucleotide polymorphism (SNP) genotyping arrays were used (Affymetrix Axiom GT1 chip with ~ 580,000 SNPs) coming from 21 patients as a second method of testing the analytical sensitivity. The variants detected by SNP arrays were compared to those detected by the next generation sequencing (NGS) technology for each sample. From a total of 3,319 SNPs lying within the target regions of the panels, the resulting SNP sensitivity was about 95%. Interestingly, 30 extra SNPs were identified that were called by the assay but were not called with high confidence on the chip. For analytical specificity, a predetermined quality score of 100 was used (this takes into account strand-bias, homopolymer errors, etc.). Analytical specificity was based on the Sanger validation of 1,078 variants called by the assay. Sanger sequencing confirmed 93% (819/881) of SNVs and 78% (154/197) of indels that met or were higher than that quality score.

A total of 2,357 patients representing a very wide range of suspected genetic diseases were tested by the Mendeliome assay (see Table 14 below for the number of patients tested on each panel). Only one panel was chosen per patient based on the most prominent primary clinical feature. The overall clinical sensitivity (i.e., detection of a likely causal variant that is subsequently confirmed by Sanger sequencing) was 43%. Table 14 also summarizes the clinical sensitivity per panel as well as per clinical feature within each panel. As expected, specialties with the highest referral rate were neurology, dysmorphology, pediatric ophthalmology and immunology because of the nonspecificity of the clinical presentation, extreme and genetic heterogeneity, and because a genetic cause is highly suspected for a large fraction of their patient population. In fact, a relatively high yield for the respective panels of 40%, 38%, 52%, and 37% were noted (see Table 15). Specificity of the presentation appeared to bear appreciably on the clinical sensitivity of the assay. For example, with an objective evidence of skeletal dysplasia the sensitivity of the

dymorphology/dysplasia panel was 45% as compared to 32% when any degree of dysmorphism was used as the entry point. Similarly, the finding of a specific pattern of neurological abnormality (e.g., muscular dystrophy and neurodegenerative disorders) was associated with a much higher sensitivity as compared with non-syndromic developmental delay/intellectual disability of any degree (56% and 42% vs 11%). Also consistent with this is the finding that retinal dystrophies (almost always Mendelian in etiology) were more likely to have positive hits than the overall performance of the fision panel (65% vs 52%). Table 15: Clinical Sensitivities Per Panel

Total Overall

Gene Panel Type Patients Clinical Selected Subgroup Clinical Sensitivity

Run Sensitivity

32%

Cardiomyopathy

Cardiovascular 243 28% Congenital heart disease 10%

Arrhythmias 31%

Aneurysms 29%

Deafness 147 54% Hearing Loss -

Nonspecific Dermatological

Dermatology 68 62% - Features

45%

Skeletal dysplasia

Dysmorphology-

354 38%

Dysplasia 32%

Dysmorphism

Endocrinology 36 61% Pituitary and Thyroid Disorders -

Gastroenterology 73 29% Persistent Jaundice -

Hematology 33 24% Aplastic Anemia -

Inborn errors of

122 59% Metabolic disorders - metabolism

Syndromic DD/ID _Recognizable 47% syndromes

Syndromic DD/ID NYD (not yet

25% determined)_Unrecognizable syndrome

Structural Brain (Cerebral/Cerebellar/brain stem) 34% and spinal malformations/anomalies* 1

Non Syndromic DD/ID NYD (not

Neurology 524 40% 11% yet determined, unrecognizable) *2

42%

Neurodegenerative disorders

Coordination* 3/Movement 69% disorders

33%

Peripheral neuropathy

56%

Myopathies/Joint abnormalities* 4

Primary immunodeficiency

PID 196 37% - disorders

Pulmonology 36 36% Chronic lung infection suspected - cystic fibrosis

Glomerular/Tubular Disorders

Renal 107 57% 41% Cystic Kidney Disease

63%

Kidney Malformation

69%

Retinal dystrophy (syndromic, non-syndromic, RP, CRD,

65% macular dystrophy, FEVR, GFS)

Cataract (syndromic and non- syndromic) 34%

Aniridia

Vision 418 52% 33%

Microphthalmia/anophthalmia

(with and without coloboma) 30%

Corneal dystrophy (CHED and all other subtypes) 40%

Others 23%

*1: Primary microcephaly cases are included in this group ,*2: Non syndromic cases of Autism/mental disorder and epilepsy are included under this group, *3: Ataxia cases secondary to cerebellar hypoplasia are included under the structural brain abnormalities group, *4: Cases with Arthrogryposis Multiplex syndromes are included under myopathies group. PID: Primary immunodeficiency, DD: developmental delay, ID: intellectual disability, RP: retinitis pigmentosa, CRD: cone -rod dystrophy, FEVR: familial exudative vitreoretinopathy, GFS: Goldmann-Favre syndrome, CHED: corneal hereditary endothelial dystrophy

The clinical sensitivity of the Mendeliome assay (43%) is comparable to the -25% reported by several large clinical whole exome sequencing (WES) studies. The Mendeliome assay is inherently limited to established disease genes, so it will miss cases caused by large structural variants and mutations in novel genes, although the design is flexible and allows for the addition of newly published disease genes as frequently as needed, e.g.. every six months. 213 cases were randomly selected that were negative by the Mendeliome assay, and these were processed using molecular karyotyping. Thirty-five of these were found to have likely pathogenic de novo copy-number variations (CNVs). If these 35 cases are excluded, the clinical sensitivity of the present method would increase slightly to 44%. The remaining 178 were processed using WES, and only 11% (20/178) were found by WES to have a mutation in a known gene that was missed by the Mendeliome assay. Out of these 20 missed cases, the majority (n=14, 70%) were due to a design flaw (i.e., the disease gene was not included in the panel appropriate for the disease presentation) and this can easily be fixed by a spike-in approach.

The remaining six cases represent a limitation of the analytical sensitivity of the next- generation sequencing platform used in this study. On the other hand, it should be noted that two patients were included who had had negative diagnostic WES results prior to their enrollment in the Mendeliome assay, and were found to have likely causal mutations by the latter. These cases were missed at the interpretation phase of WES analysis and were solved by the Mendeliome assay, likely because of the smaller number of variants. The much smaller number of variants to be queried by the Mendeliome assay vs. WES also meant a much more rapid clinical interpretation (average 20 min per panel vs. 2 - 3 hours per WES). This has markedly reduced the cost of interpretation on top of an already appreciable reduction in running cost (24 panel samples were run per chip vs. one WES per chip). The cost is estimated to be $150 per sample with a range of $75-$150 per sample depending on the panel selected. The cost difference is even more dramatic for de novo mutations (n=31) that we identified in this study, because they are typically identifiable by WES only when a trio design is followed. These de novo mutations were identifiable as likely disease-causing heterozygous mutations in relevant Mendelian genes, and their de novo status was confirmed by Sanger sequencing of a single amplicon in both parents. Also relevant to cost reduction is that five couples who lost children with a likely recessive disease were used, but there was no access to DNA from the deceased children. By running the appropriate panel on both parents the method was able to identify the likely causal mutation at a much lower cost than the duo WES design that would have been required to reach the same conclusion.

WES is frequently requested after one or more genes deemed relevant to the patient' s clinical presentation had been excluded by Sanger sequencing in hopes of identifying a novel genetic cause. However, many WES studies have highlighted the frequent encounter of disease-causing mutations in known genes that would not have been considered good candidates owing to the marked discrepancy between their published phenotype and the clinical presentation of the patient especially for neurological and dysmorphic disorders, which are often very heterogeneous clinically. It has been shown that even in familial cases that are carefully enriched for novel gene discovery by excluding all relevant candidate genes by autozygome analysis, 11% of WES will reveal mutations in known genes missed by the enrichment step because the presentation was very atypical. In fact, in many patients with disease-causing mutations identified by the Mendeliome assay, the presentation was sufficiently different from the published phenotype of the respective gene that WES would have been pursued to establish the diagnosis (see Table 16 below). Some of the most dramatic examples are a de novo EP300 mutation causing microcephalic primordial dwarfism, a homozygous ZNF526 mutation causing a novel Noonan-like phenotype, a homozygous IFT122 mutation causing severe ocular anomalies and unusual appendicular skeletal abnormalities, and a de novo KMT2A mutation causing genital abnormalities in an affected female including absent uterus and vagina with remarkable clitoromegaly (see Table 16 below).

On the other hand, mutations in genes were identified which are typically associated with multisystem disorders in patients with a very limited phenotype, e.g., NPHP4 mutation in a patient with isolated retinal dystrophy instead of Senior- Loken syndrome, and

RAB3GAP1 causing isolated cataract instead of Warburg Micro syndrome (Table 16).

Finally, it should be noted that the highly surprising finding of a homozygous nonsense mutation in TCOF1 causing severe Treacher-Collins syndrome while the carrier parents are completely normal clinically. Interestingly, this mutation had been missed by direct Sanger sequencing of TCOF1, most likely because the expectation was a heterozygous peak on the sequence chromatogram given the dominant nature of the disease. This is the first instance of a recessive inheritance of TCOF1.

Table 16: Atypical Phenotypes

Gene MutTyp Published Observed Phenotype compared Name ation e Phenotype(s) related to published phenotype(s) to the case

Type Status Origin Typical/ Atypical

Previously feature(s) reported

feature(s)

FGFR2 Mis- HTZ De DD Craniosynostosis -Craniofacial -Upper eyelid sense Novo syndromes anomalies coloboma

Sacrococcyge

al tail

-Syndactyly

-Neonatal

teeth(with

Beare-

Stevenson

Cutis Gyrata

Syndrome)

-Choanal

atresia

-Thinning of

the genu of

corpus

callosum(with

Pfeiffer

Syndrome) HRAS Mis- HTZ De DD Costello syndrome -Dysmorphic -Corneal sense Novo facies haziness

-Multiple joint

dislocations Tracheomalacia and bronchomalacia

COL2A1 Mis- HTZ De DD Spondylometaepiphys -Valvular sense Novo eal dysplasia Disproportion disease (mild ate short TR,MR) stature -Acanthosis

-Thoracic nigricans dextroscoliosi

s

- Metaphyseal

dysplasia

-Inguinal

hernia

-Myopia

TCOF1 NonHMZ InheritDD Treacher Collins -Confirmed to sense ed syndrome 1 Underdevelop be inherited as ment zygoma AR

-Choanal

atresia

-Microtia

-No external

auditory

meatus

-Malformed

ossicles and

semicircular

canal

-Iris/optic disc

coloboma

BRAF Mis- HTZ De DD Cardiofaciocutaneous -Hypotonia -Coarse face sense Novo syndrome -Speech delay similar to

Costello syndrome

-No cardiac defects

-Acanthosis nigricans

-Deep palmar and plantar creases

EP300 NonHTZ De DD Rubinstein-Taybi None -Atypical sense Novo syndrome 2 dysmorphic facies

-Microcephalic primordial dwarfism

NFIX NonHTZ UnDD Sotos Syndrome type -Overgrowth -Marfanoid sense known 2 -ODD Habitus Father -Normal bone was not age tested

GNS Frame - HMZ InDD Mucopolysaccharidos -Mild coarse -Advanced RP shift herited is type HID face

-Mild

hepatomegaly

-Clear cornea

-Skeletal

manifestations

COL11A Mis- HMZ InDD Otospondylomegaepi Epiphyseal -Hypoplastic

2 sense herited physeal dysplasia dysplasia optic nerve

-CP -Mitral valve

-Deafness prolapse and regurgitation

IFT122 Splice HMZ InDD Cranioectodermal -Nystagmus -Iris and optic site herited dysplasia 1 - Metaphyseal nerve coloboma dysplasia

Microphthalmia -Duplicated thumb and big toe

-Post-axial Polydactyly -Very short tibiae compared to fibulae

ROR2 Mis- HMZ Parents DD - Robinow syndrome Vertebral Atypical sense not -Brachydactyly, type anomalies(in fibrochondroge tested Bl Robinow nesis-like syndrome) skeletal

dysplasia

KMT2A Frame - HTZ De DD Wiedemann-Steiner -Dysmorphic -Absent uterus shift Novo syndrome facies and vagina, remarkable clitoromegaly

NSD1 NonHTZ De DD Sotos Syndrome 1 - Dysmorphic -No overgrowth sense Novo facies

-Thin corpus

callosum,

PVL and

colpocephaly

on MRI brain

NPHP4 Mis- HMZ InVisSenior_Loken -RP -Lack of sense herited ion syndrome systemic

involvement (isolate RP)

CNNM4 Mis- HMZ Parents VisJalili syndrome -LCA, retinal Retinal sense not ion degeneration coloboma tested -No dental anomalies

BBS4 Frame - Compou Parents VisBardet-Biedl -RP -Lack of other shift nd HTZ not ion syndrome 4 features of BBS tested (isolated RP)

RAB3GA Nonse HMZ Likely VisWarburg micro -Congenital -Lack of

PI nse inion syndrome 1 cataract microcephaly herited and severe ocular anomalies

ATRX Nonse Hemizyg InVisMental retardation- -Microcephaly -RP

nse ous herited ion hypotonic facies -ODD -Optic disc syndrome, X-linked -White matter coloboma changes

ALMS1 Frame - HMZ InVisAlstrom syndrome -Lack of other shift herited ion Achromatopsi features of a Alstrom

syndrome

(isolated achromatopsia)

STXBP1 Mis- HTZ De Neu Epileptic -Seizures Pigmentary sense Novo -ro encephalopathy, early retinal changes infantile, 4

CDKL5 NonHMZ InNeu Epileptic -ODD -Macrocephaly sense herited -ro encephalopathy, early and overgrowth infantile, 2 -Facial

dysmorphism similar to Sotos syndrome but normal bone age and negative NSD1 mutation

-No Seizures or regression

-No abnormal movements

GTDC2 Mis- HMZ InNeu Muscular dystrophy- None -Isolated large

(POMGN sense herited -ro dystroglycanopathy occipital

T2) (congenital with brain encephalocele and eye anomalies, -No Polydactyly type A, 8 -Neonatal death

HSD17B Mis- HMZ InNeu D-bifunctional -Neonatal -Normal brain

4 sense herited -ro protein deficiency seizures MRI

-No skeletal manifestations or stippling -No eye findings -No dysmorphism

ATN1 Mis- HTZ De Neu Dentatorubro- None -Early onset sense Novo -ro pallidoluysian static atrophy encephalopathy

-Novel molecular mechanism (point mutation)

KIAA019 Mis- HTZ De Neu -Ritscher-Schinzel -Seizures -Normal brain

6 sense Novo -ro syndrome -Speech delay MRI -Spastic paraplegia 8, and learning -No ataxia or

AD disability spasticity

ADRA2B NonHMZ InNeu Non- syndromic ID None -Microcephaly sense herited -ro (Najmabadi et al, -ODD

2011)

ZNF526 Mis- HMZ InNeu Mild non-syndromic None -Novel Noonan sense herited -ro ID (Najmabadi et al, like phenotype

2011) -ODD

WDR45B NonHMZ InNeu ID and microcephaly -Primary - Epilepsy

(WDR45 sense herited -ro (Najmabadi et al, microcephaly -White matter

L) 2011) changes, brain atrophy, hypoplastic corpus callosum

WDR81 NonHMZ InNeu Cerebellar -Cerebellar -Normal corpus sense herited ro ataxia,Mental hypoplasia callosum

retardation, and -Prenatal onset Dysequilibrium complicated by syndrome 2 neonatal death

(*) Atypical case is defined as a case that has unusual clinical features, unusual mode of inheritance, a novel phenotype or lack of typical features. DD: Dysmorphia-Dysplasia Panel, GDD: Global Developmental Delay, FTT: Failure to Thrive

Large scale genomic studies offer opportunities to improve the annotation of the human variome. This study, in which more than 2,300 well phenotyped human patients in a highly consanguineous population have been specifically tested for established disease genes, offered several advantages. First, the study was able to confirm genes that were only considered candidates because their candidacy was based on single mutations/families, so their status based on this study should be upgraded in the Online Mendelian Inheritance in Man (OMIM) database as such (e.g., ARL14EP, ZNF526, WDR45B, and WDR81). Second, the study added 446 novel disease alleles from a total of 795 variants, the largest to be reported in a single study. Third, the very large number of variants identified in the course of this study represented an unprecedented resource on the Arab variome (nearly all patients in this study were Arab in ethnicity), and this will be invaluable to the interpretation of clinical molecular genetic tests on Mendelian genes in Arab patients since it will help address the uncertainty surrounding the identification of many Arab-specific or Arab-enriched variants. Fourth, the high degree of consanguinity allowed the study to observe many variants in homozygosity as a result of autozygosity. This is particularly helpful when these variants were previously reported as disease-causing because observing them in the homozygous state at a relatively high population frequency strongly argues against their purported disease link. Furthermore, the finding of previously reported disease genes that harbor apparently inactivating mutations in the homozygous state at a relatively high frequency and in patients who lack the purported phenotype challenges their listing as disease genes (e.g., CACNA1F, MYH8, and PRX1) although it is acknowledged they have a potential role of such confounding factors as reduced penetrance.

The above method was initially limited to genes that were very likely to be disease- causing in a Mendelian context (based on the best available evidence) in order to eliminate the uncertainty surrounding the finding of variants in genes not known to be linked to human diseases. The study mainly included genes whose pathogenicity was supported by the presence of two pathogenic alleles. However, exceptions were made for genes with a single reported mutation but which were further supported by compelling mouse data or positional mapping data. This is important because it must be acknowledged that clinical WGS/WES currently appears to saddle the divide between clinical care and research.

If the Mendeliome assay is negative, it may be easier to prepare the patient for the possibility of identifying a novel genetic cause by WGS/WES that requires confirmation in a research setting. Unlike currently available gene panels, the present method seeks to be as inclusive as possible to minimize the challenge of atypical cases. For example, a gene for myopia presenting with ectopia lentis would still be identified because virtually every gene known to present with a prominent eye phenotype was included in the vision panel. In fact, the present analysis showed that only 3% (62/2,357) of cases may have been missed because the gene was not included in the right panel, and even this limitation can be addressed through a spike-in design. Such a broad and inclusive design was particularly helpful in disease categories that are characterized by a very high rate of heterogeneity. In addition to the vision panel, the high rate of atypical cases identified by the dysmorphology/dysplasia, neurology and immunology panels are also noted, although such cases were encountered in nearly all the panels.

Patients with various hereditary disorders most often are referred to the medical geneticist either through their primary care provider or through a medical subspecialist who attended to most prominent clinical presentation (i.e., neurological, ophthalmology, skin, renal, hematological, etc.). Therefore, the present symptom/sign based gene panels, collectively known as "The Mendeliome", were designed in a way that simulates the way these patients present in clinical practice to the respective specialty.

Mendelian disorders are defined as hereditary disorders caused by a single autosomal or X-linked gene. The OMIM database, which currently contains about 4,300 monogenic disorders associated with known molecular defects, represents the most comprehensive source of such information on monogenic disorders. Therefore, it was used as the primary source for gene identification. However, it was manually curated to ensure that only genes with confirmed links to disease are included. It was also supplemented with additional data from PubMed, Genetic Testing Registry (GTR), and gene tests. As such, the above 13 gene panels, which cover the spectrum of pediatric and adult clinical genetic medicine, were constructed. Within each panel, genes were sorted based on the most prominent

sign/symptom with which they are most likely to be associated upon presentation to clinical care. This presentation may help the referring clinician, and without requiring sophisticated knowledge about these genes, decide on the appropriateness of genetic testing using these gene panels. Since many genetic disorders are as likely to present to several medical specialties, the present method allows for redundancy between the different panels (average 15%) such that a gene may be present in more than one panel.

3,070 genes covering over 4,000 Mendelian disorders (as annotated by OMIM up to August of 2013) were used as a basis for the design and synthesis of the highly multiplexed gene panels using Ion AmpliSeq Designer software (produced by Life Technologies of California). Tables 1-3 display the list of genes, their corresponding panels, information about the used transcripts, physical positions, and number of exons. From these 3,070 genes, there are 2,826 genes already listed in the genetic testing registry (GTR). Thirteen panels encompassing nearly all of the OMIM genes were defined broadly based upon clinical disciplines with some redundancy in gene content of individual panels. Primer design was based upon generating amplicons with an average length of 200 bp providing 90% minimum coverage of the coding DNA sequence (CDS) and on average 10 bp flanking regions of associated exons. Following this, in silico design coverage was assessed for compliance with design criteria and manual processes applied on a gene by gene basis to ensure adequate coverage and resolve factors such as 3'- SNPs that could impact primer efficiency. Primers for each panel were then synthesized and pooled into two multiplex reactions based upon polymerase chain reaction (PCR) compatibility minimizing likelihood of primer-primer interactions. Following this, synthesis primer pools were tested for coverage, recommended multiplexing and other quality control (QC) metrics to ensure specifications were met.

Panels ranged from 96-758 gene with >90% coverage in 97-100% of genes in each panel.

Ten nanograms each of all DNA samples were treated to obtain the Ion Proton

AmpliSeq library for one of the thirteen gene panels, as appropriate. DNA was amplified with 10-15 amplification cycles. PCR pools for each sample were combined and subjected to primer digestion with a FuPa reagent. Pooled amplicons were then ligated with universal adapters. After purification, libraries were quantitated by qPCR and normalized to 100 pM. Normalized libraries were barcoded (ligated with 24 different Ion Xpress Barcode adapters) and pooled in equal ratios for emulsion PCR (ePCR) on an Ion OneTouch System. Following ePCR, templated Ion Sphere particles were enriched using the Ion OneTouch ES. Both ePCR and enrichment procedures followed the manufacturer's instructions. The template-positive Ion PI Ion Sphere particles were processed for sequencing on the Ion Proton instrument.

The data of each run has been analyzed through a multistep pipeline. In the first step of this pipeline, the quality of the reads were verified and regions of the reads with low quality (less than 20) were trimmed out before alignment. The runs with low yield after this quality check were excluded. In the second step, the reads were aligned to the reference hgl9 sequence. The observed depth after alignment ranges from 162X (for the neurology panel including 758 genes) to 840X (for the renal panel including 96 genes). In the third step, the aligned reads were processed for variant calling. In the subsequent step, the variants were annotated using public knowledge databases as well as in-house variants databases. The in- house databases include collections of disease-causing variants published by different Saudi teams and aggregation of the variants produced by the samples in this study.

In the final step of the pipeline, the non-relevant variants were filtered out based on their functional characteristics and their abundance in the datasets. Variants that are less likely to play a functional role (intronic and synonymous) and variants that were present in population databases (e.g., in the lOOOGenome database with MAF > 1%) were filtered out. Furthermore, variants that were frequent in the in-house database were also filtered out; a variant with more than 20 occurrences was considered frequent. The cutoff of 20 occurrences was selected on test data to assure 100% sensitivity. An individual base quality of 100 (using Phred-like score) was also selected to exclude low confidence variants. The few remaining variants were then analyzed based on relevance of gene to phenotype, zygosity (when indicated), and SIFT and PolyPhen scores (for missense variants). Table 16 below shows the efficiency of the filtering strategy. Table 16 shows that the subsequent filtering steps lead to a short list of variants to be examined by domain experts. In this table, and as expected, the larger the panel, the larger the list. It is also important to note that more samples included in the in-house database leads to more filtration power and makes the list even shorter. Ultimately, the recognized causal variant was identified as pathogenic or likely pathogenic as defined by the recent American College of Medical Genetics and Genomics (ACMG) guidelines, and the extensive variant data obtained by sequencing thousands of ethnically comparable patients (Saudis) was helpful in applying population frequency as a reliable criterion for pathogenicity in this study. Table 17: Filtering Results Over All Variant Files

Given that the Mendeliome assay is inherently limited to established disease genes and will miss cases caused by large structural variants, 213 cases that are negative by the Mendeliome assay were randomly selected and processed using molecular karyotyping.

CytoScan HD arrays were used for the majority of the patients. This array platform contains 2.6 million markers for copy number variation (CNV) detection, of which 750,000 are genotype SNPs and 1.9 million are nonpolymorphic probes, for whole genome coverage. Briefly, 250 ng of genomic DNA was digested with the restriction enzyme Nspl and then ligated to an adapter, followed by polymerase chain reaction (PCR) amplification using a single pair of primers that recognized the adapter sequence. The PCR products were run on a 2% Tris-borate-EDTA (TBE) gel to confirm that the majority of products were between 150 and 2,000 bp in length.

To obtain a sufficient quantity of PCR product for further analysis, all products from each sample were combined and purified using magnetic beads. The purified PCR products were fragmented using DNase I and visualized on a 4% TBE agarose gel to confirm that the fragment sizes ranged from 25 to 125 bp. The fragmented PCR products were subsequently end-labeled with biotin and hybridized to the array. Arrays were then washed and stained, and then scanned and analyzed. The hidden Markov model was used to determine the copy- number states and their breakpoints. Thresholds of log₂ ratio > 0.58 and < -1 were used to categorize altered regions as CNV gains (amplification) and copy-number losses (deletions), respectively.

To minimize the detection of false-positive CNVs arising due to inherent microarray noise, only alterations that involved at least 50 consecutive probes and that were at least 500 kb in size were used to categorize altered regions as CNV gains (amplification), whereas those at least 200 kb in size were used to categorize copy-number losses (deletions). The CNVs detected in the patients were then evaluated based on the ACMG standards and guidelines.

The genie content in the CNV interval of all the patients who had a molecular karyotype performed was taken into consideration by seeking recent publications to compare breakpoints, pheno types, and different sizes of CNVs that overlapped. To exclude aberrations representing common benign CNVs, all the identified CNVs were compared with those reported in the Database of Genomic Variants and those reported in the in-house database for individuals who have been classified as normal.

De novo CNVs that met the size cutoff of 200 kb for deletions and 500 kb for duplications (based on the laboratory's consideration of the performance characteristics of the assay used) and were not found in either parent were classified as pathogenic. However, this does not eliminate the possibility that pathogenic CNVs exhibiting incomplete penetrance or variable expressivity can be present in an unaffected parent.

The remaining 178 were processed using WES. One hundred nanograms of each

DNA sample was treated to obtain the Ion Proton AmpliSeq library. Briefly, DNA was amplified in twelve separate wells with 10 amplification cycles. All twelve PCR pools were combined in one well and subjected to primer digestion performing incubation with FuPa reagent. Amplified exome targets were ligated with Ion PI and Ion Xpress Barcode adapters. Following this, purification libraries were quantified using qPCR. The prepared exome library was further used for emulsion PCR and templated Ion Sphere particles were enriched using Ion OneTouch ES, both procedures following the manufacturer's instructions. The template-positive Ion PI Ion Sphere particles were processed for sequencing on the Ion Proton instrument. Approximately 15-17 Gb of sequence was generated per sequencing run.

It is to be understood that the present invention is not limited to the embodiments described above, but encompasses any and all embodiments within the scope of the following claims.

Claims

CLAIMS I claim:

1. A method for diagnosing Mendelian disease in a patient, comprising the steps of:

obtaining a sample from a patient;

contacting the sample with a set of primers from a Mendelian Disease Panel, the Mendelian Disease Panel including at least one of a Cardiovascular Mendelian Disease Panel, a Deafness Mendelian Disease Panel, a Dermatological Mendelian Disease Panel, a

Dysmorph-Dysplasia Mendelian Disease Panel, an Endocrine Mendelian Disease Panel, a GI Mendelian Disease Panel, a Hematological Mendelian Disease Panel, an Inborn Errors of Metabolism (IEM) Mendelian Disease Panel, a Neurological Disorder Mendelian Disease Panel, a Pelvic Inflammatory Disease (PID) Mendelian Disease Panel, a Pulmonary

Mendelian Disease Panel, a Renal Mendelian Disease Panel, and a Vision Mendelian Disease Panel; and

determining that the patient has a Mendelian disease if at least one genetic marker for Mendelian disease is detected by the Mendelian Disease Panel.

2. The method for diagnosing Mendelian disease in a patient according to Claim 1, further comprising the step of:

using the set of primers from the Mendelian Disease Panel to perform sequencing reactions.

3. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for cardiovascular diseases, and

contacting the sample with forward primers of SEQ IDs 1-10,517 and reverse primers of SEQ IDs 10,518-21,034.

4. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for deafness diseases, and

contacting the sample with forward primers of SEQ IDs 31,552-34,958 and reverse primers of SEQ IDs 34,959-38,365.

5. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for dermatological diseases, and

contacting the sample with forward primers of SEQ IDs 41,773-46,604 and reverse primers of SEQ IDs 46,605-51,436.

6. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Dysmorphia-Dysplasia diseases, and contacting the sample with forward primers of SEQ IDs 56,269-65,217 and reverse primers of SEQ IDs 65,218-74,166.

7. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Endocrine diseases, and

contacting the sample with forward primers of SEQ IDs 83,116-88,751 and reverse primers of SEQ IDs 88,752-94,387.

8. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Gastrointestinal diseases, and

contacting the sample with forward primers of SEQ IDs 100,024-103,947 and reverse primers of SEQ IDs 103,948-107,871.

9. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Hematologic diseases, and

contacting the sample with forward primers of SEQ IDs 111,796-119,291 and reverse primers of SEQ IDs 119,292-126,787.

10. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of: selecting the patient for screening for Inborn Errors of Metabolism diseases, and contacting the sample with forward primers of SEQ IDs 134,284-143,555 and reverse primers of SEQ IDs 143,556-152,827.

11. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Neurologic diseases, and

contacting the sample with forward primers of SEQ IDs 162,100-180,231 and reverse primers of SEQ IDs 180,232-198,363.

12. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Pelvic Inflammatory diseases, and

contacting the sample with forward primers of SEQ IDs 216,496-221,625 and reverse primers of SEQ IDs 221,626-226,755.

13. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Pulmonary diseases, and

contacting the sample with forward primers of SEQ IDs 231,886-235,250 and reverse primers of SEQ IDs 235,251-238,615.

14. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Renal diseases, and

contacting the sample with forward primers of SEQ IDs 241,981-244,593 and reverse primers of SEQ IDs 244,594-247,206.

15. The method for diagnosing Mendelian disease in a patient according to claim 2, further comprising the steps of:

selecting the patient for screening for Vision diseases, and

contacting the sample with forward primers of SEQ IDs 249,820-257,137 and reverse primers of SEQ IDs 257,138-264,445.

16. A method for diagnosing Mendelian disease in a patient, consisting of the steps of:

obtaining a sample from a patient;

Mendelian Disease Panel, a Renal Mendelian Disease Panel, and a Vision Mendelian Disease Panel;

using the set of primers from the Mendelian Disease Panel to perform sequencing reactions; and

determining that the patient has a Mendelian disease if at least one genetic marker for

Mendelian disease is detected by the Mendelian Disease Panel

wherein the set of primers for the Cardiovascular Mendelian Disease Panel include forward primers of SEQ IDs 1-10,517 and reverse primers of SEQ IDs 10,518-21,034; the set of primers for the Deafness Mendelian Disease Panel include forward primers of SEQ IDs 31,552-34,958 and reverse primers of SEQ IDs 34,959-38,365; the set of primers for the

Dermatological Mendelian Disease Panel include forward primers of SEQ IDs 41,773-46,604 and reverse primers of SEQ IDs 46,605-51,436; the set of primers for the Dysmorph- Dysplasia Mendelian Disease Panel include forward primers of SEQ IDs 56,269-65,217 and reverse primers of SEQ IDs 65,218-74,166; the set of primers for the Endocrine Mendelian Disease Panel include forward primers of SEQ IDs 83,116-88,751 and reverse primers of SEQ IDs 88,752-94,387; the set of primers for the Gastrointestinal Mendelian Disease Panel include forward primers of SEQ IDs 100,024-103,947 and reverse primers of SEQ IDs 103,948-107,871; the set of primers for the Hematological Mendelian Disease Panel include forward primers of SEQ IDs 111,796-119,291 and reverse primers of SEQ IDs 119,292- 126,787; the set of primers for the Inborn Errors of Metabolism (IEM) Mendelian Disease Panel include forward primers of SEQ IDs 134,284-143,555 and reverse primers of SEQ IDs 143, 556-152, 827the set of primers for the Neurological Disorder Mendelian Disease Panel include forward primers of SEQ IDs 162,100-180,231 and reverse primers of SEQ IDs 180,232-198,363; the set of primers for the Pelvic Inflammatory Disease (PID) Mendelian Disease Panel include forward primers of SEQ IDs 216,496-221,625 and reverse primers of SEQ IDs 221,626-226,755; the set of primers for the Pulmonary Mendelian Disease Panel include forward primers of SEQ IDs 231,886-235,250 and reverse primers of SEQ IDs 235,251-238,615; the set of primers for the Renal Mendelian Disease Panel include forward primers of SEQ IDs 241,981-244,593 and reverse primers of SEQ IDs 244,594-247,206; and the set of primers for the Vision Mendelian Disease Panel include forward primers of SEQ IDs 249,820-257,137 and reverse primers of SEQ IDs 257,138-264,445.

17. A kit for diagnosing Mendelian disease, comprising:

a set of primers from a Mendelian Disease Panel, the Mendelian Disease Panel including at least one of a Cardiovascular Mendelian Disease Panel, a Deafness Mendelian Disease Panel, a Dermatological Mendelian Disease Panel, a Dysmorph-Dysplasia Mendelian Disease Panel, an Endocrine Mendelian Disease Panel, a GI Mendelian Disease Panel, a Hematological Mendelian Disease Panel, an Inborn Errors of Metabolism (IEM) Mendelian Disease Panel, a Neurological Disorder Mendelian Disease Panel, a Pelvic Inflammatory Disease (PID) Mendelian Disease Panel, a Pulmonary Mendelian Disease Panel, a Renal Mendelian Disease Panel, and a Vision Mendelian Disease Panel, and

reagents to perform a sequencing reaction using the Mendelian Disease Panel primers, wherein the set of primers for the Cardiovascular Mendelian Disease Panel include forward primers of SEQ IDs 1-10,517 and reverse primers of SEQ IDs 10,518-21,034; the set of primers for the Deafness Mendelian Disease Panel include forward primers of SEQ IDs 31,552-34,958 and reverse primers of SEQ IDs 34,959-38,365; the set of primers for the Dermatological Mendelian Disease Panel include forward primers of SEQ IDs 41,773-46,604 and reverse primers of SEQ IDs 46,605-51,436; the set of primers for the Dysmorph- Dysplasia Mendelian Disease Panel include forward primers of SEQ IDs 56,269-65,217 and reverse primers of SEQ IDs 65,218-74,166; the set of primers for the Endocrine Mendelian Disease Panel include forward primers of SEQ IDs 83,116-88,751 and reverse primers of SEQ IDs 88,752-94,387; the set of primers for the Gastrointestinal Mendelian Disease Panel include forward primers of SEQ IDs 100,024-103,947 and reverse primers of SEQ IDs

103,948-107,871; the set of primers for the Hematological Mendelian Disease Panel include forward primers of SEQ IDs 111,796-119,291 and reverse primers of SEQ IDs 119,292- 126,787; the set of primers for the Inborn Errors of Metabolism (IEM) Mendelian Disease Panel include forward primers of SEQ IDs 134,284-143,555 and reverse primers of SEQ IDs 143, 556-152, 827the set of primers for the Neurological Disorder Mendelian Disease Panel include forward primers of SEQ IDs 162,100-180,231 and reverse primers of SEQ IDs 180,232-198,363; the set of primers for the Pelvic Inflammatory Disease (PID) Mendelian Disease Panel include forward primers of SEQ IDs 216,496-221,625 and reverse primers of SEQ IDs 221,626-226,755; the set of primers for the Pulmonary Mendelian Disease Panel include forward primers of SEQ IDs 231,886-235,250 and reverse primers of SEQ IDs 235,251-238,615; the set of primers for the Renal Mendelian Disease Panel include forward primers of SEQ IDs 241,981-244,593 and reverse primers of SEQ IDs 244,594-247,206; and the set of primers for the Vision Mendelian Disease Panel include forward primers of SEQ IDs 249,820-257,137 and reverse primers of SEQ IDs 257,138-264,445.